Original Research Paper-English Issue
Emerging educational technologies
M. Eftekhari; M. Rahimi
Abstract
Background and Objectives: Educational technology has long been recognized as a powerful tool for enhancing foreign language learning opportunities, with particular relevance for students in under-resourced environments where instructional quality and materials are often limited. Among emerging tools, ...
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Background and Objectives: Educational technology has long been recognized as a powerful tool for enhancing foreign language learning opportunities, with particular relevance for students in under-resourced environments where instructional quality and materials are often limited. Among emerging tools, virtual reality (VR) videos have gained increasing attention for their capacity to create immersive, authentic learning experiences in recent years. Despite the promise of these emerging technologies, little is known about how their pedagogical effectiveness varies among learners with different psychological profiles. One such psychological factor-learned helplessness (LH)- plays a critical role in students’ academic behaviours, motivation, and resilience. Learners with high LH often experience persistent negative expectations about their abilities, reduced perseverance, and diminished engagement, potentially limiting the benefits they receive from technology-enhanced learning environments. Although previous research has explored LH in EFL settings and the equity implications of educational technology, no study to date has examined how teacher-made 360° VR videos influence language learning outcomes across LH levels in a low socioeconomic status (SES). Therefore, the present study was designed to fill this gap by examining the effects of teacher-made 360° VR tours on English achievement among students with different levels of LH in an underprivileged setting.Materials and Methods: The study employed a mixed-methods experimental design. Fifty-eight female 10th-grade students (aged 15-16) from an underprivileged school were randomly assigned to an experimental (n=29) and a control group (n=29). The experimental group used tailored 360° VR tours, made by a Samsung Gear 360 camera, and the control group used ready-made 360 VR videos from YouTube for one academic year. The learning gains were assessed by the English final exam, and the level of LH was evaluated by the EFL-LH scale. Quantitative data were analyzed using a two-way analysis of variance (ANOVA) to compare post-test performance between research groups and participants with different levels of LH. To explore learner perceptions, an open-ended questionnaire was used with a purposive subsample representing both high- and low-LH groups. Qualitative data were analyzed thematically to identify patterns in learners’ perceptions of the VR learning experience. achievement between the teacher-made 360° VR tour group and the ready-made VR video group, although the experimental group demonstrated slightly higher mean gains. However, LH emerged as a strong differentiating factor [F(2, 52)=5.311, p=0.008<0.05]. Learners with low LH significantly outperformed high-LH learners both within and across the two instructional conditions. Low-LH learners in the experimental group demonstrated the greatest improvement, suggesting that immersive, teacher-designed experiences may be particularly effective for motivated and self-efficacious learners. Qualitative findings illustrated that low-LH learners expressed positive attitudes, describing the tours as engaging, relevant, and helpful in improving vocabulary and comprehension. In contrast, high-LH learners reported difficulties in maintaining interest, scepticism about the educational value of the VR tours, and occasional feelings of being overwhelmed by the immersive environment. Conclusions: The study highlights the nuanced role of LH in shaping learners’ responses to immersive educational technologies. While teacher-made 360° VR tours have the potential to enhance engagement and learning, their benefits are not equally distributed among all learners. In low-SES contexts, where LH may be more prevalent due to environmental and systemic constraints, simply introducing advanced technologies is not sufficient for ensuring equitable learning outcomes. Effective integration of VR tools requires pedagogical scaffolding, emotional support, and targeted interventions to address LH-related barriers. These findings underscore the need for context-sensitive technology integration frameworks that consider both technological affordances and learners' psychological differences.
Original Research Paper-English Issue
Gamification
J. Keyhan; Go Sheikhloo
Abstract
Background and Objectives: In recent years, gamification has emerged as a prominent strategy for redesigning learning experiences and enhancing students’ motivation and engagement, gaining a significant position in the literature on school-based education. Despite the growth of empirical studies, ...
