Title:
Analysis of the Impact of Active Learning Based Instructional Design on Students’ Cognitive Engagement
Authors:
Abstract:
The present study aimed to analyze the impact of active learning based instructional design on the cognitive engagement of students in universities in Ardabil Province. In terms of purpose, the research is applied, and in terms of methodology it is descriptive–correlational. The statistical population consisted of all students studying at universities in Ardabil Province during the 2024–2025 academic year. Based on Cochran’s formula, 384 students were selected using a stratified random sampling method.
Data collection tools included an Active Learning Based Instructional Design Questionnaire derived from the active learning framework of Bonwell and Eison (1991), and the Cognitive Engagement Questionnaire developed by Fredricks, Blumenfeld, and Paris (2004). The validity of the instruments was confirmed through expert opinion, and their reliability was assessed using Cronbach’s alpha coefficient, which yielded values of 0.82 for the active learning based instructional design questionnaire and 0.79 for the cognitive engagement questionnaire. Data analysis was conducted using descriptive and inferential statistics in SPSS software. Pearson correlation coefficient and multiple regression analysis were applied to examine relationships between variables.
The results showed that the mean scores of active learning based instructional design and students’ cognitive engagement were at a relatively desirable level. Pearson correlation results indicated a positive and significant relationship between active learning based instructional design and students’ cognitive engagement (r = 0.61). Furthermore, regression analysis demonstrated that active learning based instructional design significantly predicts students’ cognitive engagement and explains approximately 37% of its variance. Based on the findings, it can be concluded that applying active learning strategies in the design of instructional processes can play an important role in increasing students’ mental participation and cognitive processing, thereby improving the quality of learning in higher education.
Data collection tools included an Active Learning Based Instructional Design Questionnaire derived from the active learning framework of Bonwell and Eison (1991), and the Cognitive Engagement Questionnaire developed by Fredricks, Blumenfeld, and Paris (2004). The validity of the instruments was confirmed through expert opinion, and their reliability was assessed using Cronbach’s alpha coefficient, which yielded values of 0.82 for the active learning based instructional design questionnaire and 0.79 for the cognitive engagement questionnaire. Data analysis was conducted using descriptive and inferential statistics in SPSS software. Pearson correlation coefficient and multiple regression analysis were applied to examine relationships between variables.
The results showed that the mean scores of active learning based instructional design and students’ cognitive engagement were at a relatively desirable level. Pearson correlation results indicated a positive and significant relationship between active learning based instructional design and students’ cognitive engagement (r = 0.61). Furthermore, regression analysis demonstrated that active learning based instructional design significantly predicts students’ cognitive engagement and explains approximately 37% of its variance. Based on the findings, it can be concluded that applying active learning strategies in the design of instructional processes can play an important role in increasing students’ mental participation and cognitive processing, thereby improving the quality of learning in higher education.