https://jlt.iaet.ir/ Trends and Achievements in Learning Technology en daily 1 Mon, 22 Dec 2025 00:00:00 +0330 Mon, 22 Dec 2025 00:00:00 +0330 https://jlt.iaet.ir/article_734177.html This research was conducted with the aim of investigating the impact of feedback from artificial intelligence tools on students' motivation and personalized learning in English language acquisition. The research method was quasi-experimental with a pre-test and post-test design. The statistical population included high school students, from whom 45 students were selected using a purposive sampling method and divided into three equal groups: a teacher feedback group, an AI feedback group, and a hybrid feedback group. The educational intervention was implemented over a 6-session period. The research instruments included the Hermans 1977 Achievement Motivation Questionnaire and a researcher-made personalized learning questionnaire. Covariance analysis was used to analyze the data. The results showed that both the AI feedback and hybrid feedback groups had a significant impact on increasing students' achievement motivation and enhancing their personalized learning. Furthermore, in a comparison among the groups, hybrid feedback was significantly more effective than teacher feedback, but in the area of personalized learning, no significant difference was observed between AI feedback and hybrid feedback. These findings indicate the high potential of artificial intelligence as an effective tool for increasing motivation and enhancing personalized learning in students. https://jlt.iaet.ir/article_735510.html AbstractThe present study was conducted to determine the main components of the professional competencies of educational technologists at Farhangian University. The research question was: What are the main components of the professional competencies of educational technologists at Farhangian University? The study used a systematic review method following the PRISMA protocol. The systematic review included scientific articles and other valid documents, of which 58 of 162 were included in the study. The keywords used were technologist, educational technologist, educational technology, competencies, and related words. The texts were studied and coded. In the first coding stage, 638 codes were extracted; in the second stage, after classifying the codes, 28 subcomponents; and in the third stage, 17 main components of the model were identified. The findings showed that the main components included managerial, organizational, ethical, collaboration, cognitive and perceptual, scientific, technological, educational design, learning environment design, content design and production, educational media, evaluation and feedback, distance learning, support, entrepreneurial, performance improvement, and competencies for the application of artificial intelligence in education. It was suggested that these competencies be used for educational technologists and that courses related to educational technology should be implemented at Farhangian University. Keywords: Professional competencies, Educational technology, Educational technologists, Farhangian University, Systematic review method. https://jlt.iaet.ir/article_735235.html The expansion of emerging technologies and cyberspace has influenced children’s lives and made media literacy education in primary school essential. Media literacy includes the ability to analyze, evaluate, produce, and consciously interact with media messages, enabling the development of responsible and informed citizens in the digital age. Despite the importance of this competency, Iran’s education system still lacks a comprehensive and localized program for media literacy at the primary level, and teachers and families face serious challenges in guiding children’s encounters with media. The absence of a scientific and operational framework has led to children growing up in cyberspace without the necessary skills, exposing them to cultural, psychological, and educational harms. This study adopted a sequential exploratory mixed-methods design. In the qualitative phase, through a research synthesis of 16 selected studies, the components of a media literacy curriculum model were extracted and an initial model was developed. In the quantitative phase, a researcher-made questionnaire based on the model was developed and administered to 200 primary school teachers and experts in curriculum planning and media literacy to examine the instrument’s validity and reliability and to validate the model. The findings indicated that the model, comprising five main components—analytical skills, digital security, visual literacy, implementation methods, and challenges—has high validity and strong feasibility, and can serve as a comprehensive framework for promoting primary students’ media literacy, critical thinking, creativity, and digital citizenship. Successful implementation of this model requires intersectoral coordination, teacher training, and continuous monitoring so that it can be improved in line with rapid technological changes and achieve sustainable impact. https://jlt.iaet.ir/article_735236.html This study aimed to systematically examine empirical evidence on the effects of the digital game Minecraft on the cognitive structures and processes