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Background and Objectives: In recent years, gamification has emerged as a prominent strategy for redesigning learning experiences and enhancing students’ motivation and engagement, gaining a significant position in the literature on school-based education. Despite the growth of empirical studies, a considerable portion of the existing evidence has focused on short-term outcomes, and a conclusive synthesis of the long-term effects of gamification on academic performance, particularly in elementary education, is still lacking. Given that the early school years are critical for the development of learning habits and stable motivational patterns, evaluating the long-term impacts of gamification from the perspective of curriculum planning and educational policy is of particular importance. Accordingly, the present study aimed to conduct a meta-analysis of quantitative studies on gamification, with an emphasis on its long-term effects on the academic performance of elementary school students, to determine the combined effect size and the consistency of longitudinal study results in this domain.Materials and Methods: This study was conducted using a meta-analytic approach. The research population included all published domestic and international quantitative studies over the past 24 years that reported the long-term effects of gamification on the academic performance of elementary school students. Literature search and retrieval were conducted using keywords related to gamification, academic performance, longitudinal studies, and elementary education, and the retrieved studies were screened based on inclusion and exclusion criteria. Key inclusion criteria comprised a focus on elementary school students, use of quasi-experimental longitudinal designs, provision of quantitative data convertible to effect sizes, and reporting of outcomes over a long-term period. Following evaluation and coding of data using the data extraction forms, a total of 21 quasi-experimental and longitudinal studies were included in the analysis. Data analyses were performed using Comprehensive Meta-Analysis (CMA) software, focusing on effect sizes and heterogeneity indices across studies.Findings: The fixed-effect model indicated that gamification exerts a positive and statistically significant long-term impact on students’ academic performance, yielding a pooled effect size of 0.472, which falls within the moderate range. The heterogeneity indices suggested no statistically meaningful between-study variability (Q = 19.14, χ² = 36.415, I² = 0%), indicating overall consistency across the included studies. Nevertheless, interpretation of the long-term effect should remain sensitive to contextual conditions and implementation quality, as substantive variations in real-world impact may not be fully captured by heterogeneity statistics. Within this framework, students’ developmental and individual characteristics, classroom and school contexts, and the intensity and quality of gamified technology design and use may moderate the magnitude and durability of academic outcomes. Moreover, intervention duration and the timing of follow-up assessments are key factors that likely shape whether gamification effects are sustained or attenuate over time in longitudinal research.Conclusions: Based on the synthesized evidence, gamification can positively and significantly improve the long-term academic performance of elementary school students. This finding extends gamification beyond a short-term motivational intervention, positioning it as a reliable strategy for designing sustainable learning experiences, provided that game elements align with educational objectives and curriculum logic. Practically, it is recommended that the development and implementation of gamified approaches in elementary schools be supported, with emphasis on design quality, developmental appropriateness, and continuity of implementation. Furthermore, future research that reports detailed intervention components, follow-up duration, and implementation quality can enable more nuanced analyses and clarify the mechanisms underlying the long-term effectiveness of gamification.
Original Research Paper-English Issue
Technology-based learning environments
Z. Cheraghi; H. Omranpour; A. Motaharinejad
Abstract
Background and Objectives: The growing influence of Information and Communication Technology (ICT) has considerably altered educational practices, particularly in language learning contexts. In English for Specific Purposes (ESP) courses, mastering technical vocabulary is a fundamental yet challenging ...
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Background and Objectives: The growing influence of Information and Communication Technology (ICT) has considerably altered educational practices, particularly in language learning contexts. In English for Specific Purposes (ESP) courses, mastering technical vocabulary is a fundamental yet challenging requirement due to the specialized nature of the content and learners’ limited exposure beyond academic settings. Traditional vocabulary instruction methods often provide insufficient repetition and lack flexibility, which can negatively affect retention and long-term learning. In response to these challenges, technology-enhanced learning tools have emerged as effective alternatives for supporting vocabulary development. Digital flashcards, especially when used through online platforms, offer structured repetition, learner autonomy, and increased engagement. However, despite their widespread use, there is limited empirical research examining the effectiveness of digital flashcards implemented at predetermined time intervals in ESP contexts. Therefore, this mixed-methods study aimed to investigate the effects of using ICT-based digital flashcards with spaced repetition on undergraduate ESP learners’ acquisition of technical vocabulary. Additionally, the study explored learners’ perceptions of using Quizlet as a technology-supported instructional tool.Materials and Methods: The study employed a mixed-methods research design integrating quantitative and qualitative data to provide a comprehensive understanding of the research objectives. The participants were 60 undergraduate