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=C3=B3n Descripci=C3=B3n generada autom=C3=A1ticamente con confian= za media" style=3D"margin-top:88pt; margin-left:403.5pt; position:absolute"= /></span><span> </span><span style=3D"font-style:italic">Set of educa= tional activities using PhET interactive simulation for learning fractions = in adults</span></p><p class=3D"Default" style=3D"line-height:115%; font-si= ze:14pt"><span style=3D"font-style:italic"> </span></p><table style=3D= "width:396pt; margin-bottom:0pt; border:0.75pt solid #000000; padding:0pt; = border-collapse:collapse"><tr><td style=3D"width:3.25pt; border-right:0.75p= t solid #000000; border-bottom:0.75pt solid #000000; padding:0pt 5.03pt; ve= rtical-align:top"><p style=3D"margin-bottom:0pt; text-align:center; line-he= ight:115%; font-size:10pt"><span style=3D"line-height:115%; font-size:6.67p= t; font-weight:bold; vertical-align:super">1</span></p></td><td style=3D"wi= dth:171.95pt; border-right:0.75pt solid #000000; border-left:0.75pt solid #= 000000; border-bottom:0.75pt solid #000000; padding:0pt 5.03pt; vertical-al= ign:top"><p style=3D"margin-left:7.1pt; margin-bottom:0pt; text-indent:-7.1= pt; text-align:justify; line-height:115%; font-size:10pt"><span>Manuel Rodr= igo Faic=C3=A1n Pauta</span></p></td><td style=3D"width:10.5pt; border-righ= t:0.75pt solid #000000; border-left:0.75pt solid #000000; border-bottom:0.7= 5pt solid #000000; padding:0pt 5.03pt; vertical-align:top"><p style=3D"marg= in-bottom:0pt; text-align:center; line-height:115%; font-size:10pt"><span s= tyle=3D"height:0pt; text-align:left; display:block; position:absolute; z-in= dex:1"><img src=3D"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAABQAAAAUCA= YAAACNiR0NAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAAOxAAADsQBlSsOGwAAA2lJREFUOI21l= EtoXVUUhr+197n3nNzbJN6omdTWRmwbikVq4iMxk0ZU2oGgA1FnQcQiUhUnFqo4cGIRQUGd+KDY= +Jp25ouiGCOxElqjhba0URPzsPQmuY9zzj1nLwcnuU1iQ0f+mzXZe///Wv/aiy1cBV/83NNOPr/= VWHunqO5OVNuNlQVjmZCGjCVhcPHR3q8XrsaVNUITu/KSlu7LFeSpNNZ+57RTjDTvqFM1IvNiGX= 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" height=3D"20" alt=3D"" style=3D"margin-top:0.25pt; margin-left:-0.3pt; po= sition:absolute" /></span><span> </span></p></td><td style=3D"width:16= 6.35pt; border-left:0.75pt solid #000000; border-bottom:0.75pt solid #00000= 0; padding:0pt 5.03pt; vertical-align:top"><p style=3D"margin-bottom:0pt; l= ine-height:115%"><a href=3D"https://orcid.org/0000-0002-6620-698X" style=3D= "text-decoration:none"><span class=3D"Hyperlink" style=3D"line-height:115%;= font-size:10pt">https://orcid.org/0000-0002-6620-698X</span></a></p></td><= /tr><tr><td style=3D"width:3.25pt; border-top:0.75pt solid #000000; border-= right:0.75pt solid #000000; border-bottom:0.75pt solid #000000; padding:0pt= 5.03pt; vertical-align:top"><p style=3D"margin-bottom:0pt; text-align:cent= er; line-height:115%; font-size:10pt"><span style=3D"font-size:6.67pt; font= -weight:bold; vertical-align:super"> </span></p></td><td colspan=3D"3"= style=3D"width:370.4pt; border-top:0.75pt solid #000000; border-left:0.75p= t solid #000000; border-bottom:0.75pt solid #000000; padding:0pt 5.03pt; ve= rtical-align:top"><p style=3D"margin-bottom:0pt; text-align:justify; line-h= eight:115%; font-size:10pt"><span>Maestr=C3=ADa en Educaci=C3=B3n con menci= =C3=B3n en Entornos Tecnol=C3=B3gicos</span></p><p style=3D"margin-bottom:0= pt; text-align:justify; line-height:115%; font-size:10pt"><span>Universidad= Bolivariana del Ecuador (UBE), Dur=C3=A1n, Ecuador.</span></p><p style=3D"= margin-bottom:0pt; line-height:115%"><a href=3D"mailto:mrfaicanp@ube.edu.ec= " style=3D"text-decoration:none"><span class=3D"Hyperlink" style=3D"line-he= ight:115%; font-size:10pt">mrfaicanp@ube.edu.ec</span></a></p></td></tr><tr= ><td style=3D"width:3.25pt; border-top:0.75pt solid #000000; border-right:0= .75pt solid #000000; border-bottom:0.75pt solid #000000; padding:0pt 5.03pt= ; vertical-align:top"><p style=3D"margin-bottom:0pt; text-align:center; lin= e-height:115%; font-size:10pt"><span style=3D"line-height:115%; font-size:6= .67pt; font-weight:bold; vertical-align:super">2</span></p></td><td style= =3D"width:171.95pt; border:0.75pt solid #000000; padding:0pt 5.03pt; vertic= al-align:top"><p style=3D"margin-left:7.1pt; margin-bottom:0pt; text-indent= :-7.1pt; text-align:justify; line-height:115%; font-size:10pt"><span>Elio W= ashington Yagual Mor=C3=A1n</span></p></td><td style=3D"width:10.5pt; borde= r:0.75pt solid #000000; padding:0pt 5.03pt; vertical-align:top"><p style=3D= "margin-bottom:0pt; text-align:center; line-height:115%; font-size:10pt"><s= pan style=3D"height:0pt; text-align:left; display:block; position:absolute;= z-index:2"><img src=3D"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAABQAA= AAUCAYAAACNiR0NAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAAOxAAADsQBlSsOGwAAA2lJREFU= OI21lEtoXVUUhr+197n3nNzbJN6omdTWRmwbikVq4iMxk0ZU2oGgA1FnQcQiUhUnFqo4cGIRQUG= d+KDY+Jp25ouiGCOxElqjhba0URPzsPQmuY9zzj1nLwcnuU1iQ0f+mzXZe///Wv/aiy1cBV/83N= NOPr/VWHunqO5OVNuNlQVjmZCGjCVhcPHR3q8XrsaVNUITu/KSlu7LFeSpNNZ+57RTjDTvqFM1I= vNiGXWJvD/9x8yXB/efizYU/Hy8/0W/aA/Xq43r1P3nOCNIFsW2XLleTd648Z/863v3nkjWCL59= dp/fWSsfzOXNkShKacvfgnMRlXjqqqIrwr5vkihyhxbT+K2ne082AAzADZXyPj+wL8ehQ1NH700= v0N35OAroutW0rxDF6rUUvddaJfdwM9HwqYFSa0GO1SrpfucUVUXEZCQcqQtZ0VEU1QTPtmAkDy= giEBTsTxq6hx65fWTOy7l0exjKgGrGcjTo2/oKS9EUZ2aPcf/Oo1iTI9UGqFJrzDF5+Sv+Wvg+y= +IEVXaGibsbOO5hGBSkbUUQdRT9zaQuBhE6Ct2MT7/D9OIIVnw6Ct3csfk52oNtTMwcBbE0Ytee= C7we4LinSI9Z03dBNUVxTdu1eI7FcBIjHvPVU1Tjv7nn5sNMXv6WSjyFiIg17AAwqpRW9fqayNk= iM0tjqDrag67mDCi0ARiB6gaTsSEEg4htusj2qGeCIr9dW0JR3PKrR2zreIDURZTrZ7NTBYdeBP= AU+cY59zxCkFlXjHiI2GY1pZbtRMkC1gZcX9hFV+lBTs98SDWexYjFGqkldT0J4EkY/ZovBb+kl= bQ/G1zDYvQntXgWFC5VJ9hSGmRLaRCnCZeqE3x34SXK9XMY8bK+BvZ8JUzGAEQV+Wy87xm/xbwZ= 1lwewGmCIIhYnCZXjKvDaQNrfIzkAKXYZl11wR16omfkyHIP0RB/2CV8GrRkNldbNmKbYU2enC0= uV6bkfUNUd8P1ury3ktQADO05UV6azx1IE/dRULDomjGSVXEFhVbrXMoncTV99smBH5ZW327igz= P3trY2ONCyyQ6FtbRLUw2yZ8p+FwARifyCvRDV048rcfXdoT3j5fXp1+BVxdx2um+HGnuX9egX4= dY01U0iVK2R80nMaELy42O7R39fz/1f8C/hZ5YvjpSKGwAAAABJRU5ErkJggg=3D=3D" width= =3D"20" height=3D"20" alt=3D"" style=3D"margin-top:0.5pt; margin-left:-0.3p= t; position:absolute" /></span><span> </span></p></td><td style=3D"wid= th:166.35pt; border-top:0.75pt solid #000000; border-left:0.75pt solid #000= 000; border-bottom:0.75pt solid #000000; padding:0pt 5.03pt; vertical-align= :top"><p style=3D"margin-bottom:0pt; line-height:115%"><a href=3D"https://o= rcid.org/0009-0001-8644-0108" style=3D"text-decoration:none"><span class=3D= "Hyperlink" style=3D"line-height:115%; font-size:10pt">https://orcid.org/00= 09-0001-8644-0108</span></a><span style=3D"line-height:115%; font-size:10pt= "> </span></p></td></tr><tr><td style=3D"width:3.25pt; border-top:0.75pt so= lid #000000; border-right:0.75pt solid #000000; border-bottom:0.75pt solid = #000000; padding:0pt 5.03pt; vertical-align:top"><p style=3D"margin-bottom:= 0pt; text-align:center; line-height:115%; font-size:10pt"><span style=3D"fo= nt-size:6.67pt; font-weight:bold; vertical-align:super"> </span></p></= td><td colspan=3D"3" style=3D"width:370.4pt; border-top:0.75pt solid #00000= 0; border-left:0.75pt solid #000000; border-bottom:0.75pt solid #000000; pa= dding:0pt 5.03pt; vertical-align:top"><p style=3D"margin-bottom:0pt; text-a= lign:justify; line-height:115%; font-size:10pt"><span>Maestr=C3=ADa en Educ= aci=C3=B3n con menci=C3=B3n en Entornos Tecnol=C3=B3gicos</span></p><p styl= e=3D"margin-bottom:0pt; text-align:justify; line-height:115%; font-size:10p= t"><span>Universidad Bolivariana del Ecuador (UBE), Dur=C3=A1n, Ecuador.</s= pan></p><p style=3D"margin-bottom:0pt; line-height:115%"><a href=3D"mailto:= ewyagualm@ube.edu.ec" style=3D"text-decoration:none"><span class=3D"Hyperli= nk" style=3D"line-height:115%; font-size:10pt">ewyagualm@ube.edu.ec</span><= /a></p></td></tr><tr><td style=3D"width:3.25pt; border-top:0.75pt solid #00= 0000; border-right:0.75pt solid #000000; border-bottom:0.75pt solid #000000= ; padding:0pt 5.03pt; vertical-align:top"><p style=3D"margin-bottom:0pt; te= xt-align:center; line-height:115%; font-size:10pt"><span style=3D"line-heig= ht:115%; font-size:6.67pt; font-weight:bold; vertical-align:super">3</span>= </p></td><td style=3D"width:171.95pt; border:0.75pt solid #000000; padding:= 0pt 5.03pt; vertical-align:top"><p style=3D"margin-left:7.1pt; margin-botto= m:0pt; text-indent:-7.1pt; text-align:justify; line-height:115%; font-size:= 10pt"><span>Janette Santos Baranda</span></p></td><td style=3D"width:10.5pt= ; border:0.75pt solid #000000; padding:0pt 5.03pt; vertical-align:top"><p s= tyle=3D"margin-bottom:0pt; text-align:center; line-height:115%; font-size:1= 0pt"><span style=3D"height:0pt; text-align:left; display:block; position:ab= solute; z-index:3"><img src=3D"data:image/png;base64,iVBORw0KGgoAAAANSUhEUg= AAABQAAAAUCAYAAACNiR0NAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAAOxAAADsQBlSsOGwAAA= 2lJREFUOI21lEtoXVUUhr+197n3nNzbJN6omdTWRmwbikVq4iMxk0ZU2oGgA1FnQcQiUhUnFqo4= cGIRQUGd+KDY+Jp25ouiGCOxElqjhba0URPzsPQmuY9zzj1nLwcnuU1iQ0f+mzXZe///Wv/aiy1= cBV/83NNOPr/VWHunqO5OVNuNlQVjmZCGjCVhcPHR3q8XrsaVNUITu/KSlu7LFeSpNNZ+57RTjD= TvqFM1IvNiGXWJvD/9x8yXB/efizYU/Hy8/0W/aA/Xq43r1P3nOCNIFsW2XLleTd648Z/863v3n= kjWCL59dp/fWSsfzOXNkShKacvfgnMRlXjqqqIrwr5vkihyhxbT+K2ne082AAzADZXyPj+wL8eh= Q1NH700v0N35OAroutW0rxDF6rUUvddaJfdwM9HwqYFSa0GO1SrpfucUVUXEZCQcqQtZ0VEU1QT= PtmAkDygiEBTsTxq6hx65fWTOy7l0exjKgGrGcjTo2/oKS9EUZ2aPcf/Oo1iTI9UGqFJrzDF5+S= v+Wvg+y+IEVXaGibsbOO5hGBSkbUUQdRT9zaQuBhE6Ct2MT7/D9OIIVnw6Ct3csfk52oNtTMwcB= bE0YteeC7we4LinSI9Z03dBNUVxTdu1eI7FcBIjHvPVU1Tjv7nn5sNMXv6WSjyFiIg17AAwqpRW= 9fqayNkiM0tjqDrag67mDCi0ARiB6gaTsSEEg4htusj2qGeCIr9dW0JR3PKrR2zreIDURZTrZ7N= TBYdeBPAU+cY59zxCkFlXjHiI2GY1pZbtRMkC1gZcX9hFV+lBTs98SDWexYjFGqkldT0J4EkY/Z= ovBb+klbQ/G1zDYvQntXgWFC5VJ9hSGmRLaRCnCZeqE3x34SXK9XMY8bK+BvZ8JUzGAEQV+Wy87= xm/xbwZ1lwewGmCIIhYnCZXjKvDaQNrfIzkAKXYZl11wR16omfkyHIP0RB/2CV8GrRkNldbNmKb= YU2enC0uV6bkfUNUd8P1ury3ktQADO05UV6azx1IE/dRULDomjGSVXEFhVbrXMoncTV99smBH5Z= W327igzP3trY2ONCyyQ6FtbRLUw2yZ8p+FwARifyCvRDV048rcfXdoT3j5fXp1+BVxdx2um+HGn= uX9egX4dY01U0iVK2R80nMaELy42O7R39fz/1f8C/hZ5YvjpSKGwAAAABJRU5ErkJggg=3D=3D"= width=3D"20" height=3D"20" alt=3D"" style=3D"margin-top:0.45pt; margin-lef= t:-0.3pt; position:absolute" /></span><span> </span></p></td><td style= =3D"width:166.35pt; border-top:0.75pt solid #000000; border-left:0.75pt sol= id #000000; border-bottom:0.75pt solid #000000; padding:0pt 5.03pt; vertica= l-align:top"><p style=3D"margin-bottom:0pt; line-height:115%"><a href=3D"ht= tps://orcid.org/0000-0002-0225-5926" style=3D"text-decoration:none"><span c= lass=3D"Hyperlink" style=3D"line-height:115%; font-size:10pt">https://orcid= .org/0000-0002-0225-5926</span></a><span style=3D"line-height:115%; font-si= ze:10pt"> </span></p></td></tr><tr><td style=3D"width:3.25pt; border-top:0.= 75pt solid #000000; border-right:0.75pt solid #000000; border-bottom:0.75pt= solid #000000; padding:0pt 5.03pt; vertical-align:top"><p style=3D"margin-= bottom:0pt; text-align:center; line-height:115%; font-size:10pt"><span styl= e=3D"font-size:6.67pt; font-weight:bold; vertical-align:super"> </span= ></p></td><td colspan=3D"3" style=3D"width:370.4pt; border-top:0.75pt solid= #000000; border-left:0.75pt solid #000000; border-bottom:0.75pt solid #000= 000; padding:0pt 5.03pt; vertical-align:top"><p style=3D"margin-bottom:0pt;= text-align:justify; line-height:115%; font-size:10pt"><span>Universidad Te= cnol=C3=B3gica de La Habana Jos=C3=A9 Antonio Echeverr=C3=ADa,</span><span>=  </span><span>La</span><span> </span><span>Habana,</span><span>&#= xa0;</span><span>Cuba.</span></p><p style=3D"margin-bottom:0pt; line-height= :115%"><a href=3D"mailto:jsantos@tesla.cujae.edu.cu" style=3D"text-decorati= on:none"><span class=3D"Hyperlink" style=3D"line-height:115%; font-size:10p= t">jsantos@tesla.cujae.edu.cu</span></a></p></td></tr><tr><td style=3D"widt= h:3.25pt; border-top:0.75pt solid #000000; border-right:0.75pt solid #00000= 0; border-bottom:0.75pt solid #000000; padding:0pt 5.03pt; vertical-align:t= op"><p style=3D"margin-bottom:0pt; text-align:center; line-height:115%; fon= t-size:10pt"><span style=3D"line-height:115%; font-size:6.67pt; font-weight= :bold; vertical-align:super">4</span></p></td><td style=3D"width:171.95pt; = border:0.75pt solid #000000; padding:0pt 5.03pt; vertical-align:top"><p sty= le=3D"margin-left:7.1pt; margin-bottom:0pt; text-indent:-7.1pt; text-align:= justify; line-height:115%; font-size:10pt"><span>Arian V=C3=A1zquez Alvarez= </span></p></td><td style=3D"width:10.5pt; border:0.75pt solid #000000; pad= ding:0pt 5.03pt; vertical-align:top"><p style=3D"margin-bottom:0pt; text-al= ign:center; line-height:115%; font-size:10pt"><span style=3D"height:0pt; te= xt-align:left; display:block; position:absolute; z-index:4"><img src=3D"dat= a:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAABQAAAAUCAYAAACNiR0NAAAABHNCSVQI= CAgIfAhkiAAAAAlwSFlzAAAOxAAADsQBlSsOGwAAA2lJREFUOI21lEtoXVUUhr+197n3nNzbJN6= omdTWRmwbikVq4iMxk0ZU2oGgA1FnQcQiUhUnFqo4cGIRQUGd+KDY+Jp25ouiGCOxElqjhba0UR= PzsPQmuY9zzj1nLwcnuU1iQ0f+mzXZe///Wv/aiy1cBV/83NNOPr/VWHunqO5OVNuNlQVjmZCGj= CVhcPHR3q8XrsaVNUITu/KSlu7LFeSpNNZ+57RTjDTvqFM1IvNiGXWJvD/9x8yXB/efizYU/Hy8= /0W/aA/Xq43r1P3nOCNIFsW2XLleTd648Z/863v3nkjWCL59dp/fWSsfzOXNkShKacvfgnMRlXj= qqqIrwr5vkihyhxbT+K2ne082AAzADZXyPj+wL8ehQ1NH700v0N35OAroutW0rxDF6rUUvddaJf= dwM9HwqYFSa0GO1SrpfucUVUXEZCQcqQtZ0VEU1QTPtmAkDygiEBTsTxq6hx65fWTOy7l0exjKg= GrGcjTo2/oKS9EUZ2aPcf/Oo1iTI9UGqFJrzDF5+Sv+Wvg+y+IEVXaGibsbOO5hGBSkbUUQdRT9= zaQuBhE6Ct2MT7/D9OIIVnw6Ct3csfk52oNtTMwcBbE0YteeC7we4LinSI9Z03dBNUVxTdu1eI7= FcBIjHvPVU1Tjv7nn5sNMXv6WSjyFiIg17AAwqpRW9fqayNkiM0tjqDrag67mDCi0ARiB6gaTsS= EEg4htusj2qGeCIr9dW0JR3PKrR2zreIDURZTrZ7NTBYdeBPAU+cY59zxCkFlXjHiI2GY1pZbtR= MkC1gZcX9hFV+lBTs98SDWexYjFGqkldT0J4EkY/ZovBb+klbQ/G1zDYvQntXgWFC5VJ9hSGmRL= aRCnCZeqE3x34SXK9XMY8bK+BvZ8JUzGAEQV+Wy87xm/xbwZ1lwewGmCIIhYnCZXjKvDaQNrfIz= kAKXYZl11wR16omfkyHIP0RB/2CV8GrRkNldbNmKbYU2enC0uV6bkfUNUd8P1ury3ktQADO05UV= 6azx1IE/dRULDomjGSVXEFhVbrXMoncTV99smBH5ZW327igzP3trY2ONCyyQ6FtbRLUw2yZ8p+F= wARifyCvRDV048rcfXdoT3j5fXp1+BVxdx2um+HGnuX9egX4dY01U0iVK2R80nMaELy42O7R39f= z/1f8C/hZ5YvjpSKGwAAAABJRU5ErkJggg=3D=3D" width=3D"20" height=3D"20" alt=3D= "" style=3D"margin-top:0.45pt; margin-left:-0.3pt; position:absolute" /></s= pan><span> </span></p></td><td style=3D"width:166.35pt; border-top:0.7= 5pt solid #000000; border-left:0.75pt solid #000000; border-bottom:0.75pt s= olid #000000; padding:0pt 5.03pt; vertical-align:top"><p style=3D"margin-bo= ttom:0pt; line-height:115%"><a href=3D"https://orcid.org/0009-0001-8605-491= X" style=3D"text-decoration:none"><span class=3D"Hyperlink" style=3D"line-h= eight:115%; font-size:10pt">https://orcid.org/0009-0001-8605-491X</span></a= ><span style=3D"line-height:115%; font-size:10pt">   </span></p><= /td></tr><tr><td style=3D"width:3.25pt; border-top:0.75pt solid #000000; bo= rder-right:0.75pt solid #000000; padding:0pt 5.03pt; vertical-align:top"><p= style=3D"margin-bottom:0pt; text-align:center; line-height:115%; font-size= :10pt"><span style=3D"font-size:6.67pt; font-weight:bold; vertical-align:su= per"> </span></p></td><td colspan=3D"3" style=3D"width:370.4pt; border= -top:0.75pt solid #000000; border-left:0.75pt solid #000000; padding:0pt 5.= 03pt; vertical-align:top"><p style=3D"margin-bottom:0pt; text-align:justify= ; line-height:115%; font-size:10pt"><span>Universidad Bolivariana del Ecuad= or (UBE),</span><span> </span><span>Dur=C3=A1n,</span><span> </sp= an><span>Ecuador.</span></p><p style=3D"margin-bottom:0pt; line-height:115%= "><a href=3D"mailto:arian.vazquez@ube.edu.ec" style=3D"text-decoration:none= "><span class=3D"Hyperlink" style=3D"line-height:115%; font-size:10pt">aria= n.vazquez@ube.edu.ec</span></a></p></td></tr></table><p class=3D"Default" s= tyle=3D"text-indent:36pt; text-align:center; line-height:115%; font-size:14= pt"><span style=3D"font-style:italic"> </span></p><table style=3D"widt= h:436.35pt; margin-left:0.25pt; margin-bottom:0pt; padding:0pt; border-coll= apse:collapse"><tr><td colspan=3D"3" style=3D"width:156.4pt; padding:0pt 5.= 4pt; vertical-align:top"><p style=3D"margin-bottom:0pt; text-align:right; l= ine-height:115%; font-size:10pt"><a id=3D"_Hlk92186133"><span class=3D"Hype= rlink" style=3D"text-decoration:none; color:#000000"> </span></a></p><= p style=3D"margin-bottom:0pt; text-align:right; line-height:115%; font-size= :10pt"><span> </span></p></td><td colspan=3D"2" style=3D"width:258.35p= t; border-top:0.75pt solid #000000; padding:0pt 5.4pt; vertical-align:top">= <p style=3D"margin-bottom:0pt; text-align:right; line-height:115%; font-siz= e:10pt"><span style=3D"font-weight:bold">Art=C3=ADculo de Investigaci=C3=B3= n Cient=C3=ADfica y Tecnol=C3=B3gica</span></p><p style=3D"margin-bottom:0p= t; text-align:right; line-height:115%; font-size:10pt"><span>Enviado: </spa= n></p><p style=3D"margin-bottom:0pt; text-align:right; line-height:115%; fo= nt-size:10pt"><span>Revisado: </span></p><p style=3D"margin-bottom:0pt; tex= t-align:right; line-height:115%; font-size:10pt"><span>Aceptado: </span></p= ><p style=3D"margin-bottom:0pt; text-align:right; line-height:115%; font-si= ze:10pt"><span>Publicado:</span></p><p style=3D"margin-bottom:0pt; text-ali= gn:right; line-height:115%; font-size:10pt"><span class=3D"label" style=3D"= background-color:#ffffff">DOI:</span><span class=3D"label" style=3D"backgro= und-color:#ffffff"> </span></p></td></tr><tr style=3D"height:6.55pt"><= td colspan=3D"3" style=3D"width:156.4pt; padding:0pt 5.4pt; vertical-align:= top"><p style=3D"margin-bottom:0pt; text-align:right; line-height:115%; fon= t-size:6pt"><span class=3D"Hyperlink" style=3D"text-decoration:none; color:= #000000"> </span></p><p style=3D"margin-bottom:0pt; text-align:right; = line-height:115%; font-size:6pt"><span class=3D"Hyperlink" style=3D"text-de= coration:none; color:#000000"> </span></p></td><td colspan=3D"2" style= =3D"width:258.35pt; border-bottom:0.75pt solid #000000; padding:0pt 5.4pt; = vertical-align:top"><p style=3D"margin-bottom:0pt; text-align:right; line-h= eight:115%; font-size:6pt"><span style=3D"font-weight:bold"> </span></= p></td></tr><tr><td style=3D"width:37.8pt; padding:0pt 5.4pt; vertical-alig= n:top"><p style=3D"margin-bottom:0pt; text-align:justify; line-height:115%"= ><span style=3D"font-weight:bold"> </span></p><p style=3D"margin-botto= m:0pt; text-align:justify; line-height:115%"><span style=3D"font-weight:bol= d">C=C3=ADtese:</span><span> </span></p></td><td style=3D"width:1.55pt; pad= ding:0pt 5.4pt; vertical-align:top"><p style=3D"margin-bottom:0pt; text-ali= gn:justify; line-height:115%"><span style=3D"font-weight:bold"> </span= ></p></td><td colspan=3D"2" style=3D"width:358.55pt; border-bottom:0.75pt s= olid #000000; padding:0pt 5.4pt; vertical-align:top"><p style=3D"margin-bot= tom:0pt; text-align:justify; line-height:115%; font-size:10pt"><span> = </span></p><p style=3D"margin-bottom:0pt; text-align:justify; line-height:1= 15%; font-size:10pt"><span>DATOS 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kZGB0+mkT58+t1TovYZSqaRz585UVlai1+tp1aoVaWlpJCUlER4ezv79+8nMzLylsqtWq+XOO+8= kIiKC/Px8lEolhYWF1NbW0r9/f1auXHlDYCSXy5k3b96fVtL14MGDBw8ePPxr3Jbgxmg08uSTT1= 7dLXWLgf7EDqM/y7V+f73F/Nfj//J/f/3z77W/dvyaHs+t+v81CoWCN998kwkTJvxm3x48ePDgw= YOH28NtCW6cTifl5eVYLJZbD/QXBje3i79ijjKZjICAAHQ6nbuA04MHDx48ePDw13FbghsPHjx4= 8ODBg4f/FDxLCR48ePDgwYOH/yo8wY0HDx48ePDg4b+KP7UVPDs72+3C7cGDBw8ePHjw8L+BRqO= hRYsWtzz+p4Kb77777qYqvB48ePDgwYMHD38X4eHhTJky5ZbHPQXFHjx48ODBg4f/Kjw1Nx48eP= DgwYOH/yo8wY0HDx48ePDg4b8KT3DjwYMHDx48ePiv4v8DkrKy3KIORuIAAAAASUVORK5CYII= =3D" width=3D"567" height=3D"140" alt=3D"" /></p><table style=3D"width:437.= 1pt; margin-left:0.25pt; margin-bottom:0pt; border:0.75pt solid #000000; pa= dding:0pt; border-collapse:collapse"><tr><td style=3D"width:73.75pt; border= -right:0.75pt solid #000000; border-bottom:0.75pt solid #000000; padding:0p= t 5.03pt; vertical-align:top"><p style=3D"margin-bottom:0pt; text-align:jus= tify; line-height:115%"><span style=3D"font-weight:bold">Palabras claves:</= span><span> </span></p><p style=3D"margin-bottom:0pt; line-height:115%"><sp= an>Educaci=C3=B3n de personas adultas; fracciones; simulaciones PhET; andra= gog=C3=ADa</span></p></td><td style=3D"width:5.3pt; border-right:0.75pt sol= id #000000; border-left:0.75pt solid #000000; border-bottom:0.75pt solid #0= 00000; padding:0pt 5.03pt; vertical-align:top"><p class=3D"Title" style=3D"= margin-top:6pt; margin-bottom:12pt; text-align:justify; line-height:115%; f= ont-size:12pt"><span style=3D"font-family:'Times New Roman'"> </span><= /p></td><td style=3D"width:324.9pt; border-left:0.75pt solid #000000; borde= r-bottom:0.75pt solid #000000; padding:0pt 5.03pt; vertical-align:top"><p s= tyle=3D"margin-bottom:0pt; text-align:justify; line-height:115%"><span>Resu= men</span></p><p style=3D"margin-bottom:0pt; text-align:justify; line-heigh= t:115%"><span style=3D"font-weight:bold">Introducci=C3=B3n: </span><span>el= aprendizaje de fracciones en adultos exige estrategias did=C3=A1cticas act= ivas con tecnolog=C3=ADas digitales. En este sentido las simulaciones son u= n recurso valioso al proporcionar un entorno interactivo. </span><span styl= e=3D"font-weight:bold">Objetivos: </span><span>esta investigaci=C3=B3n tuvo= como objetivo dise=C3=B1ar un sistema de actividades mediante la integraci= =C3=B3n de PHET Interactive Simulation para fortalecer el aprendizaje de fr= acciones matem=C3=A1ticas en adultos de 40+ a=C3=B1os en la modalidad noctu= rna de la Escuela de Educaci=C3=B3n B=C3=A1sica PCEI Rumi=C3=B1ahui. </span= ><span style=3D"font-weight:bold">Metodolog=C3=ADa: </span><span>El estudio= adopt=C3=B3 un enfoque mixto, aplicado y de campo, con alcance descriptivo= -propositivo. Emple=C3=B3 m=C3=A9todos te=C3=B3ricos (anal=C3=ADtico-sint= =C3=A9tico, inductivo-deductivo, modelaci=C3=B3n) y emp=C3=ADricos (prueba = diagn=C3=B3stica, encuesta a estudiantes, entrevista a docentes). </span><s= pan style=3D"font-weight:bold">Resultados: </span><span>el an=C3=A1lisis de= datos se realiz=C3=B3 mediante distribuci=C3=B3n de frecuencias. La evalua= ci=C3=B3n se centr=C3=B3 en cuatro dimensiones con sus indicadores: compren= si=C3=B3n conceptual, procedimientos-operatividad, representaci=C3=B3n comu= nicaci=C3=B3n, actitudes y metacognici=C3=B3n. El diagn=C3=B3stico inicial = mostr=C3=B3 una comprensi=C3=B3n global reducida tanto en procedimientos, r= epresentaci=C3=B3n, comunicaci=C3=B3n y una baja autorregulaci=C3=B3n. Se d= ise=C3=B1=C3=B3 un sistema de actividades con PhET que incluye objetivos es= pec=C3=ADficos, orientaciones, trabajo con el simulador y evaluaci=C3=B3n. = </span><span style=3D"font-weight:bold">Conclusiones: </span><span>tras la = implementaci=C3=B3n en el proceso de ense=C3=B1anza-aprendizaje los resulta= dos mejoraron significativamente todos los indicadores evaluados a excepci= =C3=B3n del promedio simple que se mantuvo con el mismo valor. Adem=C3=A1s,= se reflej=C3=B3 alta aceptaci=C3=B3n y factibilidad por parte de los estud= iantes. </span><span style=3D"font-weight:bold">=C3=81rea de estudio genera= l:</span><span> educaci=C3=B3n. </span><span style=3D"font-weight:bold">=C3= =81rea de estudio espec=C3=ADfica</span><span>: Tecnolog=C3=ADa educativa. = </span><span style=3D"font-weight:bold; background-color:#ffffff">Tipo de e= studio:</span><span style=3D"background-color:#ffffff">  </span><span = style=3D"background-color:#ffffff">Art=C3=ADculo original.