of learners. Following the PRISMA guidelines, a comprehensive search was conducted in the Scopus, ScienceDirect, ERIC, and Web of Science databases for studies published between 2015 and 2025. After completing the screening process, 15 eligible studies meeting the inclusion and exclusion criteria were selected and subjected to qualitative analysis. The synthesis of findings led to the identification of four cognitive themes: foundations of spatial processing (mental rotation, spatial retrieval, and spatial thinking); logical–computational reasoning (algorithmic understanding, computational and abstract thinking, and procedural thinking); executive and regulatory functions (management of attentional resources, cognitive–emotional self-regulation, episodic memory, and semantic memory); and the development of adaptive and creative capacities (spatial reasoning, creative representation, and creativity). The evidence indicates that Minecraft, as an interactive cognitive ecosystem, provides a platform for deep mental engagement. In addition, bibliometric mapping was conducted using VOSviewer to visualize thematic structures and research trends within the selected studies. However, the effects of this game are influenced by moderating variables such as age, group structure, and the cognitive load arising from social competition. This review highlights the potential of Minecraft as a multifaceted educational tool and underscores the need for the development of novel assessment instruments and the investigation of underlying neural mechanisms to fully understand these adaptive capacities. https://jlt.iaet.ir/article_735237.html The present study was conducted to investigate the role of the game‑based Wordwall platform in reducing mathematics anxiety and enhancing cognitive presence among fifth‑grade elementary students. This applied research employed a quasi‑experimental design using a pretest–posttest control group. The statistical population consisted of all fifth‑grade students at Andisheh‑Sazan‑e Bartar School in Sanandaj during the 2024–2025 academic year. From this population, 40 students were selected through convenience sampling and randomly assigned to an experimental group and a control group (20 students in each group). The experimental group participated in an eight‑session instructional program based on the AI‑based Wordwall protocol, while the control group received traditional instruction. Data collection instruments included the Children’s Mathematics Anxiety Scale (Chiu & Henry, 1990), encompassing dimensions of learning anxiety, problem-solving anxiety, teacher anxiety, and evaluation anxiety, and the Cognitive Presence Questionnaire (Arbaugh et al., 2008), comprising the stages of triggering event, exploration, integration, and resolution or application. The results of the multivariate analysis of covariance (MANCOVA) indicated that the instructional intervention significantly reduced overall mathematics anxiety and enhanced cognitive presence. A detailed analysis of the subcomponents showed that learning anxiety, problem‑solving anxiety, and evaluation anxiety decreased significantly, whereas no significant change was observed in mathematics‑teacher anxiety. Regarding cognitive presence, the stages of triggering event, exploration, and integration improved significantly, while the final stage—resolution or application—did not show a statistically significant effect. These findings highlight the effectiveness of interactive artificial intelligence in improving students’ cognitive experiences and reducing test‑related anxiety. Accordingly, it is recommended that teachers employ digital gamified environments to enrich the assessment environment and deepen exploratory processes in mathematics instruction. https://jlt.iaet.ir/article_734549.html In recent decades, the "Philosophy for Children" (P4C) program, as an inquiry-based and dialogic approach, has significantly enhanced elementary students' critical, creative, collaborative, and reasoning thinking skills. Accordingly, the present study was conducted with the aim of enriching the Philosophy for Children program through artificial intelligence (AI) technology and examining its impact on the cognitive and reasoning skills of elementary school students. The research employed a quasi-experimental design with a pretest–posttest control group. The statistical population consisted of sixth-grade elementary students in Tehran during the 2025–2026 academic year, from which 34 students were selected via convenience sampling and randomly assigned to either an experimental group (n = 17) or a control group (n = 17). The experimental group received eight sessions of AI-enhanced Philosophy for Children instruction, while the control group followed the conventional curriculum. Data were collected using Thomson’s Reasoning Scale (2005) and Najati’s Standard Cognitive Skills Questionnaire (2013). Data analysis was performed using multivariate analysis of covariance (MANCOVA). Findings revealed a statistically significant difference between the two groups’ posttest mean scores in cognitive and reasoning skills (p < 0.05). Therefore, implementing an AI-enhanced Philosophy for Children program can significantly improve students’ cognitive and reasoning