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
Wu Xiaofan, Nagaletchimee Annamalai
CONT ED TECHNOLOGY, Volume 17, Issue 2, Article No: ep578
ABSTRACT
This investigation utilized a phenomenological approach to investigate the experience of English language educators in employing artificial intelligence (AI) tools into English language learning. The study used purposive sampling and 20 participants were interviewed. The data analysis was guided by Bronfenbrenner’s (1979) ecological systems theory, particularly microsystem, exosystem, and macrosystem. The findings demonstrated that the AI tools enable interactive, personalized, and gamified learning experiences that enhance student engagement, motivation, and English proficiency. The study also emphasized the importance of technological content knowledge and technological pedagogical knowledge in improving instructional methodologies. Challenges, including AI-related distractions and reduced direct interaction between educators and students, were identified, necessitating a balanced integration of these tools despite the inherent advantages. Furthermore, the research underscored the significance of institutional support, which encompasses ongoing professional development and technical assistance, to facilitate the successful integration of AI into education.
Keywords: artificial intelligence, English language learning, phenomenology, qualitative study, technology
Review Article
Klarisa I. Vorobyeva, Svetlana Belous, Natalia V. Savchenko, Lyudmila M. Smirnova, Svetlana A. Nikitina, Sergei P. Zhdanov
CONT ED TECHNOLOGY, Volume 17, Issue 2, Article No: ep574
ABSTRACT
In this analysis, we review artificial intelligence (AI)-supported personalized learning (PL) systems, with an emphasis on pedagogical approaches and implementation challenges. We searched the Web of Science and Scopus databases. After the preliminary review, we examined 30 publications in detail. ChatGPT and machine learning technologies are among the most often utilized tools; studies show that general education and language learning account for the majority of AI applications in the field of education. Supported by particular learning approaches stressing student characteristics and expectations, the results show that automated feedback systems and adaptive content distribution define AI’s educational responsibilities mostly. The study notes major difficulties in three areas: technical constraints and data privacy concerns; educational and pragmatic barriers. Although curriculum integration and teacher preparation are considered major concerns, pedagogical challenges come first above technology integration. The results also underline the need for thorough professional development activities for teachers and AI tools for especially targeted instruction. The study shows that the efficient application of AI-enabled PL requires a comprehensive strategy addressing technological, pedagogical, and ethical issues all at once. These results help to describe the current state of AI in education and provide ideas for future developments as well as techniques for its use.
Keywords: artificial intelligence, personalized learning, adaptive learning, intelligent tutoring systems, ethics in AI education
Research Article
Fatema Al Nabhani, Mahizer Bin Hamzah, Hassan Abuhassna
CONT ED TECHNOLOGY, Volume 17, Issue 2, Article No: ep573
ABSTRACT
This study sought to investigate the effects of employing artificial intelligence (AI) on the customization of educational content and the enhancement of academic performance and engagement among students and teachers. The research involved a sample of ninth-grade students and their educators from diverse subjects, utilizing questionnaires to evaluate their expectations and experiences with AI in education. The data were examined utilizing statistical techniques including means, standard deviations, and one-way ANOVA. The findings indicated that students held strong positive expectations regarding the influence of AI on the personalization of educational content, suggesting that customizing material to their specific needs would enhance their academic performance and boost engagement with the learning resources. Teachers concurred with the significance of AI in improving content personalization, especially given the difficulties encountered with conventional techniques. The study indicated that educators from various disciplines exhibited no significant differences in their evaluations of AI’s influence on education, implying that this technology may be advantageous across multiple courses. Furthermore, both educators and learners anticipated that AI would deliver swifter and more efficient feedback, hence improving the educational experience and engagement within the classroom. The study advocated for the incorporation of AI into educational curricula and the establishment of training programs for educators on the appropriate utilization of this technology. It also recommended undertaking additional long-term experimental research to assess the effects of AI over prolonged durations and within broader student populations. The study advocated for the enhancement of technology infrastructure to facilitate the effective integration of AI in educational settings, hence promoting more tailored and efficient learning experiences.