</span></p></td><= /tr><tr><td style=3D"width:73.75pt; border-top:0.75pt solid #000000; border= -right:0.75pt solid #000000; padding:0pt 5.03pt; vertical-align:top"><p cla= ss=3D"Title" style=3D"margin-top:6pt; margin-bottom:12pt; text-align:justif= y; line-height:115%; font-size:12pt"><span style=3D"font-family:'Times New = Roman'; font-weight:bold">Keywords:</span><span style=3D"font-family:'Times= New Roman'"> Adult education; fractions; PhET simulations; andragogy. </sp= an></p></td><td style=3D"width:5.3pt; border-top:0.75pt solid #000000; bord= er-right:0.75pt solid #000000; border-left:0.75pt solid #000000; padding:0p= t 5.03pt; vertical-align:top"><p class=3D"Title" style=3D"margin-top:6pt; m= argin-bottom:12pt; text-align:justify; line-height:115%; font-size:12pt"><s= pan style=3D"font-family:'Times New Roman'; font-weight:bold"> </span>= </p></td><td style=3D"width:324.9pt; border-top:0.75pt solid #000000; borde= r-left:0.75pt solid #000000; padding:0pt 5.03pt; vertical-align:top"><p sty= le=3D"margin-bottom:0pt; text-align:justify; line-height:115%"><span style= =3D"background-color:#ffffff">Abstract</span></p><p style=3D"margin-bottom:= 0pt; text-align:justify; line-height:115%"><span style=3D"font-weight:bold"= >Introduction: </span><span>The learning of fractions in adults requires ac= tive didactic strategies with digital technologies. In this sense, simulati= ons are a valuable resource by providing an interactive environment. </span= ><span style=3D"font-weight:bold">Objectives: </span><span>This research ai= med to design a system of activities through the integration of PHET Intera= ctive Simulation to strengthen the learning of mathematical fractions in ad= ults aged 40+ years in the night modality of the PCEI Rumi=C3=B1ahui Basic = Education School. </span><span style=3D"font-weight:bold">Methodology: </sp= an><span>The study adopted a mixed, applied and field approach, with a desc= riptive-propositional scope. He used theoretical (analytical-synthetic, ind= uctive-deductive, modeling) and empirical (diagnostic test, student survey,= teacher interview) methods. </span><span style=3D"font-weight:bold">Result= s: </span><span>Data analysis was performed using frequency distribution. T= he evaluation focused on four dimensions with their indicators: conceptual = understanding, procedures-operability, representation, communication, attit= udes, and metacognition. The initial diagnosis showed reduced global unders= tanding in procedures, representation, communication, and low self-regulati= on. A system of activities with PhET was designed that includes specific ob= jectives, orientations, work with the simulator and evaluation. </span><spa= n style=3D"font-weight:bold">Conclusions: </span><span>after implementation= in the teaching-learning process, the results significantly improved all t= he indicators evaluated, except for the simple average, which remained with= the same value. In addition, high acceptance and feasibility by the studen= ts was reflected. </span><span style=3D"font-weight:bold">General area of s= tudy:</span><span> education. </span><span style=3D"font-weight:bold">Speci= fic area of study</span><span>: Educational technology. </span><span style= =3D"font-weight:bold; background-color:#ffffff">Type of study:</span><span = style=3D"background-color:#ffffff"> Original article.</span></p></td></tr><= /table><p class=3D"Default" style=3D"margin-bottom:10pt; line-height:115%">= <span style=3D"font-weight:bold"> </span></p><p class=3D"ListParagraph= " style=3D"margin-bottom:0pt; text-indent:-18pt; text-align:justify; line-h= eight:115%"><span style=3D"font-weight:bold"><span>1.</span></span><span st= yle=3D"width:9pt; font:7pt 'Times New Roman'; display:inline-block"> &= #xa0;    </span><span style=3D"font-weight:bold">Introducci= =C3=B3n</span></p><p style=3D"margin-bottom:0pt; text-align:justify; line-h= eight:115%"><span>La reintegraci=C3=B3n de adultos mayores de 40 a=C3=B1os = en la educaci=C3=B3n formal, especialmente en programas de educaci=C3=B3n b= =C3=A1sica y secundaria para aprendices con escolarizaci=C3=B3n discontinua= , es un fen=C3=B3meno educativo cada vez m=C3=A1s importante en Am=C3=A9ric= a Latina (Salinas & Negri, 2020). El regreso a la escolarizaci=C3=B3n r= epresenta mucho m=C3=A1s que un objetivo acad=C3=A9mico: es una transformac= i=C3=B3n personal multifac=C3=A9tica, un logro de metas postergadas y, en m= uchos casos, una postura desafiante frente a adversidades sociales, econ=C3= =B3micas y estructurales que hist=C3=B3ricamente limitaron sus oportunidade= s educativas (Banco de Desarrollo de Am=C3=A9rica Latina y el Caribe [CAF-b= anco], 2024). Estos estudiantes que durante mucho tiempo ejercieron roles c= omo trabajadores, madres y padres, o cuidadores, regresan a clase motivados= y con ricas experiencias, pero tambi=C3=A9n con brechas en su formaci=C3= =B3n, temores respecto al contenido acad=C3=A9mico e influenciados por fact= ores externos que impactan directamente en sus procesos de aprendizaje (Org= anizaci=C3=B3n de las Naciones Unidas para la Educaci=C3=B3n, la Ciencia y = la Cultura UNESCO, 2024). </span></p><p style=3D"margin-bottom:0pt; text-al= ign:justify; line-height:115%"><span>A diferencia de los estudiantes m=C3= =A1s j=C3=B3venes, los adultos enfrentan un entorno de aprendizaje que se r= ealiza de manera paralela con obligaciones laborales, familiares y sociales= . Todas estas responsabilidades, combinadas con la ansiedad acad=C3=A9mica,= posibles dificultades respecto al uso de herramientas digitales o software= y otras preocupaciones crean desaf=C3=ADos muy distintos que un educador d= ebe abordar con estrategias especializadas (=C3=81vila, 2018). M=C3=A1s rec= ientemente Terhune et</span><span> </span><span>al. (2021) y Stojanovi= c (2022) comparten la opini=C3=B3n de que los adultos mayores que regresan = a estudiar a menudo se enfrentan a barreras significativas: baja autoestima= en sus habilidades cognitivas, ausencia de rutinas de estudio, actitudes i= nflexibles hacia la tecnolog=C3=ADa educativa, marcos curriculares insufici= entes que se alineen con sus intereses y contextos de vida. </span></p><p s= tyle=3D"margin-bottom:0pt; text-align:justify; line-height:115%"><span>Desd= e una perspectiva latinoamericana el </span><span style=3D"text-decoration:= underline">Banco de Desarrollo de Am=C3=A9rica Latina y el Caribe</span><sp= an> (CAF-banco, 2024) se=C3=B1ala que estos problemas se ven agravados por = las inequidades estructurales del sistema educativo, como la inadecuada for= maci=C3=B3n de maestros en educaci=C3=B3n de adultos, falta de herramientas= tecnol=C3=B3gicas pedag=C3=B3gicas adecuadas e infraestructura, y el acces= o persistentemente desigual a la tecnolog=C3=ADa y al internet. </span></p>= <p style=3D"margin-bottom:0pt; text-align:justify; line-height:115%"><span>= Un enfoque educativo para adultos requiere un cambio en la metodolog=C3=ADa= aplicada y, por lo tanto, debe sustentarse en un marco te=C3=B3rico que co= nsidere sus particularidades. La andragog=C3=ADa, se define como la ciencia= que se encarga de facilitar el aprendizaje en los adultos, por lo que cobr= a gran importancia en este punto. Desde los a=C3=B1os 70, la andragog=C3=AD= a propuesta por Malcolm Knowles (2020) se aleja de los modelos de ense=C3= =B1anza infantil y se enfoca en el aprendizaje centrado en el alumno que, a= dem=C3=A1s, valora su experiencia vital, demanda autonom=C3=ADa y busca res= olver problemas que le son =C3=BAtiles. Esta manera de ver la educaci=C3=B3= n no solo implica el uso de una metodolog=C3=ADa activa, participativa y si= gnificativa. Adem=C3=A1s, transforma la figura del docente en un mediador f= acilitador y no solo emisor unidireccional de informaci=C3=B3n (Note et</sp= an><span> </span><span>al., 2021).</span></p><p style=3D"margin-bottom= :0pt; text-align:justify; line-height:115%"><span>En t=C3=A9rminos pr=C3=A1= cticos, la implementaci=C3=B3n de la andragog=C3=ADa en entornos educativos= reales requiere una adaptaci=C3=B3n precisa de las estrategias de ense=C3= =B1anza. El dise=C3=B1o de actividades debe tener en cuenta la diversidad d= el grupo adulto, incorporar sus experiencias previas como recursos valiosos= y fomentar la colaboraci=C3=B3n activa y la reflexi=C3=B3n cr=C3=ADtica (M= elliofatria et</span><span> </span><span>al., 2024). El aprendizaje de= los adultos se potencia por el compromiso del aprendiz en definir sus obje= tivos, la relevancia directa del contenido para la vida cotidiana y la perc= epci=C3=B3n de un entorno educativo seguro, respetuoso y motivador (Knowles= , 2020). Los contextos europeos desarrollaron a=C3=BAn m=C3=A1s esta perspe= ctiva con enfoques socio comunitarios que enfatizan la importancia del apre= ndizaje como una experiencia colectiva, transformadora y liberadora, expres= ada mediante los t=C3=A9rminos =E2=80=9Caprendizaje para la vida=E2=80=9D y= =E2=80=9Cmomentos de comunidad=E2=80=9D (Efgivia et</span><span> </sp= an><span>al., 2021).</span></p><p style=3D"margin-bottom:0pt; text-align:ju= stify; line-height:115%"><span>El aprendizaje de la matem=C3=A1tica en los = adultos requiere atenci=C3=B3n de los aprendices debido a los altos niveles= de ansiedad que este contenido puede inducir, m=C3=A1s a=C3=BAn en individ= uos con trayectorias educativas interrumpidas. La ense=C3=B1anza de la mate= m=C3=A1tica desde una perspectiva andrag=C3=B3gica requiere romper modelos = tradicionales que se centran en el aprendizaje mec=C3=A1nico de f=C3=B3rmul= as a trav=C3=A9s de la aplicaci=C3=B3n de algoritmos, hacia uno centrado en= la comprensi=C3=B3n, la resoluci=C3=B3n de problemas, la identificaci=C3= =B3n de desaf=C3=ADos significativos y la conexi=C3=B3n con experiencias re= ales (El-Amin, 2020). </span></p><p style=3D"margin-bottom:0pt; text-align:= justify; line-height:115%"><span>Estudios realizados por S=C3=A1nchez-Domen= ech & Cabeza-Rodr=C3=ADguez (2024) y Perry et</span><span> </span>= <span>al. (2025) indican que los adultos tienen una mayor eficacia en el ap= rendizaje de la matem=C3=A1tica cuando el contenido se conecta con su vida = diaria, actividades profesionales o comunitarias, as=C3=AD como cuando se l= es permite explorar, cometer errores y construir conocimiento de manera seg= ura.</span></p><p style=3D"margin-bottom:0pt; text-align:justify; line-heig= ht:115%"><span>En este contexto, las tecnolog=C3=ADas digitales emergen com= o aliados fundamentales para transformar las pr=C3=A1cticas educativas. Int= egrarlas en los diversos entornos de ense=C3=B1anza y aprendizaje ayuda a a= mpliar la variedad de formas de acceder a la informaci=C3=B3n de manera vis= ual, interactiva y con contenido atractivo para ofrecer experiencias format= ivas m=C3=A1s contextualizadas (S=C3=A1nchez-Domenech & Cabeza-Rodr=C3= =ADguez, 2024). En particular los simuladores digitales educativos ganaron = prominencia como herramientas innovadoras que permiten la representaci=C3= =B3n de fen=C3=B3menos abstractos o complejos a trav=C3=A9s de entornos int= eractivos, seguros y controlados (Almadrones & Tadifa, 2024). Al permit= ir la manipulaci=C3=B3n de variables, la observaci=C3=B3n instant=C3=A1nea = de resultados y la toma de decisiones independiente, los simuladores foment= an un aprendizaje activo y significativo de acuerdo con los principios de l= a andragog=C3=ADa y las expectativas del siglo XXI (Diab et</span><span>&#x= a0;</span><span>al., 2024).</span></p><p style=3D"margin-bottom:0pt; text-a= lign:justify; line-height:115%"><span>Entre estas herramientas, vale la pen= a destacar las simulaciones interactivas desarrolladas por el </span><span = style=3D"text-decoration:underline">Proyecto de Simulaciones Interactivas P= hET</span><span> de la Universidad de Colorado. Aunque estas simulaciones f= ueron dise=C3=B1adas inicialmente para apoyar la ense=C3=B1anza de la cienc= ia y las matem=C3=A1ticas, demostraron ser muy =C3=BAtiles para comprender = conceptos abstractos dif=C3=ADciles, fomentar la participaci=C3=B3n activa = de los estudiantes y el aprendizaje autodirigido (Kumar, 2024). Numerosos e= studios como los de Garc=C3=ADa (2019) o Acquah et</span><span> </span= ><span>al. (2024) documentaron el impacto positivo de PhET en el rendimient= o acad=C3=A9mico, la motivaci=C3=B3n y las habilidades de pensamiento cr=C3= =ADtico, especialmente en situaciones donde los recursos educativos tradici= onales disponibles son inadecuados o mal adaptados a las necesidades de los= estudiantes.</span></p><p style=3D"margin-bottom:0pt; text-align:justify; = line-height:115%"><span>Por otra parte uno de los temas m=C3=A1s complejos = relacionados con la ense=C3=B1anza-aprendizaje de la matem=C3=A1tica en la = etapa adulta, son las fracciones. Sin embargo con las simulaciones PhET es = posible mostrar con ilustraciones el proceso de manipular y trabajar con fr= acciones, as=C3=AD como sumar, restar y comparar valores de forma intuitiva= . Para estudiantes adultos, especialmente aquellos mayores de 40 a=C3=B1os = que regresan a la educaci=C3=B3n formal, estas representaciones din=C3=A1mi= cas suponen un lazo entre el saber abstracto y la vivencia concreta, por lo= que ayuda a otorgar una comprensi=C3=B3n m=C3=A1s profunda. La utilizaci= =C3=B3n de PhET puede potenciar el rol del aprendiz en el desarrollo de hab= ilidades, calmar la ansiedad y construir una experiencia accesible, motivan= te e inclusiva.</span></p><p style=3D"margin-bottom:0pt; text-align:justify= ; line-height:115%"><span>Un ejemplo representativo de esta situaci=C3=B3n = se observa en la </span><span style=3D"text-decoration:underline">Escuela d= e Educaci=C3=B3n B=C3=A1sica PCEI Rumi=C3=B1ahui</span><span>, ubicada en l= a ciudad de Guayaquil. En su modalidad nocturna dirigida a personas mayores= de 18 a=C3=B1os, se identific=C3=B3 una problem=C3=A1tica concreta: estudi= antes mayores de 40 a=C3=B1os presentan serias dificultades en el aprendiza= je de las matem=C3=A1ticas. Estos alumnos manifiestan desconexi=C3=B3n con = los contenidos curriculares, inseguridad frente a conceptos b=C3=A1sicos y = bajo rendimiento acad=C3=A9mico, lo cual influye negativamente en su perman= encia dentro del sistema educativo. En este contexto, el problema cient=C3= =ADfico que gu=C3=ADa la presente investigaci=C3=B3n radica en =C2=BFc=C3= =B3mo mejorar el aprendizaje de fracciones matem=C3=A1ticas en adultos mayo= res de 40 a=C3=B1os?</span></p><p style=3D"margin-bottom:0pt; text-align:ju= stify; line-height:115%"><span>En este sentido, el objetivo general de esta= investigaci=C3=B3n es dise=C3=B1ar un sistema de actividades mediante la i= ntegraci=C3=B3n de </span><span style=3D"font-style:italic; text-decoration= :underline">PHET Interactive Simulation</span><span> para fortalecer el apr= endizaje de fracciones matem=C3=A1ticas en adultos de 40+ a=C3=B1os en la m= odalidad nocturna de la </span><span style=3D"text-decoration:underline">Es= cuela de Educaci=C3=B3n B=C3=A1sica PCEI Rumi=C3=B1ahui</span><span>. Esta = propuesta no solo pretende mejorar el aprendizaje, sino tambi=C3=A9n contri= buir al desarrollo de una educaci=C3=B3n m=C3=A1s inclusiva, adaptada y ori= entada a las necesidades reales de los aprendices adultos.</span></p><p sty= le=3D"margin-bottom:0pt; line-height:115%"><span style=3D"font-weight:bold"= > </span></p><p class=3D"ListParagraph" style=3D"margin-bottom:0pt; te= xt-indent:-18pt; line-height:115%"><span style=3D"font-weight:bold"><span>2= .</span></span><span style=3D"width:9pt; font:7pt 'Times New Roman'; displa= y:inline-block">      </span><span style=3D"font-w= eight:bold">Metodolog=C3=ADa</span></p><p style=3D"margin-bottom:0pt; text-= align:justify; line-height:115%"><span>La presente investigaci=C3=B3n adopt= =C3=B3 un enfoque mixto ya que combina el an=C3=A1lisis de datos cuantitati= vos a partir de la aplicaci=C3=B3n de una prueba diagn=C3=B3stica y la medi= ci=C3=B3n del progreso acad=C3=A9mico de los estudiantes mediante un an=C3= =A1lisis cualitativo de necesidades y percepciones. Asimismo, es una invest= igaci=C3=B3n aplicada y de campo, ya que responde a la necesidad de observa= r el objeto de estudio en la modalidad nocturna de la </span><span style=3D= "text-decoration:underline">Escuela PCEI Rumi=C3=B1ahui</span><span>. </spa= n></p><p style=3D"margin-bottom:0pt; text-align:justify; line-height:115%">= <span>En cuanto a su alcance, la investigaci=C3=B3n es descriptivo-proposit= iva, ya que primero se caracterizan las dificultades en el aprendizaje de l= as fracciones en adultos de 40 + a=C3=B1os y a partir del diagn=C3=B3stico = se dise=C3=B1a un sistema de actividades sustentado en simulaciones PhET.</= span></p><p style=3D"margin-bottom:0pt; text-align:justify; line-height:115= %"><span>En la investigaci=C3=B3n se emplearon varios m=C3=A9todos que perm= itieron guiar cada una de las fases investigativas. Desde el punto de vista= te=C3=B3rico, se aplicaron los m=C3=A9todos anal=C3=ADtico-sint=C3=A9tico = e inductivo-deductivo para el an=C3=A1lisis de los conceptos relacionados c= on el aprendizaje de fracciones, la andragog=C3=ADa y los simuladores PhET.= Mientras que la modelaci=C3=B3n se utiliz=C3=B3 para el dise=C3=B1o de la = propuesta. </span></p><p style=3D"margin-bottom:0pt; text-align:justify; li= ne-height:115%"><span>Para la recolecci=C3=B3n de datos se emplearon m=C3= =A9todos emp=C3=ADricos. Se aplic=C3=B3 una prueba diagn=C3=B3stica que eva= lu=C3=B3 el aprendizaje de fracciones (parte-todo, equivalencias, operacion= es y representaci=C3=B3n) con el fin de identificar errores frecuentes y fo= calizar la intervenci=C3=B3n. Asimismo, se implement=C3=B3 una encuesta a e= studiantes para recabar percepciones sobre actitudes, niveles de comprensi= =C3=B3n, uso pr=C3=A1ctico y comunicaci=C3=B3n de las fracciones. El tratam= iento estad=C3=ADstico de los datos se realiz=C3=B3 mediante an=C3=A1lisis = de distribuci=C3=B3n de frecuencias. Adem=C3=A1s, se aplic=C3=B3 una entrev= ista a docentes, que permiti=C3=B3 caracterizar el contexto, documentar dif= icultades observadas, el uso de estrategias did=C3=A1cticas y de tecnolog= =C3=ADas digitales. </span></p><p style=3D"margin-bottom:0pt; text-align:ju= stify; line-height:115%"><span>La poblaci=C3=B3n de estudio son los estudia= ntes de la modalidad nocturna de la </span><span style=3D"text-decoration:u= nderline">Escuela de Educaci=C3=B3n B=C3=A1sica PCEI Rumi=C3=B1ahui</span><= span>, ubicada en la ciudad de Guayaquil. La unidad de an=C3=A1lisis estuvo= compuesta por adultos mayores de 40 a=C3=B1os matriculados en este program= a educativo. </span></p><p style=3D"margin-bottom:0pt; text-align:justify; = line-height:115%"><span>Para seleccionar la muestra, se aplicaron criterios= de reclutamiento basados en inclusi=C3=B3n, tales como: ser un estudiante = matriculado en el turno nocturno, tener un m=C3=ADnimo de 40 a=C3=B1os y as= istencia regular a las clases de matem=C3=A1ticas. Como criterios de exclus= i=C3=B3n, se consideraron a los estudiantes menores de 40 a=C3=B1os, o aque= llos que indicaron dificultades cognitivas severas que obstaculizan su capa= cidad para participar activamente en la recolecci=C3=B3n de datos o en la p= ropuesta de intervenci=C3=B3n. Los participantes que no presenten el consen= timiento informado o se retiren antes de finalizar la recolecci=C3=B3n de d= atos fueron eliminados de la muestra. En total, la muestra estuvo compuesta= por 10 estudiantes que cumplieron con los criterios anteriormente descrito= s.</span></p><p style=3D"margin-bottom:0pt; text-align:justify; line-height= :115%"><span>Con respecto a los aspectos =C3=A9ticos, la investigaci=C3=B3n= se llev=C3=B3 a cabo observando los principios de respeto, confidencialida= d y consentimiento libre e informado. En este caso, se realiz=C3=B3 una sol= icitud de autorizaci=C3=B3n institucional al director de la </span><span st= yle=3D"text-decoration:underline">Escuela de Educaci=C3=B3n B=C3=A1sica PCE= I Rumi=C3=B1ahui</span><span>. Se elabor=C3=B3 un formulario de consentimie= nto informado que fue entregado a los participantes donde se asegur=C3=B3 u= na participaci=C3=B3n voluntaria, an=C3=B3nima y desvinculada de cualquier = repercusi=C3=B3n acad=C3=A9mica. No se llevaron a cabo procedimientos que c= ausen da=C3=B1o de ninguna naturaleza, ya sea f=C3=ADsico, emocional o psic= ol=C3=B3gico a los involucrados.