students enrolled in ESP courses, who were randomly assigned to an experimental group and a control group. Before the instructional intervention, both groups completed a background questionnaire and a technical vocabulary pre-test to ensure comparability in terms of prior knowledge. During the treatment phase, the experimental group learned technical vocabulary through digital flashcards delivered via an online platform at planned and systematic time intervals based on spaced learning principles. In contrast, the control group received conventional vocabulary instruction without the use of digital flashcards or ICT-based tools. Data collection instruments included technical vocabulary pre- and post-tests, post-treatment questionnaires, and semi-structured interviews. Quantitative data were analyzed using paired-samples t-tests to examine within-group changes and an independent-samples t-test on gain scores to compare the magnitude of vocabulary improvement between the two groups. Qualitative interview data were analyzed through content analysis using NVivo software.Findings: The results of the quantitative analysis showed that the experimental group achieved significantly greater vocabulary gains than the control group, as confirmed by an independent-samples t-test on gain scores. These findings indicate that the use of digital flashcards with spaced intervals had a positive and statistically significant effect on ESP learners’ vocabulary acquisition. Learners who experienced repeated and structured exposure to technical terms demonstrated higher levels of retention and recall. Moreover, the results suggested that Quizlet functioned as an effective and reliable ICT-based platform for facilitating vocabulary learning. The qualitative findings further supported the quantitative results, revealing that learners held positive attitudes toward the use of digital flashcards. Participants reported increased motivation, improved engagement, and greater control over their learning process. They also noted that spaced repetition helped reduce cognitive load and made learning complex technical vocabulary more manageable.Background and Objectives: The growing influence of Information and Communication Technology (ICT) has considerably altered educational practices, particularly in language learning contexts. In English for Specific Purposes (ESP) courses, mastering technical vocabulary is a fundamental yet challenging requirement due to the specialized nature of the content and learners’ limited exposure beyond academic settings. Traditional vocabulary instruction methods often provide insufficient repetition and lack flexibility, which can negatively affect retention and long-term learning. In response to these challenges, technology-enhanced learning tools have emerged as effective alternatives for supporting vocabulary development. Digital flashcards, especially when used through online platforms, offer structured repetition, learner autonomy, and increased engagement. However, despite their widespread use, there is limited empirical research examining the effectiveness of digital flashcards implemented at predetermined time intervals in ESP contexts. Therefore, this mixed-methods study aimed to investigate the effects of using ICT-based digital flashcards with spaced repetition on undergraduate ESP learners’ acquisition of technical vocabulary. Additionally, the study explored learners’ perceptions of using Quizlet as a technology-supported instructional tool.Materials and Methods: The study employed a mixed-methods research design integrating quantitative and qualitative data to provide a comprehensive understanding of the research objectives. The participants were 60 undergraduate students enrolled in ESP courses, who were randomly assigned to an experimental group and a control group. Before the instructional intervention, both groups completed a background questionnaire and a technical vocabulary pre-test to ensure comparability in terms of prior knowledge. During the treatment phase, the experimental group learned technical vocabulary through digital flashcards delivered via an online platform at planned and systematic time intervals based on spaced learning principles. In contrast, the control group received conventional vocabulary instruction without the use of digital flashcards or ICT-based tools. Data collection instruments included technical vocabulary pre- and post-tests, post-treatment questionnaires, and semi-structured interviews. Quantitative data were analyzed using paired-samples t-tests to examine within-group changes and an independent-samples t-test on gain scores to compare the magnitude of vocabulary improvement between the two groups. Qualitative interview data were analyzed through content analysis using NVivo software.Findings: The results of the quantitative analysis showed that the experimental group achieved significantly greater vocabulary gains than the control group, as confirmed by an independent-samples t-test on gain scores. These findings indicate that the use of digital flashcards with spaced intervals had a positive and statistically significant effect on ESP learners’ vocabulary acquisition. Learners who experienced repeated and structured exposure to technical terms demonstrated higher levels of retention and recall. Moreover, the results suggested that Quizlet functioned as an effective and reliable ICT-based platform for facilitating vocabulary learning. The qualitative findings further supported the quantitative results, revealing that learners held positive attitudes toward the use of digital flashcards. Participants reported increased motivation, improved engagement, and greater control over their learning process. They also noted that spaced repetition helped reduce cognitive load and made learning complex technical vocabulary more manageable.
Original Research Paper-English Issue
Educational Technology - Blended Learning
S. Bibak; S. Asadian
Abstract
Background and Objectives: The accelerating pace of technological change has rendered the effective integration of technology into education not merely desirable, but essential for preparing students for the demands of the 21st century. Educational systems worldwide have invested substantially in technological ...