Keywords: artificial intelligence, personalizing educational content, integrated educational environment
Research Article
Izida I. Ishmuradova, Alexey A. Chistyakov, Tatyana A. Brodskaya, Nikolay N. Kosarenko, Natalia V. Savchenko, Natalya N. Shindryaeva
CONT ED TECHNOLOGY, Volume 17, Issue 2, Article No: ep565
ABSTRACT
This investigation aimed to ascertain latent profiles of university students predicated on fundamental factors influencing their intentions to acquire knowledge in artificial intelligence (AI). The study scrutinized four dimensions: supportive social norms, facilitating conditions, self-efficacy in AI learning, and perceived utility of AI. Through the utilization of latent profile analysis (LPA), the investigation endeavored to unveil distinct subgroups of students delineated by unique amalgamations of these factors. The study was carried out with a cohort of 391 university students from diverse academic disciplines. LPA disclosed five unique subgroups of students: Cautious Participants, Enthusiastic Advocates, Reserved Skeptics, Pragmatic Acceptors, and Disengaged Critics. These categories showed somewhat different goals to learn AI; Enthusiastic Advocates showed the highest intention while Disengaged Critics showed the lowest. The findings enhance the growing corpus of research on AI education in higher education by providing a sophisticated knowledge of the variation among university students about their attitudes and preparedness to learn AI. Subgroups of students show that learners need unique educational strategies and interventions to meet their diverse needs and attitudes. AI is changing many fields, therefore college students must learn about it and prepare for it. The findings advance AI education research and impact curriculum and policy.
Keywords: artificial intelligence, higher education, latent profile analysis, situated expectancy-value theory, intention to learn AI
Research Article
Marwan Mohammad Abualrob
CONT ED TECHNOLOGY, Volume 17, Issue 1, Article No: ep547
ABSTRACT
This study aims to uncover the prompts most frequently repeated by pre-service teachers when using the Copilot technique, as well as their reflections on its use in preparing and planning science lessons for fourth graders. The qualitative research methodology with an exploratory case-study design was conducted on a purposeful sample of 20 pre-service teachers. The sample was divided into four focus groups. Data was collected through document analysis of the outcomes from the pre-service teachers’ artificial intelligence creations, their reflective journal entries, and the discussion that occurred during the four focus groups’ interviews. The study’s results revealed that the applications mostly used by pre-service teachers include lesson plans, instructional media, authentic assessment, tables, pictures, drawings, and instructional strategies. Six themes emerged from the reflective Journal and focus groups’ interview analysis connected to the use of the Copilot method in teaching. These themes were the following: developing cognition of new ideas, attracting attention to things that never crossed their minds, saving time and effort, compatibility with students’ needs, less human interaction, and dependency.
Keywords: artificial intelligence, Copilot, pre-service teachers, science
Research Article
Aminah Saad Aldossary, Alia Abdullah Aljindi, Jamilah Mohammed Alamri
CONT ED TECHNOLOGY, Volume 16, Issue 4, Article No: ep536
ABSTRACT
Purpose: This study aims to provide an analysis of students’ perceptions of the role of generative artificial intelligence (GenAI) tools in education, through five axes: (1) level of knowledge and awareness, (2) level of acceptance and readiness, (3) the role of GenAI in education, (4 (level of awareness of potential concerns and challenges, and (5) The impact of GenAI tools on achieving the sustainable development goals in education.
Materials and methods: The study followed a descriptive quantitative methodology based on surveying through a questionnaire. The sample consisted of 1390 students from 15 Saudi universities.
