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Mathematics Self- Efficacy, Mathematics Anxiety, Community of Inquiry, and Mathematics Engagement of Performance in Mathematics among College Students using an Online Learning Modality

Published:04 December 2023Publication History

ABSTRACT

The study investigated whether self-efficacy and anxiety in mathematics, engagement and community of inquiry predicts mathematics performance among Filipino college students. Since 2020, the COVID pandemic has hit the world and it has left schools to resort to online schooling. The independent variables of the study are mathematics anxiety, mathematics self-efficacy, mathematics engagement, and Community of Inquiry. The dependent variable is Mathematics Performance. The study expands the knowledge on self-efficacy, anxiety, engagement in mathematics, and community of inquiry in the Philippine context. Cross-sectional explanatory method was used as the research method, in which the researcher used the Online Student Engagement Scale, Math Self-efficacy and Anxiety Questionnaire, Community of Inquiry Questionnaire, and the modular long quizzes of students as a method to gather data in a total of 168 students. Using Structural Equation Modeling, it was revealed that Mathematics Anxiety contributes most to Mathematics performance with a beta coefficient of .927, followed by Mathematics engagement with .875. Mathematics Efficacy was third, with a beta coefficient of .669, while Community of Inquiry was last with .187. Results reveal that cognitive and affective thoughts contribute much to mathematics performance as well as community of inquiry as an environmental factor. Conclusions and recommendations are hereby presented.

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  1. Mathematics Self- Efficacy, Mathematics Anxiety, Community of Inquiry, and Mathematics Engagement of Performance in Mathematics among College Students using an Online Learning Modality

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    • Published in

      cover image ACM Other conferences
      ICEMT '23: Proceedings of the 7th International Conference on Education and Multimedia Technology
      August 2023
      429 pages
      ISBN:9798400709142
      DOI:10.1145/3625704

      Copyright © 2023 ACM

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      • Published: 4 December 2023

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