Research Article
Izida I. Ishmuradova, Sergei P. Zhdanov, Sergey V. Kondrashev, Natalya S. Erokhova, Elena E. Grishnova, Nonna Yu. Volosova
CONT ED TECHNOLOGY, Volume 17, Issue 3, Article No: ep579
ABSTRACT
The development of generative artificial intelligence (AI) has started a conversation on its possible uses and inherent difficulties in the field of education. It becomes essential to understand the perceptions of pre-service teachers about the integration of this technology into teaching practices as AI models including ChatGPT, Claude, and Gemini acquire popularity. This investigation sought to create a valid and trustworthy instrument for evaluating pre-service science teachers’ opinions on the implementation of generative AI in educational settings related to science. This work was undertaken within the faculty of education at Kazan Federal University. The total number of participants is 401 undergraduate students. The process of scale development encompassed expert evaluation for content validity, exploratory factor analysis, confirmatory factor analysis, and assessments of reliability. The resultant scale consisted of four dimensions: optimism and utility of AI in science education, readiness and openness to AI integration, AI’s role in inclusivity and engagement, and concerns and skepticism about AI in science education. The scale demonstrated robust psychometric properties, evidenced by elevated reliability coefficients. Cluster analysis unveiled distinct profiles of pre-service teachers based on their responses, encompassing a spectrum from enthusiastic participants to skeptical disengaged individuals. This study provides a comprehensive instrument for evaluating pre-service teachers’ perceptions, thereby informing teacher education programs and professional development initiatives regarding the responsible integration of AI. Recommendations entail the validation of the scale across varied contexts, the exploration of longitudinal changes, and the investigation of subject-specific applications of generative AI in science education.
Keywords: generative artificial intelligence, science education, scale development, pre-service teacher’s perceptions
Research Article
Rana Saeed Al-Maroof, Ragad M. Tawafak, Waleed Mugahed Al-Rahmi, Khadijah Amru Alhashmi, Ibrahim Yaussef Alyoussef
CONT ED TECHNOLOGY, Volume 17, Issue 3, Article No: ep580
ABSTRACT
Despite the spread of artificial intelligence (AI) tools and applications, the Apple Vision Pro (AVP) stands out for its innovative features compared to other types of wearable technology. Moreover, traditional glasses have been deficient in incorporating many AI innovations that could enhance user experiences and pose new challenges. In response to these innovative aspects, this study aims to develop a theoretical model by integrating constructs from the expectation confirmation model (ECM) (expectation confirmation and satisfaction [SAT]) and aspects from the Uses and Gratifications (U&G) theory. The perceived human likeness of AI mediates the model. This study focuses on the educational domain, aiming to assess how this technology enhances the academic environment and improves learning outcomes. The method used was a survey distributed among 134 participants from Al Buraimi University College, Oman, for two departments: English, linguistics, and information technology. The study consists of seven hypotheses to emphasize the conceptual model. The findings significantly impact predicting the actual use (AU) of AI features of AVP, indicating that users’ expectations and SAT play a pivotal role in technology adoption and are closely linked to the variable human likeness. Similarly, factors such as entertainment value, informativeness, and the lack of web irritations significantly influence technology adoption and are associated with the human likeness variable. However, Informativeness gratification failed to pass the proposal and showed a negative indicator for predicting the AU of AI. The implications drawn from these results suggest that educational institutions should tailor their courses and curricula to promote the effective use of AI.
Keywords: Apple Vision Pro, vision, ECM, U&G theory, human likeness
Review Article
Rita Wong Mee Mee, Fatin Syamilah Che Yob, Lim Seong Pek, Muhammad Fairuz Abd Rauf, Yang Mingmei, Ali Derahvasht
CONT ED TECHNOLOGY, Volume 17, Issue 3, Article No: ep581
ABSTRACT
Computational thinking (CT) has emerged as a foundational skill for young learners, preparing them to navigate and contribute to an increasingly digital world. This bibliometric analysis utilizes 374 articles from the Web of Science database to explore the research landscape surrounding CT in children’s learning, focusing on its applications in language acquisition and cognitive development. Using co-citation and keyword co-occurrence analyses, the study identifies key thematic clusters, including CT’s integration into curricula, its role in enhancing critical thinking, and its social-emotional benefits. Findings suggest that CT holds significant potential in advancing equitable and inclusive education, aligning with Sustainable Development Goal (SDG) 4 by promoting accessible, high-quality learning experiences. Furthermore, CT’s interactive and problem-solving methodologies, such as coding exercises and robotics, actively engage children and encourage collaborative learning, directly supporting SDG 10 by reducing educational inequalities across diverse learning environments. This analysis not only highlights CT’s transformative impact on traditional educational practices but also reveals critical research gaps, particularly in the areas of inclusivity and accessibility. Future research is encouraged to investigate these areas further, advancing sustainable educational strategies that equip children with essential skills for a rapidly evolving technological landscape, thus fostering resilience, adaptability, and creativity among young learners.