</span></p><p style=3D"margin-bottom:0pt; t= ext-align:justify; line-height:115%"><span>Como se observa en la </span><sp= an style=3D"font-weight:bold">Tabla 1</span><span style=3D"color:#ee0000"> = </span><span>para realizar la operacionalizaci=C3=B3n de categor=C3=ADas de= an=C3=A1lisis se parti=C3=B3 de los resultados te=C3=B3ricos planteados po= r </span><span style=3D"text-decoration:underline">National Research Counci= l</span><span> (2001) quienes se=C3=B1alan que el aprendizaje de fracciones= se articula en cuatro dimensiones fundamentales: la comprensi=C3=B3n conce= ptual, que posibilita reconocer la fracci=C3=B3n como relaci=C3=B3n parte= =E2=80=93todo, raz=C3=B3n y operador, estableciendo conexiones entre repres= entaciones y significados; los procedimientos y habilidades operativas, que= implican dominar algoritmos, transformaciones equivalentes y estrategias d= e c=C3=A1lculo exacto o estimativo para resolver problemas; la representaci= =C3=B3n y comunicaci=C3=B3n matem=C3=A1tica, orientada a expresar ideas fra= ccionarias en registros num=C3=A9ricos, gr=C3=A1ficos, pict=C3=B3ricos y ve= rbales, argumentando y socializando razonamientos con precisi=C3=B3n; y la = actitud y metacognici=C3=B3n, que fomenta la autorregulaci=C3=B3n, el monit= oreo de estrategias, la reflexi=C3=B3n cr=C3=ADtica sobre el propio desempe= =C3=B1o y una disposici=C3=B3n positiva hacia la resoluci=C3=B3n de situaci= ones novedosas vinculadas a las fracciones.</span></p><p style=3D"margin-bo= ttom:0pt; text-align:justify; line-height:115%"><span> </span></p><p s= tyle=3D"margin-bottom:0pt; text-align:center; line-height:115%"><span style= =3D"font-weight:bold">Tabla 1</span></p><p style=3D"margin-bottom:0pt; text= -align:center; line-height:115%"><span style=3D"font-style:italic">Operacio= nalizaci=C3=B3n de categor=C3=ADas de an=C3=A1lisis</span></p><table style= =3D"margin-bottom:0pt; padding:0pt; border-collapse:collapse"><tr><td style= =3D"border-top:0.75pt solid #000000; border-bottom:0.75pt solid #000000; pa= dding:0pt 5.4pt; vertical-align:middle"><p style=3D"margin-bottom:0pt; text= -align:center; line-height:115%; font-size:10pt"><span>Categor=C3=ADa princ= ipal</span></p></td><td style=3D"width:74.6pt; border-top:0.75pt solid #000= 000; border-bottom:0.75pt solid #000000; padding:0pt 5.4pt; vertical-align:= middle"><p style=3D"margin-bottom:0pt; text-align:center; line-height:115%;= font-size:10pt"><span>Dimensi=C3=B3n</span></p></td><td style=3D"width:215= .7pt; border-top:0.75pt solid #000000; border-bottom:0.75pt solid #000000; = padding:0pt 5.4pt; vertical-align:middle"><p style=3D"margin-bottom:0pt; te= xt-align:center; line-height:115%; font-size:10pt"><span>Indicadores</span>= </p></td></tr><tr><td rowspan=3D"4" style=3D"border-top:0.75pt solid #00000= 0; border-bottom:0.75pt solid #000000; padding:0pt 5.4pt; vertical-align:mi= ddle"><p style=3D"margin-bottom:0pt; text-align:center; line-height:115%; f= ont-size:10pt"><span>Aprendizaje de fracciones</span></p></td><td style=3D"= width:74.6pt; border-top:0.75pt solid #000000; border-bottom:0.75pt solid #= 000000; padding:0pt 5.4pt; vertical-align:middle"><p style=3D"margin-bottom= :0pt; text-align:center; line-height:115%; font-size:10pt"><span>Comprensi= =C3=B3n conceptual</span></p></td><td style=3D"width:215.7pt; border-top:0.= 75pt solid #000000; border-bottom:0.75pt solid #000000; padding:0pt 5.4pt; = vertical-align:middle"><p class=3D"ListParagraph" style=3D"margin-left:21.9= 5pt; margin-bottom:0pt; text-indent:-18pt; line-height:115%; font-size:10pt= "><span><span>=E2=80=A2</span></span><span style=3D"width:14.5pt; font:7pt = 'Times New Roman'; display:inline-block">      = 0;    </span><span>Reconoce y explica el concepto de fracci= =C3=B3n como parte de un todo.</span></p><p class=3D"ListParagraph" style= =3D"margin-left:21.95pt; margin-bottom:0pt; text-indent:-18pt; line-height:= 115%; font-size:10pt"><span><span>=E2=80=A2</span></span><span style=3D"wid= th:14.5pt; font:7pt 'Times New Roman'; display:inline-block">  &#= xa0;       </span><span>Comprende la equivale= ncia entre fracciones y la formaci=C3=B3n de la unidad.</span></p></td></tr= ><tr><td style=3D"width:74.6pt; border-top:0.75pt solid #000000; border-bot= tom:0.75pt solid #000000; padding:0pt 5.4pt; vertical-align:middle"><p styl= e=3D"margin-bottom:0pt; text-align:center; line-height:115%; font-size:10pt= "><span>Procedimientos y habilidades operativas</span></p></td><td style=3D= "width:215.7pt; border-top:0.75pt solid #000000; border-bottom:0.75pt solid= #000000; padding:0pt 5.4pt; vertical-align:middle"><p class=3D"ListParagra= ph" style=3D"margin-left:21.95pt; margin-bottom:0pt; text-indent:-18pt; lin= e-height:115%; font-size:10pt"><span><span>=E2=80=A2</span></span><span sty= le=3D"width:14.5pt; font:7pt 'Times New Roman'; display:inline-block"> = ;         </span><span>Realiza oper= aciones b=C3=A1sicas con fracciones (suma, resta, multiplicaci=C3=B3n, divi= si=C3=B3n).</span></p><p class=3D"ListParagraph" style=3D"margin-left:21.95= pt; margin-bottom:0pt; text-indent:-18pt; line-height:115%; font-size:10pt"= ><span><span>=E2=80=A2</span></span><span style=3D"width:14.5pt; font:7pt '= Times New Roman'; display:inline-block">      = ;    </span><span>Resuelve problemas pr=C3=A1cticos que invo= lucran fracciones.</span></p></td></tr><tr><td style=3D"width:74.6pt; borde= r-top:0.75pt solid #000000; border-bottom:0.75pt solid #000000; padding:0pt= 5.4pt; vertical-align:middle"><p style=3D"margin-bottom:0pt; text-align:ce= nter; line-height:115%; font-size:10pt"><span>Representaci=C3=B3n y comunic= aci=C3=B3n matem=C3=A1tica</span></p></td><td style=3D"width:215.7pt; borde= r-top:0.75pt solid #000000; border-bottom:0.75pt solid #000000; padding:0pt= 5.4pt; vertical-align:middle"><p class=3D"ListParagraph" style=3D"margin-l= eft:21.95pt; margin-bottom:0pt; text-indent:-18pt; line-height:115%; font-s= ize:10pt"><span><span>=E2=80=A2</span></span><span style=3D"width:14.5pt; f= ont:7pt 'Times New Roman'; display:inline-block">    &#= xa0;     </span><span>Expresa fracciones mediante diver= sas representaciones (dibujos, modelos manipulativos, s=C3=ADmbolos).</span= ></p><p class=3D"ListParagraph" style=3D"margin-left:21.95pt; margin-bottom= :0pt; text-indent:-18pt; line-height:115%; font-size:10pt"><span><span>=E2= =80=A2</span></span><span style=3D"width:14.5pt; font:7pt 'Times New Roman'= ; display:inline-block">        &#x= a0; </span><span>Comunica razonamientos y estrategias para comparar y opera= r con fracciones.</span></p></td></tr><tr><td style=3D"width:74.6pt; border= -top:0.75pt solid #000000; border-bottom:0.75pt solid #000000; padding:0pt = 5.4pt; vertical-align:middle"><p style=3D"margin-bottom:0pt; text-align:cen= ter; line-height:115%; font-size:10pt"><span>Actitudes y metacognici=C3=B3n= </span></p></td><td style=3D"width:215.7pt; border-top:0.75pt solid #000000= ; border-bottom:0.75pt solid #000000; padding:0pt 5.4pt; vertical-align:mid= dle"><p class=3D"ListParagraph" style=3D"margin-left:21.95pt; margin-bottom= :0pt; text-indent:-18pt; line-height:115%; font-size:10pt"><span><span>=E2= =80=A2</span></span><span style=3D"width:14.5pt; font:7pt 'Times New Roman'= ; display:inline-block">        &#x= a0; </span><span>Muestra inter=C3=A9s y persistencia en el aprendizaje de f= racciones.</span></p><p class=3D"ListParagraph" style=3D"margin-left:21.95p= t; margin-bottom:0pt; text-indent:-18pt; line-height:115%; font-size:10pt">= <span><span>=E2=80=A2</span></span><span style=3D"width:14.5pt; font:7pt 'T= imes New Roman'; display:inline-block">      =     </span><span>Utiliza estrategias para autoevaluar y corr= egir errores.</span></p></td></tr></table><p style=3D"margin-bottom:0pt; li= ne-height:115%"><span style=3D"font-weight:bold"> </span></p><p class= =3D"ListParagraph" style=3D"margin-bottom:0pt; text-indent:-18pt; line-heig= ht:115%"><span style=3D"font-weight:bold"><span>3.</span></span><span style= =3D"width:9pt; font:7pt 'Times New Roman'; display:inline-block">  = 0;    </span><span style=3D"font-weight:bold">Resultados </s= pan></p><p style=3D"margin-bottom:0pt; line-height:115%"><span style=3D"fon= t-style:italic"> </span></p><p style=3D"text-align:justify"><span>En l= a presente secci=C3=B3n se exponen los hallazgos obtenidos de los instrumen= tos de diagn=C3=B3stico, encuesta y entrevista, as=C3=AD como la implementa= ci=C3=B3n del sistema de actividades dise=C3=B1ado con el uso de las simula= ciones interactivas PhET. Se presentan los datos organizados de acuerdo con= las dimensiones de an=C3=A1lisis previamente establecidas, con el prop=C3= =B3sito de ofrecer una visi=C3=B3n clara y estructurada del desempe=C3=B1o = y las percepciones de los participantes antes y despu=C3=A9s de la interven= ci=C3=B3n.</span></p><p style=3D"margin-bottom:0pt; line-height:115%"><span= style=3D"font-style:italic"> </span></p><p class=3D"ListParagraph" st= yle=3D"margin-bottom:0pt; text-indent:-18pt; line-height:115%"><span style= =3D"font-style:italic"><span>3.1.</span></span><span style=3D"font-style:it= alic"> Prueba diagn=C3=B3stica</span></p><p style=3D"margin-bottom:0pt; tex= t-align:justify; line-height:115%"><span>En la dimensi=C3=B3n de comprensi= =C3=B3n conceptual los resultados evidencian un dominio muy limitado: s=C3= =B3lo el 20=E2=80=AF% de los estudiantes reconoci=C3=B3 la equivalencia num= =C3=A9rica de fracciones, mientras que la representaci=C3=B3n gr=C3=A1fica,= la identificaci=C3=B3n de partes y la noci=C3=B3n misma de fracci=C3=B3n m= arcaron 0=E2=80=AF% de aciertos. El porcentaje global de =C3=A9xito en este= bloque es apenas del 5=E2=80=AF%, lo que indica dificultades severas en la= s ideas b=C3=A1sicas sobre la fracci=C3=B3n y la relaci=C3=B3n numerador</s= pan><span>‑</span><span>denominador, requiriendo intervenci=C3=B3n p= rioritaria y actividades manipulativas.</span></p><p style=3D"margin-bottom= :0pt; text-align:justify; line-height:115%"><span>En procedimientos y habil= idades operativas el desempe=C3=B1o muestra contrastes marcados. Los estudi= antes resolvieron con soltura la suma de fracciones con denominador com=C3= =BAn (80=E2=80=AF% de aciertos), pero cayeron a 20=E2=80=AF% en la resta y = 0=E2=80=AF% en los dos =C3=ADtems de promedios, elevando s=C3=B3lo hasta 25= =E2=80=AF% el =C3=A9xito global de la categor=C3=ADa. El patr=C3=B3n sugier= e que las destrezas algor=C3=ADtmicas b=C3=A1sicas se activan cuando la ope= raci=C3=B3n es directa, pero se desvanecen ante c=C3=A1lculos que requieren= interpretaci=C3=B3n o elaboraci=C3=B3n de representaciones intermedias.</s= pan></p><p style=3D"margin-bottom:0pt; text-align:justify; line-height:115%= "><span>En la dimensi=C3=B3n de representaci=C3=B3n y comunicaci=C3=B3n mat= em=C3=A1tica presenta un perfil mixto: la notaci=C3=B3n simb=C3=B3lica y la= comparaci=C3=B3n de fracciones resultaron familiares para la mayor=C3=ADa,= con 80=E2=80=AF% de respuestas correctas en ambos =C3=ADtems; sin embargo,= ning=C3=BAn estudiante consigui=C3=B3 justificar su ordenamiento por escri= to, lo que reduce el promedio de la secci=C3=B3n a 53,3=E2=80=AF%. El contr= aste revela que los alumnos pueden aplicar procedimientos aprendidos, pero = encuentran dificultades al explicar sus razonamientos, evidenciando una bre= cha entre hacer matem=C3=A1ticas y comunicar las ideas subyacentes. Los res= ultados se aprecian en la </span><span style=3D"font-weight:bold">Tabla 2</= span><span>.</span></p><p style=3D"margin-bottom:0pt; text-align:justify; l= ine-height:115%"><span> </span></p><p style=3D"margin-bottom:0pt; text= -align:center; line-height:115%"><span style=3D"font-weight:bold">Tabla 2</= span></p><p style=3D"margin-bottom:0pt; text-align:center; line-height:115%= "><span style=3D"font-style:italic">Resultados de la prueba diagn=C3=B3stic= a aplicada a los estudiantes</span></p><table style=3D"width:100%; margin-b= ottom:0pt; padding:0pt; border-collapse:collapse"><tr style=3D"height:16.5p= t"><td style=3D"width:20.36%; border-top:0.75pt solid #000000; border-botto= m:0.75pt solid #000000; padding:0pt 3.5pt; vertical-align:middle"><p style= =3D"margin-bottom:0pt; text-align:center; line-height:115%; font-size:10pt"= ><span>Tipo</span></p></td><td style=3D"width:7.94%; border-top:0.75pt soli= d #000000; border-bottom:0.75pt solid #000000; padding:0pt 3.5pt; vertical-= align:middle"><p style=3D"margin-bottom:0pt; text-align:center; line-height= :115%; font-size:10pt"><span>N=C2=BA</span></p></td><td style=3D"width:32.1= 6%; border-top:0.75pt solid #000000; border-bottom:0.75pt solid #000000; pa= dding:0pt 3.5pt; vertical-align:middle"><p style=3D"margin-bottom:0pt; text= -align:center; line-height:115%; font-size:10pt"><span>Criterio</span></p><= /td><td style=3D"width:12.92%; border-top:0.75pt solid #000000; border-bott= om:0.75pt solid #000000; padding:0pt 3.5pt; vertical-align:middle"><p style= =3D"margin-bottom:0pt; text-align:center; line-height:115%; font-size:10pt"= ><span>Correcto</span></p></td><td style=3D"width:14.38%; border-top:0.75pt= solid #000000; border-bottom:0.75pt solid #000000; padding:0pt 3.5pt; vert= ical-align:middle"><p style=3D"margin-bottom:0pt; text-align:center; line-h= eight:115%; font-size:10pt"><span>Incorrecto</span></p></td><td style=3D"wi= dth:12.24%; border-top:0.75pt solid #000000; border-bottom:0.75pt solid #00= 0000; padding:0pt 3.5pt; vertical-align:middle"><p style=3D"margin-bottom:0= pt; text-align:center; line-height:115%; font-size:10pt"><span>%=E2=80=AF= =C3=89xito</span></p></td></tr><tr style=3D"height:4.8pt"><td rowspan=3D"4"= style=3D"width:20.36%; border-top:0.75pt solid #000000; border-bottom:0.75= pt solid #000000; padding:0pt 3.5pt; vertical-align:middle"><p style=3D"mar= gin-bottom:0pt; text-align:center; line-height:115%; font-size:10pt"><span>= Comprensi=C3=B3n conceptual (CC)</span></p></td><td style=3D"width:7.94%; b= order-top:0.75pt solid #000000; border-bottom:0.75pt solid #000000; padding= :0pt 3.5pt; vertical-align:middle"><p style=3D"margin-bottom:0pt; text-alig= n:center; line-height:115%; font-size:10pt"><span>P1</span></p></td><td sty= le=3D"width:32.16%; border-top:0.75pt solid #000000; border-bottom:0.75pt s= olid #000000; padding:0pt 3.5pt; vertical-align:middle"><p style=3D"margin-= bottom:0pt; text-align:center; line-height:115%; font-size:10pt"><span>Repr= esentaci=C3=B3n de una fracci=C3=B3n</span></p></td><td style=3D"width:12.9= 2%; border-top:0.75pt solid #000000; border-bottom:0.75pt solid #000000; pa= dding:0pt 3.5pt; vertical-align:middle"><p style=3D"margin-bottom:0pt; text= -align:center; line-height:115%; font-size:10pt"><span>0</span></p></td><td= style=3D"width:14.38%; border-top:0.75pt solid #000000; border-bottom:0.75= pt solid #000000; padding:0pt 3.5pt; vertical-align:middle"><p style=3D"mar= gin-bottom:0pt; text-align:center; line-height:115%; font-size:10pt"><span>= 10</span></p></td><td style=3D"width:12.24%; border-top:0.75pt solid #00000= 0; border-bottom:0.75pt solid #000000; padding:0pt 3.5pt; vertical-align:mi= ddle"><p style=3D"margin-bottom:0pt; text-align:center; line-height:115%; f= ont-size:10pt"><span>0=E2=80=AF%</span></p></td></tr><tr style=3D"height:18= .95pt"><td style=3D"width:7.94%; border-top:0.75pt solid #000000; border-bo= ttom:0.75pt solid #000000; padding:0pt 3.5pt; vertical-align:middle"><p sty= le=3D"margin-bottom:0pt; text-align:center; line-height:115%; font-size:10p= t"><span>P2</span></p></td><td style=3D"width:32.16%; border-top:0.75pt sol= id #000000; border-bottom:0.75pt solid #000000; padding:0pt 3.5pt; vertical= -align:middle"><p style=3D"margin-bottom:0pt; text-align:center; line-heigh= t:115%; font-size:10pt"><span>Identificaci=C3=B3n de partes de una fracci= =C3=B3n</span></p></td><td style=3D"width:12.92%; border-top:0.75pt solid #= 000000; border-bottom:0.75pt solid #000000; padding:0pt 3.5pt; vertical-ali= gn:middle"><p style=3D"margin-bottom:0pt; text-align:center; line-height:11= 5%; font-size:10pt"><span>0</span></p></td><td style=3D"width:14.38%; borde= r-top:0.75pt solid #000000; border-bottom:0.75pt solid #000000; padding:0pt= 3.5pt; vertical-align:middle"><p style=3D"margin-bottom:0pt; text-align:ce= nter; line-height:115%; font-size:10pt"><span>10</span></p></td><td style= =3D"width:12.24%; border-top:0.75pt solid #000000; border-bottom:0.75pt sol= id #000000; padding:0pt 3.5pt; vertical-align:middle"><p style=3D"margin-bo= ttom:0pt; text-align:center; line-height:115%; font-size:10pt"><span>0=E2= =80=AF%</span></p></td></tr><tr style=3D"height:4.25pt"><td style=3D"width:= 7.94%; border-top:0.75pt solid #000000; border-bottom:0.75pt solid #000000;= padding:0pt 3.5pt; vertical-align:middle"><p style=3D"margin-bottom:0pt; t= ext-align:center; line-height:115%; font-size:10pt"><span>P3</span></p></td= ><td style=3D"width:32.16%; border-top:0.75pt solid #000000; border-bottom:= 0.75pt solid #000000; padding:0pt 3.5pt; vertical-align:middle"><p style=3D= "margin-bottom:0pt; text-align:center; line-height:115%; font-size:10pt"><s= pan>Equivalencia (num=C3=A9rica)</span></p></td><td style=3D"width:12.92%; = border-top:0.75pt solid #000000; border-bottom:0.75pt solid #000000; paddin= g:0pt 3.5pt; vertical-align:middle"><p style=3D"margin-bottom:0pt; text-ali= gn:center; line-height:115%; font-size:10pt"><span>2</span></p></td><td sty= le=3D"width:14.38%; border-top:0.75pt solid #000000; border-bottom:0.75pt s= olid #000000; padding:0pt 3.5pt; vertical-align:middle"><p style=3D"margin-= bottom:0pt; text-align:center; line-height:115%; font-size:10pt"><span>8</s= pan></p></td><td style=3D"width:12.24%; border-top:0.75pt solid #000000; bo= rder-bottom:0.75pt solid #000000; padding:0pt 3.5pt; vertical-align:middle"= ><p style=3D"margin-bottom:0pt; text-align:center; line-height:115%; font-s= ize:10pt"><span>20=E2=80=AF%</span></p></td></tr><tr style=3D"height:3pt"><= td style=3D"width:7.94%; border-top:0.75pt solid #000000; border-bottom:0.7= 5pt solid #000000; padding:0pt 3.5pt; vertical-align:middle"><p style=3D"ma= rgin-bottom:0pt; text-align:center; line-height:115%; font-size:10pt"><span= >P4</span></p></td><td style=3D"width:32.16%; border-top:0.75pt solid #0000= 00; border-bottom:0.75pt solid #000000; padding:0pt 3.5pt; vertical-align:m= iddle"><p style=3D"margin-bottom:0pt; text-align:center; line-height:115%; = font-size:10pt"><span>Equivalencia (representaci=C3=B3n)</span></p></td><td= style=3D"width:12.92%; border-top:0.75pt solid #000000; border-bottom:0.75= pt solid #000000; padding:0pt 3.5pt; vertical-align:middle"><p style=3D"mar= gin-bottom:0pt; text-align:center; line-height:115%; font-size:10pt"><span>= 0</span></p></td><td style=3D"width:14.38%; border-top:0.75pt solid #000000= ; border-bottom:0.75pt solid #000000; padding:0pt 3.5pt; vertical-align:mid= dle"><p style=3D"margin-bottom:0pt; text-align:center; line-height:115%; fo= nt-size:10pt"><span>10</span></p></td><td style=3D"width:12.24%; border-top= :0.75pt solid #000000; border-bottom:0.75pt solid #000000; padding:0pt 3.5p= t; vertical-align:middle"><p style=3D"margin-bottom:0pt; text-align:center;= line-height:115%; font-size:10pt"><span>0=E2=80=AF%</span></p></td></tr><t= r style=3D"height:16.5pt"><td colspan=3D"3" style=3D"border-top:0.75pt soli= d #000000; border-bottom:0.75pt solid #000000; padding:0pt 3.5pt; vertical-= align:middle"><p style=3D"margin-bottom:0pt; text-align:center; line-height= :115%; font-size:10pt"><span>Subtotal=E2=80=AFCC</span></p></td><td style= =3D"width:12.92%; border-top:0.75pt solid #000000; border-bottom:0.75pt sol= id #000000; padding:0pt 3.5pt; vertical-align:middle"><p style=3D"margin-bo= ttom:0pt; text-align:center; line-height:115%; font-size:10pt"><span>2</spa= n></p></td><td style=3D"width:14.38%; border-top:0.75pt solid #000000; bord= er-bottom:0.75pt solid #000000; padding:0pt 3.5pt; vertical-align:middle"><= p style=3D"margin-bottom:0pt; text-align:center; line-height:115%; font-siz= e:10pt"><span>38</span></p></td><td style=3D"width:12.24%; border-top:0.75p= t solid #000000; border-bottom:0.75pt solid #000000; padding:0pt 3.5pt; ver= tical-align:middle"><p style=3D"margin-bottom:0pt; text-align:center; line-= height:115%; font-size:10pt"><span>5.0=E2=80=AF%</span></p></td></tr><tr st= yle=3D"height:3pt"><td rowspan=3D"4" style=3D"width:20.36%; border-top:0.75= pt solid #000000; border-bottom:0.75pt solid #000000; padding:0pt 3.5pt; ve= rtical-align:middle"><p style=3D"margin-bottom:0pt; text-align:center; line= -height:115%; font-size:10pt"><span>Procedimientos y habilidades operativas= (PHO)</span></p></td><td style=3D"width:7.94%; border-top:0.75pt solid #00= 0000; border-bottom:0.75pt solid #000000; padding:0pt 3.5pt; vertical-align= :middle"><p style=3D"margin-bottom:0pt; text-align:center; line-height:115%= ; font-size:10pt"><span>P5</span></p></td><td style=3D"width:32.16%; border= -top:0.75pt solid #000000; border-bottom:0.75pt solid #000000; padding:0pt = 3.5pt; vertical-align:middle"><p style=3D"margin-bottom:0pt; text-align:cen= ter; line-height:115%; font-size:10pt"><span>Suma de fracciones</span></p><= /td><td style=3D"width:12.92%; border-top:0.75pt solid #000000; border-bott= om:0.75pt solid #000000; padding:0pt 3.5pt; vertical-align:middle"><p style= =3D"margin-bottom:0pt; text-align:center; line-height:115%; font-size:10pt"= ><span>8</span></p></td><td style=3D"width:14.38%; border-top:0.75pt solid = #000000; border-bottom:0.75pt solid #000000; padding:0pt 3.5pt; vertical-al= ign:middle"><p style=3D"margin-bottom:0pt; text-align:center; line-height:1= 15%; font-size:10pt"><span>2</span></p></td><td style=3D"width:12.24%; bord= er-top:0.75pt solid #000000; border-bottom:0.75pt solid #000000; padding:0p= t 3.5pt; vertical-align:middle"><p style=3D"margin-bottom:0pt; text-align:c= enter; line-height:115%; font-size:10pt"><span>80=E2=80=AF%</span></p></td>= </tr><tr style=3D"height:3pt"><td style=3D"width:7.94%; border-top:0.75pt s= olid #000000; border-bottom:0.75pt solid #000000; padding:0pt 3.5pt; vertic= al-align:middle"><p style=3D"margin-bottom:0pt; text-align:center; line-hei= ght:115%; font-size:10pt"><span>P6</span></p></td><td style=3D"width:32.16%= ; border-top:0.75pt solid #000000; border-bottom:0.75pt solid #000000; padd= ing:0pt 3.5pt; vertical-align:middle"><p style=3D"margin-bottom:0pt; text-a= lign:center; line-height:115%; font-size:10pt"><span>Resta de fracciones</s= pan></p></td><td style=3D"width:12.92%; border-top:0.75pt solid #000000; bo= rder-bottom:0.75pt solid #000000; padding:0pt 3.5pt; vertical-align:middle"= ><p style=3D"margin-bottom:0pt; text-align:center; line-height:115%; font-s= ize:10pt"><span>2</span></p></td><td style=3D"width:14.38%; border-top:0.75= pt solid #000000; border-bottom:0.75pt solid #000000; padding:0pt 3.5pt; ve= rtical-align:middle"><p style=3D"margin-bottom:0pt; text-align:center; line= -height:115%; font-size:10pt"><span>8</span></p></td><td style=3D"width:12.