Journal of Research in Educational Systems

Abstract Objective: The present study aimed to investigate the psychometric properties of the Student Parental Self-Regulation Scale.
Method: The present research method was descriptive and psychometric. The statistical population of the research was all parents of elementary school students in District 1 of Ardabil city in the academic year 2025-2026, from which a sample of 220 people was selected by random sampling method and they responded to the Parental Self-Regulation Scale (Sanders et al., 2017), Parenting Self-Efficacy Scale (Dumka et al., 1996), and Parental Burnout Questionnaire (Roskam et al., 2018). Internal consistency, concurrent validity, and confirmatory factor analysis were used to analyze the data. The data were analyzed using SPSS26 and Amos24 software.
Results: The results of the internal consistency coefficient showed that this scale has adequate reliability (α=0.91). The results of the correlation coefficient showed that the significant positive relationship between the two variables of parental self-regulation and parenting self-efficacy (r=0.54, P<0.01) indicates appropriate convergent validity and the significant negative correlation coefficient between the two variables of parental self-regulation and parental burnout (r=-0.42, P<0.01) indicates appropriate divergent validity. The fit indices of the confirmatory factor analysis model also confirmed the final model of this scale (P<0.001).
Conclusions: The results of this study showed that the Persian version of the Student Parent Self-Regulation Scale has adequate validity and reliability in Iranian parents and is a suitable scale for clinical and research situations.

Abstract Objective: The aim of this study was to design an integrated model of the conditions, processes, and outcomes of educational quality in universities of medical sciences.
Method: This applied, descriptive, and qualitative study was conducted using the grounded theory approach based on the Strauss and Corbin (1990) model. Data were collected through semi-structured interviews with 21 experts. Purposeful sampling was employed and continued until theoretical saturation was achieved. Data analysis was carried out in three stages: open, axial, and selective coding. To ensure the trustworthiness of the findings, credibility, transferability, confirmability, and dependability criteria were applied. The reliability of the coding process was confirmed using Cohen’s kappa coefficient (0.808).
Results: The findings indicated that educational quality is a multidimensional, dynamic, and systemic phenomenon shaped through continuous interaction among conditions, strategies, and outcomes. In total, 90 initial concepts were extracted and organized into 30 major categories and 10 core categories, including curriculum quality, comprehensive educational services, faculty competencies, educational evaluation, clinical learning, educational governance, digital education, internal evaluation, educational ethics and justice, and educational data intelligence. These categories were integrated into a comprehensive model entitled the “Integrated Educational Quality System,” encompassing five main dimensions: causal conditions, contextual conditions, intervening conditions, interactive strategies, and consequences.
Conclusions: Achieving educational quality in universities of medical sciences requires adopting an integrated and systematic approach that simultaneously addresses structural, managerial, procedural, value-based, and outcome-oriented dimensions. The proposed model provides a context-based and evidence-informed framework for policymaking, performance improvement, enhancement of clinical learning, and strengthening social accountability.

Abstract Objective: While computational thinking (CT) is a key competency in elementary education, its valid assessment faces significant conceptual and psychometric challenges. This research provides a diagnostic analysis that moves beyond mere classification, employing a dual approach: first, mapping the scientific landscape through scientometric analysis, and second, critically evaluating existing assessment tools.

Method: In this systematic critical review (PRISMA 2020), 45 eligible articles were identified from Scopus and Google Scholar (2006–2025). The analysis was conducted in two phases: (1) a scientometric analysis using R and VOSviewer to map the field's conceptual structure, and (2) a qualitative critical analysis of eight key instruments, focusing on their theoretical foundations and psychometric properties.

Findings: The scientometric analysis revealed a field characterized by rapid yet imbalanced growth. Keyword co-occurrence maps highlighted a strong focus on "educational applications" and "programming tools," alongside a significant absence of core assessment concepts like "validity" and "fairness." This structural gap is mirrored in the instruments, revealing three primary limitations: 1) psychometric weakness, due to over-reliance on traditional metrics (e.g., Cronbach's alpha) while neglecting modern standards (e.g., McDonald's omega, DIF analysis); 2) conceptual narrowness, focusing on algorithmic knowledge at the expense of process skills (e.g., debugging) and dispositions (e.g., perseverance); and 3) an instrumental gap for upper elementary students.

Conclusion: No single instrument is sufficient for a comprehensive assessment of CT. The maturation of this field requires adopting modern psychometric standards, designing contextually-relevant tests, and developing hybrid assessment frameworks that integrate standardized tests with performance-based measures.