abilities. https://jlt.iaet.ir/article_733318.html Improving the quality of teaching–learning processes has long been a major concern in school systems, and existing evidence has indicated that the absence of a comprehensive management framework can hinder sustainable enhancement of educational quality. Accordingly, the present study was conducted with the aim of designing a Total Quality Management (TQM) model tailored to the needs of schools. This research employed a qualitative design using thematic analysis. The study population consisted of all credible documents, scientific sources, and research studies related to TQM and teaching–learning processes, from which 48 sources were selected through purposive sampling. Data were analyzed using a three-stage coding process including initial, axial, and selective coding, and the analysis was carried out through constant comparison and iterative refinement of themes. The findings revealed that the proposed model comprised six core components—educational leadership, learner-centeredness, teacher empowerment, planning and continuous improvement, management of instructional processes, and quality evaluation—each containing several sub-themes that collectively contributed to the improvement of teaching–learning quality. These components demonstrated that alignment among leadership practices, professional development, instructional organization, and continuous evaluation played a key role in enhancing learning experiences and educational performance. Based on the results, the proposed modelare foundational pillars of TQM. Nevertheless, much of the existing literature has focused on administrative efficiency rather than the pedagogical core. Several scholars have suggested that the adaptation of TQM to instructional processes requires a deeper understanding of classroom interactions, student engagement, professional development, and curriculum alignment. Moreover, technological developments and modern learning theories have highlighted the need for TQM frameworks to integrate learner-centered principles and data-driven decision-making. https://jlt.iaet.ir/article_734178.html The limit concept, foundational to calculus, is frequently associated with persistent student misconceptions that can be effectively diagnosed and remediated through rigorous assessment and targeted feedback. This study investigates the advantages and limitations of employing artificial intelligence (AI)—specifically Grok—in evaluating first-year undergraduate mathematics students’ mastery of the limit concept. Conducted as an applied mixed-methods investigation, the research involved 37 students from the Mathematics Education Department at Farhangian University of Isfahan. Data were collected via a researcher-designed questionnaire comprising seven items on limits; responses were digitized and submitted to the AI for analysis. Evaluation adhered to the CIPP framework, with emphasis on the process dimension, encompassing answer correction, scoring, ranking, error classification (conceptual, procedural, computational), and individualized feedback for students and the instructor. Quantitative results revealed no statistically significant difference between AI-generated and researcher-assigned scores. Qualitative content analysis identified key strengths—rapid processing, scoring precision, analytical feedback, and resource recommendations—alongside notable weaknesses, including deficiencies in graphical interpretation, overemphasis on final answers at the expense of procedural reasoning, and dependency on grammatically precise input for accurate recognition of mathematical notation. Findings underscore AI’s viability as a supplementary assessment tool in mathematics education, contingent upon enhancements in visual processing and process-oriented evaluation. https://jlt.iaet.ir/article_734550.html This study aimed to analyze the impact of education in the Metaverse city on improving urban quality of life in Tabriz. The Metaverse, as a new platform for digital interaction, enables interactive learning and urban living experiences in three-dimensional environments. The research employed a descriptive–analytical method, and data were collected using a questionnaire with 45 items across seven main dimensions: social, cultural, environmental, technological, psychological, educational, and economic. The statistical population consisted of 200 experts in urban planning, technology, and education, selected through purposive and snowball sampling. Data were analyzed using SmartPLS software. The measurement model results showed that all factor loadings were above 0.7, and composite reliability ranged between 0.85 and 0.92. The overall model fit index GoF was equal to 0.62, and the coefficient of determination for urban quality of life was equal to 0.73, indicating a good model fit. In the structural model, the Metaverse education path to quality of life had a coefficient of 0.22, the technological dimension 0.29, and the social dimension 0.18, representing the strongest effects. The findings reveal that education in the Metaverse environment enhances digital literacy, social interaction, reduction of urban travel, and spatial perception, thereby improving urban sustainability and well-being. Overall, Metaverse-based education is an