= 24%; border-top:0.75pt solid #000000; border-bottom:0.75pt solid #000000; p= adding:0pt 3.5pt; vertical-align:middle"><p style=3D"margin-bottom:0pt; tex= t-align:center; line-height:115%; font-size:10pt"><span>20=E2=80=AF%</span>= </p></td></tr><tr style=3D"height:3pt"><td style=3D"width:7.94%; border-top= :0.75pt solid #000000; border-bottom:0.75pt solid #000000; padding:0pt 3.5p= t; vertical-align:middle"><p style=3D"margin-bottom:0pt; text-align:center;= line-height:115%; font-size:10pt"><span>P7</span></p></td><td style=3D"wid= th:32.16%; border-top:0.75pt solid #000000; border-bottom:0.75pt solid #000= 000; padding:0pt 3.5pt; vertical-align:middle"><p style=3D"margin-bottom:0p= t; text-align:center; line-height:115%; font-size:10pt"><span>Promedio simp= le entre fracciones</span></p></td><td style=3D"width:12.92%; border-top:0.= 75pt solid #000000; border-bottom:0.75pt solid #000000; padding:0pt 3.5pt; = vertical-align:middle"><p style=3D"margin-bottom:0pt; text-align:center; li= ne-height:115%; font-size:10pt"><span>0</span></p></td><td style=3D"width:1= 4.38%; border-top:0.75pt solid #000000; border-bottom:0.75pt solid #000000;= padding:0pt 3.5pt; vertical-align:middle"><p style=3D"margin-bottom:0pt; t= ext-align:center; line-height:115%; font-size:10pt"><span>10</span></p></td= ><td style=3D"width:12.24%; border-top:0.75pt solid #000000; border-bottom:= 0.75pt solid #000000; padding:0pt 3.5pt; vertical-align:middle"><p style=3D= "margin-bottom:0pt; text-align:center; line-height:115%; font-size:10pt"><s= pan>0=E2=80=AF%</span></p></td></tr><tr style=3D"height:3pt"><td style=3D"w= idth:7.94%; border-top:0.75pt solid #000000; border-bottom:0.75pt solid #00= 0000; padding:0pt 3.5pt; vertical-align:middle"><p style=3D"margin-bottom:0= pt; text-align:center; line-height:115%; font-size:10pt"><span>P8</span></p= ></td><td style=3D"width:32.16%; border-top:0.75pt solid #000000; border-bo= ttom:0.75pt solid #000000; padding:0pt 3.5pt; vertical-align:middle"><p sty= le=3D"margin-bottom:0pt; text-align:center; line-height:115%; font-size:10p= t"><span>Promedio contextualizado entre fracciones</span></p></td><td style= =3D"width:12.92%; border-top:0.75pt solid #000000; border-bottom:0.75pt sol= id #000000; padding:0pt 3.5pt; vertical-align:middle"><p style=3D"margin-bo= ttom:0pt; text-align:center; line-height:115%; font-size:10pt"><span>0</spa= n></p></td><td style=3D"width:14.38%; border-top:0.75pt solid #000000; bord= er-bottom:0.75pt solid #000000; padding:0pt 3.5pt; vertical-align:middle"><= p style=3D"margin-bottom:0pt; text-align:center; line-height:115%; font-siz= e:10pt"><span>10</span></p></td><td style=3D"width:12.24%; border-top:0.75p= t solid #000000; border-bottom:0.75pt solid #000000; padding:0pt 3.5pt; ver= tical-align:middle"><p style=3D"margin-bottom:0pt; text-align:center; line-= height:115%; font-size:10pt"><span>0=E2=80=AF%</span></p></td></tr><tr styl= e=3D"height:3pt"><td colspan=3D"3" style=3D"border-top:0.75pt solid #000000= ; border-bottom:0.75pt solid #000000; padding:0pt 3.5pt; vertical-align:mid= dle"><p style=3D"margin-bottom:0pt; text-align:center; line-height:115%; fo= nt-size:10pt"><span>Subtotal=E2=80=AFPHO</span></p></td><td style=3D"width:= 12.92%; border-top:0.75pt solid #000000; border-bottom:0.75pt solid #000000= ; padding:0pt 3.5pt; vertical-align:middle"><p style=3D"margin-bottom:0pt; = text-align:center; line-height:115%; font-size:10pt"><span>10</span></p></t= d><td style=3D"width:14.38%; border-top:0.75pt solid #000000; border-bottom= :0.75pt solid #000000; padding:0pt 3.5pt; vertical-align:middle"><p style= =3D"margin-bottom:0pt; text-align:center; line-height:115%; font-size:10pt"= ><span>30</span></p></td><td style=3D"width:12.24%; border-top:0.75pt solid= #000000; border-bottom:0.75pt solid #000000; padding:0pt 3.5pt; vertical-a= lign:middle"><p style=3D"margin-bottom:0pt; text-align:center; line-height:= 115%; font-size:10pt"><span>25.0=E2=80=AF%</span></p></td></tr><tr style=3D= "height:3pt"><td rowspan=3D"3" style=3D"width:20.36%; border-top:0.75pt sol= id #000000; border-bottom:0.75pt solid #000000; padding:0pt 3.5pt; vertical= -align:middle"><p style=3D"margin-bottom:0pt; text-align:center; line-heigh= t:115%; font-size:10pt"><span>Representaci=C3=B3n y comunicaci=C3=B3n matem= =C3=A1tica (RCM)</span></p></td><td style=3D"width:7.94%; border-top:0.75pt= solid #000000; border-bottom:0.75pt solid #000000; padding:0pt 3.5pt; vert= ical-align:middle"><p style=3D"margin-bottom:0pt; text-align:center; line-h= eight:115%; font-size:10pt"><span>P9</span></p></td><td style=3D"width:32.1= 6%; border-top:0.75pt solid #000000; border-bottom:0.75pt solid #000000; pa= dding:0pt 3.5pt; vertical-align:middle"><p style=3D"margin-bottom:0pt; text= -align:center; line-height:115%; font-size:10pt"><span>Notaci=C3=B3n</span>= </p></td><td style=3D"width:12.92%; border-top:0.75pt solid #000000; border= -bottom:0.75pt solid #000000; padding:0pt 3.5pt; vertical-align:middle"><p = style=3D"margin-bottom:0pt; text-align:center; line-height:115%; font-size:= 10pt"><span>8</span></p></td><td style=3D"width:14.38%; border-top:0.75pt s= olid #000000; border-bottom:0.75pt solid #000000; padding:0pt 3.5pt; vertic= al-align:middle"><p style=3D"margin-bottom:0pt; text-align:center; line-hei= ght:115%; font-size:10pt"><span>2</span></p></td><td style=3D"width:12.24%;= border-top:0.75pt solid #000000; border-bottom:0.75pt solid #000000; paddi= ng:0pt 3.5pt; vertical-align:middle"><p style=3D"margin-bottom:0pt; text-al= ign:center; line-height:115%; font-size:10pt"><span>80=E2=80=AF%</span></p>= </td></tr><tr style=3D"height:3pt"><td style=3D"width:7.94%; border-top:0.7= 5pt solid #000000; border-bottom:0.75pt solid #000000; padding:0pt 3.5pt; v= ertical-align:middle"><p style=3D"margin-bottom:0pt; text-align:center; lin= e-height:115%; font-size:10pt"><span>P10</span></p></td><td style=3D"width:= 32.16%; border-top:0.75pt solid #000000; border-bottom:0.75pt solid #000000= ; padding:0pt 3.5pt; vertical-align:middle"><p style=3D"margin-bottom:0pt; = text-align:center; line-height:115%; font-size:10pt"><span>Orden de fraccio= nes</span></p></td><td style=3D"width:12.92%; border-top:0.75pt solid #0000= 00; border-bottom:0.75pt solid #000000; padding:0pt 3.5pt; vertical-align:m= iddle"><p style=3D"margin-bottom:0pt; text-align:center; line-height:115%; = font-size:10pt"><span>8</span></p></td><td style=3D"width:14.38%; border-to= p:0.75pt solid #000000; border-bottom:0.75pt solid #000000; padding:0pt 3.5= pt; vertical-align:middle"><p style=3D"margin-bottom:0pt; text-align:center= ; line-height:115%; font-size:10pt"><span>2</span></p></td><td style=3D"wid= th:12.24%; border-top:0.75pt solid #000000; border-bottom:0.75pt solid #000= 000; padding:0pt 3.5pt; vertical-align:middle"><p style=3D"margin-bottom:0p= t; text-align:center; line-height:115%; font-size:10pt"><span>80=E2=80=AF%<= /span></p></td></tr><tr style=3D"height:16.5pt"><td style=3D"width:7.94%; b= order-top:0.75pt solid #000000; border-bottom:0.75pt solid #000000; padding= :0pt 3.5pt; vertical-align:middle"><p style=3D"margin-bottom:0pt; text-alig= n:center; line-height:115%; font-size:10pt"><span>P11</span></p></td><td st= yle=3D"width:32.16%; border-top:0.75pt solid #000000; border-bottom:0.75pt = solid #000000; padding:0pt 3.5pt; vertical-align:middle"><p style=3D"margin= -bottom:0pt; text-align:center; line-height:115%; font-size:10pt"><span>Exp= licaci=C3=B3n</span></p></td><td style=3D"width:12.92%; border-top:0.75pt s= olid #000000; border-bottom:0.75pt solid #000000; padding:0pt 3.5pt; vertic= al-align:middle"><p style=3D"margin-bottom:0pt; text-align:center; line-hei= ght:115%; font-size:10pt"><span>0</span></p></td><td style=3D"width:14.38%;= border-top:0.75pt solid #000000; border-bottom:0.75pt solid #000000; paddi= ng:0pt 3.5pt; vertical-align:middle"><p style=3D"margin-bottom:0pt; text-al= ign:center; line-height:115%; font-size:10pt"><span>10</span></p></td><td s= tyle=3D"width:12.24%; border-top:0.75pt solid #000000; border-bottom:0.75pt= solid #000000; padding:0pt 3.5pt; vertical-align:middle"><p style=3D"margi= n-bottom:0pt; text-align:center; line-height:115%; font-size:10pt"><span>0= =E2=80=AF%</span></p></td></tr><tr style=3D"height:16.5pt"><td colspan=3D"3= " style=3D"border-top:0.75pt solid #000000; border-bottom:0.75pt solid #000= 000; padding:0pt 3.5pt; vertical-align:middle"><p style=3D"margin-bottom:0p= t; text-align:center; line-height:115%; font-size:10pt"><span>Subtotal=E2= =80=AFRCM</span></p></td><td style=3D"width:12.92%; border-top:0.75pt solid= #000000; border-bottom:0.75pt solid #000000; padding:0pt 3.5pt; vertical-a= lign:middle"><p style=3D"margin-bottom:0pt; text-align:center; line-height:= 115%; font-size:10pt"><span>16</span></p></td><td style=3D"width:14.38%; bo= rder-top:0.75pt solid #000000; border-bottom:0.75pt solid #000000; padding:= 0pt 3.5pt; vertical-align:middle"><p style=3D"margin-bottom:0pt; text-align= :center; line-height:115%; font-size:10pt"><span>14</span></p></td><td styl= e=3D"width:12.24%; border-top:0.75pt solid #000000; border-bottom:0.75pt so= lid #000000; padding:0pt 3.5pt; vertical-align:middle"><p style=3D"margin-b= ottom:0pt; text-align:center; line-height:115%; font-size:10pt"><span>53.3= =E2=80=AF%</span></p></td></tr></table><p style=3D"margin-bottom:0pt; line-= height:115%"><span style=3D"font-weight:bold"> </span></p><p style=3D"= margin-bottom:0pt; text-align:justify; line-height:115%"><span>En la dimens= i=C3=B3n actitudes y metacognici=C3=B3n se observa un contraste llamativo. = Ocho de los diez alumnos declaran que les resulta interesante aprender frac= ciones, lo que refleja una disposici=C3=B3n positiva hacia el contenido; si= n embargo, ninguno manifiesta un entusiasmo =E2=80=9Ctotal=E2=80=9D y dos e= xpresan completo desinter=C3=A9s. Por el contrario, la autopercepci=C3=B3n = de resiliencia es muy baja: el 100=E2=80=AF% se sit=C3=BAa en la zona de de= sacuerdo respecto a detectar y corregir sus propios errores (</span><span s= tyle=3D"font-weight:bold">Tabla 3</span><span>).</span></p><p style=3D"marg= in-bottom:0pt; line-height:115%"><span style=3D"font-weight:bold"> </s= pan></p><p style=3D"margin-bottom:0pt; text-align:center; line-height:115%"= ><span style=3D"font-weight:bold">Tabla 3</span></p><p style=3D"margin-bott= om:0pt; text-align:center; line-height:115%"><span style=3D"font-style:ital= ic">Resultados de la prueba diagn=C3=B3stica =E2=80=93 actitudes y metacogn= ici=C3=B3n</span></p><table style=3D"margin-bottom:0pt; padding:0pt; border= -collapse:collapse"><tr><td style=3D"border-top:0.75pt solid #000000; borde= r-bottom:0.75pt solid #000000; padding:0pt 5.4pt; vertical-align:middle"><p= style=3D"margin-bottom:0pt; text-align:center; line-height:115%; font-size= :10pt"><span>=C3=8Dtem</span></p></td><td style=3D"border-top:0.75pt solid = #000000; border-bottom:0.75pt solid #000000; padding:0pt 5.4pt; vertical-al= ign:middle"><p style=3D"margin-bottom:0pt; text-align:center; line-height:1= 15%; font-size:10pt"><span>TD</span></p></td><td style=3D"border-top:0.75pt= solid #000000; border-bottom:0.75pt solid #000000; padding:0pt 5.4pt; vert= ical-align:middle"><p style=3D"margin-bottom:0pt; text-align:center; line-h= eight:115%; font-size:10pt"><span>ED</span></p></td><td style=3D"border-top= :0.75pt solid #000000; border-bottom:0.75pt solid #000000; padding:0pt 5.4p= t; vertical-align:middle"><p style=3D"margin-bottom:0pt; text-align:center;= line-height:115%; font-size:10pt"><span>DA</span></p></td><td style=3D"bor= der-top:0.75pt solid #000000; border-bottom:0.75pt solid #000000; padding:0= pt 5.4pt; vertical-align:middle"><p style=3D"margin-bottom:0pt; text-align:= center; line-height:115%; font-size:10pt"><span>TA</span></p></td></tr><tr>= <td style=3D"border-top:0.75pt solid #000000; border-bottom:0.75pt solid #0= 00000; padding:0pt 5.4pt; vertical-align:middle"><p style=3D"margin-bottom:= 0pt; line-height:115%; font-size:10pt"><span>Me resulta interesante aprende= r sobre fracciones.</span></p></td><td style=3D"border-top:0.75pt solid #00= 0000; border-bottom:0.75pt solid #000000; padding:0pt 5.4pt; vertical-align= :middle"><p style=3D"margin-bottom:0pt; text-align:center; line-height:115%= ; font-size:10pt"><span>2</span></p></td><td style=3D"border-top:0.75pt sol= id #000000; border-bottom:0.75pt solid #000000; padding:0pt 5.4pt; vertical= -align:middle"><p style=3D"margin-bottom:0pt; text-align:center; line-heigh= t:115%; font-size:10pt"><span>0</span></p></td><td style=3D"border-top:0.75= pt solid #000000; border-bottom:0.75pt solid #000000; padding:0pt 5.4pt; ve= rtical-align:middle"><p style=3D"margin-bottom:0pt; text-align:center; line= -height:115%; font-size:10pt"><span>8</span></p></td><td style=3D"border-to= p:0.75pt solid #000000; border-bottom:0.75pt solid #000000; padding:0pt 5.4= pt; vertical-align:middle"><p style=3D"margin-bottom:0pt; text-align:center= ; line-height:115%; font-size:10pt"><span>0</span></p></td></tr><tr><td sty= le=3D"border-top:0.75pt solid #000000; border-bottom:0.75pt solid #000000; = padding:0pt 5.4pt; vertical-align:middle"><p style=3D"margin-bottom:0pt; li= ne-height:115%; font-size:10pt"><span>Cuando cometo un error con fracciones= , puedo darme cuenta y corregirlo.</span></p></td><td style=3D"border-top:0= .75pt solid #000000; border-bottom:0.75pt solid #000000; padding:0pt 5.4pt;= vertical-align:middle"><p style=3D"margin-bottom:0pt; text-align:center; l= ine-height:115%; font-size:10pt"><span>2</span></p></td><td style=3D"border= -top:0.75pt solid #000000; border-bottom:0.75pt solid #000000; padding:0pt = 5.4pt; vertical-align:middle"><p style=3D"margin-bottom:0pt; text-align:cen= ter; line-height:115%; font-size:10pt"><span>8</span></p></td><td style=3D"= border-top:0.75pt solid #000000; border-bottom:0.75pt solid #000000; paddin= g:0pt 5.4pt; vertical-align:middle"><p style=3D"margin-bottom:0pt; text-ali= gn:center; line-height:115%; font-size:10pt"><span>0</span></p></td><td sty= le=3D"border-top:0.75pt solid #000000; border-bottom:0.75pt solid #000000; = padding:0pt 5.4pt; vertical-align:middle"><p style=3D"margin-bottom:0pt; te= xt-align:center; line-height:115%; font-size:10pt"><span>0</span></p></td><= /tr></table><p style=3D"margin-bottom:0pt; text-align:justify; line-height:= 115%; font-size:9pt"><span style=3D"font-weight:bold">Nota</span><span>: TD= =3D Totalmente en desacuerdo, ED =3D En desacuerdo, DA =3D De acuerdo, TA = =3D Totalmente de acuerdo. </span></p><p style=3D"margin-bottom:0pt; line-h= eight:115%"><span style=3D"font-style:italic"> </span></p><p class=3D"= ListParagraph" style=3D"margin-bottom:0pt; text-indent:-18pt; line-height:1= 15%"><span style=3D"font-style:italic"><span>3.2.</span></span><span style= =3D"font-style:italic"> Encuesta a estudiantes</span></p><p style=3D"margin= -bottom:0pt; text-align:justify; line-height:115%"><span>Los resultados de = la encuesta a estudiantes aparecen en la </span><span style=3D"font-weight:= bold">Tabla 4</span><span>, </span><span> </span><span>donde la dimens= i=C3=B3n comprensi=C3=B3n=E2=80=AFconceptual predomina una percepci=C3=B3n = positiva de las ideas b=C3=A1sicas: la mitad del grupo (50=E2=80=AF%) se de= clara completamente seguro de que una fracci=C3=B3n representa =E2=80=9Cuna= parte de un todo=E2=80=9D y otro 10=E2=80=AF% adicional lo confirma, de mo= do que 60=E2=80=AF% respalda la afirmaci=C3=B3n. Aun as=C3=AD, un quinto de= los alumnos muestra dudas (20=E2=80=AF% en desacuerdo) y 10=E2=80=AF% la r= echaza frontalmente. El reconocimiento de fracciones equivalentes exhibe ma= yor solidez: 90=E2=80=AF% acuerda, 70=E2=80=AF% de ellos con un tono modera= do y 20=E2=80=AF% con convicci=C3=B3n total, dejando solo 10=E2=80=AF% de r= echazo. El reto radica, pues, m=C3=A1s en afianzar la definici=C3=B3n intui= tiva de fracci=C3=B3n que en la equivalencia entre ellas.</span></p><p styl= e=3D"margin-bottom:0pt; text-align:justify; line-height:115%"><span>En proc= edimientos y habilidades operativas los estudiantes se sienten relativament= e c=C3=B3modos con los algoritmos: 80=E2=80=AF% afirma realizar sumas y res= tas sin ayuda, repartido a partes iguales entre acuerdo pleno y moderado, a= unque un 20=E2=80=AF% reconoce dificultad. Al trasladar esos procedimientos= a situaciones cotidianas, la seguridad desciende: apenas 10=E2=80=AF% se d= eclara completamente capaz de usar fracciones en recetas, medidas o compras= y 50=E2=80=AF% se siente =E2=80=9Cde acuerdo=E2=80=9D, mientras 30=E2=80= =AF% permanece neutral y 10=E2=80=AF% admite problemas. Los datos sugieren = que la destreza mec=C3=A1nica no siempre se traduce en aplicaci=C3=B3n pr= =C3=A1ctica, demandando tareas contextualizadas que consoliden el c=C3=A1lc= ulo en la vida diaria.</span></p><p style=3D"margin-bottom:0pt; text-align:= justify; line-height:115%"><span>La dimensi=C3=B3n representaci=C3=B3n y co= municaci=C3=B3n matem=C3=A1tica revela un =C3=A1rea fr=C3=A1gil. Ning=C3=BA= n estudiante expres=C3=B3 completo dominio para graficar fracciones, y solo= 40=E2=80=AF% se siente razonablemente confiado; la mayor=C3=ADa (60=E2=80= =AF%) permanece neutral, evidenciando inseguridad al pasar del s=C3=ADmbolo= a la imagen concreta. Para explicar estrategias de comparaci=C3=B3n, 60=E2= =80=AF% muestra acuerdo moderado, pero el entusiasmo firme es nulo y aparec= e un 10=E2=80=AF% de desacuerdo rotundo, acompa=C3=B1ados de un 30=E2=80=AF= % neutral. El panorama indica que los alumnos manejan procedimientos intern= os, pero carecen de herramientas y vocabulario visual</span><span>‑<= /span><span>verbal para externalizar su pensamiento, lo que exige actividad= es de representaci=C3=B3n m=C3=BAltiple y modelado de explicaciones.</span>= </p><p style=3D"margin-bottom:0pt; text-align:justify; line-height:115%"><s= pan>En actitudes y metacognici=C3=B3n la disposici=C3=B3n es alentadora. Si= ete de cada diez estudiantes se sienten motivados a seguir aprendiendo frac= ciones, con 40=E2=80=AF% en acuerdo pleno y 30=E2=80=AF% moderado; solo 10= =E2=80=AF% muestra desinter=C3=A9s absoluto. Respecto a la autorregulaci=C3= =B3n, 80=E2=80=AF% cree identificar y corregir sus errores; dividido equita= tivamente entre convencidos y moderadamente seguros, mientras 10=E2=80=AF% = permanece neutral y otro 10=E2=80=AF% lo niega. Este perfil sugiere un clim= a emocional favorable y cierta confianza metacognitiva, pero todav=C3=ADa e= xiste margen para fortalecer estrategias expl=C3=ADcitas de autoevaluaci=C3= =B3n y reflexi=C3=B3n que consoliden la resiliencia de forma generalizada.<= /span></p><p style=3D"margin-bottom:0pt; text-align:justify; line-height:11= 5%"><span> </span></p><p style=3D"margin-bottom:0pt; text-align:center= ; line-height:115%"><span style=3D"font-weight:bold">Tabla 4</span></p><p s= tyle=3D"margin-bottom:0pt; text-align:center; line-height:115%"><span style= =3D"font-style:italic">Resultados de la encuesta a estudiantes</span></p><t= able style=3D"margin-bottom:0pt; padding:0pt; border-collapse:collapse"><tr= ><td style=3D"width:12.65pt; border-top:0.75pt solid #000000; border-bottom= :0.75pt solid #000000; padding:0pt 5.4pt; vertical-align:middle"><p style= =3D"margin-bottom:0pt; text-align:center; line-height:115%; font-size:10pt"= ><span>N=C2=BA</span></p></td><td style=3D"width:64.75pt; border-top:0.75pt= solid #000000; border-bottom:0.75pt solid #000000; padding:0pt 5.4pt; vert= ical-align:middle"><p style=3D"margin-bottom:0pt; text-align:center; line-h= eight:115%; font-size:10pt"><span>Categor=C3=ADa</span></p></td><td style= =3D"width:138.15pt; border-top:0.75pt solid #000000; border-bottom:0.75pt s= olid #000000; padding:0pt 5.4pt; vertical-align:middle"><p style=3D"margin-= bottom:0pt; text-align:center; line-height:115%; font-size:10pt"><span>=C3= =8Dtem (enunciado abreviado)</span></p></td><td style=3D"width:29.55pt; bor= der-top:0.75pt solid #000000; border-bottom:0.75pt solid #000000; padding:0= pt 5.4pt; vertical-align:middle"><p style=3D"margin-bottom:0pt; text-align:= center; line-height:115%; font-size:10pt"><span>TA%</span></p></td><td styl= e=3D"width:29.35pt; border-top:0.75pt solid #000000; border-bottom:0.75pt s= olid #000000; padding:0pt 5.4pt; vertical-align:middle"><p style=3D"margin-= bottom:0pt; text-align:center; line-height:115%; font-size:10pt"><span>DA%<= /span></p></td><td style=3D"width:23.1pt; border-top:0.75pt solid #000000; = border-bottom:0.75pt solid #000000; padding:0pt 5.4pt; vertical-align:middl= e"><p style=3D"margin-bottom:0pt; text-align:center; line-height:115%; font= -size:10pt"><span>N=E2=80=AF%</span></p></td><td style=3D"width:14.75pt; bo= rder-top:0.75pt solid #000000; border-bottom:0.75pt solid #000000; padding:= 0pt 5.4pt; vertical-align:middle"><p style=3D"margin-bottom:0pt; text-align= :center; line-height:115%; font-size:10pt"><span>ED %</span></p></td><td st= yle=3D"width:26pt; border-top:0.75pt solid #000000; border-bottom:0.75pt so= lid #000000; padding:0pt 5.4pt; vertical-align:middle"><p style=3D"margin-b= ottom:0pt; text-align:center; line-height:115%; font-size:10pt"><span>TDA %= </span></p></td></tr><tr><td style=3D"width:12.65pt; border-top:0.75pt soli= d #000000; border-bottom:0.75pt solid #000000; padding:0pt 5.4pt; vertical-= align:middle"><p style=3D"margin-bottom:0pt; text-align:center; line-height= :115%; font-size:10pt"><span>=E2=80=AF1</span></p></td><td rowspan=3D"2" st= yle=3D"width:64.75pt; border-top:0.75pt solid #000000; border-bottom:0.75pt= solid #000000; padding:0pt 5.4pt; vertical-align:middle"><p style=3D"margi= n-bottom:0pt; text-align:center; line-height:115%; font-size:10pt"><span>Co= mprensi=C3=B3n conceptual</span></p></td><td style=3D"width:138.15pt; borde= r-top:0.75pt solid #000000; border-bottom:0.75pt solid #000000; padding:0pt= 5.4pt; vertical-align:middle"><p style=3D"margin-bottom:0pt; text-align:ce= nter; line-height:115%; font-size:10pt"><span>Entiendo que una fracci=C3=B3= n representa una parte de un todo.