Journal of Research in Educational Systems

Abstract Objective: Academic boredom, a complex and pervasive emotional phenomenon, is increasingly recognized as a key inhibitory factor in learning processes and academic achievement, particularly in cognitively challenging domains such as Mathematics. The present study aimed to investigate the causal model of Mathematics academic boredom based on cognitive strategies and academic goal orientations, mediated by academic hope, among second-grade high school students.
Method: The present study was descriptive and conducted using a path analysis approach. The statistical population comprised all female students in the second period of public high schools in Tehran during the 2024-2025 academic year. A sample of 400 students was selected using multi-stage cluster sampling. Data were collected using the Academic Boredom Questionnaire (Pekrun et al., 2002), the Self-Regulated Learning Questionnaire (Bouffard et al., 1995), the Academic Goal Orientation Questionnaire (Bouffard et al., 1998), and the Academic Hope Questionnaire (Pekrun et al., 2002). The data were analyzed using path analysis in SPSS-24 and AMOS-2024 software.
Results: The results indicated that the proposed research model demonstrated a good fit with the data. Furthermore, the findings revealed that cognitive strategies (β=-0/13) and mastery goal orientation (β=0/39), performance goal orientation (β=-0/15), and avoidance goal orientation (β=-0/15) had direct effects on Mathematics academic boredom. Moreover, academic hope played a mediating role in the relationship between mastery goal orientation and cognitive strategies with Mathematics academic boredom.
Conclusions: Based on these findings, focusing on the strengthening of academic hope and the instruction of effective learning strategies can be utilized as an efficient .....

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 the present study was to explore the lifeworld of educational feedback in the lived experience of elementary education student teachers at Farhangian University and to explain its consequences on their motivation and learning.
Method: The research was conducted with a qualitative approach and within the framework of descriptive phenomenology. The participants included 34 student teachers in the fifth semester of elementary education at Farhangian University of Khuzestan Province in the first semester of the academic year 2025-26, who were selected purposively. Data were collected through semi-structured interviews and transcribed verbatim. Data analysis was conducted based on Claise's seven-step method. To increase validity and reliability, participant review, independent coding, and expert judgment were used.
Results: The findings led to the identification of a set of main themes that represented the pre-service teachers' educational feedback lifeworld. Positive feedback, including verbal encouragement, constructive criticism, respect, and attention to individual differences, increased intrinsic motivation, active participation, deep learning, and strengthened professional identity. In contrast, negative or ineffective feedback, such as indifference, unconstructive criticism, grade-based, and a focus on formal aspects, resulted in consequences such as reduced motivation, anxiety, superficial learning, and a weakening of the teacher's self-concept. Also, the role of the teacher, the classroom setting, and the emotional characteristics of the feedback played a decisive role in how student teachers received and responded.
Conclusions: The results showed that educational feedback is an integral part of the pre-service teachers' learning lifeworld, which creates broad motivational, learning, identity, and educational consequences.

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 investigate correlation of perfectionism with English language learning mediated by emotional creativity and cognitive flexibility in students.
Method: The research method was correlational using path analysis, and the statistical population included all female students in the second grade of secondary school, that 235 of whom were selected as the convenience sampling method and responded to the Averill's Emotional Creativity Questionnaire (1991), Dennis & Vander Wal' Flexibility (2010), and Hewitt & Flett's Perfectionism (1991). The students' end-of-semester English language course scores were used to measure the English language learning variable. The data were analyzed using the Pearson correlation coefficient formula and path analysis using SPSS 24 and Amos 23 software.
Results: The results showed that perfectionism, emotional creativity, and cognitive flexibility have a direct effect on English language learning. Also, perfectionism has an indirect effect on English language learning through the mediation of cognitive flexibility and emotional creativity (0/001). The research model was also confirmed and the results showed that the research model had a good fit for the variables and 35% of the variance in English language learning was explained by the research variables.
Conclusions: According to the research findings, it is recommended that educational authorities and practitioners pay special attention to the role of perfectionism, emotional creativity, and cognitive flexibility of students in learning a second language, especially English as an international language, in order to increase their language learning ability.

Abstract Objective: Organizational cronyism is a significant issue in public organizations, particularly educational institutions, whose identification and assessment require reliable tools. The present study aimed to develop and validation a questionnaire for identifying organizational cronyism in educational settings.
Method: This research employed a mixed-method approach with a sequential exploratory design. In the qualitative phase, data were collected and analyzed using descriptive phenomenology through semi-structured interviews with 17 employees of the Department of Education in Hamedan Province. Based on the qualitative findings, a 65-item questionnaire was developed. Following face and content validity assessments, it was administered to 545 employees of the same organization using stratified random sampling. The psychometric properties of the questionnaire were examined using exploratory factor analysis, confirmatory factor analysis, Pearson’s correlation coefficient, and Cronbach’s alpha.
Results: Psychometric analyses revealed that the final questionnaire, consisting of 44 items and five main factors—'favoritism,' 'unfair allocation,' 'unregulated appointments,' 'partisanship,' and 'kinship hierarchy'—explained 57.94% of the total variance. Confirmatory factor analysis results indicated that all final items had factor loadings above 0.40, and the fit indices (CFI = 0.908, TLI = 0.901, RMSEA = 0.057) demonstrated a good fit of the measurement model. The questionnaire's convergent validity was 0.621, its reliability coefficient measured by Cronbach’s alpha was 0.92, and the test-retest correlation coefficient was 0.733. The results confirmed that the Organizational Cronyism Questionnaire has satisfactory validity and reliability.
Conclusions: The Organizational Cronyism Questionnaire is a comprehensive, reliable, and valid instrument for assessing organizational cronyism in educational environments.

Abstract Objective:The primary aim of this study is to systematically analyze the key competencies required by university instructors in the digital age to effectively utilize artificial intelligence (AI) in higher education.
Method: This research was conducted through a systematic literature review and targeted searches in reputable international databases, including Scopus, ScienceDirect, ProQuest, ERIC, Springer, Google Scholar, and ResearchGate. Using keywords such as “artificial intelligence,” “competency,” “instructor,” and “digital,” a total of 438 scientific sources published between 2018 and the end of the first quarter of 2024 were identified. After removing 115 duplicate articles and screening the titles and abstracts of the remaining 323, 268 articles were excluded due to irrelevance to the research focus. Ultimately, 55 articles were selected for full-text review, and based on qualitative and subject-specific criteria, 20 studies were chosen for final analysis.
Results: The findings revealed that the AI-related competencies required by instructors in the digital era can be categorized into five main components: (1) AI mindset and pedagogy (including understanding benefits and challenges, contextual strategies, and managing long-term impacts); (2) AI ethics (emphasizing human-centered use, social skills, and the value of human dignity); (3) Foundational AI knowledge (including data and algorithm literacy, AI analytics, data modeling, and basic coding); (4) Practical skills (covering use, experimentation, deep integration, and working with AI-powered tools); and (5) AI-enhanced teaching methods (such as AI-assisted assignment management, curriculum design and delivery, and teaching enhancement).