Personalized Learning: A Techno-Educational Strategy for High School Computer Science Students (Docentes 2.0 Journal, 2021)
In the learning environments of educational institutions, transformations are being generated to offer more flexible and valuable learning with a practical application. In the teaching-learning process, there must be the student's active involvement. A strategy to achieve this can be personalized learning, which seeks a more coarse adjustment of the courses to the students' individual needs. That is why the proposal arises to make use of personalized learning through an Adaptive System to identify its impact on improving students' academic performance in computing at a higher-level educational institution. To carry it out, a quantitative approach of an experimental type has been considered with a test group plus a control group; the data analysis is based on inferential statistics. This proposal was made with a sample of 30 participants; for its collection, the following instruments are considered: learning style tests, standardized instruments, learning strategies tests, diagnostic evaluation, final evaluation, and student satisfaction questionnaire. In addition, to improve the students' academic performance, generating a reference guide of good practices and a dissemination program for this type of learning. Therefore, the implementation of educational methods such as personalized learning through adaptive systems reflects a positive impact on students' academic performance.
Keywords: Personalized learning; adaptive tecnhology; adaptive systems; academic performance