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Background and Objectives: The accelerating pace of technological change has rendered the effective integration of technology into education not merely desirable, but essential for preparing students for the demands of the 21st century. Educational systems worldwide have invested substantially in technological infrastructure to facilitate this integration. Yet, despite these considerable investments, the actual use of technology by teachers in classroom practice often remains below expectations. This persistent gap between infrastructure availability and meaningful technology integration suggests that access alone is insufficient. Prior research has identified teachers' beliefs, knowledge structures, and individual characteristics as key determinants of this phenomenon. Teachers' pedagogical beliefs function as cognitive filters that shape their decisions about whether and how to incorporate technology into their teaching. Their knowledge structures, particularly regarding how to integrate technology with subject content and pedagogical approaches, determine their capacity for effective implementation. Additionally, individual characteristics such as gender, age, teaching experience, and educational attainment may influence teachers' readiness to adopt technological innovations. However, studies simultaneously examining the roles of these variables within a comprehensive model remain scarce, particularly in the Iranian educational context. Accordingly, this study was conducted to elucidate the roles of technological beliefs, knowledge structures, and individual characteristics in technology integration among secondary school teachers in Tabriz, thereby addressing this significant gap in the literature.Materials and Methods: This quantitative, applied study followed a descriptive-correlational design. The statistical population comprised all secondary school teachers in Tabriz during the 2023-2024 academic year (N = 4,973), representing diverse subject areas and educational districts. Using the Krejcie and Morgan table, a sample of 357 participants was selected through proportionate stratified random sampling to ensure representation across the city's five educational districts. Data were collected via four validated instruments: (1) a researcher-developed demographic questionnaire collecting information on gender, age, teaching experience, and educational attainment; (2) a 17-item knowledge structures questionnaire, measuring three dimensions (perceived technological knowledge, perceived knowledge for technology integration, and pedagogical uses of ICT) on a 5-point Likert scale; (3) a 14-item technological beliefs questionnaire inspired by Digital Pedagogical Beliefs framework; and (4) the 19-item technology integration questionnaire. Validity was established through confirmatory factor analysis and expert judgment by a panel of specialists in educational technology. Reliability coefficients (Cronbach's α) exceeded 0.70 for all instruments, indicating acceptable internal consistency. Data were analyzed using descriptive statistics and structural equation modeling (SEM) with Smart PLS 4 software.Findings: The results revealed that technological beliefs were the strongest positive and significant predictor of classroom technology integration (β = 0.388, p < 0.01), consistent with theoretical frameworks emphasizing the role of teachers' perceptual filters in adopting educational innovations. Knowledge structures emerged as the second most influential factor (β = 0.287, p < 0.01), underscoring the centrality of the TPACK framework in meaningful technology integration. Among individual characteristics, only educational attainment showed a positive, significant association (β = 0.094, p < 0.05), whereas gender, age, and teaching experience had no statistically significant effects. This finding reinforces the notion that the capacity for technology integration is broadly distributed across the teaching force and not confined to specific demographic subgroups. The proposed model demonstrated excellent fit (NFI = 0.93, CFI = 0.96, RMSEA = 0.056) and explained 68% of the variance in technology integration (R² = 0.68), indicating that the independent variables collectively account for a substantial proportion of predictive power.Conclusions: The findings affirm that successful technology integration hinges less on demographic variables and more on the evolution of teachers' professional beliefs and the growth of integrated pedagogical-technological-content knowledge. This underscores the necessity of redefining teacher professional development programs—not merely as technical skill workshops, but as initiatives aimed at nurturing positive beliefs about technology's role in meaningful learning and cultivating TPACK-based knowledge structures grounded in authentic classroom challenges. Educational policymakers should prioritize interventions that target belief transformation and knowledge integration rather than focusing exclusively on infrastructure provision or basic digital literacy training.
Original Research Paper-English Issue
Technology-based learning environments
A. Taghizadeh; A. Akbari Balootbangan
Abstract
Background and Objectives: Perceived social support is a critical factor in enhancing academic engagement and satisfaction in online learning environments. However, the mechanisms through which social support influences satisfaction, particularly the mediating role of distinct dimensions of academic ...
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Background and Objectives: Perceived social support is a critical factor in enhancing academic engagement and satisfaction in online learning environments. However, the mechanisms through which social support influences satisfaction, particularly the mediating role of distinct dimensions of academic engagement, remain underexplored. So, the current study seeks to develop and test a structural model that explores how academic engagement, specifically its affective and behavioral components, mediates the relationship between perceived social support and satisfaction among master’s students enrolled in online learning environments within Iranian higher education institutions.Materials and Methods: A total of 391 master's students from several universities in Iran participated in this study through an online survey conducted in April 2024. Participants completed validated Persian versions of three instruments: the Online Social Support Questionnaire, the Online Student Engagement Questionnaire, and the Satisfaction with E-learning Scale. Structural equation modeling (SEM) was employed to assess the fit of the hypothesized structural model. Bootstrapping procedures (5,000 resamples) were subsequently used to test the significance of the indirect (mediating) effects.Findings: The results revealed that social support had a significant positive direct effect on satisfaction (β = 0.37, p < 0.01). Additionally, social support significantly predicted both affective engagement (β = 0.90, p < 0.001) and behavioral engagement (β = 0.92, p < 0.001). Both affective engagement (β = 0.41, p < 0.001) and behavioral engagement (β = 0.25, p < 0.05) positively influenced satisfaction. Mediation analyses confirmed that affective engagement (β = 0.37, 95% CI [0.26, 0.64]) and behavioral engagement (β = 0.23, 95% CI [0.05, 0.57]) partially mediated the relationship between social support and satisfaction, with affective engagement demonstrating a stronger mediating effect. The proposed structural model exhibited good fit to the data (CMIN/df = 3.34, CFI = 0.92, RMSEA = 0.07, SRMR = 0.05). Conclusions: Perceived social support enhances e-learning satisfaction both directly and indirectly through academic engagement. Affective engagement mediates this relationship more strongly than behavioral engagement, highlighting the critical role of emotional connection, particularly in collectivist cultural contexts. To enhance student satisfaction, eLearning environments should be deliberately designed to cultivate supportive interpersonal dynamics and foster meaningful academic engagement alongside active participation.