</span></p></td><td style=3D"width:29.55p= t; border-top:0.75pt solid #000000; border-bottom:0.75pt solid #000000; pad= ding:0pt 5.4pt; vertical-align:middle"><p style=3D"margin-bottom:0pt; text-= align:center; line-height:115%; font-size:10pt"><span>50</span></p></td><td= style=3D"width:29.35pt; border-top:0.75pt solid #000000; border-bottom:0.7= 5pt solid #000000; padding:0pt 5.4pt; vertical-align:middle"><p style=3D"ma= rgin-bottom:0pt; text-align:center; line-height:115%; font-size:10pt"><span= >10</span></p></td><td style=3D"width:23.1pt; border-top:0.75pt solid #0000= 00; border-bottom:0.75pt solid #000000; padding:0pt 5.4pt; vertical-align:m= iddle"><p style=3D"margin-bottom:0pt; text-align:center; line-height:115%; = font-size:10pt"><span>10</span></p></td><td style=3D"width:14.75pt; border-= top:0.75pt solid #000000; border-bottom:0.75pt solid #000000; padding:0pt 5= .4pt; vertical-align:middle"><p style=3D"margin-bottom:0pt; text-align:cent= er; line-height:115%; font-size:10pt"><span>20</span></p></td><td style=3D"= width:26pt; border-top:0.75pt solid #000000; border-bottom:0.75pt solid #00= 0000; padding:0pt 5.4pt; vertical-align:middle"><p style=3D"margin-bottom:0= pt; text-align:center; line-height:115%; font-size:10pt"><span>10</span></p= ></td></tr><tr><td style=3D"width:12.65pt; border-top:0.75pt solid #000000;= border-bottom:0.75pt solid #000000; padding:0pt 5.4pt; vertical-align:midd= le"><p style=3D"margin-bottom:0pt; text-align:center; line-height:115%; fon= t-size:10pt"><span>=E2=80=AF2</span></p></td><td style=3D"width:138.15pt; b= order-top:0.75pt solid #000000; border-bottom:0.75pt solid #000000; padding= :0pt 5.4pt; vertical-align:middle"><p style=3D"margin-bottom:0pt; text-alig= n:center; line-height:115%; font-size:10pt"><span>Puedo reconocer cu=C3=A1n= do dos fracciones diferentes son equivalentes.</span></p></td><td style=3D"= width:29.55pt; border-top:0.75pt solid #000000; border-bottom:0.75pt solid = #000000; padding:0pt 5.4pt; vertical-align:middle"><p style=3D"margin-botto= m:0pt; text-align:center; line-height:115%; font-size:10pt"><span>20</span>= </p></td><td style=3D"width:29.35pt; border-top:0.75pt solid #000000; borde= r-bottom:0.75pt solid #000000; padding:0pt 5.4pt; vertical-align:middle"><p= style=3D"margin-bottom:0pt; text-align:center; line-height:115%; font-size= :10pt"><span>70</span></p></td><td style=3D"width:23.1pt; border-top:0.75pt= solid #000000; border-bottom:0.75pt solid #000000; padding:0pt 5.4pt; vert= ical-align:middle"><p style=3D"margin-bottom:0pt; text-align:center; line-h= eight:115%; font-size:10pt"><span>0</span></p></td><td style=3D"width:14.75= pt; border-top:0.75pt solid #000000; border-bottom:0.75pt solid #000000; pa= dding:0pt 5.4pt; vertical-align:middle"><p style=3D"margin-bottom:0pt; text= -align:center; line-height:115%; font-size:10pt"><span>0</span></p></td><td= style=3D"width:26pt; border-top:0.75pt solid #000000; border-bottom:0.75pt= solid #000000; padding:0pt 5.4pt; vertical-align:middle"><p style=3D"margi= n-bottom:0pt; text-align:center; line-height:115%; font-size:10pt"><span>10= </span></p></td></tr><tr><td style=3D"width:12.65pt; border-top:0.75pt soli= d #000000; border-bottom:0.75pt solid #000000; padding:0pt 5.4pt; vertical-= align:middle"><p style=3D"margin-bottom:0pt; text-align:center; line-height= :115%; font-size:10pt"><span>=E2=80=AF3</span></p></td><td rowspan=3D"2" st= yle=3D"width:64.75pt; border-top:0.75pt solid #000000; border-bottom:0.75pt= solid #000000; padding:0pt 5.4pt; vertical-align:middle"><p style=3D"margi= n-bottom:0pt; text-align:center; line-height:115%; font-size:10pt"><span>Pr= ocedimientos y habilidades operativas</span></p></td><td style=3D"width:138= .15pt; border-top:0.75pt solid #000000; border-bottom:0.75pt solid #000000;= padding:0pt 5.4pt; vertical-align:middle"><p style=3D"margin-bottom:0pt; t= ext-align:center; line-height:115%; font-size:10pt"><span>Realizo sumas y r= estas de fracciones sin necesidad de ayuda.</span></p></td><td style=3D"wid= th:29.55pt; border-top:0.75pt solid #000000; border-bottom:0.75pt solid #00= 0000; padding:0pt 5.4pt; vertical-align:middle"><p style=3D"margin-bottom:0= pt; text-align:center; line-height:115%; font-size:10pt"><span>40</span></p= ></td><td style=3D"width:29.35pt; border-top:0.75pt solid #000000; border-b= ottom:0.75pt solid #000000; padding:0pt 5.4pt; vertical-align:middle"><p st= yle=3D"margin-bottom:0pt; text-align:center; line-height:115%; font-size:10= pt"><span>40</span></p></td><td style=3D"width:23.1pt; border-top:0.75pt so= lid #000000; border-bottom:0.75pt solid #000000; padding:0pt 5.4pt; vertica= l-align:middle"><p style=3D"margin-bottom:0pt; text-align:center; line-heig= ht:115%; font-size:10pt"><span>0</span></p></td><td style=3D"width:14.75pt;= border-top:0.75pt solid #000000; border-bottom:0.75pt solid #000000; paddi= ng:0pt 5.4pt; vertical-align:middle"><p style=3D"margin-bottom:0pt; text-al= ign:center; line-height:115%; font-size:10pt"><span>20</span></p></td><td s= tyle=3D"width:26pt; border-top:0.75pt solid #000000; border-bottom:0.75pt s= olid #000000; padding:0pt 5.4pt; vertical-align:middle"><p style=3D"margin-= bottom:0pt; text-align:center; line-height:115%; font-size:10pt"><span>0</s= pan></p></td></tr><tr><td style=3D"width:12.65pt; border-top:0.75pt solid #= 000000; border-bottom:0.75pt solid #000000; padding:0pt 5.4pt; vertical-ali= gn:middle"><p style=3D"margin-bottom:0pt; text-align:center; line-height:11= 5%; font-size:10pt"><span>=E2=80=AF4</span></p></td><td style=3D"width:138.= 15pt; border-top:0.75pt solid #000000; border-bottom:0.75pt solid #000000; = padding:0pt 5.4pt; vertical-align:middle"><p style=3D"margin-bottom:0pt; te= xt-align:center; line-height:115%; font-size:10pt"><span>Utilizo fracciones= para resolver situaciones pr=C3=A1cticas de mi vida diaria.</span></p></td= ><td style=3D"width:29.55pt; border-top:0.75pt solid #000000; border-bottom= :0.75pt solid #000000; padding:0pt 5.4pt; vertical-align:middle"><p style= =3D"margin-bottom:0pt; text-align:center; line-height:115%; font-size:10pt"= ><span>10</span></p></td><td style=3D"width:29.35pt; border-top:0.75pt soli= d #000000; border-bottom:0.75pt solid #000000; padding:0pt 5.4pt; vertical-= align:middle"><p style=3D"margin-bottom:0pt; text-align:center; line-height= :115%; font-size:10pt"><span>50</span></p></td><td style=3D"width:23.1pt; b= order-top:0.75pt solid #000000; border-bottom:0.75pt solid #000000; padding= :0pt 5.4pt; vertical-align:middle"><p style=3D"margin-bottom:0pt; text-alig= n:center; line-height:115%; font-size:10pt"><span>30</span></p></td><td sty= le=3D"width:14.75pt; border-top:0.75pt solid #000000; border-bottom:0.75pt = solid #000000; padding:0pt 5.4pt; vertical-align:middle"><p style=3D"margin= -bottom:0pt; text-align:center; line-height:115%; font-size:10pt"><span>10<= /span></p></td><td style=3D"width:26pt; border-top:0.75pt solid #000000; bo= rder-bottom:0.75pt solid #000000; padding:0pt 5.4pt; vertical-align:middle"= ><p style=3D"margin-bottom:0pt; text-align:center; line-height:115%; font-s= ize:10pt"><span>0</span></p></td></tr><tr><td style=3D"width:12.65pt; borde= r-top:0.75pt solid #000000; border-bottom:0.75pt solid #000000; padding:0pt= 5.4pt; vertical-align:middle"><p style=3D"margin-bottom:0pt; text-align:ce= nter; line-height:115%; font-size:10pt"><span>=E2=80=AF5</span></p></td><td= rowspan=3D"2" style=3D"width:64.75pt; border-top:0.75pt solid #000000; bor= der-bottom:0.75pt solid #000000; padding:0pt 5.4pt; vertical-align:middle">= <p style=3D"margin-bottom:0pt; text-align:center; line-height:115%; font-si= ze:10pt"><span>Representaci=C3=B3n y comunicaci=C3=B3n matem=C3=A1tica</spa= n></p></td><td style=3D"width:138.15pt; border-top:0.75pt solid #000000; bo= rder-bottom:0.75pt solid #000000; padding:0pt 5.4pt; vertical-align:middle"= ><p style=3D"margin-bottom:0pt; text-align:center; line-height:115%; font-s= ize:10pt"><span>Me resulta f=C3=A1cil expresar una fracci=C3=B3n mediante d= ibujos, diagramas o barras.</span></p></td><td style=3D"width:29.55pt; bord= er-top:0.75pt solid #000000; border-bottom:0.75pt solid #000000; padding:0p= t 5.4pt; vertical-align:middle"><p style=3D"margin-bottom:0pt; text-align:c= enter; line-height:115%; font-size:10pt"><span>0</span></p></td><td style= =3D"width:29.35pt; border-top:0.75pt solid #000000; border-bottom:0.75pt so= lid #000000; padding:0pt 5.4pt; vertical-align:middle"><p style=3D"margin-b= ottom:0pt; text-align:center; line-height:115%; font-size:10pt"><span>40</s= pan></p></td><td style=3D"width:23.1pt; border-top:0.75pt solid #000000; bo= rder-bottom:0.75pt solid #000000; padding:0pt 5.4pt; vertical-align:middle"= ><p style=3D"margin-bottom:0pt; text-align:center; line-height:115%; font-s= ize:10pt"><span>60</span></p></td><td style=3D"width:14.75pt; border-top:0.= 75pt solid #000000; border-bottom:0.75pt solid #000000; padding:0pt 5.4pt; = vertical-align:middle"><p style=3D"margin-bottom:0pt; text-align:center; li= ne-height:115%; font-size:10pt"><span>0</span></p></td><td style=3D"width:2= 6pt; border-top:0.75pt solid #000000; border-bottom:0.75pt solid #000000; p= adding:0pt 5.4pt; vertical-align:middle"><p style=3D"margin-bottom:0pt; tex= t-align:center; line-height:115%; font-size:10pt"><span>0</span></p></td></= tr><tr><td style=3D"width:12.65pt; border-top:0.75pt solid #000000; border-= bottom:0.75pt solid #000000; padding:0pt 5.4pt; vertical-align:middle"><p s= tyle=3D"margin-bottom:0pt; text-align:center; line-height:115%; font-size:1= 0pt"><span>=E2=80=AF6</span></p></td><td style=3D"width:138.15pt; border-to= p:0.75pt solid #000000; border-bottom:0.75pt solid #000000; padding:0pt 5.4= pt; vertical-align:middle"><p style=3D"margin-bottom:0pt; text-align:center= ; line-height:115%; font-size:10pt"><span>Puedo explicar con claridad los p= asos que sigo para comparar dos fracciones.</span></p></td><td style=3D"wid= th:29.55pt; border-top:0.75pt solid #000000; border-bottom:0.75pt solid #00= 0000; padding:0pt 5.4pt; vertical-align:middle"><p style=3D"margin-bottom:0= pt; text-align:center; line-height:115%; font-size:10pt"><span>0</span></p>= </td><td style=3D"width:29.35pt; border-top:0.75pt solid #000000; border-bo= ttom:0.75pt solid #000000; padding:0pt 5.4pt; vertical-align:middle"><p sty= le=3D"margin-bottom:0pt; text-align:center; line-height:115%; font-size:10p= t"><span>60</span></p></td><td style=3D"width:23.1pt; border-top:0.75pt sol= id #000000; border-bottom:0.75pt solid #000000; padding:0pt 5.4pt; vertical= -align:middle"><p style=3D"margin-bottom:0pt; text-align:center; line-heigh= t:115%; font-size:10pt"><span>30</span></p></td><td style=3D"width:14.75pt;= border-top:0.75pt solid #000000; border-bottom:0.75pt solid #000000; paddi= ng:0pt 5.4pt; vertical-align:middle"><p style=3D"margin-bottom:0pt; text-al= ign:center; line-height:115%; font-size:10pt"><span>0</span></p></td><td st= yle=3D"width:26pt; border-top:0.75pt solid #000000; border-bottom:0.75pt so= lid #000000; padding:0pt 5.4pt; vertical-align:middle"><p style=3D"margin-b= ottom:0pt; text-align:center; line-height:115%; font-size:10pt"><span>10</s= pan></p></td></tr><tr><td style=3D"width:12.65pt; border-top:0.75pt solid #= 000000; border-bottom:0.75pt solid #000000; padding:0pt 5.4pt; vertical-ali= gn:middle"><p style=3D"margin-bottom:0pt; text-align:center; line-height:11= 5%; font-size:10pt"><span>=E2=80=AF7</span></p></td><td rowspan=3D"2" style= =3D"width:64.75pt; border-top:0.75pt solid #000000; border-bottom:0.75pt so= lid #000000; padding:0pt 5.4pt; vertical-align:middle"><p style=3D"margin-b= ottom:0pt; text-align:center; line-height:115%; font-size:10pt"><span>Actit= udes y metacognici=C3=B3n</span></p></td><td style=3D"width:138.15pt; borde= r-top:0.75pt solid #000000; border-bottom:0.75pt solid #000000; padding:0pt= 5.4pt; vertical-align:middle"><p style=3D"margin-bottom:0pt; text-align:ce= nter; line-height:115%; font-size:10pt"><span>Me siento motivado(a) a segui= r aprendiendo sobre fracciones.</span></p></td><td style=3D"width:29.55pt; = border-top:0.75pt solid #000000; border-bottom:0.75pt solid #000000; paddin= g:0pt 5.4pt; vertical-align:middle"><p style=3D"margin-bottom:0pt; text-ali= gn:center; line-height:115%; font-size:10pt"><span>40</span></p></td><td st= yle=3D"width:29.35pt; border-top:0.75pt solid #000000; border-bottom:0.75pt= solid #000000; padding:0pt 5.4pt; vertical-align:middle"><p style=3D"margi= n-bottom:0pt; text-align:center; line-height:115%; font-size:10pt"><span>30= </span></p></td><td style=3D"width:23.1pt; border-top:0.75pt solid #000000;= border-bottom:0.75pt solid #000000; padding:0pt 5.4pt; vertical-align:midd= le"><p style=3D"margin-bottom:0pt; text-align:center; line-height:115%; fon= t-size:10pt"><span>20</span></p></td><td style=3D"width:14.75pt; border-top= :0.75pt solid #000000; border-bottom:0.75pt solid #000000; padding:0pt 5.4p= t; vertical-align:middle"><p style=3D"margin-bottom:0pt; text-align:center;= line-height:115%; font-size:10pt"><span>0</span></p></td><td style=3D"widt= h:26pt; border-top:0.75pt solid #000000; border-bottom:0.75pt solid #000000= ; padding:0pt 5.4pt; vertical-align:middle"><p style=3D"margin-bottom:0pt; = text-align:center; line-height:115%; font-size:10pt"><span>10</span></p></t= d></tr><tr><td style=3D"width:12.65pt; border-top:0.75pt solid #000000; bor= der-bottom:0.75pt solid #000000; padding:0pt 5.4pt; vertical-align:middle">= <p style=3D"margin-bottom:0pt; text-align:center; line-height:115%; font-si= ze:10pt"><span>=E2=80=AF8</span></p></td><td style=3D"width:138.15pt; borde= r-top:0.75pt solid #000000; border-bottom:0.75pt solid #000000; padding:0pt= 5.4pt; vertical-align:middle"><p style=3D"margin-bottom:0pt; text-align:ce= nter; line-height:115%; font-size:10pt"><span>Cuando me equivoco con fracci= ones, identifico mi error y lo corrijo por mi cuenta.</span></p></td><td st= yle=3D"width:29.55pt; border-top:0.75pt solid #000000; border-bottom:0.75pt= solid #000000; padding:0pt 5.4pt; vertical-align:middle"><p style=3D"margi= n-bottom:0pt; text-align:center; line-height:115%; font-size:10pt"><span>40= </span></p></td><td style=3D"width:29.35pt; border-top:0.75pt solid #000000= ; border-bottom:0.75pt solid #000000; padding:0pt 5.4pt; vertical-align:mid= dle"><p style=3D"margin-bottom:0pt; text-align:center; line-height:115%; fo= nt-size:10pt"><span>40</span></p></td><td style=3D"width:23.1pt; border-top= :0.75pt solid #000000; border-bottom:0.75pt solid #000000; padding:0pt 5.4p= t; vertical-align:middle"><p style=3D"margin-bottom:0pt; text-align:center;= line-height:115%; font-size:10pt"><span>10</span></p></td><td style=3D"wid= th:14.75pt; border-top:0.75pt solid #000000; border-bottom:0.75pt solid #00= 0000; padding:0pt 5.4pt; vertical-align:middle"><p style=3D"margin-bottom:0= pt; text-align:center; line-height:115%; font-size:10pt"><span>10</span></p= ></td><td style=3D"width:26pt; border-top:0.75pt solid #000000; border-bott= om:0.75pt solid #000000; padding:0pt 5.4pt; vertical-align:middle"><p style= =3D"margin-bottom:0pt; text-align:center; line-height:115%; font-size:10pt"= ><span>0</span></p></td></tr></table><p style=3D"margin-bottom:0pt; text-al= ign:justify; line-height:115%; font-size:10pt"><span>Nota: TDA =3D Totalmen= te en desacuerdo, ED =3D En desacuerdo, N=3D Neutral, DA =3D De acuerdo, TA= =3D Totalmente de acuerdo. </span></p><p style=3D"margin-bottom:0pt; line-= height:115%"><span> </span></p><p class=3D"ListParagraph" style=3D"mar= gin-bottom:0pt; text-indent:-18pt; line-height:115%"><span style=3D"font-st= yle:italic"><span>3.3.</span></span><span style=3D"font-style:italic"> Entr= evista a docente</span></p><p style=3D"margin-bottom:0pt; text-align:justif= y; line-height:115%"><span>Contexto y caracter=C3=ADsticas del estudiante a= dulto: la docente se=C3=B1ala que los estudiantes adultos mayores de 40 a= =C3=B1os suelen centrar su aprendizaje en la resoluci=C3=B3n de tareas inme= diatas, m=C3=A1s que en la adquisici=C3=B3n de conocimientos transferibles = a su vida cotidiana; desde su perspectiva, esta orientaci=C3=B3n restringe = la aplicaci=C3=B3n de los conceptos matem=C3=A1ticos a situaciones reales. = Asimismo, comenta que estos adultos =E2=80=9Cestudian solo para el momento= =E2=80=9D, lo que le plantea el reto de motivarlos hacia un aprendizaje m= =C3=A1s funcional y significativo, conectado con experiencias y necesidades= concretas de su d=C3=ADa a d=C3=ADa.</span></p><p style=3D"margin-bottom:0= pt; text-align:justify; line-height:115%"><span>Dificultades espec=C3=ADfic= as con las fracciones: desde la mirada de la docente, las fracciones genera= n confusi=C3=B3n porque los estudiantes encuentran dif=C3=ADcil comprender = y diferenciar las =E2=80=9Creglas=E2=80=9D que rigen sus operaciones; esto;= afirma, provoca errores recurrentes en tareas como la suma y la resta. A= =C3=B1ade que la sensaci=C3=B3n de no dominar los procedimientos alimenta l= a inseguridad y afecta la actitud de los alumnos frente al aprendizaje.</sp= an></p><p style=3D"margin-bottom:0pt; text-align:justify; line-height:115%"= ><span>Estrategias pedag=C3=B3gicas empleadas: la docente menciona que recu= rre al =E2=80=9Cm=C3=A9todo de la tijera=E2=80=9D para simplificar la b=C3= =BAsqueda de denominadores comunes en sumas y restas de fracciones, y subra= ya que adapta su ense=C3=B1anza a los adultos mediante metodolog=C3=ADas ac= tivas enfocadas en la participaci=C3=B3n y la resoluci=C3=B3n de problemas = cercanos a su realidad.</span></p><p style=3D"margin-bottom:0pt; text-align= :justify; line-height:115%"><span>Uso de tecnolog=C3=ADa y simulaciones int= eractivas: seg=C3=BAn la docente aunque todav=C3=ADa no utilizo el simulado= r PhET, emplea otras aplicaciones digitales para reforzar los contenidos, l= o que; afirma, mejora la comprensi=C3=B3n conceptual. No obstante, advierte= que algunos estudiantes no dominan las herramientas tecnol=C3=B3gicas, lo = cual limita el aprovechamiento de los recursos disponibles; por ello, sugie= re trabajar primero la alfabetizaci=C3=B3n digital para optimizar los resul= tados.</span></p><p style=3D"margin-bottom:0pt; text-align:justify; line-he= ight:115%"><span>Evaluaci=C3=B3n, motivaci=C3=B3n y proyecci=C3=B3n: desde = su perspectiva, el progreso en fracciones se eval=C3=BAa eficazmente con ap= licaciones interactivas que permiten monitorear el desempe=C3=B1o y ofrecer= retroalimentaci=C3=B3n inmediata. La docente concluye que resulta indispen= sable capacitar a los estudiantes con mayor frecuencia para afianzar los co= nceptos y procedimientos abordados.</span></p><p style=3D"margin-bottom:0pt= ; text-align:justify; line-height:115%"><span style=3D"font-weight:bold; fo= nt-style:italic"> </span></p><p class=3D"ListParagraph" style=3D"margi= n-bottom:0pt; text-indent:-18pt; text-align:justify; line-height:115%"><spa= n style=3D"font-style:italic"><span>3.4.</span></span><span style=3D"font-w= eight:bold; font-style:italic"> </span><span style=3D"font-style:italic">Si= stema de actividades</span></p><p style=3D"margin-bottom:0pt; text-align:ju= stify; line-height:115%"><span> </span></p><p style=3D"margin-bottom:0= pt; text-align:justify; line-height:115%"><span>A partir de los resultados = del diagn=C3=B3stico se elabor=C3=B3 un sistema de actividades, entendido p= or Burgos-Posligua & Samada-Grasst (2023) como un conjunto de acciones = interrelacionadas que integran una unidad orientada a un objetivo com=C3=BA= n y estructurada por objetivos, procedimientos, recursos y evaluaci=C3=B3n.= En este caso el sistema integra las simulaciones interactivas de PhET para= fortalecer el aprendizaje de fracciones en adultos mayores de 40 a=C3=B1os= . Las simulaciones de PhET como =E2=80=9CConstruyamos una fracci=C3=B3n=E2= =80=9D y =E2=80=9CFracciones: Igualdad=E2=80=9D, permiten a los estudiantes= manipular representaciones visuales, experimentar con equivalencias y oper= aciones, y recibir retroalimentaci=C3=B3n inmediata, lo que fomenta un apre= ndizaje activo, contextualizado y alineado con los principios andrag=C3=B3g= icos de autonom=C3=ADa y relevancia pr=C3=A1ctica.</span></p><p style=3D"ma= rgin-bottom:0pt; text-align:justify; line-height:115%"><a id=3D"_Hlk2086487= 57"></a><a id=3D"_Hlk208648791"><span style=3D"font-weight:bold; font-style= :italic">Objetivo general del sistema de actividades: </span><span>fortalec= er la comprensi=C3=B3n conceptual, las habilidades operativas y la comunica= ci=C3=B3n matem=C3=A1tica sobre fracciones en adultos de 40+, asegurando pe= rtinencia, motivaci=C3=B3n y seguimiento del progreso.