Integrating canva-AI and deep learning approaches into interactive mathematics videos to enhance mathematical literacy and self-regulated learning in vocational education - Yolanda Pratiwi; Fitrianto Eko Subekti (Journal of Advanced Sciences and Mathematics Education, 2026)
Background: Mathematical literacy and self-regulated learning (SRL) remain significant challenges in Indonesian secondary education, as reflected in students’ low PISA performance. Conventional teacher-centered instruction often limits students’ opportunities to develop mathematical problem-solving skills, communication abilities, and learning autonomy. Therefore, innovative interactive learning media are needed to support meaningful and independent mathematics learning. Aims: This study aimed to develop an interactive mathematics learning video on exponential functions by integrating Canva-AI and deep learning approaches and to evaluate its validity, practicality, and effectiveness in enhancing students’ mathematical literacy and SRL in vocational education. Method: This study employed a Research and Development (R&D) design using the ADDIE model, including Analysis, Design, Development, Implementation, and Evaluation stages. Data were collected through expert validation questionnaires, student practicality questionnaires, and pretest–posttest assessments of mathematical literacy and SRL. Data were analyzed using MANCOVA after fulfilling normality and homogeneity assumptions. Results: The developed video achieved highly valid and highly practical categories. MANCOVA results revealed a significant simultaneous effect on students’ mathematical literacy and SRL posttest scores (p < 0.05). The experimental group demonstrated better posttest performance than the control group. Conclusion: The interactive mathematics video is valid, practical, and effective in improving vocational students’ mathematical literacy and self-regulated learning through AI-assisted and student-centered learning.