Original Research Paper-English Issue
CALL
R. Nejati
Abstract
Background and Objectives: The integration of information and communication technologies (ICTs) into English as a foreign language (EFL) instruction is now a routine aspect of educational practice. It may be related to teachers’ motivation, emotional experiences, and professional well-being. Previous ...
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Background and Objectives: The integration of information and communication technologies (ICTs) into English as a foreign language (EFL) instruction is now a routine aspect of educational practice. It may be related to teachers’ motivation, emotional experiences, and professional well-being. Previous research has mainly focused on issues such as technology adoption, technical skills and attitudes toward ICT. Much less attention has been paid to the emotional consequences of technology use. In particular, positive emotions such as teaching enjoyment remain underexplored. Age may be especially relevant in this respect. The present study examined the relationships among ICT self-efficacy, ICT engagement, and teaching enjoyment among Iranian high school EFL teachers. The study tested whether ICT engagement mediates the relationship between ICT self-efficacy and teaching enjoyment. It also investigated whether age moderates both the direct and indirect associations among these variables.Materials and Methods: A cross-sectional correlational design was employed. Participants comprised 194 Iranian high school EFL teachers recruited through purposive sampling via social networking platforms. Participation was voluntary and anonymous. Teachers completed three self-report questionnaires assessing ICT self-efficacy, ICT engagement, and foreign language teaching enjoyment. All instruments were administered in Persian following a rigorous translation, back-translation, and content validation procedure. Teaching enjoyment was measured using a scale capturing personal enjoyment, student-related enjoyment, and collegial enjoyment. ICT engagement assessed teachers’ behavioral, cognitive, motivational, and social involvement with digital technologies. ICT self-efficacy measured teachers’ perceived capability to use ICT for instructional, professional, and communicative purposes. Age was operationalized as a categorical variable. Before analysis, data were screened for normality, multicollinearity, and suitability for parametric procedures. Structural equation modeling and regression-based analyses were conducted to test mediation, moderation, and moderated mediation associations. Indirect associations were evaluated using bootstrapped confidence intervals to ensure robust estimation of conditional relationships.Findings: The results indicated that ICT self-efficacy was positively associated with both ICT engagement and teaching enjoyment. ICT engagement was also positively associated with teaching ICT self-efficacy and teaching enjoyment. Age significantly moderated the relationship between ICT engagement and teaching enjoyment. Among younger teachers, higher levels of ICT engagement were associated with greater teaching enjoyment. Among older teachers, this relationship was weak and not statistically significant. ICT self-efficacy was negatively related to ICT engagement among older teachers. Moderated mediation analyses further showed that ICT engagement mediated the relationship between ICT self-efficacy and teaching enjoyment only among younger teachers. For older teachers, the indirect association did not reach statistical significance. After accounting for engagement, the relationship between ICT self-efficacy and teaching enjoyment is partially moderated by age.Conclusions: These findings suggest that ICT engagement plays a crucial role in translating teachers’ ICT self-efficacy into teaching enjoyment, but this process is partially moderated by age. For younger teachers, engagement with technology appears to be an emotionally meaningful activity through which confidence in ICT use is associated with teaching enjoyment. For older teachers, ICT use may be more selective or instrumental, carrying less affective significance. The results underscore the importance of adopting an age-sensitive perspective in professional development and technology integration policies. Teaching enjoyment is associated with more than improving technical skills. It is also associated with meaningful, autonomy-supportive forms of ICT engagement that align with teachers’ pedagogical values and professional identities. Limitations include reliance on self-report measures, non-probability sampling and a cross-sectional design that precludes causal inference. Future research would benefit from longitudinal designs to explore how technology-related emotions are associated across teachers’ age groups and how contextual factors shape these experiences in diverse educational settings.