innovative strategy that can contribute to achieving smart, sustainable, and human-centered cities in Iran. https://jlt.iaet.ir/article_734634.html This study aimed to explore the lived experiences and the meaning-making of religious education teachers regarding the redefinition of educational competencies in the era of smart technologies. The research employed a descriptive phenomenological approach and utilized Colaizzi’s method of data analysis. The study population consisted of religious education teachers in secondary schools in Mashhad, selected through purposive criterion-based sampling based on their experience with smart technologies and teaching tenure. Data were collected through in-depth semi-structured interviews and analyzed in seven steps according to Colaizzi’s method. From the data analysis, 324 meaningful statements and 142 initial codes were extracted, which ultimately led to the formation of five main themes: 1) dual experiences (awe/excitement) in confronting technology, 2) the transformation of competencies from content delivery to integrating digital ethics and meaning-making, 3) existential and ethical challenges (such as maintaining spiritual identity and trusting AI-generated data), 4) adaptive strategies through self-reflection and continuous learning, and 5) educational outcomes, including the emergence of the teacher’s new role as a “meaning-making guide in the digital world.” The findings indicated that redefining the competencies of religious teachers in the context of smart technologies is not merely a skill-based transformation but an existential and meaning-oriented phenomenon, shaped by the integration of three dimensions: technological understanding, ethical responsibility, and interpretive capability. This highlights the necessity of redesigning religious teacher education programs with an emphasis on technology literacy grounded in theological principles and the cultivation of meaning-guiding abilities in smart learning environments. https://jlt.iaet.ir/article_734789.html The rapid expansion of emerging technologies, particularly artificial intelligence (AI), has subjected education-oriented organizations to profound transformations and complex challenges in the process of innovation adoption. The purpose of this study is to design and propose a structural, hierarchical, and non-linear model to identify and explain the causal relationships among the factors influencing the adoption of AI-driven innovations in such organizations. Unlike conventional linear and technology-centered models such as the (TAM) and the (UTAUT), the proposed model adopts a systematic and holistic perspective by elucidating multi-layered causal relationships underlying AI innovation adoption.This applied research employs a mixed-methods approach, integrating qualitative and quantitative phases. Thirteen key factors were identified through a systematic literature review and subsequently analyzed using Interpretive Structural Modeling (ISM), through which they were organized into seven hierarchical levels. Model validation and the assessment of variables’ driving and dependence power were conducted using MICMAC analysis. The findings reveal that perceptual and information-processing infrastructures constitute the most fundamental and influential driving forces, forming the foundation for other components such as digital motivational mechanisms, organizational transformation frameworks, and structural dynamism. The MICMAC results further confirm the structural stability of the system and the clarity of causal relationships among variables. By offering a multidimensional analytical framework, the proposed model provides practical guidance for policymakers and organizational leaders to allocate strategic resources toward the development of perceptual and information-processing infrastructures rather than focusing on superficial instrumental layers. This approach not only prevents resource misallocation but also facilitates the sustainable and effective adoption of artificial intelligence within education-oriented organizations. https://jlt.iaet.ir/article_735511.html This study aimed to develop a multidimensional framework for the design and implementation criteria of gamification in education. A qualitative approach utilizing Braun and Clarke's thematic analysis method was employed. The research data comprised 14 relevant articles (10 international and 4 domestic studies) published between 2021–2026 (and 1400–1403 in the Solar Hijri calendar), which were purposefully selected after a systematic search and screening based on inclusion criteria. The analysis process involved repeated reading of the texts, extracting meaning units related to gamification criteria, primary coding, clustering codes, reviewing and naming themes, and ultimately extracting the overarching theme. As a result of the analysis, 20 initial codes were identified, organized into 12 basic themes (sub-themes), which were further grouped into five organizing themes. The organizing themes include: 1) Purposefulness and Educational Alignment, 2) Logic of Learning Experience Design and Component Cohesion, 3) Fairness and Inclusiveness, 4) Practical Implementation and Sustainability, and 5) Measurability and Iterative Improvement. The derived