Abstract Objective: The aim of this study was to evaluate the current status of the teaching quality of faculty members of the Faculty of Psychology and Educational Sciences, University of Tehran, using a localized tool to identify strengths and weaknesses and provide an evidence-based basis for improving educational processes.
Method: The research was conducted with a mixed exploratory design. In the qualitative phase, the data-driven theory method was used at the conceptual level, and semi-structured interviews were conducted with 22 students until data saturation was reached. An evaluation framework was developed including 5 factors, 16 criteria, and 70 indicators. In the quantitative phase, a researcher-made instrument (in the form of a scale based on a framework of developed criteria and indicators) was administered to 410 students, with a content validity index of 0.98 and a Cronbach's alpha of 0.88, based on this framework. Data were analyzed using descriptive statistics.
Results: the overall state of teaching quality to be "relatively unfavorable" (M=5/03 out of 10). A key imbalance was observed: only the "Professor-related personal factor" (M=6.81) was rated "relatively favorable," indicating faculty competence. In contrast, other factors -Educational (M=5/32), Communicational (M=5/11), and Student-related (M=4/63)- were rated unfavorably. The "Structural factor," with the lowest mean (M=3/28), was the most significant weakness, indicating serious challenges.
Conclusions: It is concluded that competent professors operate in a weak structural and policy context. Improving quality requires a dual approach that simultaneously focuses on developing the pedagogical skills of professors as well as fundamental reforms in faculty infrastructure.

Abstract Objective:

The present study aimed to examine the psychometric properties of the Digital Communication Empathy Scale (DCES), designed to assess multiple dimensions of empathy in online and virtual communication contexts.

Method:

This applied, descriptive–survey study was conducted among individuals aged 18 years and older who actively used social networks and online messaging platforms between August and September 2025 (N = 570). Participants were selected using a convenience sampling method. Data collection instruments included the Digital Communication Empathy Scale (Collins et al., 2022) and the Toronto Empathy Questionnaire (Spreng et al., 2009). Exploratory factor analysis (EFA) was performed using SPSS version 25, and confirmatory factor analysis (CFA) was conducted with LISREL version 8.8. Content validity was assessed through expert evaluation using the Content Validity Ratio (CVR) and Content Validity Index (CVI). Criterion validity was examined by correlating the DCES with the Toronto Empathy Questionnaire.

Results:

EFA results supported a six-factor structure for the 36-item DCES. First- and second-order CFA indicated a good model fit and acceptable reliability and validity of the subscales. The overall CVR was 0.98 and the overall CVI was 0.92, demonstrating strong expert agreement. A significant positive correlation was observed between the DCES and the Toronto Empathy Questionnaire (r = 0.46, p < 0.001).

Conclusion:

The findings indicate that the Persian version of the DCES demonstrates satisfactory psychometric properties and can be used as a valid and reliable instrument for assessing empathy in digital communication environments.

Abstract Objective: The National University Entrance Exam (Konkur) is designed to select students for admission to universities and higher education institutions in Iran. This study aims to identify and analyze the conceptual structure and latent abilities assessed in this exam, which play a critical role in ensuring accurate and fair student selection.
Method: This research employed a descriptive-correlational design. A random sample of 48,436 candidates from the Experimental Sciences track of the 2021 Konkur was selected. Data were analyzed using statistical techniques including Principal Component Analysis (PCA), Cluster Analysis, Multidimensional Scaling (MDS), and Structural Equation Modeling (SEM).
Results: The results revealed a structure of three abilities in the exam, consisting of general subjects, specialized subjects, and English as an independent ability. The structural equation model showed that general ability underpin the development of the other two abilities, and the relationships between these were statistically significant. English was also identified as a distinct domain.
Conclusions: The identified structure offers a coherent model of the abilities assessed by the exam, which can inform question design, score interpretation, and educational planning. The confirmation of the conceptual model provides theoretical and empirical support for understanding the exam's structure.

Abstract Objective: The aim of the present study was to identify faking responses in the Big Five personality inventory. In this study, data were collected by administering the NEO-FF short form personality inventory to students of Allameh Tabataba'i University. Methods: 748 participants in two instructed (n = 366) and honest (n = 382) groups completed the research questionnaire. In this study, the participants were randomly assigned to two groups: those who responded honestly and those with instructed responses. Results: The findings, by examining the differences in class means, the composition of the main groups, the selection threshold graphs, and the probability of confirming the answer choices by class, identified most dimensions of the two classes of samples as simulated and honest groups. Conclusion: Finally, it can be said that over the past 10 years, research on identifying faking responses has attracted considerable attention in assessments areas; however, there seems to be a relative lack of empirical studies in evaluating faking responses, apart from limited applications in simulation studies, that can accurately explain how to identify, describe and correct individual inconsistencies. Additionally, despite a few initial reports in this area, patterns of individual inconsistency are rarely reported in official reports for large-scale educational screenings such as national employment tests and psychological assessments. Therefore, statistical methods such as item response theory and factor analysis can be used to identify faking responses in employment or psychological assessment with specific goals. .