Original Research Paper-English Issue
Educational Technology - Artificial Intelligence
A. Ramazani
Abstract
Background and Objectives: The rapid advancement of AI (AI) in higher education, particularly through adaptive learning systems, intelligent tutoring agents, and generative AI tools, has catalyzed a paradigm shift in traditional teaching and learning models. Also, the increased use of AI in higher education ...
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Background and Objectives: The rapid advancement of AI (AI) in higher education, particularly through adaptive learning systems, intelligent tutoring agents, and generative AI tools, has catalyzed a paradigm shift in traditional teaching and learning models. Also, the increased use of AI in higher education in many different fields offers a more personalized, responsive, and effective learning experience. Yet, as AI systems increasingly determine how students interact with and process knowledge, and create knowledge outputs, it is important to answer both basic questions about learner agency in relation to the very paradigm of the autonomous learner that underpins theories of adult and higher education. This article considers whether AI-enhanced learning environments support or deter learners’ sense of cognitive authorship.Methods: This study used a qualitative method that is a mixture of conceptual and empirical inquiry to show pressing issues related to educational theory and emerging technologies: in the age of AI, are self-directed learners still authors of their learning? The philosophical method examines issues about the ontological and epistemic grounds of cognitive agency in an AI-mediated context using semi-structured interviews with 23 students in different fields at Tehran universities. It includes the question of the lived experience of university students who are engaging with AI to be educated. To increase methodological precision Colaizzi‘s seven step was used; this was chosen because of its specificity and effective depth for interpretation, as well as its fit with a focus on phenomenology in its aim to examine how 'agency', 'authorship', and 'self-direction' of students are lived in an algorithmic context that is mediating cognitive agency. This method includes seven steps: 1) Reading and re-reading all the transcribed interviews to make sense of them, 2) Extracting significant statements. These are phrases or sentences that directly pertain to the investigated phenomenon, 3) Giving meaning to the statements: During the process pertinent quotes are categorized the themes are generated based on multiple statements that convey similar meaning, 4) Repeating step 1-3 for each interview, then the researcher can begin to create theme based on the formulated meaning, 5) Gathering an exhaustive description of everything generated in step 1-4, 6) Summarizing the exhaustive description so that there is an identification of the fundamental structure of the phenomenon and 7) Ensuring the credibility of the data through member checking.Findings: Results indicated that using AI in different fields has both negative and positive effects on learning and cognitive agency of students. Central outcomes on the positive side include cognitive scaffolding, increased access to complex knowledge, the ability of AI as a cognitive extension, co-authorship with AI through critical engagement, increasing critical thinking, and improving self-learning through simulation and interactive environments. On the other hand, it has some challenges such as: Ambiguous intellectual authorship, Erosion of epistemic self-Trust, Illusion of mastery, Passive deference to algorithmic authority, and ethical dissonance and academic guilt.Conclusions: Based on these findings and different aspects of AI in student cognitive agency, the paper proposes a framework for self-directed learning in the age of AI in which authorship is not isolated, as the learner is still the one who makes learning; however, this issue needs basic changes in pedagogical, curricular, and philosophical perspectives.
Original Research Paper-English Issue
Technology-based learning environments
M. Keshavarz Turk
Abstract
Background and Objectives: 'Career and Technology' Textbooks have the vital role in education in equipping students with technical skills, creativity, and digital literacy. The review of international studies highlights the rapid pace of technological change driven by digital transformation and new technologies ...
