Impact of Adaptive Platforms on the Academic Performance of University Students

Resumen

In a context where higher education faces increasing challenges to personalize learning and improve academic performance, adaptive platforms emerge as innovative tools. These technologies use algorithms to adjust content and activities according to the individual needs of students. Even so, their effectiveness in university contexts such as the Universidad Peruana Los Andes, still needs to be empirically corroborated. The purpose of this study is to analyze the effects of the use of adaptive platforms on academic performance and student satisfaction, with the aim of verifying their effectiveness in personalizing learning in university students. A quasi-experimental design of a comparative type and quantitative approach was developed. The sample consisted of 120 undergraduate students divided into an experimental group and a comparison group. Questionnaires and academic records were used to measure performance and satisfaction. For statistical analysis, Student's t test and factorial ANOVA were used, which checked whether there were significant differences. The results showed that the experimental group that used adaptive platforms obtained higher grades (M = 85.4, SD = 5.6) than the comparison group (M = 78.2, SD = 6.4; p < 0.001). Likewise, students in the experimental group reported greater satisfaction with learning (p = 0.002). No significant effects of the variables age or previous experience with technology were recorded. This study confirms that adaptive platforms allow for increased academic performance and student satisfaction, also showing that they are effective in disparate contexts, so their implementation by higher education institutions as a teaching strategy is recommended.