Results: The students have positive perceptions towards the role of GenAI tools in education, as students have a high level of awareness and acceptance of adopting these tools. In addition, students are highly aware of the role of GenAI tools in improving their understanding of complex concepts, developing skills, improving their self-efficacy, learning outcomes, providing feedback, and making learning meaningful. The results also confirm their general awareness of the concerns and challenges. A relationship exists between students’ perceptions of GenAI and their scientific specializations, as students in computer sciences showed greater awareness regarding concerns and challenges, whereas students in agricultural sciences showed greater awareness of the impact of GenAI tools on achieving sustainable development goals.
Conclusions: The study offers valuable insights on GenAI adoption in higher education, also there is an urgent need to consider developing appropriate use policies, spreading awareness, and creating systems capable of detecting unethical cases.
Keywords: artificial intelligence, ChatGPT, LLM, technology role, education filed, perceptions of Saudi students
Research Article
Reginald Gerald Govender
CONT ED TECHNOLOGY, Volume 16, Issue 2, Article No: ep509
ABSTRACT
A new era of artificial intelligence (AI) has begun, which can radically alter how humans interact with and profit from technology. The confluence of chat interfaces with large language models lets humans write a natural language inquiry and receive a natural language response from a machine. This experimental design study tests the capabilities of three popular AI chatbot services referred to as my AI students: Microsoft Bing, Google Bard, and OpenAI ChatGPT on completeness and accuracy. A Likert scale was used to rate completeness and accuracy, respectively, a three-point and five-point. Descriptive statistics and non-parametric tests were used to compare marks and scale ratings. The results show that AI chatbots were awarded a score of 80.0% overall. However, they struggled with answering questions from the higher Bloom’s taxonomic levels. The median completeness was 3.00 with a mean of 2.75 and the median accuracy was 5.00 with a mean of 4.48 across all Bloom’s taxonomy questions (n=128). Overall, the completeness of the solution was rated mostly incomplete due to limited response (76.2%), while accuracy was rated mostly correct (83.3%). In some cases, generative text was found to be verbose and disembodied, lacking perspective and coherency. Microsoft Bing ranked first among the three AI text generative tools in providing correct answers (92.0%). The Kruskal-Wallis test revealed a significant difference in completeness (asymp. sig.=0.037, p<0.05) and accuracy (asymp. sig.=0.006, p<0.05) among the three AI chatbots. A series of Mann and Whitney tests were carried out showing no significance between AI chatbots for completeness (all p-values>0.015 and 0<r<0.2), while a significant difference was found for accuracy between Google Bard and Microsoft Bing (asymp. sig.=0.002, p<0.05, r=0.3 medium effect). The findings suggest that while AI chatbots can generate comprehensive and correct responses, they may have limits when dealing with more complicated cognitive tasks.
Keywords: artificial intelligence, chatbots, generative text, completeness, accuracy
Review Article
Othman Abu Khurma, Fayrouz Albahti, Nagla Ali, Aiman Bustanji
CONT ED TECHNOLOGY, Volume 16, Issue 2, Article No: ep503
ABSTRACT
This PRISMA-based literature review aims to assess and analyze the measurement of student engagement dimensions within AI ChatGPT interactions. The central question is how to effectively evaluate these dimensions using established methods and leverage insights to enhance AI ChatGPT’s capacity to foster student engagement. The systematic review of PRISMA methodology identifies 16 relevant peer-reviewed research. All relevant and eligible research according to PRISMA methodology are analyzed to comprehend the intricacies of student engagement in AI ChatGPT interactions. The synthesis of these findings unveils the current state of knowledge on AI ChatGPT’s influence on student engagement and uncovers opportunities for future research. This review underscores AI ChatGPT’s potential as an educational tool, offering personalized experiences that bolster student engagement and learning outcomes. The systematic review established that, even though using ChatGPT has many advantages such as enhancing student engagement and academic involvement and supporting inquiry-based learning. However, there are some negative aspects such as lacking empathy and human emotions, limited contextual understanding, increased technology dependence and possibility of Inaccurate or Biased Information. In summary, this PRISMA-based review contributes to understanding the measurement of student engagement within AI ChatGPT. It identifies best practices, laying the foundation for further research and development. By optimizing AI ChatGPT’s effectiveness, educators and developers can craft more engaging and tailored learning experiences, ultimately enhancing educational outcomes.
