IMPACT OF AN APPLICATION WITH ARTIFICIAL INTELLIGENCE FOR SELF-REGULATED LEARNING, INTEGRATED INTO THE VIRTUAL CLASSROOM, ON THE DEVELOPMENT OF SELF-REGULATED LEARNING AND THE EDUCATIONAL RESULTS OF UNIVERSITY STUDENTS.

The present project seeks to perfect, expand and elevate the scope of a self-regulated learning web application developed and integrated into the virtual classroom of the LMS CANVAS during the years 2022 to 2024 within the framework of the Research Start-up Fondecyt 11221355 and which was implemented with undergraduate students of critical subjects in STEM careers at our university. In this second stage the aim is to improve the tool in its functionalities, expand its use in all areas of knowledge and generate evidence of its effectiveness in improving the self-regulation skills of students' learning and their educational results (grade and approval of subjects).
The design will be quasi-experimental randomized by clusters, with an experimental and control group, using pre- and post-test measurement. The aim is to manipulate the independent variable, the use of the virtual classroom with the new version of the self-regulated learning application in the CANVAS virtual classroom v/s the non-use of this application, to observe its effects on the levels of development of strategies for willingness to study, execution and evaluation of the self-regulated learning processes and on the performance and approval of subjects. OECD, with stable enrollment over the last 5 years, with low passing rates (<25%) in each of the three committed universities and their respective headquarters, Universidad de Concepción, Universidad del Desarrollo and Universidad Andrés Bellos. If we use an effect size of d=0.4 with 95% power, assuming an intraclass correlation of 0.2 and a significance level of 5%, we require a sample of 323 students per university to evaluate the effect of the intervention. Considering a sample loss of 30%, a minimum of 420 students is considered for each university. Despite this minimum, to cover the 5 areas of knowledge, considering subjects that have, on average, 50 students, we would have a sample of 1,000 students per University, sufficient for the analyzes that the study proposes.

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