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Background and Objectives: 'Career and Technology' Textbooks have the vital role in education in equipping students with technical skills, creativity, and digital literacy. The review of international studies highlights the rapid pace of technological change driven by digital transformation and new technologies like AI, VR/AR, 3D printing, and IoT. The paper argues that these trends challenge traditional teaching methods and create unprecedented opportunities for personalized and interactive learning. This study, using futures studies methods with a foresight approach—which constitutes a systematic, anticipatory, and analytical process for anticipating future changes and threats—identifies key technological trends and emerging educational opportunities in the 'Career and Technology' course. It aims to align the content of this course with future educational needs and skill requirements.Methods: The research employed a mixed-methods (quantitative-qualitative) exploratory approach. The process was executed in three distinct stages: Step 1: Identifying Technological Trends: A systematic review of academic literature and educational reports was conducted to identify 11 key technological trends with the potential to influence 'Career and Technology' education. Step 2: Prioritizing Trends: A questionnaire was developed to rank the identified trends based on their potential to create opportunities in the next 5-7 years. The survey was sent to 60 experts, with 48 valid responses collected. The data were analyzed using SPSS26 and the Friedman test to rank the trends. Step 3: Identifying and Classifying Opportunities: Semi-structured interviews were conducted with 24 experts (university professors and teachers) to understand the benefits and impacts of the prioritized trends. The interview transcripts were analyzed using qualitative content analysis with ATLAS.ti software.Findings: The Friedman test results (Chi-Square = 392.912, df=10, p<0.000) showed significant differences in the experts' rankings. The top three trends, based on their potential to create future opportunities, were: Artificial Intelligence (AI) (Average Rank: 9.84), Online Learning (Average Rank: 9.64), and Internet of Things (IoT) (Average Rank: 9.40). The qualitative analysis process generated 362 initial codes, which were then synthesized into 44 main themes representing the key opportunities. Key future-oriented opportunities identified include enhancing cognitive activity, blending hard and soft skills, and creating smart workshops, as well as personalizing learning, intelligent assessment, and safe, low-cost simulation. Additionally, updating the role of teachers, designing engaging technology-based content, automating processes, digital collaboration, real-world projects, virtual visits, and AI-assisted entrepreneurship education are highlighted, aligning the 'Career and Technology' course with future needs. Finally, the analysis categorizes the impact of the prioritized technological trends across the four essential domains of teaching and learning: Content Design and Production, Presentation and Teaching, Performance Assessment, and Learning Environment ManagementConclusion: The research affirms that technology is a key driver for transforming the "Career and Technology" course. The coming years should focus on personalized and deep learning (driven by AI) and facilitating safe, practical learning (driven by VR/AR and IoT). These opportunities are crucial for developing the hard and soft skills students need for the future project-based economy. Such comprehensive integration is essential for teaching these courses, equipping students with skills in adaptability, teamwork, and problem-solving, while simultaneously nurturing their ability in creative inquiry, data-driven decision-making, and effective collaboration within smart, technology-enriched environments. These are, in fact, the very competencies that fully align with the future-oriented opportunities identified by experts.
Original Research Paper-English Issue
Educational Technology - Artificial Intelligence
N. Azadi; E. Reyhani; M. Ghorbani; R. Ebrahimpour; S. Haghjoo
Abstract
Background and Objectives: Mathematical modelling has increasingly become a central component of mathematics education, as it helps students connect abstract mathematical concepts to real-world situations. Despite its importance, many elementary pre-service teachers (PSTs) face challenges when attempting ...
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Background and Objectives: Mathematical modelling has increasingly become a central component of mathematics education, as it helps students connect abstract mathematical concepts to real-world situations. Despite its importance, many elementary pre-service teachers (PSTs) face challenges when attempting to design or solve modelling problems, partly due to their limited exposure to such tasks during their teacher education programs. With the rapid development of AI (AI), new opportunities have emerged to compare human problem-solving approaches with machine-generated solutions. The purpose of this study is to examine how elementary PSTs and an AI system perform on mathematical modelling tasks. Specifically, the study seeks to understand the strengths and weaknesses of PSTs’ modelling competencies, while also exploring the potential contributions of AI as a supportive tool in mathematics education. The objective is not only to evaluate performance but also to address the broader significance of integrating AI into teacher education, highlighting both opportunities and risks.Methods: A convenience sample of 50 PSTs participated in the study. Participants were asked to complete a researcher-developed test that included mathematical modelling tasks designed to evaluate different aspects of modelling competence. The face and content validity of the instrument were reviewed and confirmed by two experts in mathematics education, ensuring the appropriateness and relevance of the items. Data were collected in written form and analyzed using both quantitative and qualitative approaches. The PSTs’ responses were examined based on the competency framework, which provides structured criteria for assessing modelling skills such as understanding the problem, using mathematics, interpreting results, and validating solutions. AI-generated responses were also collected for the same tasks, and these were compared with the human responses in terms of strategy, accuracy, creativity, and solution quality. The study followed a qualitative design with deductive (directed) content analysis, which allowed the researchers to systematically code and interpret the data while drawing comparisons across human and AI performance.Findings: The findings revealed several important patterns. Many PSTs demonstrated weaknesses in mathematical modelling, particularly in the stages of validation and interpretation. Their answers were often incomplete or lacked sufficient reasoning. However, the participants performed relatively better in the criterion of 'use of mathematics', indicating that they could carry out mathematical procedures but struggled to connect them meaningfully to real-world contexts. No statistically significant differences were found between participants based on gender or academic background, suggesting that the difficulties with modelling are widespread among elementary PSTs regardless of their demographic characteristics. In contrast, the AI system produced solutions that were generally more coherent and well-structured, particularly in terms of validation and creativity. The AI was able to provide step-by-step explanations and generate multiple approaches to solving the same problem, which could serve as a model for PSTs. Nevertheless, the AI responses were not flawless, and in some cases, over-simplifications or assumptions were made without sufficient justification.Conclusion: The study concludes that while PSTs have some foundational skills in mathematical modelling, their overall competencies are insufficient for solving complex modelling tasks independently. This finding points to a need for teacher education programs to place greater emphasis on developing modelling skills through practice, reflection, and guided instruction. At the same time, the study highlights the potential of AI as a valuable educational resource. AI can accelerate the learning process by providing worked examples, alternative solutions, and creative perspectives on modelling tasks. However, the findings also caution against over-reliance on AI. If PSTs depend too heavily on AI-generated solutions without critical evaluation, their own problem-solving and reasoning abilities may be undermined. Therefore, AI should be integrated into teacher education thoughtfully, with clear guidelines for its use as a supportive rather than substitutive tool. By balancing human learning with technological support, teacher educators can better prepare future teachers to engage their students in meaningful mathematical modelling activities.