</span></a></p><p sty= le=3D"margin-bottom:0pt; text-align:justify; line-height:115%"><span style= =3D"font-weight:bold; font-style:italic">Contenidos del sistema de activida= des</span></p><p style=3D"margin-bottom:0pt; text-align:justify; line-heigh= t:115%"><span>Las actividades del curr=C3=ADculo de educaci=C3=B3n b=C3=A1s= ica superior se enfocan en la comprensi=C3=B3n de las fracciones, utilizand= o un enfoque pr=C3=A1ctico y vivencial. Los estudiantes trabajan con el con= cepto de "parte-todo", fracciones propias e impropias, equivalencias y simp= lificaci=C3=B3n. Se abordan las operaciones de suma y resta, con y sin deno= minador com=C3=BAn, aplicando a problemas cotidianos. Seg=C3=BAn el curr=C3= =ADculo (O.M.4.6), los estudiantes practicar=C3=A1n la conversi=C3=B3n y co= mparaci=C3=B3n de fracciones, justificando procedimientos mediante metacogn= ici=C3=B3n (OG.M.2). Usando simulaciones PhET y herramientas interactivas, = los estudiantes traducir=C3=A1n entre representaciones gr=C3=A1ficas, num= =C3=A9ricas y verbales, mejorando la capacidad de detectar y corregir error= es, seg=C3=BAn O.M.5.5.</span></p><p class=3D"ListParagraph" style=3D"margi= n-bottom:0pt; text-indent:-18pt; text-align:justify; line-height:115%"><spa= n style=3D"font-weight:bold"><span>a)</span></span><span style=3D"width:8pt= ; font:7pt 'Times New Roman'; display:inline-block">    = ; </span><span style=3D"font-weight:bold">Actividad 1</span></p><p style=3D= "margin-bottom:0pt; text-align:justify; line-height:115%"><span>Construir f= racciones con el uso de PhET I.S (</span><span style=3D"font-weight:bold">F= igura 1</span><span>).</span></p><p style=3D"margin-bottom:0pt; text-align:= justify; line-height:115%"><span style=3D"font-weight:bold">Objetivo espec= =C3=ADfico:</span><span> Reconocer la fracci=C3=B3n como parte=E2=80=93todo= , comprendiendo numerador/denominador y equivalencias mediante representaci= ones visuales interactivas. </span></p><p style=3D"margin-bottom:0pt; text-= align:justify; line-height:115%"><span style=3D"font-weight:bold">Orientaci= ones: </span><span>El docente reparte material que puede fraccionarse, tale= s como pizzas o tortas de papel, barras, tiras, recipientes con marcas. Com= ienza con una escena cercana: =E2=80=9CImagina que compartimos esta pizza e= ntre cuatro. =C2=BFQu=C3=A9 porci=C3=B3n recibe cada uno?=E2=80=9D. Se invi= ta a mostrar la unidad, la mitad, el tercio y los cuartos coloreando o sepa= rando partes iguales. Mientras circula por el aula, el docente modela el le= nguaje: =E2=80=9CEl denominador indica el total de partes iguales; el numer= ador, cu=C3=A1ntas tomamos o coloreamos=E2=80=9D. Se pide verbalizar con la= estructura: =E2=80=9Cde ___ partes, tomo ___=E2=80=9D. </span></p><p style= =3D"margin-bottom:0pt; text-align:justify; line-height:115%"><span>Criterio= de dominio antes de avanzar: cada estudiante exhibe correctamente: (a) una= unidad entera, (b) =C2=BD y =E2=85=93, y (c) =C2=BE en su material, y expl= ica con sus palabras numerador y denominador. Solo entonces se pasa a la si= mulaci=C3=B3n.</span></p><p style=3D"margin-bottom:0pt; text-align:justify;= line-height:115%"><span style=3D"font-weight:bold">Trabajo en el simulador= : </span><span>Presentaci=C3=B3n de PhET I.S. (Build a Fraction): El docent= e proyecta la pantalla y gu=C3=ADa el acceso: ingresar a PhET =E2=86=92 sel= eccionar Build a Fraction. Presenta la interfaz: elegir forma (barra/c=C3= =ADrculo), ajustar el n=C3=BAmero de partes, colorear segmentos, leer la fr= acci=C3=B3n que aparece y usar reset. Luego realiza un ejemplo guiado: =E2= =80=9CPara =C2=BE, divido en 4 partes y coloreo 3. Leo: =E2=80=98tres cuart= os=E2=80=99=E2=80=9D. Anticipa el prop=C3=B3sito: =E2=80=9CEl reto ser=C3= =A1 reproducir fracciones que pida el simulador y justificar equivalencias = observando qu=C3=A9 cambia (el denominador) y qu=C3=A9 permanece (la cantid= ad coloreada)=E2=80=9D.</span></p><p style=3D"margin-bottom:0pt; text-align= :justify; line-height:115%"><span>Actividad del alumno (interacci=C3=B3n + = trabajo colaborativo): Primero, de forma individual, cada estudiante elige = un objeto de la interfaz y lo modifica con el cursor hasta construir las fr= acciones solicitadas por defecto: =C2=BD, =E2=85=93 y =C2=BE. Debe ajustar = partes, colorear y leer en voz alta la fracci=C3=B3n lograda. Luego pasan a= parejas con roles rotativos: A manipula la simulaci=C3=B3n mientras B expl= ica y registra en el cuaderno con el esquema modelo =E2=86=92 fracci=C3=B3n= =E2=86=92 explicaci=C3=B3n (p. ej., =E2=80=9Cc=C3=ADrculo en 4 partes; 3 c= oloreadas =E2=86=92 =C2=BE; el denominador 4 es el total de partes iguales= =E2=80=9D). Cambian roles en cada nuevo reto.</span></p><p style=3D"margin-= bottom:0pt; text-align:justify; line-height:115%"><span style=3D"font-weigh= t:bold">Evaluaci=C3=B3n: </span><span>Lista de cotejo o r=C3=BAbrica breve = con los siguientes componentes: (1) representar 3/4 en un diagrama; (2) dec= idir si 2/4 =3D 1/2 y justificar; (3) describir con una frase una situaci= =C3=B3n real donde usar 1/3.</span></p><p style=3D"margin-bottom:0pt; text-= align:justify; line-height:115%"><span style=3D"font-weight:bold"> </s= pan></p><p style=3D"margin-bottom:0pt; text-align:center; line-height:115%"= ><span style=3D"font-weight:bold">Figura 1</span></p><p style=3D"margin-bot= tom:0pt; text-align:center; line-height:115%"><span style=3D"font-style:ita= lic">Actividad 1 en PhET I.S.</span></p><p style=3D"margin-bottom:0pt; text= -align:center; line-height:115%"><img src=3D"data:image/png;base64,iVBORw0K= GgoAAAANSUhEUgAAAfgAAAFVCAYAAAADqv1PAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAAOxAA= 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/JOPVLaJ4n0cTSrkhoaGOVzfh+pvqvopUaofjwaIQ+1D4v5dthgXIKexTi/91qzEQZhgmS0EyGJ= tu9bU5f9VMDEW+0y49tpr52zq5Knkz/iw5CXGaxWn698lpoujoqlukD5Fgc8Yx9yW8hAl4+FP/6= 8KOeU2XA2kxPnYHxSNqj8ERS3EkcSmqBDwpYdXergTwz+ee+65b8ZtVZkDCEWU1dalep8o5Ds7O= +ns7JydAlY57qxZs4Y1a9bMdjGqHAe8Xi/nn3/+bBejyjGmLMHHm+QL4Q7+JZVY9qFnsPZPrZav= Mv+Qlo2qqCgeD6qqHpHRRpUqVapUmR+UBbwcp+JTVbWc4UkC+Wd3kX9212yVscoxQFUVdK+3YhV= fpUqVKlVOHIQsSvaSgHccB8uyME0TwzDIZrNlS+lS2tWZGGZVmRuMV71rRctjXdfx+/34/X68Xi= +ecSv5qqCvUqVKlRODSSp6RVEq/EpVVS2nxhtv1VoV7vODia4kpXSeuq6X3dqqK/gqVapUOfEor= +BLlKyIS5mkSu4J4y0Qq8JgflGq4vEGdSVBP95atVqvVapUqXLiMMlNrjTIl1bxouhbDdVV+3xm= vAHlRG+JKlWqVKly4vH/AHhXG95qv4meAAAAAElFTkSuQmCC" width=3D"504" height=3D"3= 41" alt=3D"" /></p><p style=3D"margin-bottom:0pt; text-align:center; line-h= eight:115%; font-size:10pt"><span style=3D"font-weight:bold">Nota.</span><s= pan> Tomado de PhET I.S. - 2025</span></p><p class=3D"ListParagraph" style= =3D"margin-bottom:0pt; text-indent:-18pt; text-align:justify; line-height:1= 15%"><span style=3D"font-weight:bold"><span>b)</span></span><span style=3D"= width:7.33pt; font:7pt 'Times New Roman'; display:inline-block">  = ;   </span><span style=3D"font-weight:bold">Actividad 2</span></p= ><p style=3D"margin-bottom:0pt; text-align:justify; line-height:115%"><span= >Sumas de fracciones mediante el uso de PhET + Wordwall (</span><span style= =3D"font-weight:bold">Figura 2</span><span>).</span></p><p style=3D"margin-= bottom:0pt; text-align:justify; line-height:115%"><span style=3D"font-weigh= t:bold">Objetivo espec=C3=ADfico: </span><span>Realizar sumas y restas de f= racciones (con y sin denominador com=C3=BAn) y resolver problemas pr=C3=A1c= ticos usando representaciones equivalentes y pr=C3=A1ctica interactiva.</sp= an></p><p style=3D"margin-bottom:0pt; text-align:justify; line-height:115%"= ><span style=3D"font-weight:bold">Orientaciones: </span><span>Se introducen= situaciones cercanas; ajuste de una receta y registro simple de gastos, pa= ra transitar del modelo gr=C3=A1fico a la notaci=C3=B3n. Se enfatiza la ide= a clave: =E2=80=9Cdenominador com=C3=BAn =3D mismo tama=C3=B1o de parte=E2= =80=9D. Se ilustra brevemente un caso con igual denominador y otro con dife= rente denominador para mostrar el papel de las equivalencias.</span></p><p = style=3D"margin-bottom:0pt; text-align:justify; line-height:115%"><span>Cri= terio de dominio antes de avanzar: Cada estudiante: (a) resuelve una suma o= resta con igual denominador usando modelo y notaci=C3=B3n; (b) decide y ex= plica si requiere denominador com=C3=BAn; (c) construye al menos una equiva= lencia correcta y justifica qu=C3=A9 cambia y qu=C3=A9 permanece. Con este = umbral, se pasa a la pr=C3=A1ctica digital.</span></p><p style=3D"margin-bo= ttom:0pt; text-align:justify; line-height:115%"><span style=3D"font-weight:= bold">Trabajo en el simulador: </span><span>Presentaci=C3=B3n de PhET I.S. = (Fraction Matcher) y Wordwall. Se proyecta </span><span style=3D"font-style= :italic">Fraction Matcher</span><span> y se explicita la regla central: emp= arejar fracciones con sus representaciones equivalentes. Un ejemplo (1/2 = =E2=89=A1 2/4) sirve para mostrar c=C3=B3mo las equivalencias habilitan la = operaci=C3=B3n (p. ej., 1/2 + 1/4 =E2=86=92 2/4 + 1/4 =3D 3/4). Se indican = brevemente navegaci=C3=B3n, niveles y reinicio. A continuaci=C3=B3n se pres= enta Wordwall como concurso de problemas contextualizados, con tiempo por = =C3=ADtem y justificaci=C3=B3n obligatoria de la respuesta (equivalencias = =E2=86=92 operaci=C3=B3n =E2=86=92 verificaci=C3=B3n).</span></p><p style= =3D"margin-bottom:0pt; text-align:justify; line-height:115%"><span>Activida= d del alumno (interacci=C3=B3n + trabajo colaborativo): Primero, de forma i= ndividual en PhET, el estudiante forma 2=E2=80=933 pares equivalentes y reg= istra uno siguiendo el esquema: </span><span style=3D"font-style:italic">mo= delo =E2=86=92 fracci=C3=B3n =E2=86=92 fracci=C3=B3n equivalente =E2=86=92 = explicaci=C3=B3n</span><span>. Luego, en parejas con roles rotativos, A man= ipula y B explica y registra una suma y una resta con distintos denominador= es, asegurando denominador com=C3=BAn, operaci=C3=B3n y simplificaci=C3=B3n= cuando corresponda. Se realiza una mini puesta en com=C3=BAn para contrast= ar estrategias y validar resultados.</span></p><p style=3D"margin-bottom:0p= t; text-align:justify; line-height:115%"><span style=3D"font-weight:bold">E= valuaci=C3=B3n: </span><span>R=C3=BAbrica breve en el cuaderno del estudian= te con los siguientes temas: (1) resuelve una suma o resta con justificaci= =C3=B3n; (2) verifica una equivalencia; (3) escribe un caso real donde usar= =C3=ADa la operaci=C3=B3n. Lista de cotejo alineada a los indicadores.</spa= n></p><p style=3D"margin-bottom:0pt; text-align:justify; line-height:115%">= <span style=3D"font-weight:bold"> </span></p><p style=3D"margin-bottom= :0pt; text-align:center; line-height:115%"><span style=3D"font-weight:bold"= >Figura 2</span></p><p style=3D"margin-bottom:0pt; text-align:center; line-= height:115%"><span style=3D"font-style:italic">Actividad 2 en PhET I.S.</sp= an></p><p style=3D"margin-bottom:0pt; text-align:center; line-height:115%">= <img src=3D"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAWYAAAFKCAYAAAAuS= PVbAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAAOxAAADsQBlSsOGwAAIABJREFUeJzsvXl8HNWZ= 7/09tfXe2i1Zlm1ZtrENNjYOYBzssCQQbjaYsAx3skwyM3dyJ/OSZUKSmQm5MyFMQt4wWSAL92Z= CyJvJmwUIScgKIQQStsHGBLAhXvBua5da6rWWc+4f1d2WZG22W7Ik6vv5yLKqq7tOdZ361XOe8z= zPEUopRUBAQEDAjEE73Q0ICAgICBhOIMwBAQEBMwxj6B87d+4kFoudrrYEBAQEvKoZGBhg1apVw= 4U5FouxYMGC09WmgICAgFc1+XweCFwZAQEBATOOQJgDAgICZhiBMAcEBATMMIyJdwGlFI7jkM1m= 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Qnkd61i70KLR6LqmvAYRCOZAcw4E9NQq0OtCeR3rWJvQgoyg4Gd9Mq8tTBXCa4kTeh3rWMc61rG= OdaxjzeD/B88CLoDx13zPAAAAAElFTkSuQmCC" width=3D"358" height=3D"330" alt=3D"= " /></p><p style=3D"margin-bottom:0pt; text-align:center; line-height:115%;= font-size:10pt"><span style=3D"font-weight:bold">Nota.</span><span> Tomado= de PhET I.S. - 2025</span></p><p style=3D"margin-bottom:0pt; text-align:ju= stify; line-height:115%"><span style=3D"font-weight:bold"> </span></p>= <p class=3D"ListParagraph" style=3D"margin-bottom:0pt; text-indent:-18pt; t= ext-align:justify; line-height:115%"><span style=3D"font-weight:bold"><span= >c)</span></span><span style=3D"width:8.68pt; font:7pt 'Times New Roman'; d= isplay:inline-block">      </span><span style=3D"f= ont-weight:bold">Actividad 3</span></p><p style=3D"margin-bottom:0pt; text-= align:justify; line-height:115%"><span>Representaci=C3=B3n y comunicaci=C3= =B3n de fracciones con PHET (</span><span style=3D"font-weight:bold">Figura= 3</span><span>).</span></p><p style=3D"margin-bottom:0pt; text-align:justi= fy; line-height:115%"><span style=3D"font-weight:bold">Objetivo espec=C3=AD= fico</span><span>: Comunicar razonamientos sobre fracciones en m=C3=BAltipl= es formas (barras, c=C3=ADrculos, rect=C3=A1ngulos) con explicaciones orale= s y escritas claras.</span></p><p style=3D"margin-bottom:0pt; text-align:ju= stify; line-height:115%"><span style=3D"font-weight:bold">Orientaciones: </= span><span>Se parte de escenas cercanas; indicador de gasolina, barra de de= scarga y reparto de materiales, para transitar de lo concreto al s=C3=ADmbo= lo. El docente solicita identificar numerador (partes consideradas) y denom= inador (total de partes iguales) y verbalizar con la estructura: =E2=80=9Cd= e ___ partes, tomo ___=E2=80=9D. Se registran breves diagramas en pizarra (= barra/c=C3=ADrculo/recta) como puente a la notaci=C3=B3n.</span></p><p styl= e=3D"margin-bottom:0pt; text-align:justify; line-height:115%"><span>Criteri= o de dominio antes de avanzar: Cada estudiante: (a) identifica correctament= e numerador y denominador en un ejemplo del contexto; (b) representa la mis= ma fracci=C3=B3n en dos formas (p. ej., diagrama y recta num=C3=A9rica); y = (c) la lee y describe con precisi=C3=B3n. Cumplido este umbral, se pasa a l= a pr=C3=A1ctica digital.</span></p><p style=3D"margin-bottom:0pt; text-alig= n:justify; line-height:115%"><span style=3D"font-weight:bold">Trabajo en el= simulador: </span><span>Presentaci=C3=B3n de PhET I.S. (</span><span style= =3D"font-style:italic">Fractions: Mixed Numbers</span><span>). El docente p= royecta la simulaci=C3=B3n y muestra c=C3=B3mo seleccionar el modo con m=C3= =BAltiples representaciones (=C3=A1rea/recta). Modela un ejemplo breve: con= struir 3/4, leer la fracci=C3=B3n y cambiar de representaci=C3=B3n para com= probar consistencia; luego compara 3/4 y 2/3, explicitando el criterio: =E2= =80=9Cmismo tama=C3=B1o de parte o argumento visual equivalente=E2=80=9D. P= rop=C3=B3sito declarado: representar y justificar.</span></p><p style=3D"ma= rgin-bottom:0pt; text-align:justify; line-height:115%"><span>Actividad del = alumno (interacci=C3=B3n + trabajo colaborativo): Primero, individual, cada= estudiante construye 3/4 y 2/3 en dos formas (p. ej., barra y recta) y reg= istra en su cuaderno el esquema modelo =E2=86=92 fracci=C3=B3n =E2=86=92 ex= plicaci=C3=B3n. Despu=C3=A9s, en parejas con roles rotativos: A manipula la= simulaci=C3=B3n y B explica y registra la comparaci=C3=B3n (>, <, = =3D) y la justificaci=C3=B3n (equivalencias, =C3=A1rea sombreada o posici= =C3=B3n en la recta). Cambian roles en cada reto y realizan una mini puesta= en com=C3=BAn para contrastar estrategias y vocabulario (parte=E2=80=93tod= o, numerador, denominador, equivalencia).</span></p><p style=3D"margin-bott= om:0pt; text-align:justify; line-height:115%"><span style=3D"font-weight:bo= ld">Evaluaci=C3=B3n: </span><span>R=C3=BAbrica breve con los siguientes tem= as: (1) representa una fracci=C3=B3n a elecci=C3=B3n y explica su construcc= i=C3=B3n; (2) compara dos fracciones con argumento; (3) elige la representa= ci=C3=B3n que prefiere y justifica. Lista de cotejo.</span></p><p style=3D"= margin-bottom:0pt; text-align:justify; line-height:115%"><span style=3D"fon= t-weight:bold"> </span></p><p style=3D"margin-bottom:0pt; text-align:c= enter; line-height:115%"><span style=3D"font-weight:bold">Figura 3</span></= p><p style=3D"margin-bottom:0pt; text-align:center; line-height:115%"><span= style=3D"font-style:italic">Actividad 2 en PhET I.S.</span></p><p style=3D= "margin-bottom:0pt; text-align:center; line-height:115%"><img src=3D"data:i= mage/png;base64,iVBORw0KGgoAAAANSUhEUgAAAacAAAEcCAYAAABj4nsuAAAABHNCSVQICAg= IfAhkiAAAAAlwSFlzAAAOxAAADsQBlSsOGwAAIABJREFUeJzsvXmcXFWZ//8+52619pLeku6sJC= GBxBBZg0JAIEgwIi4I46AvHVwZ8at+XRAHZ0ZRkPHrvNQMAjozoijq4IzwQ4MIIwgYWRMSErLv6= aTTa3XXfu895/dHdVU6SXeS3rvT9w2Vrq6ue59zt/M5y3OeR2itNQEBAQEBAWMEIYSQo12IgICA= gICAozFHuwAjidaaoKMYEBBwKiCEQAgx2sUYNiacOG3duhXLska7KAEBAQEDRmtNWVkZ1dXVp6x= ATShxAjBNk9NOO220ixEQEBAwYJRStLa2jnYxhpUJJ05jmWDIMSBgeBmJXsZQP8enas/oRATiNM= 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taq0nDwtxzhMEbvsnMN3/I62+8waZNm953uS5CgE+DYEBgO5JSucq/6ELTNI8w0R1s9bZ7t96Tb= duYpnnmnZxCIBQFadueWVpRBFKoIEE6tmeXdhexuXPncusXv0jhe49S3rqL9l/fg9AnDmjLsti+= fTu/+MUv3hNnrYvJgw0gEaumQBgGjOXqzfDC43Rz863qzQyuWURVVcrl8pkPWBECRfMhbQuBxKd= JhCKwhR+h6tiVatKlY5oo4pgAv+222zjnnHNOKqT6+/v53ve+97a1rTMJdz64Zvr6ceTXIRQUOE= 41MCRflA1BXu5csyyrgU7nTMHzvTlOtR/czxS15qMDZOOGau3atWzYsOGkQsqyLB555JEJ9D7vF= 2ia5rGH169b9YwU9RpT/TwMh8CnCYoliWGc+RSA4/sJl6FEqW2cj+snx3G4+uqr+ehHP+oxUAgh= xETh9F//D7Pe/BEO0wjDPIvTCkVRUBBkv/2rEwond8f8fttA1MONnvprQ30uycng9tF7uYH4oMK= 1JpwMfwlz6a8Zx1d0EEKIxhXPkchShaH/9i2mDvo8i3cHEuvgAEpTdMozXE3r3SerPYvpQAhxZs= 1dZ/GOcXYuvf/gzRihKijJKOFPnDzs8izeHWjtSdSOZoR6dsKcxVmcxQcLnlnvLM7iLM7iLM7i/= QAhhPj/Ckm55Za1nXoAAAAASUVORK5CYII=3D" width=3D"423" height=3D"284" alt=3D"= " /></p><p style=3D"margin-bottom:0pt; text-align:center; line-height:115%;= font-size:10pt"><span style=3D"font-weight:bold">Nota.</span><span> Tomado= de PhET I.S. - 2025</span></p><p style=3D"margin-bottom:0pt; text-align:ju= stify; line-height:115%"><span style=3D"font-weight:bold; font-style:italic= "> </span></p><p class=3D"ListParagraph" style=3D"margin-bottom:0pt; t= ext-indent:-18pt; text-align:justify; line-height:115%"><span style=3D"font= -style:italic"><span>3.5.</span></span><span style=3D"font-weight:bold; fon= t-style:italic"> </span><span style=3D"font-style:italic">Alineaci=C3=B3n c= urricular</span></p><p style=3D"margin-bottom:0pt; text-align:justify; line= -height:115%"><span>El sistema de actividades se alinea con las =E2=80=9CAd= aptaciones curriculares con =C3=A9nfasis en competencias para la educaci=C3= =B3n de personas j=C3=B3venes, adultas y adultas mayores en situaci=C3=B3n = de escolaridad inconcluso para B=C3=A1sica Superior y Bachillerato (EPJA)= =E2=80=9D del </span><span style=3D"text-decoration:underline">Ministerio d= e Educaci=C3=B3n, Deporte y Cultura del Ecuador</span><span> (2025). Al des= arrollar los ejes de n=C3=BAmeros y operaciones, representaci=C3=B3n y comu= nicaci=C3=B3n y resoluci=C3=B3n de problemas en reconocimiento y representa= ci=C3=B3n de n=C3=BAmeros racionales en contextos cotidianos, relaciones de= orden en Q con recta num=C3=A9rica y simbolog=C3=ADa (=3D, <, =E2=89=A5= ), operaciones en Q; adici=C3=B3n y multiplicaci=C3=B3n, aplicadas a ejerci= cios y problemas con fracciones y formulaci=C3=B3n y resoluci=C3=B3n de pro= blemas con racionales, explicitando procedimientos y valorando la validez d= e soluciones. La integraci=C3=B3n de PhET y tareas situadas se ajusta al cu= rr=C3=ADculo priorizado y a la autonom=C3=ADa escolar para atender a la pob= laci=C3=B3n EPJA con experiencias motivadoras.</span></p><p style=3D"margin= -bottom:0pt; text-align:justify; line-height:115%"><span> </span></p><= p class=3D"ListParagraph" style=3D"margin-bottom:0pt; text-indent:-18pt; te= xt-align:justify; line-height:115%"><span style=3D"font-style:italic"><span= >3.6.</span></span><span style=3D"font-weight:bold; font-style:italic"> </s= pan><span style=3D"font-style:italic">Resultados post aplicaci=C3=B3n</span= ></p><p style=3D"margin-bottom:0pt; text-align:justify; line-height:115%"><= span>Como se observa en la </span><span style=3D"font-weight:bold">Tabla 5<= /span><span> en comprensi=C3=B3n conceptual se observa un avance significat= ivo claro desde un punto de partida bajo hacia una base funcional. El subto= tal pas=C3=B3 de 2 de 40 a 14 de 40, lo que equivale a un incremento de 30 = puntos porcentuales, se=C3=B1al de que la reconstrucci=C3=B3n de significad= os fue transversal. El dato m=C3=A1s representativo es que los cuatro crite= rios avanzaron homog=C3=A9neamente en 30 puntos, desde representar e identi= ficar partes hasta reconocer equivalencias num=C3=A9ricas y gr=C3=A1ficas. = </span></p><p style=3D"margin-bottom:0pt; text-align:justify; line-height:1= 15%"><span>En procedimientos y habilidades operativas el patr=C3=B3n es mix= to pero consistente con la l=C3=B3gica de la intervenci=C3=B3n. El subtotal= subi=C3=B3 de 10 de 40 a 19 de 40, es decir 22 puntos, impulsado por la re= sta con un alza de 30 y por el promedio contextualizado con un salto de 50.= La suma creci=C3=B3 solo 10, probablemente por efecto techo, ya que part= =C3=ADa con 8 aciertos de 10. La media simple no mostr=C3=B3 cambio, lo que= revela ausencia de significado y no solo de t=C3=A9cnica. Las actividades = favorecieron el uso de equivalencias y denominador com=C3=BAn, aunque persi= ste un vac=C3=ADo en la noci=C3=B3n de representatividad.</span></p><p styl= e=3D"margin-bottom:0pt; text-align:justify; line-height:115%"><span>En repr= esentaci=C3=B3n y comunicaci=C3=B3n matem=C3=A1tica se observa el salto cua= litativo m=C3=A1s contundente. El subtotal pas=C3=B3 de 16 de 30 a 30 de 30= , un incremento de 46,7 puntos, y el indicador de explicaci=C3=B3n avanz=C3= =B3 de cero a dominio pleno, lo que equivale a un cambio de cien puntos. No= taci=C3=B3n y orden tambi=C3=A9n alcanzaron el techo con aumentos de veinte= . Estas evidencias muestran que el sistema logr=C3=B3 cerrar la brecha entr= e hacer y explicar, habilitando justificaciones claras con apoyo de m=C3=BA= ltiples registros.