overarching theme revealed that high-quality gamification is achieved when it transcends fragmented, element-centric applications and evolves into a criterion-based, contextualized, and improvable process. This process integrates design decisions with implementation realities, establishes clear measurement indicators, and enables ongoing monitoring and gradual refinement. In addition to clarifying key criteria, the findings of this study provide a practical roadmap for teachers and instructional designers to design gamification aligned with learning objectives, uphold educational fairness, enable sustainable implementation in real-world conditions, and enhance intervention quality through phased assessment and revision. https://jlt.iaet.ir/article_735515.html This study examined the effectiveness of an artificial intelligence (AI)–based instructional design course on academic self-efficacy, achievement motivation, and self-regulated learning among students at Islamic Azad University, Azadshahr Branch. The research was applied in purpose and employed a quasi-experimental pretest–posttest design with a control group. The population comprised undergraduate students in Educational Sciences and related majors enrolled in the instructional design course. Sixty students were selected through multistage cluster sampling and randomly assigned to an experimental group (AI-based instructional design) or a control group (conventional instructional design). Measures included an Academic Self-Efficacy Questionnaire, Hermans’ Achievement Motivation Questionnaire, and the Self-Regulated Learning Questionnaire by Bouffard and colleagues. Data were analyzed using descriptive statistics and analysis of covariance (ANCOVA). After controlling for pretest scores, the experimental group achieved significantly higher posttest means in academic self-efficacy, achievement motivation, and self-regulated learning than the control group, and the instructional approach accounted for a substantial share of variance in all three outcomes. Accordingly, completing the AI-based course strengthened students’ beliefs in their academic capabilities, increased their motivation to strive for success, and enhanced key self-regulation processes such as planning, monitoring, and self-evaluation. Limitations include sampling from a single university branch, a limited time frame, and reliance on self-report data, which warrants cautious generalization. Practically, teacher education and educational science programs are encouraged to redesign instructional design courses by integrating AI tools in a structured manner across syllabi, assignments, and assessment. Emphasizing responsible AI use to build academic human capital, the study aligns with SDG 4 (Quality Education) and SDG 9 (Industry, Innovation and Infrastructure). https://jlt.iaet.ir/article_735526.html This research aimed to investigate the effect of teachers' motivational strategies and supportive behavior in virtual education on the academic performance of monolingual and bilingual students in English language courses. The research method was descriptive-correlational, and the statistical population included high school teachers and students in Ahvaz. Multi-stage stratified cluster sampling was performed, and data were collected from 96 teachers and 192 students (96 monolingual and 96 bilingual) using standardized questionnaires for motivational strategies (TUMSS) and supportive behavior (TUSBS). Data analysis was conducted using SPSS version 24, employing Pearson correlation coefficient, multiple regression, independent t-test, and Fisher's z-test. The findings showed that teachers' motivational strategies and supportive behavior have a positive and significant relationship with academic performance in both groups, but the strength of this relationship for supportive behavior was significantly stronger in the bilingual group (z = −2.04, p < 0.05). Additionally, the regression model indicated that in the bilingual group, both predictor variables significantly predicted performance (R² = 0.37), while in the monolingual group, only supportive behavior had a significant effect (R² = 0.16). These results suggest that in a virtual environment, teacher support for bilingual students acts not only as a facilitator but also as a compensatory factor against linguistic-cultural gaps. Furthermore, a significant difference was observed between teachers' and students' perceptions of the use of these strategies (p < 0.001), indicating the presence of self-report bias in teachers and the necessity of using multi-source assessment. Overall, the findings emphasize that the success of virtual education in multilingual regions, beyond technological infrastructure, depends on the quality of the human relationship with the teacher, especially through empathetic and responsive supportive behaviors. https://jlt.iaet.ir/article_735595.html Recent advances in artificial intelligence have transformed education; however, teachers’ readiness to effectively utilize this technology and its implications for the psychological dimensions of teaching have been less explored. The present study aimed to examine the effect of training in the use of AI tools in the design and implementation of instruction on teachers’ mindfulness in teaching