Original Research Paper-English Issue
Technology-based learning environments
M. Namdari-Pejman; M. Zandian
Abstract
Background and Objectives: The rapid advancement of digital technologies and the expansion of online learning in the wake of the COVID-19 pandemic have profoundly highlighted the critical role of parents in supporting their children's education within digital environments. Previous studies consistently ...
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Background and Objectives: The rapid advancement of digital technologies and the expansion of online learning in the wake of the COVID-19 pandemic have profoundly highlighted the critical role of parents in supporting their children's education within digital environments. Previous studies consistently show that active parental involvement contributes significantly to improvements in students' academic performance, motivation, and digital literacy. Two key factors identified as influential in this parental engagement are the quality of school-parent communication and parents' self-efficacy in the digital domain. Effective school communication acts as a vital bridge between home and school, helping to mitigate the barriers posed by the digital divide. Concurrently, parental self-efficacy—the belief in one's ability to effectively support a child's online learning—empowers parents, fostering the motivation for constructive supervision and the modeling of positive digital behaviors. Despite this background, research has focused little on an integrated examination of these factors and the mediating role of parental engagement in shaping students' positive digital agency—defined as responsible, ethical, and creative behaviors in virtual spaces. The current study aims to address this gap by testing a conceptual structural model that explores the relationships between school-parent communication, parental self-efficacy, parental digital engagement, and students' positive digital agency. A central objective is to specifically investigate the mediating role of parental digital engagement in transmitting the effects of the two antecedent factors (school communication and self-efficacy) onto the development of positive digital agency. The findings of this research aim to provide empirical evidence to inform educational policy and empower families in the digital age.Methods: This study employed a descriptive-correlational design with a quantitative approach, utilizing covariance-based structural equation modeling (SEM). The target population consisted of parents of elementary school students in Qazvin, Iran, during the 2025-2026 academic year, all of whom had at least one year of experience with their child's digital learning. A multi-stage cluster sampling method was used. After removing incomplete or unsuitable responses, the final sample size comprised 362 participants. Data were collected using four standardized Persian questionnaires: The Parental Self-Efficacy Scale, the School-Parent Communication Scale, the Parental Digital Engagement Scale, and the Students' Positive Digital Agency Scale. Data analysis involved checking preliminary assumptions (e.g., normality), conducting confirmatory factor analysis (CFA) to validate the measurement model, and testing the structural model. The significance of direct and indirect (mediating) effects was assessed using the bootstrap method with 5000 resamples.Findings: The conceptual model demonstrated an acceptable fit with the data (CFI = 0.96, RMSEA = 0.07). All direct paths were statistically significant: school-parent communication to parental digital engagement (β = 0.60), parental self-efficacy to parental digital engagement (β = 0.26), and parental digital engagement to students' positive digital agency (β = 0.53). The analysis of indirect effects confirmed the mediating role of parental digital engagement, indicating it functions as a full mediator in the relationship between the two predictor variables (school communication and parental self-efficacy) and the outcome variable (students' positive digital agency). Overall, the model explained 65% of the variance in parental digital engagement and 28% of the variance in students' positive digital agency.Conclusion: The results underscore the necessity of harmonizing environmental factors (effective school communication) and individual factors (parental self-efficacy) through practical parental digital engagement to foster students' positive digital agency. To cultivate students as responsible and creative digital citizens, schools must strengthen two-way communication channels and actively empower parents. Practical applications of these findings include the design of targeted parent training workshops focused on digital skills and supportive strategies, as well as the integration of digital citizenship education into the core school curriculum. This study's limitations include its specific geographical focus (Qazvin) and reliance on self-reported data. For future research, it is recommended to investigate the role of potential moderating variables, such as socioeconomic status, and to test practical intervention programs on a larger scale to further validate and generalize the proposed model.