</span></p><p style=3D"margin-bottom:0pt; text-align:just= ify; line-height:115%"><span> </span></p><p style=3D"margin-bottom:0pt= ; line-height:115%"><span style=3D"font-weight:bold"> </span></p><p st= yle=3D"margin-bottom:0pt; text-align:center; line-height:115%"><span style= =3D"font-weight:bold">Tabla 5</span></p><p style=3D"margin-bottom:0pt; text= -align:center; line-height:115%"><span style=3D"font-style:italic">Porcenta= je de =C3=A9xito post aplicaci=C3=B3n</span></p><table style=3D"width:100%;= margin-bottom:0pt; padding:0pt; border-collapse:collapse"><tr><td style=3D= "width:20.3%; border-top:0.75pt solid #000000; border-bottom:0.75pt solid #= 000000; padding:0pt 5.4pt; vertical-align:middle"><p class=3D"NoSpacing" st= yle=3D"text-align:center; line-height:115%; font-size:10pt"><span>Tipo</spa= n></p></td><td style=3D"width:7.98%; border-top:0.75pt solid #000000; borde= r-bottom:0.75pt solid #000000; padding:0pt 5.4pt; vertical-align:middle"><p= class=3D"NoSpacing" style=3D"text-align:center; line-height:115%; font-siz= e:10pt"><span>N=C2=BA</span></p></td><td style=3D"width:25.88%; border-top:= 0.75pt solid #000000; border-bottom:0.75pt solid #000000; padding:0pt 5.4pt= ; vertical-align:middle"><p class=3D"NoSpacing" style=3D"text-align:center;= line-height:115%; font-size:10pt"><span>Criterio</span></p></td><td style= =3D"width:13.72%; border-top:0.75pt solid #000000; border-bottom:0.75pt sol= id #000000; padding:0pt 5.4pt; vertical-align:middle"><p class=3D"NoSpacing= " style=3D"text-align:center; line-height:115%; font-size:10pt"><span>Inici= al</span></p></td><td style=3D"width:15.76%; border-top:0.75pt solid #00000= 0; border-bottom:0.75pt solid #000000; padding:0pt 5.4pt; vertical-align:mi= ddle"><p class=3D"NoSpacing" style=3D"text-align:center; line-height:115%; = font-size:10pt"><span>Despu=C3=A9s</span></p></td><td style=3D"width:16.38%= ; border-top:0.75pt solid #000000; border-bottom:0.75pt solid #000000; padd= ing:0pt 5.4pt; vertical-align:middle"><p class=3D"NoSpacing" style=3D"text-= align:center; line-height:115%; font-size:10pt"><span>% mejorado</span></p>= </td></tr><tr><td rowspan=3D"4" style=3D"width:20.3%; border-top:0.75pt sol= id #000000; border-bottom:0.75pt solid #000000; padding:0pt 5.4pt; vertical= -align:middle"><p class=3D"NoSpacing" style=3D"text-align:center; line-heig= ht:115%; font-size:10pt"><span>Comprensi=C3=B3n conceptual (CC)</span></p><= /td><td style=3D"width:7.98%; border-top:0.75pt solid #000000; border-botto= m:0.75pt solid #000000; padding:0pt 5.4pt; vertical-align:middle"><p class= =3D"NoSpacing" style=3D"text-align:center; line-height:115%; font-size:10pt= "><span>P1</span></p></td><td style=3D"width:25.88%; border-top:0.75pt soli= d #000000; border-bottom:0.75pt solid #000000; padding:0pt 5.4pt; vertical-= align:middle"><p class=3D"NoSpacing" style=3D"text-align:center; line-heigh= t:115%; font-size:10pt"><span>Representaci=C3=B3n de una fracci=C3=B3n</spa= n></p></td><td style=3D"width:13.72%; border-top:0.75pt solid #000000; bord= er-bottom:0.75pt solid #000000; padding:0pt 5.4pt; vertical-align:middle"><= p class=3D"NoSpacing" style=3D"text-align:center; line-height:115%; font-si= ze:10pt"><span>0</span></p></td><td style=3D"width:15.76%; border-top:0.75p= t solid #000000; border-bottom:0.75pt solid #000000; padding:0pt 5.4pt; ver= tical-align:middle"><p class=3D"NoSpacing" style=3D"text-align:center; line= -height:115%; font-size:10pt"><span>3</span></p></td><td style=3D"width:16.= 38%; border-top:0.75pt solid #000000; border-bottom:0.75pt solid #000000; p= adding:0pt 5.4pt; vertical-align:middle"><p class=3D"NoSpacing" style=3D"te= xt-align:center; line-height:115%; font-size:10pt"><span>+30</span></p></td= ></tr><tr><td style=3D"width:7.98%; border-top:0.75pt solid #000000; border= -bottom:0.75pt solid #000000; padding:0pt 5.4pt; vertical-align:middle"><p = class=3D"NoSpacing" style=3D"text-align:center; line-height:115%; font-size= :10pt"><span>P2</span></p></td><td style=3D"width:25.88%; border-top:0.75pt= solid #000000; border-bottom:0.75pt solid #000000; padding:0pt 5.4pt; vert= ical-align:middle"><p class=3D"NoSpacing" style=3D"text-align:center; line-= height:115%; font-size:10pt"><span>Identificaci=C3=B3n de partes de una fra= cci=C3=B3n</span></p></td><td style=3D"width:13.72%; border-top:0.75pt soli= d #000000; border-bottom:0.75pt solid #000000; padding:0pt 5.4pt; vertical-= align:middle"><p class=3D"NoSpacing" style=3D"text-align:center; line-heigh= t:115%; font-size:10pt"><span>0</span></p></td><td style=3D"width:15.76%; b= order-top:0.75pt solid #000000; border-bottom:0.75pt solid #000000; padding= :0pt 5.4pt; vertical-align:middle"><p class=3D"NoSpacing" style=3D"text-ali= gn:center; line-height:115%; font-size:10pt"><span>3</span></p></td><td sty= le=3D"width:16.38%; border-top:0.75pt solid #000000; border-bottom:0.75pt s= olid #000000; padding:0pt 5.4pt; vertical-align:middle"><p class=3D"NoSpaci= ng" style=3D"text-align:center; line-height:115%; font-size:10pt"><span>+30= </span></p></td></tr><tr><td style=3D"width:7.98%; border-top:0.75pt solid = #000000; border-bottom:0.75pt solid #000000; padding:0pt 5.4pt; vertical-al= ign:middle"><p class=3D"NoSpacing" style=3D"text-align:center; line-height:= 115%; font-size:10pt"><span>P3</span></p></td><td style=3D"width:25.88%; bo= rder-top:0.75pt solid #000000; border-bottom:0.75pt solid #000000; padding:= 0pt 5.4pt; vertical-align:middle"><p class=3D"NoSpacing" style=3D"text-alig= n:center; line-height:115%; font-size:10pt"><span>Equivalencia (num=C3=A9ri= ca)</span></p></td><td style=3D"width:13.72%; border-top:0.75pt solid #0000= 00; border-bottom:0.75pt solid #000000; padding:0pt 5.4pt; vertical-align:m= iddle"><p class=3D"NoSpacing" style=3D"text-align:center; line-height:115%;= font-size:10pt"><span>2</span></p></td><td style=3D"width:15.76%; border-t= op:0.75pt solid #000000; border-bottom:0.75pt solid #000000; padding:0pt 5.= 4pt; vertical-align:middle"><p class=3D"NoSpacing" style=3D"text-align:cent= er; line-height:115%; font-size:10pt"><span>5</span></p></td><td style=3D"w= idth:16.38%; border-top:0.75pt solid #000000; border-bottom:0.75pt solid #0= 00000; padding:0pt 5.4pt; vertical-align:middle"><p class=3D"NoSpacing" sty= le=3D"text-align:center; line-height:115%; font-size:10pt"><span>+30</span>= </p></td></tr><tr><td style=3D"width:7.98%; border-top:0.75pt solid #000000= ; border-bottom:0.75pt solid #000000; padding:0pt 5.4pt; vertical-align:mid= dle"><p class=3D"NoSpacing" style=3D"text-align:center; line-height:115%; f= ont-size:10pt"><span>P4</span></p></td><td style=3D"width:25.88%; border-to= p:0.75pt solid #000000; border-bottom:0.75pt solid #000000; padding:0pt 5.4= pt; vertical-align:middle"><p class=3D"NoSpacing" style=3D"text-align:cente= r; line-height:115%; font-size:10pt"><span>Equivalencia (representaci=C3=B3= n)</span></p></td><td style=3D"width:13.72%; border-top:0.75pt solid #00000= 0; border-bottom:0.75pt solid #000000; padding:0pt 5.4pt; vertical-align:mi= ddle"><p class=3D"NoSpacing" style=3D"text-align:center; line-height:115%; = font-size:10pt"><span>0</span></p></td><td style=3D"width:15.76%; border-to= p:0.75pt solid #000000; border-bottom:0.75pt solid #000000; padding:0pt 5.4= pt; vertical-align:middle"><p class=3D"NoSpacing" style=3D"text-align:cente= r; line-height:115%; font-size:10pt"><span>3</span></p></td><td style=3D"wi= dth:16.38%; border-top:0.75pt solid #000000; border-bottom:0.75pt solid #00= 0000; padding:0pt 5.4pt; vertical-align:middle"><p class=3D"NoSpacing" styl= e=3D"text-align:center; line-height:115%; font-size:10pt"><span>+30</span><= /p></td></tr><tr><td colspan=3D"3" style=3D"border-top:0.75pt solid #000000= ; border-bottom:0.75pt solid #000000; padding:0pt 5.4pt; vertical-align:mid= dle"><p class=3D"NoSpacing" style=3D"text-align:center; line-height:115%; f= ont-size:10pt"><span>Subtotal CC</span></p></td><td style=3D"width:13.72%; = border-top:0.75pt solid #000000; border-bottom:0.75pt solid #000000; paddin= g:0pt 5.4pt; vertical-align:middle"><p class=3D"NoSpacing" style=3D"text-al= ign:center; line-height:115%; font-size:10pt"><span>2/40</span></p></td><td= style=3D"width:15.76%; border-top:0.75pt solid #000000; border-bottom:0.75= pt solid #000000; padding:0pt 5.4pt; vertical-align:middle"><p class=3D"NoS= pacing" style=3D"text-align:center; line-height:115%; font-size:10pt"><span= >14/40</span></p></td><td style=3D"width:16.38%; border-top:0.75pt solid #0= 00000; border-bottom:0.75pt solid #000000; padding:0pt 5.4pt; vertical-alig= n:middle"><p class=3D"NoSpacing" style=3D"text-align:center; line-height:11= 5%; font-size:10pt"><span>+30</span></p></td></tr><tr><td rowspan=3D"4" sty= le=3D"width:20.3%; border-top:0.75pt solid #000000; border-bottom:0.75pt so= lid #000000; padding:0pt 5.4pt; vertical-align:middle"><p class=3D"NoSpacin= g" style=3D"text-align:center; line-height:115%; font-size:10pt"><span>Proc= edimientos y habilidades operativas (PHO)</span></p></td><td style=3D"width= :7.98%; border-top:0.75pt solid #000000; border-bottom:0.75pt solid #000000= ; padding:0pt 5.4pt; vertical-align:middle"><p class=3D"NoSpacing" style=3D= "text-align:center; line-height:115%; font-size:10pt"><span>P5</span></p></= td><td style=3D"width:25.88%; border-top:0.75pt solid #000000; border-botto= m:0.75pt solid #000000; padding:0pt 5.4pt; vertical-align:middle"><p class= =3D"NoSpacing" style=3D"text-align:center; line-height:115%; font-size:10pt= "><span>Suma de fracciones</span></p></td><td style=3D"width:13.72%; border= -top:0.75pt solid #000000; border-bottom:0.75pt solid #000000; padding:0pt = 5.4pt; vertical-align:middle"><p class=3D"NoSpacing" style=3D"text-align:ce= nter; line-height:115%; font-size:10pt"><span>8</span></p></td><td style=3D= "width:15.76%; border-top:0.75pt solid #000000; border-bottom:0.75pt solid = #000000; padding:0pt 5.4pt; vertical-align:middle"><p class=3D"NoSpacing" s= tyle=3D"text-align:center; line-height:115%; font-size:10pt"><span>9</span>= </p></td><td style=3D"width:16.38%; border-top:0.75pt solid #000000; border= -bottom:0.75pt solid #000000; padding:0pt 5.4pt; vertical-align:middle"><p = class=3D"NoSpacing" style=3D"text-align:center; line-height:115%; font-size= :10pt"><span>+10</span></p></td></tr><tr><td style=3D"width:7.98%; border-t= op:0.75pt solid #000000; border-bottom:0.75pt solid #000000; padding:0pt 5.= 4pt; vertical-align:middle"><p class=3D"NoSpacing" style=3D"text-align:cent= er; line-height:115%; font-size:10pt"><span>P6</span></p></td><td style=3D"= width:25.88%; border-top:0.75pt solid #000000; border-bottom:0.75pt solid #= 000000; padding:0pt 5.4pt; vertical-align:middle"><p class=3D"NoSpacing" st= yle=3D"text-align:center; line-height:115%; font-size:10pt"><span>Resta de = fracciones</span></p></td><td style=3D"width:13.72%; border-top:0.75pt soli= d #000000; border-bottom:0.75pt solid #000000; padding:0pt 5.4pt; vertical-= align:middle"><p class=3D"NoSpacing" style=3D"text-align:center; line-heigh= t:115%; font-size:10pt"><span>2</span></p></td><td style=3D"width:15.76%; b= order-top:0.75pt solid #000000; border-bottom:0.75pt solid #000000; padding= :0pt 5.4pt; vertical-align:middle"><p class=3D"NoSpacing" style=3D"text-ali= gn:center; line-height:115%; font-size:10pt"><span>5</span></p></td><td sty= le=3D"width:16.38%; border-top:0.75pt solid #000000; border-bottom:0.75pt s= olid #000000; padding:0pt 5.4pt; vertical-align:middle"><p class=3D"NoSpaci= ng" style=3D"text-align:center; line-height:115%; font-size:10pt"><span>+30= </span></p></td></tr><tr><td style=3D"width:7.98%; border-top:0.75pt solid = #000000; border-bottom:0.75pt solid #000000; padding:0pt 5.4pt; vertical-al= ign:middle"><p class=3D"NoSpacing" style=3D"text-align:center; line-height:= 115%; font-size:10pt"><span>P7</span></p></td><td style=3D"width:25.88%; bo= rder-top:0.75pt solid #000000; border-bottom:0.75pt solid #000000; padding:= 0pt 5.4pt; vertical-align:middle"><p class=3D"NoSpacing" style=3D"text-alig= n:center; line-height:115%; font-size:10pt"><span>Promedio simple entre fra= cciones</span></p></td><td style=3D"width:13.72%; border-top:0.75pt solid #= 000000; border-bottom:0.75pt solid #000000; padding:0pt 5.4pt; vertical-ali= gn:middle"><p class=3D"NoSpacing" style=3D"text-align:center; line-height:1= 15%; font-size:10pt"><span>0</span></p></td><td style=3D"width:15.76%; bord= er-top:0.75pt solid #000000; border-bottom:0.75pt solid #000000; padding:0p= t 5.4pt; vertical-align:middle"><p class=3D"NoSpacing" style=3D"text-align:= center; line-height:115%; font-size:10pt"><span>0</span></p></td><td style= =3D"width:16.38%; border-top:0.75pt solid #000000; border-bottom:0.75pt sol= id #000000; padding:0pt 5.4pt; vertical-align:middle"><p class=3D"NoSpacing= " style=3D"text-align:center; line-height:115%; font-size:10pt"><span>0,0</= span></p></td></tr><tr><td style=3D"width:7.98%; border-top:0.75pt solid #0= 00000; border-bottom:0.75pt solid #000000; padding:0pt 5.4pt; vertical-alig= n:middle"><p class=3D"NoSpacing" style=3D"text-align:center; line-height:11= 5%; font-size:10pt"><span>P8</span></p></td><td style=3D"width:25.88%; bord= er-top:0.75pt solid #000000; border-bottom:0.75pt solid #000000; padding:0p= t 5.4pt; vertical-align:middle"><p class=3D"NoSpacing" style=3D"text-align:= center; line-height:115%; font-size:10pt"><span>Promedio contextualizado en= tre fracciones</span></p></td><td style=3D"width:13.72%; border-top:0.75pt = solid #000000; border-bottom:0.75pt solid #000000; padding:0pt 5.4pt; verti= cal-align:middle"><p class=3D"NoSpacing" style=3D"text-align:center; line-h= eight:115%; font-size:10pt"><span>0</span></p></td><td style=3D"width:15.76= %; border-top:0.75pt solid #000000; border-bottom:0.75pt solid #000000; pad= ding:0pt 5.4pt; vertical-align:middle"><p class=3D"NoSpacing" style=3D"text= -align:center; line-height:115%; font-size:10pt"><span>5</span></p></td><td= style=3D"width:16.38%; border-top:0.75pt solid #000000; border-bottom:0.75= pt solid #000000; padding:0pt 5.4pt; vertical-align:middle"><p class=3D"NoS= pacing" style=3D"text-align:center; line-height:115%; font-size:10pt"><span= >+50</span></p></td></tr><tr><td colspan=3D"3" style=3D"border-top:0.75pt s= olid #000000; border-bottom:0.75pt solid #000000; padding:0pt 5.4pt; vertic= al-align:middle"><p class=3D"NoSpacing" style=3D"text-align:center; line-he= ight:115%; font-size:10pt"><span>Subtotal PHO</span></p></td><td style=3D"w= idth:13.72%; border-top:0.75pt solid #000000; border-bottom:0.75pt solid #0= 00000; padding:0pt 5.4pt; vertical-align:middle"><p class=3D"NoSpacing" sty= le=3D"text-align:center; line-height:115%; font-size:10pt"><span>10/40</spa= n></p></td><td style=3D"width:15.76%; border-top:0.75pt solid #000000; bord= er-bottom:0.75pt solid #000000; padding:0pt 5.4pt; vertical-align:middle"><= p class=3D"NoSpacing" style=3D"text-align:center; line-height:115%; font-si= ze:10pt"><span>19/40</span></p></td><td style=3D"width:16.38%; border-top:0= .75pt solid #000000; border-bottom:0.75pt solid #000000; padding:0pt 5.4pt;= vertical-align:middle"><p class=3D"NoSpacing" style=3D"text-align:center; = line-height:115%; font-size:10pt"><span>+22</span></p></td></tr><tr><td row= span=3D"3" style=3D"width:20.3%; border-top:0.75pt solid #000000; border-bo= ttom:0.75pt solid #000000; padding:0pt 5.4pt; vertical-align:middle"><p cla= ss=3D"NoSpacing" style=3D"text-align:center; line-height:115%; font-size:10= pt"><span>Representaci=C3=B3n y comunicaci=C3=B3n matem=C3=A1tica (RCM)</sp= an></p></td><td style=3D"width:7.98%; border-top:0.75pt solid #000000; bord= er-bottom:0.75pt solid #000000; padding:0pt 5.4pt; vertical-align:middle"><= p class=3D"NoSpacing" style=3D"text-align:center; line-height:115%; font-si= ze:10pt"><span>P9</span></p></td><td style=3D"width:25.88%; border-top:0.75= pt solid #000000; border-bottom:0.75pt solid #000000; padding:0pt 5.4pt; ve= rtical-align:middle"><p class=3D"NoSpacing" style=3D"text-align:center; lin= e-height:115%; font-size:10pt"><span>Notaci=C3=B3n</span></p></td><td style= =3D"width:13.72%; border-top:0.75pt solid #000000; border-bottom:0.75pt sol= id #000000; padding:0pt 5.4pt; vertical-align:middle"><p class=3D"NoSpacing= " style=3D"text-align:center; line-height:115%; font-size:10pt"><span>8</sp= an></p></td><td style=3D"width:15.76%; border-top:0.75pt solid #000000; bor= der-bottom:0.75pt solid #000000; padding:0pt 5.4pt; vertical-align:middle">= <p class=3D"NoSpacing" style=3D"text-align:center; line-height:115%; font-s= ize:10pt"><span>10</span></p></td><td style=3D"width:16.38%; border-top:0.7= 5pt solid #000000; border-bottom:0.75pt solid #000000; padding:0pt 5.4pt; v= ertical-align:middle"><p class=3D"NoSpacing" style=3D"text-align:center; li= ne-height:115%; font-size:10pt"><span>+20</span></p></td></tr><tr><td style= =3D"width:7.98%; border-top:0.75pt solid #000000; border-bottom:0.75pt soli= d #000000; padding:0pt 5.4pt; vertical-align:middle"><p class=3D"NoSpacing"= style=3D"text-align:center; line-height:115%; font-size:10pt"><span>P10</s= pan></p></td><td style=3D"width:25.88%; border-top:0.75pt solid #000000; bo= rder-bottom:0.75pt solid #000000; padding:0pt 5.4pt; vertical-align:middle"= ><p class=3D"NoSpacing" style=3D"text-align:center; line-height:115%; font-= size:10pt"><span>Orden de fracciones</span></p></td><td style=3D"width:13.7= 2%; border-top:0.75pt solid #000000; border-bottom:0.75pt solid #000000; pa= dding:0pt 5.4pt; vertical-align:middle"><p class=3D"NoSpacing" style=3D"tex= t-align:center; line-height:115%; font-size:10pt"><span>8</span></p></td><t= d style=3D"width:15.76%; border-top:0.75pt solid #000000; border-bottom:0.7= 5pt solid #000000; padding:0pt 5.4pt; vertical-align:middle"><p class=3D"No= Spacing" style=3D"text-align:center; line-height:115%; font-size:10pt"><spa= n>10</span></p></td><td style=3D"width:16.38%; border-top:0.75pt solid #000= 000; border-bottom:0.75pt solid #000000; padding:0pt 5.4pt; vertical-align:= middle"><p class=3D"NoSpacing" style=3D"text-align:center; line-height:115%= ; font-size:10pt"><span>+20</span></p></td></tr><tr><td style=3D"width:7.98= %; border-top:0.75pt solid #000000; border-bottom:0.75pt solid #000000; pad= ding:0pt 5.4pt; vertical-align:middle"><p class=3D"NoSpacing" style=3D"text= -align:center; line-height:115%; font-size:10pt"><span>P11</span></p></td><= td style=3D"width:25.88%; border-top:0.75pt solid #000000; border-bottom:0.= 75pt solid #000000; padding:0pt 5.4pt; vertical-align:middle"><p class=3D"N= oSpacing" style=3D"text-align:center; line-height:115%; font-size:10pt"><sp= an>Explicaci=C3=B3n</span></p></td><td style=3D"width:13.72%; border-top:0.= 75pt solid #000000; border-bottom:0.75pt solid #000000; padding:0pt 5.4pt; = vertical-align:middle"><p class=3D"NoSpacing" style=3D"text-align:center; l= ine-height:115%; font-size:10pt"><span>0</span></p></td><td style=3D"width:= 15.76%; border-top:0.75pt solid #000000; border-bottom:0.75pt solid #000000= ; padding:0pt 5.4pt; vertical-align:middle"><p class=3D"NoSpacing" style=3D= "text-align:center; line-height:115%; font-size:10pt"><span>10</span></p></= td><td style=3D"width:16.38%; border-top:0.75pt solid #000000; border-botto= m:0.75pt solid #000000; padding:0pt 5.4pt; vertical-align:middle"><p class= =3D"NoSpacing" style=3D"text-align:center; line-height:115%; font-size:10pt= "><span>+100</span></p></td></tr><tr><td colspan=3D"3" style=3D"border-top:= 0.75pt solid #000000; border-bottom:0.75pt solid #000000; padding:0pt 5.4pt= ; vertical-align:middle"><p class=3D"NoSpacing" style=3D"text-align:center;= line-height:115%; font-size:10pt"><span>Subtotal RCM</span></p></td><td st= yle=3D"width:13.72%; border-top:0.75pt solid #000000; border-bottom:0.75pt = solid #000000; padding:0pt 5.4pt; vertical-align:middle"><p class=3D"NoSpac= ing" style=3D"text-align:center; line-height:115%; font-size:10pt"><span>16= /30</span></p></td><td style=3D"width:15.76%; border-top:0.75pt solid #0000= 00; border-bottom:0.75pt solid #000000; padding:0pt 5.4pt; vertical-align:m= iddle"><p class=3D"NoSpacing" style=3D"text-align:center; line-height:115%;= font-size:10pt"><span>30/30</span></p></td><td style=3D"width:16.38%; bord= er-top:0.75pt solid #000000; border-bottom:0.75pt solid #000000; padding:0p= t 5.4pt; vertical-align:middle"><p class=3D"NoSpacing" style=3D"text-align:= center; line-height:115%; font-size:10pt"><span>+46,7</span></p></td></tr><= /table><p style=3D"margin-bottom:0pt; text-align:justify; line-height:115%"= ><span> </span></p><p class=3D"ListParagraph" style=3D"margin-bottom:0= pt; text-indent:-18pt; text-align:justify; line-height:115%"><span style=3D= "font-weight:bold"><span>4.</span></span><span style=3D"width:9pt; font:7pt= 'Times New Roman'; display:inline-block">      </= span><span style=3D"font-weight:bold">Discusi=C3=B3n</span></p><p style=3D"= margin-bottom:0pt; text-align:justify; line-height:115%"><span>Los resultad= os muestran mejoras sustantivas tras integrar PhET: comprensi=C3=B3n concep= tual, procedimientos y representaci=C3=B3n=E2=80=93comunicaci=C3=B3n. Esto = sugiere que la visualizaci=C3=B3n y la manipulaci=C3=B3n guiada favorecen c= onexiones parte=E2=80=93todo, equivalencias y justificaci=C3=B3n de procedi= mientos, en l=C3=ADnea con el enfoque de educaci=C3=B3n andrag=C3=B3gica me= ncionados por Note et</span><span> </span><span>al. (2021) centrados e= n la experiencia y la resoluci=C3=B3n de problemas. Estos hallazgos son coh= erentes con evidencia sobre simulaciones interactivas que elevan desempe=C3= =B1o y participaci=C3=B3n, y con marcos que recomiendan m=C3=BAltiples repr= esentaciones en el aprendizaje de fracciones como los de Kumar (2024) o Gar= c=C3=ADa (2019).