درخت حوزه‌های تخصصی

Social control of cyberspace is a necessity to restrict online transgressions (non-normative behaviors), and reduce their disruptive effects. The current study aimed at examining the factors affecting social control of cybercultural transgressions. A questionnaire was administered to Iranian social media users, and 989 participants have filled it out. A path analysis model was constructed testing the effects of Low Self-Control, Depression, Negative Interpersonal Relationships, Computer/ Internet Self-Efficacy, Netiquette, and Normative Beliefs on Transgressive Behaviors, and Transgressive Content Consumption. The results showed that Low Self-Control increased both criterion variables, and fully or partially mediated the effects of other variables on them, except for Negative Interpersonal Relationships. The important contribution of the current study was the recognition of the role of self-control as a mediator among examined variables. The findings of this study can be employed to devise new policies and initiatives to socially control the cybercultural transgressions, without applying coercion.   

Purpose: Academic buoyancy is one of the effective variables in the academic field and learning environment of students. Therefore, the objective of this research was to design the academic buoyancy model based on life expectancy with the mediation of happiness in female high school students in Hamedan city. Methodology: The methodology of this research was correlational and SEM. The statistical population included all female students of the second secondary school in Hamedan city, and the statistical sample was selected based on the number of items used in the questionnaires as 370 people with the multi-stage cluster sampling method. Academic buoyancy (Hosseinchari and Dehghanizadeh, 2013), life expectancy (Hallajian, 2019), and Oxford happiness (Argyl et al., 1989) scales were used to collect data. For data analysis, a structural equation test was used in the PLS-3 software environment. Findings: The results showed that life expectancy has a direct and positive effect on academic buoyancy (β = 0.36, p <0.01) and happiness (β = 0.46, p < 0.01). Happiness also has a direct and significant effect on academic buoyancy (β = 0.34, p<0.01). Also, happiness has a significant mediating role in the relationship between life expectancy and academic buoyancy (β = 0.16, p<0.01). Conclusion: since life expectancy creates a more positive atmosphere, it can be effective in increasing the feeling of happiness, and happiness creates buoyancy in the academic environment, followed by an increase in academic buoyancy.

Purpose: Epistemology as one of the philosophical foundations in the field of education can play an important role in blended learning, ie using more than one method, strategy and technique for learning. Therefore, the present study was conducted with the aim of designing and validation the epistemological model in blended learning Methodology: The present study was applied from type of qualitative-quantitative. The population of the qualitative section was the documents related to epistemology and blended learning in the years 1990 to 2020 which 80 books, 60 dissertations and 60 articles were selected by purposive sampling method and in addition, included experts in the field of philosophy of education and distance learning which based on the principle of theoretical saturation number of 10 people of them were selected by purposive sampling method. The population of the quantitative section were faculty members and doctoral students of the department of philosophy of education and distance learning of Payame Noor University in 2020-2021 years which based on Krejcie and Morgan's table number of 200 people of them were selected by stratified random sampling method with using the teacher and student ratio. The tool of the qualitative section was the recording of books, dissertations and articles and interviews with experts, and the tool of the quantitative section was a researcher-made questionnaire whose psychometric indicators were confirmed. Data were analyzed by coding method in MAXQDA software and exploratory factor analysis and one-sample t-test in SPSS software. Findings: Findings showed that the epistemological model in blended learning had 60 subcategories in 9 categories including purpose, evaluation, educational correction, content, teaching method, teacher, learner, media and cognitive presence that its model was drawn. Also, validation of model indicated that the factor load of all 6 questions related to validation of model was higher than 0.30, their validity was higher than 0.50 and their reliability was higher than 0.70. In addition, the mean of all 6 questions was higher than the hypothetical mean of the population (P<0.001). Conclusion: The findings showed that the designed model for epistemology in blended learning had good validity. Therefore, curriculum specialists and planners can use this model along with other models to improve blended learning

This study presents an integrative review of scholarly literature published between 2016 and 2022 to synthesize how AI literacy has been conceptualized, taught, and measured. Drawing on over 40 empirical and theoretical sources, the review maps trends across educational levels—from primary to higher and adult education—and user groups, including students, teachers, professionals, and the general public. Key findings reveal significant diversity in pedagogical strategies, ranging from project-based learning and digital storytelling to flipped classrooms and professional development programs. Conceptualizations of AI literacy vary widely, encompassing technical, ethical, civic, and empowerment-oriented dimensions. Meanwhile, the field continues to face challenges related to definitional ambiguity, limited standardization of assessment tools, and inconsistent integration of ethical and socio-cultural considerations. The review emphasizes the need for convergence around shared frameworks, scalable pedagogies, and cross-contextual evaluation tools. It concludes by identifying future directions for inclusive, empirically grounded, and ethically aware AI literacy initiatives aimed at fostering reflective and informed engagement with AI systems.