فصلنامه اندازه گیری تربیتی
پیاپی 55 (بهار 1403)

The aim of this study was to identify the psychometric properties or indicators of the Mental Toughness Scale for Adolescents by McGowan et al. (2016) and examine its relationship with academic procrastination, generalized anxiety, and math anxiety using path analysis. The research sample consisted of 455 high school students in Zanjan City, Iran, who were selected using cluster sampling. Participants completed the relevant scales through in-person administration. Data analysis was conducted in two phases and employing factor analysis and path analysis statistical methods. In the first phase, the psychometric properties of the Mental Toughness Scale were examined. The results revealed that a six-factor solution, in line with the proposed six dimensions of the Mental Toughness Scale (challenge, commitment, control over life and emotions, and self-confidence in abilities and interpersonal relationships), provided the best fit for the competing models. Additionally, the overall internal consistency of the scale was satisfactory, with a Cronbach's alpha coefficient of 0.81. In the second phase, the direct and indirect effects of Mental Toughness on generalized anxiety, math anxiety, and academic procrastination were examined using path analysis. The findings indicated that Mental Toughness has a direct impact on generalized anxiety, math anxiety, and academic procrastination. Moreover, Mental Toughness has an indirect effect on academic procrastination and math anxiety through the mediating role of generalized anxiety. The implications of the study's findings for schools and educational environments, as well as suggestions for future research, were discussed.

The sense of belonging to a university is intricately connected to various facets of their psycho-social well-being. Nonetheless, the conceptualization and measurement of this construct remain unclear. Existing instruments in higher education predominantly evaluate the general sense of belonging, while the assessment of specific components of belonging to a university has not been adequately addressed in prior research. This study was conducted to construct and validate the "Students' Sense of Belonging to University Scale (SSBUS)". Employing a correlational and instrument development framework, 345 students from Ferdowsi University of Mashhad were recruited for the initial phase, followed by 477 students from the University of Birjand in the subsequent phase, utilizing a convenient sampling technique. Exploratory factor analysis in the initial phase identified four factors accounting for 49.72% of the variance, encompassing interactions with faculty, peer relations, institutional atmosphere, and self-esteem. Confirmatory factor analysis affirmed the suitability of the four-factor model, with Cronbach's alpha coefficients for the sub-scales ranging between 0.75 and 0.90. Further analyses substantiated the internal consistency, as well as the convergent and divergent validity of the scale. Notably, each dimension of the scale demonstrated significant correlations with university commitment, social-emotional loneliness, life satisfaction, depressive symptoms, and agentic engagement. Moreover, the retest reliability coefficients for the sub-scales varied from 0.64 to 0.74. The findings suggest that the SSBUS possesses commendable psychometric properties, qualifying it as a reliable tool for academic use.

This research was descriptive in nature, aiming to explore the psychometric characteristics of a practical aspect. The statistical sample comprised all students attending the First Secondary School in Qom City during the academic year 1400-1401. A sample of 355 students from the First Secondary School in Qom City were recruited using a multi-stage cluster random sampling method. The Academic Persistence Scale (APS) by Talib et al. (2018) was administered to them. The data were subsequently analyzed using SPSS22 and AMOS22 statistical software and subjected to exploratory factor analysis and reliability analysis. The results demonstrated that the extracted factor accounted for 79.93% of the variability in the academic persistence variable. The reliability of the tool was determined to be 0.994 using Cronbach's Alpha coefficient, with 0.989 for the first half and 0.988 for the second half using the two-halves method. The Persian version of the Academic persistence Scale (APS) was found to be an effective tool for assessment, as indicated by the outcomes of the exploratory factor analysis and reliability analysis.

In recent years, mixed methods research has gained popularity in doctoral theses, particularly in educational administration and higher education. This study delved into the approach, design, and research methodologies employed in these theses. By thoroughly analyzing the abstracts and third chapters of 85 doctoral theses, the research aimed to elucidate the prevailing trends in mixed methods research within the realm of education. The findings of this study reveal that a significant majority, 73%, of the examined doctoral theses aimed at developing patterns or models. Furthermore, 63% of the studies adhered to a sequential exploratory mixed methods approach during their exploration. Moreover, the qualitative phase of the majority (60%) of the research papers utilized grounded theory as a methodological framework. Concerning the quantitative phase, 60% of the studies relied on multiple correlation analysis. These findings not only provide valuable insights for instructing both quantitative, qualitative, and mixed methods research methodologies in doctoral programs but also underscore the significance of fostering innovation in research designs within the domain of behavioral sciences. Particularly noteworthy is the emphasis on the emergence of pattern development as a burgeoning focal point within doctoral studies.

This research was conducted using the meta-analysis method with the aim of synthesizing existing research on the relationship between identity styles and academic performance. The statistical population of the study included all relevant studies conducted in Iran from 1385-1400 and available in the databases of Jahad Daneshgahi, Nurmagz, and Magiran. After evaluating the criteria for entrances and layaway requirements research, the correlation effects of the research were analyzed by CMA software. Also, two models of random effect and fixed effect were calculated. According to the results of the heterogeneous analysis, the randomized model was selected through Q and squared I indices. The findings revealed that the size of the combined effect of the investigated research after the removal of 4 effects size was 0.107. The combined effect size of the research was calculated based on the mean Cohen’s index. The results of heterogeneous analysis revealed of the existence moderating variables in the research as well. The results of this meta-analysis of theoretical and empirical foundations are indicative of the relationship between identity style and academic performance variables. Given the results of this meta-analysis, it can be concluded that for academic performance to be successful, it is essential to address the identity style among university and school students.

The goal of this research is to explore the Likert scale questions using two distinct methods Classical Test Theory and Item Response Theory. By comparing the results of these approaches, the study aims to address the question: "Do the outcomes from these two methodologies align, or do they contradict each other?" The research design followed a descriptive methodology and utilized secondary analysis techniques. The study population consisted of 977 junior high school students. After the data screening process, the final sample size for analyzing extraversion items was 783 students, 763 students for openness items, and 784 students for conscientiousness items. The research instruments were the three subscales of extraversion, openness, and conscientiousness from the Neo Personality Test. The statistical analysis yielded results indicating that a strong internal consistency among items enhanced the accuracy and validity of outcomes derived from the graded response model. However, when items exhibit low internal consistency, caution should be exercised, as the model may yield erroneous thresholds or discrimination coefficients (i.e., false negative or positive). Overall, combining multiple methods of statistical analysis can significantly contribute to more effective analysis and obtaining highly accurate results.