</span></p><p style=3D"margin-bottom:0pt; text-align:justif= y; line-height:115%"><span>El nulo avance en =C2=ABpromedio simple=C2=BB re= vela un vac=C3=ADo de significado m=C3=A1s que de procedimiento. Cuando la = media se ense=C3=B1a solo como =E2=80=9Csumar y dividir=E2=80=9D, los estud= iantes no activan ideas de reparto justo, ponderaci=C3=B3n o punto medio; e= n cambio, las tareas de modelizaci=C3=B3n en contextos reales ampl=C3=ADan = ese significado y hacen m=C3=A1s accesible el =E2=80=9Cpromedio contextuali= zado=E2=80=9D, tal como reportan estudios recientes de Shahbari & Tabac= h (2021) que coinciden con evidencias de que el contexto de reparto justo f= avorece el razonamiento proporcional frente a situaciones descontextualizad= as. Es decir, los resultados son coherentes: hubo progreso donde hubo mayor= contextualizaci=C3=B3n y practicidad y estancamiento donde falt=C3=B3. </s= pan></p><p style=3D"margin-bottom:0pt; text-align:justify; line-height:115%= "><span>La mejora en suma y resta con y sin com=C3=BAn denominador y en pro= medio contextualizado sugiere que el anclaje situacional facilit=C3=B3 el t= raslado del algoritmo a problemas, pero no sustituy=C3=B3 la instrucci=C3= =B3n expl=C3=ADcita sobre promedios. Esto se explica a trav=C3=A9s de la in= vestigaci=C3=B3n de Landtblom (2023) en su revisi=C3=B3n sobre media en pri= maria muestra que muchos estudiantes =E2=80=9Csaben calcular=E2=80=9D la me= dia, pero carecen de significado conceptual (representatividad, punto de eq= uilibrio), por lo que requieren ense=C3=B1anza expl=C3=ADcita y tareas que = visibilicen cu=C3=A1ndo y por qu=C3=A9 usar la media; el mero algoritmo no = basta. Esto aclara por qu=C3=A9 al dar un mayor contexto en la actividad fa= voreci=C3=B3 llevar el procedimiento a problemas (mejor=C3=B3 =E2=80=9Cprom= edio contextualizado=E2=80=9D), mientras que el =E2=80=9Cpromedio simple; t= ratado de forma descontextualizada, no progres=C3=B3. Como complemento Shah= bari & Tabach (2021) muestran que tareas de modelizaci=C3=B3n contextua= l expanden el significado del promedio m=C3=A1s all=C3=A1 de =E2=80=9Csumar= y dividir=E2=80=9D. </span></p><p style=3D"margin-bottom:0pt; text-align:j= ustify; line-height:115%"><span>El patr=C3=B3n observado converge con el es= tudio de Acquah et</span><span> </span><span>al. (2024) que reportan g= anancias en comprensi=C3=B3n y motivaci=C3=B3n con PhET y tecnolog=C3=ADas = educativas, as=C3=AD como con la literatura andrag=C3=B3gica de Note et</sp= an><span> </span><span>al. (2021) que prioriza la relevancia y la auto= nom=C3=ADa del adulto. El uso de simulaciones como =E2=80=9CConstruyamos un= a fracci=C3=B3n=E2=80=9D y =E2=80=9CFracciones: Igualdad=E2=80=9D encaja co= n recomendaciones de aprendizaje activo y </span><span style=3D"font-style:= italic">feedback</span><span> inmediato. </span></p><p style=3D"margin-bott= om:0pt; text-align:justify; line-height:115%"><span>Entre las limitaciones = de la investigaci=C3=B3n. El estudio se realiz=C3=B3 en una sola escuela, c= on una muestra peque=C3=B1a (10 personas adultas de 40+ a=C3=B1os). Se us= =C3=B3 un dise=C3=B1o transversal, sin grupo de comparaci=C3=B3n, y la medi= ci=C3=B3n se aplic=C3=B3 de inmediato al terminar la intervenci=C3=B3n. Est= as limitaciones evidencian la necesidad de continuar la investigaci=C3=B3n = y aplicaci=C3=B3n de este sistema de actividades en contextos educativos si= milares. Adem=C3=A1s, es importante considerar el nivel de alfabetizaci=C3= =B3n digital del estudiantado y las competencias digitales del docente en l= a utilizaci=C3=B3n de estas tecnolog=C3=ADas digitales</span><span style=3D= "font-weight:bold">. </span></p><p class=3D"ListParagraph" style=3D"margin-= bottom:0pt; text-indent:-18pt; line-height:115%"><span style=3D"font-weight= :bold"><span>5.</span></span><span style=3D"width:9pt; font:7pt 'Times New = Roman'; display:inline-block">      </span><span s= tyle=3D"font-weight:bold">Conclusiones</span></p><p style=3D"margin-bottom:= 0pt; text-align:justify; line-height:115%"><span>La integraci=C3=B3n de sim= ulaciones PhET transform=C3=B3 la din=C3=A1mica del aula al sustituir un mo= delo transmisivo por uno exploratorio. En este nuevo enfoque, el error se c= onvirti=C3=B3 en un insumo formativo, mientras que la retroalimentaci=C3=B3= n inmediata de las simulaciones fortaleci=C3=B3 la comprensi=C3=B3n, la com= unicaci=C3=B3n matem=C3=A1tica y la motivaci=C3=B3n en estudiantes adultos = mayores de 40 a=C3=B1os.</span></p><p style=3D"margin-bottom:0pt; text-alig= n:justify; line-height:115%"><span>La propuesta del sistema de actividades = demostr=C3=B3 ser viable y curricularmente alineada con las necesidades de = los adultos que retoman sus estudios. Adem=C3=A1s, se configura como un mod= elo replicable que articula coherentemente el procedimiento, la representac= i=C3=B3n y la justificaci=C3=B3n en el aprendizaje de las fracciones.</span= ></p><p style=3D"margin-bottom:0pt; text-align:justify; line-height:115%"><= span>La intervenci=C3=B3n super=C3=B3 las dificultades iniciales y consolid= =C3=B3 aprendizajes clave: se afianz=C3=B3 la comprensi=C3=B3n desde la rel= aci=C3=B3n parte=E2=80=93todo y las equivalencias, se ampliaron las formas = de representaci=C3=B3n y mejor=C3=B3 la capacidad para explicar razonamient= os en distintos formatos. En conjunto, la visualizaci=C3=B3n y la manipulac= i=C3=B3n guiada, integradas con teor=C3=ADa andrag=C3=B3gica como el aprend= izaje desde la experiencia, resoluci=C3=B3n de problemas, roles y practicid= ad, se confirman como estrategias eficaces para cerrar brechas y sostener a= vances en contextos de educaci=C3=B3n de personas adultas.</span></p><p cla= ss=3D"ListParagraph" style=3D"margin-bottom:0pt; text-indent:-18pt; text-al= ign:justify; line-height:115%"><span><span style=3D"font-weight:bold">6.</s= pan></span><span style=3D"width:9pt; font:7pt 'Times New Roman'; display:in= line-block">      </span><span style=3D"font-weigh= t:bold">Conflicto de intereses</span></p><p style=3D"margin-bottom:0pt; tex= t-align:justify; line-height:115%"><span>Los autores declaran que no existe= conflicto de intereses en relaci=C3=B3n con el art=C3=ADculo presentado.</= span></p><p class=3D"ListParagraph" style=3D"margin-bottom:0pt; text-indent= :-18pt; text-align:justify; line-height:115%"><span style=3D"font-weight:bo= ld"><span>7.</span></span><span style=3D"width:9pt; font:7pt 'Times New Rom= an'; display:inline-block">      </span><span styl= e=3D"font-weight:bold">Declaraci=C3=B3n de contribuci=C3=B3n de los autores= </span></p><p style=3D"margin-bottom:0pt; text-align:justify; line-height:1= 15%"><span>Todos autores contribuyeron significativamente en la elaboraci= =C3=B3n del art=C3=ADculo.</span></p><p class=3D"ListParagraph" style=3D"ma= rgin-bottom:0pt; text-indent:-18pt; text-align:justify; line-height:115%"><= span style=3D"font-weight:bold"><span>8.</span></span><span style=3D"width:= 9pt; font:7pt 'Times New Roman'; display:inline-block">   &#= xa0;  </span><span style=3D"font-weight:bold">Costos de financiamiento= </span></p><p style=3D"margin-bottom:0pt; text-align:justify; line-height:= 115%"><span>La presente investigaci=C3=B3n fue financiada en su totalidad c= on fondos propios de los autores.</span></p><p class=3D"ListParagraph" styl= e=3D"margin-bottom:0pt; text-indent:-18pt; text-align:justify; line-height:= 115%"><span style=3D"font-weight:bold"><span>9.</span></span><span style=3D= "width:9pt; font:7pt 'Times New Roman'; display:inline-block">  &= #xa0;   </span><span style=3D"font-weight:bold">Referencias Bibli= ogr=C3=A1ficas</span></p><p><span> </span></p><p style=3D"margin-left:= 35.4pt; text-indent:-35.4pt; line-height:115%"><span>Acquah, I. K., Gyan, M= ., Appiah, D., Ansah, B. O., Wilson, R., & Mensah, C. E. (2024). Improv= ing students=E2=80=99 performance in resolution of vectors using PhET inter= active simulations. </span><span style=3D"font-style:italic">Schr=C3=B6ding= er: Journal of Physics Education</span><span>, </span><span style=3D"font-s= tyle:italic">5</span><span>(3), 107-116. </span><a href=3D"https://doi.org/= 10.37251/sjpe.v5i3.1078" style=3D"text-decoration:none"><span class=3D"Hype= rlink">https://doi.org/10.37251/sjpe.v5i3.1078</span></a></p><p style=3D"ma= rgin-left:35.4pt; text-indent:-35.4pt; line-height:115%"><span>Almadrones, = R. D., & Tadifa, F. G. (2024). Physics Educational Technology (PHET) si= mulations in teaching general physics 1. </span><span style=3D"font-style:i= talic">International Journal of Instruction</span><span>, </span><span styl= e=3D"font-style:italic">17</span><span>(3), 635=E2=80=93650. </span><a href= =3D"https://e-iji.net/ats/index.php/pub/article/view/632" style=3D"text-dec= oration:none"><span class=3D"Hyperlink">https://e-iji.net/ats/index.php/pub= /article/view/632</span></a></p><p class=3D"Bibliography" style=3D"line-hei= ght:115%"><span>=C3=81vila Correa, B. L. (2018). Perspectivas de transforma= ci=C3=B3n digital de las universidades del Ecuador. </span><span style=3D"f= ont-style:italic">Revista Ciencias Pedag=C3=B3gicas e Innovaci=C3=B3n</span= ><span>, </span><span style=3D"font-style:italic">6</span><span>(2), 1-11. = </span><a href=3D"https://doi.org/10.26423/rcpi.v6i2.233" style=3D"text-dec= oration:none"><span class=3D"Hyperlink">https://doi.org/10.26423/rcpi.v6i2.= 233</span></a></p><p class=3D"Bibliography" style=3D"line-height:115%"><spa= n>Banco de Desarrollo de Am=C3=A9rica Latina y el Caribe [CAF-banco]. (2024= ). </span><span style=3D"font-style:italic">Desigualdad 4.0: a cerrar la br= echa digital</span><span> [Institucional]. </span><a href=3D"https://www.ca= f.com/es/actualidad/noticias/desigualdad-40-a-cerrar-la-brecha-digital/" st= yle=3D"text-decoration:none"><span class=3D"Hyperlink">https://www.caf.com/= es/actualidad/noticias/desigualdad-40-a-cerrar-la-brecha-digital/</span></a= ></p><p class=3D"Bibliography" style=3D"line-height:115%"><span>Burgos-Posl= igua, M. O., & Samada-Grasst, Y. (2023). Sistema de actividades did=C3= =A1cticas para el desarrollo de la preescritura en ni=C3=B1os de 5 a=C3=B1o= s. </span><span style=3D"font-style:italic">MQRInvestigar</span><span>, </s= pan><span style=3D"font-style:italic">7</span><span>(3), 766-793. </span><a= href=3D"https://doi.org/10.56048/MQR20225.7.3.2023.766-793" style=3D"text-= decoration:none"><span class=3D"Hyperlink">https://doi.org/10.56048/MQR2022= 5.7.3.2023.766-793</span></a></p><p class=3D"Bibliography" style=3D"line-he= ight:115%"><span>Diab, H., Daher, W., Rayan, B., Issa, N., & Rayan, A. = (2024). Transforming science education in elementary schools: the power of = PhET simulations in enhancing student learning. </span><span style=3D"font-= style:italic">Multimodal Technologies and Interaction</span><span>, </span>= <span style=3D"font-style:italic">8</span><span>(11), 105. </span><a href= =3D"https://doi.org/10.3390/mti8110105" style=3D"text-decoration:none"><spa= n class=3D"Hyperlink">https://doi.org/10.3390/mti8110105</span></a></p><p c= lass=3D"Bibliography" style=3D"line-height:115%"><span>Efgivia, M. G., Ermi= nawati, Fitriani, E., & Herni. (2021). </span><span style=3D"font-style= :italic">Analysis of Andragogy Theory and Practice</span><span>. Published = by Atlantis Press. </span><a href=3D"https://doi.org/10.2991/assehr.k.21102= 0.027" style=3D"text-decoration:none"><span class=3D"Hyperlink">https://doi= .org/10.2991/assehr.k.211020.027</span></a></p><p class=3D"Bibliography" st= yle=3D"line-height:115%"><span>El-Amin, A. (2020). Andragogy: a theory in p= ractice in higher education. </span><span style=3D"font-style:italic">Journ= al of Research in Higher Education</span><span>, </span><span style=3D"font= -style:italic">4</span><span>(2), 54-71. </span><a href=3D"http://dx.doi.or= g/10.24193/JRHE.2020.2.4" style=3D"text-decoration:none"><span class=3D"Hyp= erlink">http://dx.doi.org/10.24193/JRHE.2020.2.4</span></a></p><p style=3D"= margin-left:35.4pt; text-indent:-35.4pt"><span>Garc=C3=ADa Aretio, L. (2019= ). Necesidad de una educaci=C3=B3n digital en un mundo digital. </span><spa= n style=3D"font-style:italic">RIED-Revista Iberoamericana de Educaci=C3=B3n= a Distancia</span><span>, </span><span style=3D"font-style:italic">22</spa= n><span>(2), 9-22. </span><a href=3D"https://doi.org/10.5944/ried.22.2.2391= 1" style=3D"text-decoration:none"><span class=3D"Hyperlink">https://doi.org= /10.5944/ried.22.2.23911</span></a></p><p style=3D"margin-left:35.4pt; text= -indent:-35.4pt; line-height:115%"><a href=3D"https://www.taylorfrancis.com= /search?contributorName=3DMalcolm%20S.%20Knowles&contributorRole=3Dauth= or&redirectFromPDP=3Dtrue&context=3Dubx" style=3D"text-decoration:n= one"><span class=3D"Hyperlink" style=3D"text-decoration:none; color:#000000= ">Knowles</span></a><span>, M. S.,</span><span> </span><a href=3D"http= s://www.taylorfrancis.com/search?contributorName=3DElwood%20F.%20Holton%20I= II&contributorRole=3Dauthor&redirectFromPDP=3Dtrue&context=3Dub= x" style=3D"text-decoration:none"><span class=3D"Hyperlink" style=3D"text-d= ecoration:none; color:#000000">Holton</span></a><span>, E. F.,</span><span>=  </span><span> </span><a href=3D"https://www.taylorfrancis.com/search?= contributorName=3DRichard%20A.%20Swanson&contributorRole=3Dauthor&r= edirectFromPDP=3Dtrue&context=3Dubx" style=3D"text-decoration:none"><sp= an class=3D"Hyperlink" style=3D"text-decoration:none; color:#000000">Swanso= n</span></a><span>, R. A. & </span><a href=3D"https://www.taylorfrancis= .com/search?contributorName=3DPetra%20A.%20Robinson&contributorRole=3Da= uthor&redirectFromPDP=3Dtrue&context=3Dubx" style=3D"text-decoratio= n:none"><span class=3D"Hyperlink" style=3D"text-decoration:none; color:#000= 000">Robinson</span></a><span>, P. A.</span><span> </span><span> (2020= ). </span><span style=3D"font-style:italic">The Adult Learner: the definiti= ve classic in adult education and human resource development (9th edition).= </span><span> Imprint Routledge. </span><a href=3D"https://doi.org/10.4324/= 9780429299612" target=3D"_blank" style=3D"text-decoration:none"><span class= =3D"Hyperlink">https://doi.org/10.4324/9780429299612</span></a></p><p class= =3D"Bibliography" style=3D"line-height:115%"><span>Kumar, D. (2024). PhET: = an interactive simulation technology for learning outcomes-based teaching-l= earning science. </span><span style=3D"font-style:italic">International Edu= cation and Research Journal (IERJ)</span><span>, </span><span style=3D"font= -style:italic">10</span><span>(5). </span><a href=3D"https://doi.org/10.212= 76/IERJ24501797296604" style=3D"text-decoration:none"><span class=3D"Hyperl= ink">https://doi.org/10.21276/IERJ24501797296604</span></a></p><p class=3D"= Bibliography" style=3D"line-height:115%"><span>Landtblom, K. (2023). Opport= unities to learn mean, media, and mode afforded by textbook tasks. </span><= span style=3D"font-style:italic">Statistics Education Research Journal, 22<= /span><span>(3), Article 6. </span><a href=3D"https://doi.org/10.52041/serj= .v22i3.655" style=3D"text-decoration:none"><span class=3D"Hyperlink">https:= //doi.org/10.52041/serj.v22i3.655</span></a></p><p class=3D"Bibliography" s= tyle=3D"line-height:115%"><span>Melliofatria, Mahdum, Hadriana, & Purwa= nti, I. T. (2024). Models For Andragogy: A Systematic Review and Meta-Analy= sis. </span><span style=3D"font-style:italic">Evolutionary studies in imagi= native culture</span><span>, 583-616. https://doi.org/10.70082/esiculture.v= i.757</span></p><p class=3D"Bibliography" style=3D"line-height:115%"><span>= Ministerio de Educaci=C3=B3n, Deporte y Cultura del Ecuador. (2025). </span= ><span style=3D"font-style:italic">Adaptaciones curriculares con =C3=A9nfas= is en competencias para la educaci=C3=B3n de personas j=C3=B3venes, adultas= y adultas mayores en situaci=C3=B3n de escolaridad inconcluso para B=C3=A1= sica Superior y Bachillerato. </span><a href=3D"https://educacion.gob.ec/wp= -content/uploads/downloads/2025/09/adaptaciones-curriculares-EGB-BS-BG.pdf"= style=3D"text-decoration:none"><span class=3D"Hyperlink">https://educacion= .gob.ec/wp-content/uploads/downloads/2025/09/adaptaciones-curriculares-EGB-= BS-BG.pdf</span></a></p><p class=3D"Bibliography" style=3D"line-height:115%= "><span>National Research Council. (2001). </span><span style=3D"font-style= :italic">Adding it up: helping children learn mathematics</span><span> (1</= span><span style=3D"line-height:115%; font-size:8pt; vertical-align:super">= st</span><span>. edition). National Research Council Press. </span><a href= =3D"https://doi.org/10.17226/9822" style=3D"text-decoration:none"><span cla= ss=3D"Hyperlink">https://doi.org/10.17226/9822</span></a></p><p class=3D"Bi= bliography" style=3D"line-height:115%"><span>Note, N., De Backer, F., &= Donder, L. D. (2021). A novel viewpoint on andragogy: enabling moments of = community. </span><span style=3D"font-style:italic">Adult Education Quarter= ly</span><span>, </span><span style=3D"font-style:italic">71</span><span>(1= ), 3-19. </span><a href=3D"https://doi.org/10.1177/0741713620921361" style= =3D"text-decoration:none"><span class=3D"Hyperlink">https://doi.org/10.1177= /0741713620921361</span></a></p><p class=3D"Bibliography" style=3D"line-hei= ght:115%"><span>Organizaci=C3=B3n de las Naciones Unidas para la Educaci=C3= =B3n, la Ciencia y la Cultura [UNESCO]. (2024). </span><span style=3D"font-= style:italic">El derecho a la educaci=C3=B3n</span><span>. </span><a href= =3D"https://www.unesco.org/es/right-education" style=3D"text-decoration:non= e"><span class=3D"Hyperlink">https://www.unesco.org/es/right-education</spa= n></a></p><p class=3D"Bibliography" style=3D"line-height:115%"><span>Perry,= R., Neumayer DePiper, J., Tsinnajinnie, B., Jackson, B. E., & Thornley= , L. (2025). Numeracy education for adult learners: a scan of the field and= principles for course and materials design. </span><span style=3D"font-sty= le:italic">Adult Learning</span><span>, </span><span style=3D"font-style:it= alic">36</span><span>(2), 84-95. </span><a href=3D"https://doi.org/10.1177/= 10451595241245146" style=3D"text-decoration:none"><span class=3D"Hyperlink"= >https://doi.org/10.1177/10451595241245146</span></a></p><p style=3D"margin= -left:35.4pt; text-indent:-35.4pt"><span>Salinas Villacr=C3=A9s, D., & = Negri Cort=C3=A9s, M. I. (2021). =C2=BFPor qu=C3=A9 volver a la escuela? Un= estudio de caso sobre Educaci=C3=B3n de Adultos en Ecuador. </span><span s= tyle=3D"font-style:italic">International Journal of New Education</span><sp= an>, (6). </span><a href=3D"https://doi.org/10.24310/IJNE3.2.2020.10248" st= yle=3D"text-decoration:none"><span class=3D"Hyperlink">https://doi.org/10.2= 4310/IJNE3.2.2020.10248</span></a></p><p style=3D"margin-left:35.4pt; text-= indent:-35.4pt"><span>S=C3=A1nchez-Domenech, I., & Cabeza-Rodr=C3=ADgue= z, M.-=C3=81. (2024). Andragog=C3=ADa digital: necesidad de saber y papel d= e la experiencia en un m=C3=A1ster universitario en l=C3=ADnea. </span><spa= n style=3D"font-style:italic">RIED-Revista Iberoamericana de Educaci=C3=B3n= a Distancia</span><span>, </span><span style=3D"font-style:italic">27</spa= n><span>(2), 357=E2=80=93382. </span><a href=3D"https://doi.org/10.5944/rie= d.27.2.38799" style=3D"text-decoration:none"><span class=3D"Hyperlink">http= s://doi.org/10.5944/ried.27.2.38799</span></a></p><p style=3D"margin-left:3= 5.4pt; text-indent:-35.4pt"><span>Shahbari, J. A., & Tabach, M. (2020).= Making sense of the average concept through engagement in model-eliciting = activities. </span><span style=3D"font-style:italic">International Journal = of Mathematical Education in Science and Technology</span><span>, </span><s= pan style=3D"font-style:italic">52</span><span>(8), 1143=E2=80=931160. </sp= an><a href=3D"https://doi.org/10.1080/0020739X.2020.1740803" style=3D"text-= decoration:none"><span class=3D"Hyperlink">https://doi.org/10.1080/0020739X= .2020.1740803</span></a></p><p class=3D"Bibliography" style=3D"line-height:= 115%"><span>Stojanovic, M. (2022). Book Review: The adult learner: The defi= nitive classic in adult education and human resource development by M. S. K= nowles, E. F. Holton III, R. A. Swanson, & P. A. Robinson. </span><span= style=3D"font-style:italic">Adult Education Quarterly</span><span>, </span= ><span style=3D"font-style:italic">72</span><span>(2), 216-217. </span><a h= ref=3D"https://doi.org/10.1177/07417136211045695" style=3D"text-decoration:= none"><span class=3D"Hyperlink">https://doi.org/10.1177/07417136211045695</= span></a></p><p style=3D"margin-left:35.4pt; text-indent:-35.4pt"><span>Ter= hune, K., Conwell, S., Danzo, A., Graf, A., & Kim, S.-H. (2021). Suppor= ting educational needs of older adult learners: strategies for virtual tran= sitioning and student engagement. </span><span style=3D"font-style:italic">= Innovation in Aging</span><span>, </span><span style=3D"font-style:italic">= 5</span><span>(Supplement 1), 385. </span><a href=3D"https://doi.org/10.109= 3/geroni/igab046.1496" style=3D"text-decoration:none"><span class=3D"Hyperl= ink">https://doi.org/10.1093/geroni/igab046.1496</span></a></p><p style=3D"= text-indent:36pt; line-height:115%"><span style=3D"font-weight:bold"> = </span></p><p style=3D"text-indent:36pt; text-align:right; line-height:115%= "><img src=3D"data:image/jpeg;base64,/9j/4AAQSkZJRgABAQEAYABgAAD/2wBDAAEBAQ= EBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBA= QEBAQH/2wBDAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEB= AQEBAQEBAQEBAQEBAQEBAQH/wAARCABAAHoDASIAAhEBAxEB/8QAHgAAAwEAAgMBAQAAAAAAAAA= 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style=3D"width:63.4pt; letter-spacing:3pt; display:inline-block"> <= /span><span style=3D"width:27.7pt; letter-spacing:3pt; display:inline-block= "> </span><span style=3D"width:35.4pt; letter-spacing:3pt; display:inl= ine-block"> </span><span style=3D"letter-spacing:3pt; color:#ffffff"> = </span><span style=3D"width:32.4pt; letter-spacing:3pt; display:inline-bloc= k"> </span><span style=3D"color:#ffffff"> </span><span style=3D"color:= #ffffff; background-color:#ffff00">1</span></p><p class=3D"Footer"><span>&#= xa0;</span></p></div></div></body></html>