Measuring Achievement Interest: The strategic Role of Deep Learning, Academic Engagement, and Family Resilience of Science Students. Daniar Setyo Rini, Fitria Pusparini, Nailul Rahmi Aulya
Universitas Negeri Jakarta
Abstract
Amid such rapid technological developments, the education and learning process in the current era takes place more easily and quickly, so that it is felt that students become less attached to the learning process in the classroom, which makes learning less meaningful. This has an impact on decreasing students^ interest in achievement. This study aims to determine the influence of Family Resilience, Academic engagement, and Deep learning on the interest in achievement in MIPA students. The research uses a quantitative approach with a survey method. Data were collected through questionnaires using the Likert scale and analyzed by multiple linear regression analysis. The analysis showed that the regression model consisting of three independent variables simultaneously significantly affected achievement interest (F 33.220- p<0.001). An R2 value of 0.470 indicates that the model can explain 47% of the variation in achievement interest. Partially, Deep Learning contributed the most (b=0.405, p<0.001), followed by Academic engagement (b=0.337, p<0.001), both of which had a significant impact.
Meanwhile, family resilience (b=0.133, p<0.086) did not have a significant effect, but showed a positive influence. These findings suggest that the development of deep learning strategies, as well as increased student academic engagement, can effectively increase interest in achievement. Therefore, the university or school and lecturers as educators are advised to strengthen these aspects in the learning process.
Keywords: Academic Engagement, Deep learning, Family Resilience, Achievement Interest
