Iranian Journal of Learning and Memory

Abstract Objective: Academic boredom, as one of the key negative emotions in educational environments, particularly in mathematics, can lead to numerous effects. The present study was conducted with the aim of examining the model of mathematics academic boredom based on metacognitive strategies and goal orientations, mediated by academic procrastination, among high school students. Method: This research was descriptive in nature employing structural equation modeling and path analysis. The statistical population included all female high school students in public schools in Tehran during the academic year 2024-2025, from which 400 individuals were selected using multi-stage cluster sampling. Data collection tools included the Academic Boredom Questionnaire (Pekrun et al., 2002), Self-Regulated Learning Questionnaire (Bouffard et al., 1995), Goal Orientations Questionnaire (Bouffard et al., 1998), and Academic Procrastination Questionnaire (Solomon & Rothblum, 1984). The data were analyzed using path analysis in SPSS 24 and AMOS 2024 software. Results: The results indicated that the proposed model has a good fit. Metacognitive strategies (β=-0.13) and mastery goal orientation (β =-0.29), performance goal orientation (β= 0.19), and avoidance goal orientation (β= 0.05) had a direct and significant effect on mathematics academic boredom. Furthermore, academic procrastination mediated the relationship between goal orientations and academic boredom. Conclusions: These findings can inform the design of effective educational interventions to reduce academic boredom, emphasizing the strengthening of metacognitive strategies and promotion of mastery goal orientations as key self-regulatory tools. Such approaches not only mitigate academic procrastination but also enhance overall motivation and academic performance.ance.

Abstract Objective: This research aimed to investigate the relationships between future self-continuity, savoring beliefs, and academic procrastination with the academic grit of Urmia University students in the 2023-2024 academic year.
Method: This was descriptive and correlational research. The study's statistical population consisted of all Urmia University students in the academic year 2023-2024 (N=13,000). A total of 393 students were selected through convenience sampling. The data collection tools included the Future Self-Continuity Questionnaire (FSCQ) (2020), the Savoring Beliefs Inventory (SBI) (2003), the Academic Procrastination Questionnaire (APQ) (2012), and the Academic Grit Scale (AGS) (2017). Pearson correlation and multiple regression were used for data analysis.
Results: The results of the data analysis revealed a significant positive relationship between future self-continuity and savoring beliefs with students’ academic grit, and a significant negative relationship between academic procrastination and academic grit (P<0.01). Moreover, based on the results of multiple regression analysis, future self-continuity had the highest predictive power (β=0.304) for academic grit in students.
Conclusions: Based on the results of this study, strengthening future self-continuity, savoring beliefs, and skills for reducing academic procrastination is recommended to enhance the academic grit of students.

Abstract Given that academic procrastination originates from various factors, two of the most important factors in this field are cyberspace addiction and executive functions. Therefore, this research aims to model structural equations for predicting academic procrastination based on cyberspace addiction and executive functions. The research method is a descriptive-correlation type of structural equation modeling. The statistical population of this research includes 8150 female first-secondary school students in the city of Kerman in the academic year 2022-2023; according to Morgan's table, 384 people have been selected as a sample using stratified random sampling. Widyanto and McMorran's (2004) cyberspace dependence, Brief's (2000) executive functions, and Solomon and Rothbloom's (1984) academic procrastination questionnaires were used to collect data. Data analysis was done with SPSS25 and AMOS24 software, and descriptive and inferential statistics such as mean, standard deviation, and structural equation modeling were used. The research results showed that the model for predicting academic procrastination based on dependence on cyberspace and executive functions has an acceptable fit. There is a significant relationship between cyberspace addiction, executive functions, and academic procrastination (p<0.05), so cyberspace addiction and executive functions simultaneously explain 0.70 of the variance of academic procrastination. Therefore, it can be concluded that the high dependence on cyberspace and spending much time aimlessly in this space cause students to procrastinate in doing their homework and to suffer from a kind of procrastination in academic subjects. Also, defects in executive functions aggravate the academic procrastination of students.