Keywords: computational thinking, children’s education, digital literacy, cognitive development, creativity
Research Article
Luis Eduardo Muñoz Guerrero, Yony Fernando Ceballos, Luis David Trejos Rojas
CONT ED TECHNOLOGY, Volume 17, Issue 3, Article No: ep582
ABSTRACT
Recent progress made in conversational AI lays emphasis on the need for development of language models that possess solid logical reasoning skills and further extrapolated capabilities. An examination into this phenomenon investigates how well the Capybara dataset can improve one’s ability to reason using language-based systems. Multiple cutting-edge linguistic models were fine-tuned using the Capybara corpus before assessing their performances on standard tasks demanding sophisticated reasoning. The comparison using different ways reveals that the logical reasoning of models improves and their ability to make inferences is enhanced. This research explores this further by considering what it means for developers who want more human-like machine conversation intelligence. We also see that this could become an invaluable tool when training reasoning-oriented language generating models.
Keywords: logical reasoning, language models, Capybara dataset, fine-tuning, extrapolation, conversational AI
Research Article
Betül Yıldızhan Bora, Cansu Şahin Kölemen
CONT ED TECHNOLOGY, Volume 17, Issue 3, Article No: ep583
ABSTRACT
This study investigates the impact of artificial intelligence (AI)-supported education in higher education, specifically examining its integration into a digital photography course and its effects on both students and instructors. A qualitative research methodology was employed, and participants were selected through purposive sampling. The study involved one instructor and 38 students, with data collected through semi-structured interviews and analyzed using content analysis within a qualitative case study design. The findings indicate that AI enhances educational processes by facilitating individualized learning, improving instructional effectiveness, supporting digital content development, and advancing academic language proficiency. Students demonstrated improvements in critical evaluation and technological adaptability. Additionally, the study revealed that AI-supported tools contributed to the development of students’ technical skills and promoted active engagement in learning processes. The immediate feedback provided by AI tools aided students’ understanding of fundamental photography principles. However, some students expressed concerns about potential risks associated with AI, including decreased engagement, learner passivity, and exposure to misinformation or contradictory content. The study highlights the importance of integrating AI within a sound pedagogical framework to ensure its effective application in educational contexts. Drawing on the experiences of both students and the instructor, the findings suggest that AI-supported educational models can enhance learning efficiency, while also emphasizing the need to bolster information reliability and foster critical thinking skills.
Keywords: artificial intelligence, education, integration, instructional design, higher education
Review Article
Thanapat Sripan, Pattarawat Jeerapattanatorn
CONT ED TECHNOLOGY, Volume 17, Issue 3, Article No: ep584
ABSTRACT
Based on an analysis of 36 peer-reviewed publications from academic databases, including ERIC, Scopus, Web of Science, and Google Scholar, this review article provides an in-depth examination of the current trends, challenges, and future implications of metaverse-based learning in education. To ascertain the quality and applicability of the papers studied, the scoping review applied a thorough methodology that included specific inclusion and exclusion criteria. A thematic analysis approach was employed to extract and synthesize the collected data. To guarantee the consistency and dependability of the results, tools like quality evaluation frameworks and structured data extraction forms were used. Findings revealed that immersive technologies like virtual reality, augmented reality, gamification, and collaborative virtual environments represent key developments that have significantly enhanced student engagement, practical skill development, and individualized learning experiences. However, there are also obstacles including high cost, limited accessibility, teacher readiness, and data concerns about privacy that keep widespread use in resource-poor places. The results show how metaverse technologies have the potential to democratize access to academic excellence, transcend cultural and geographic barriers, and facilitate experiential learning through simulation-based systems. Future studies must deal with these issues by examining the long-term effects of artificial intelligence-powered adaptive learning systems and concentrating on inclusive design, affordable solutions, and the moral use of data. If these barriers are overcome, the metaverse might serve as an essential tool for improving fair, exciting, and cutting-edge education globally.
Keywords: metaverse-based learning, immersive learning, educational challenges, personalized education
Review Article
Aigul I. Akhmetova, Salima S. Seitenova, Begzod K. Khodjaev, Odinakhon R. Jamoldinova, Saule Z. Yerkebaeva, Kenzhegul U. Kazybayeva
CONT ED TECHNOLOGY, Volume 17, Issue 3, Article No: ep585
ABSTRACT
This study presents the first comprehensive dual-database bibliometric analysis of game-based learning research, investigating its evolution between 2015 and 2024 through analysis of 34,125 documents from Scopus (18,487) and Web of Science (WoS) (15,638) using advanced visualization techniques. The findings reveal consistent field expansion with notable database variations: Scopus demonstrates steady growth while WoS experienced a significant 2020 decline. Citation analysis shows a higher impact on 2015-2018 studies, with Hwang, G. J. as the most influential author and “Computers and Education” as the top journal. Co-keyword analysis reveals distinct conceptual structures—Scopus exhibits two clusters (human-centered studies and game-based learning/serious games) versus three in WoS (education-motivation, health-rehabilitation, technology-design). Thematic analysis demonstrates that game-based learning, serious games, and virtual reality occupy different maturity positions across databases, indicating varied theoretical consolidation. Collaboration networks show US, China, and European dominance, with weaker ties involving developing countries. These findings provide critical insights for educational policymakers and curriculum designers, identifying research clusters to guide targeted funding, collaboration gaps requiring international partnerships, and evidence-based guidance on established versus emerging game-based learning approaches. The dual-database methodology offers comprehensive research landscape mapping that supports strategic decisions in educational technology implementation and research prioritization.
Keywords: game-based learning, bibliometric analysis, scientific mapping, data visualization, research trends