and their readiness to adopt AI. This research employed a quasi-experimental design with a pretest–posttest control group. The statistical population consisted of 258 primary school teachers in Soltaniyeh, from whom 60 participants were selected through convenience sampling and randomly assigned to the experimental and control groups. The experimental group received eight training sessions on the use of Magic School, Fobizz, and Teach Better, while the control group used non-AI educational technologies such as Wordwall and Wayground during the same period. Data were collected using the Teachers’ Readiness for AI Applications Questionnaire (Ramazanoglu & Eklen, 2024) and the Mindfulness in Teaching Scale (Frank et al., 2016). The results of analysis of covariance indicated that the experimental group obtained significantly higher posttest scores than the control group on both mindfulness in teaching and readiness to use AI (p < 0.001). Moreover, AI-based training led to improvements in the experimental group’s technological self-efficacy, teacher–student interaction, and ethical awareness. The findings suggest that structured training in AI tools can enhance teachers’ professional readiness and, by reducing cognitive pressures associated with instructional design and implementation, facilitate the development of mindfulness in teaching. https://jlt.iaet.ir/article_735822.html The present study aimed to examine the role of religious orientation in predicting AI ethical reflection among student teachers. The statistical population consisted of undergraduate student teachers in the Faculty of Educational Sciences (fourth semester and above) during the 2024–25 academic year, all of whom used AI tools for at least one hour daily. A sample of 150 participants was selected using a random sampling method. Research instruments included the Religious Commitment Questionnaire (intrinsic and extrinsic) and the AI Ethical Reflection Scale, which comprises three components: ethical awareness, critical evaluation, and the use of AI for social good. Data were analyzed using Pearson correlation and standard regression. The findings indicated that both intrinsic and extrinsic religious commitment had positive and significant correlations with all dimensions of AI ethical reflection (r = 0.28 to 0.47, p < 0.01). Intrinsic religious commitment showed the strongest relationships with critical evaluation and the use of AI for social good. Regression analysis also demonstrated that both dimensions of religious commitment significantly predicted AI ethical reflection; however, intrinsic religious commitment was the stronger predictor (B = 0.59, t = 5.12, p < 0.01), while extrinsic commitment had a weaker predictive role (B = 0.31, t = 2.05, p < 0.05). The overall regression model was significant (F = 15.5, p < 0.01) and accounted for approximately 36% of the variance in AI ethical reflection. Based on the results, intrinsic adherence to religious beliefs and values plays a more influential role in shaping ethical sensitivity, critical thinking, and responsible use of AI among student teachers. These findings highlight the importance of integrating religious and ethical education within academic programs related to emerging technologies. https://jlt.iaet.ir/article_735912.html This qualitative phenomenological study aimed to explore the challenges of the Farhangian University curriculum with an emphasis on the content component and to document the solutions experienced by pre-service teachers, Farhangian University faculty, and graduates in Ardabil Province. Methods: Purposive and convenience sampling were employed, with inclusion criteria: for faculty, at least five years of teaching at Farhangian University and teaching courses related to the elementary education curriculum content; for pre-service teachers (entry cohorts 2020 and 2021 in Elementary Education)—completion of practicum units and at least half of the program units; for graduates (entry cohorts 97 and 98 in Elementary Education)—at least one year of service in public and Shahed schools in Ardabil Province. Data were collected over three months (October–December 2023) through semi-structured interviews. In this qualitative study, interviews continued until theoretical saturation, ending with 11 interviews from pre-service teachers, 15 from faculty, and 20 from graduates. For trustworthiness, Lincoln & Guba (1985) criteria—credibility, transferability, dependability, and confirmability—were applied. Findings: The results indicate that the content of the Farhangian University curriculum faces several challenges. Participants proposed solutions to overcome these challenges, including: empowering faculty, conducting needs assessments, reflective approaches in content development, revisions to curricular resources, organizing conferences and calls for engagement to improve content, soliciting feedback from pre-service teachers, expanding university libraries, foresight in planning, addressing resource shortages, developing novel content, improving the quantity and quality of practicum units, delivering capacity-building workshops for pre-service teachers, bringing university training closer to school practice, and elevating the scholarly and research caliber of pre-service teachers.