Keywords: artificial intelligence, ChatGPT, teaching, learning, student engagement
Research Article
Stavros Papakonstantinidis, Piotr Kwiatek, Filomachi Spathopoulou
CONT ED TECHNOLOGY, Volume 16, Issue 2, Article No: ep495
ABSTRACT
This research investigates the perspectives of using artificial intelligence writing software (AIWS) in professional contexts, focusing on academic and non-academic writers. These two groups, while standing to gain increased productivity through the adoption of AIWS, also express concerns regarding the widespread implementation of this technology. Notably, artificial intelligence (AI) writing tech’s impact on content creation has been profound, with its swift grammatically accurate content generation. This adoption, however, remains controversial. The study employs a quantitative approach, combining technology acceptance model and new computer game attitude scale. This approach allows us to discern implications of using AI-powered writing tools while accounting for possible differences in different domains of use. Through a survey of 219 participants, spanning academia and business, the study explores attitudes and willingness to use AIWS. Findings yield insights into non-academic writers’ readiness and implications of AIWS adoption. Business, non-academic professionals view AIWS as a tool for efficiency and content quality, while writers in academic contexts express concerns about biases, manipulation, and job displacement. The study contributes to AIWS understanding, benefiting developers, educational institutions, and content creators, and elucidates differing attitudes and age dynamics between academics and professionals. The research underscores the multifaceted influence of AIWS, providing a foundation for future exploration in this emerging domain, as well as practical applications for industries and educational institutions.
Keywords: artificial intelligence, chatbots, ChatGPT, education, educational technologies
Research Article
Mohammed Muneerali Thottoli, Badria Hamed Alruqaishi, Arockiasamy Soosaimanickam
CONT ED TECHNOLOGY, Volume 16, Issue 1, Article No: ep485
ABSTRACT
Purpose: Chatbots and artificial intelligence (AI) have the potential to alleviate some of the challenges faced by humans. Faculties frequently swamped with teaching and research may find it difficult to act in a parental role for students by offering them individualized advice. Hence, the primary purpose of this study is to review the literature on chatbots and AI in light of their role in auto-advising systems. The authors aimed to gain insights into the most pertinent topics and concerns related to robo academic advisor and identify any gaps in the literature that could serve as potential avenues for further research.
Design/methodology/approach: The research employs a systematic literature review and bibliometric techniques to find 67 primary papers that have been published between 1984 and 2023. Using the Scopus database, the researchers built a summary of the literature on chatbots and AI in academic advice.
Findings: Chatbot applications can be a promising approach to address the challenges of balancing personalized student advising with automation. More empirical research is required, especially on chatbots and other AI-based advising systems, to understand their effectiveness and how they can be integrated into educational settings.
Research limitations/implications: This research’s sample size may restrict its findings’ generalizability. Furthermore, the study’s focus on chatbots may overlook the potential benefits of other AI technologies in enhancing robo academic advising systems. Future research could explore the impact of robo academic advisors in diverse societal backgrounds to gain a more comprehensive understanding of their implications.
Practical implications: Higher educational institutions (HEIs) should establish a robo academic advising system that serves various stakeholders. The system’s chatbots and AI features must be user-friendly, considering the customers’ familiarity with robots.
Originality/value: This study contributes to a better understanding of HEIs’ perceptions of the adoption of chatbots and AI in academic advising by providing insightful information about the main forces behind robo academic advising, illuminating the most frequently studied uses of chatbots and AI in academic advising.
Keywords: Artificial intelligence, chatbots, robo, academic advisor, human interaction
Review Article
Roza S. Akhmadieva, Natalia N. Udina, Yuliya P. Kosheleva, Sergei P. Zhdanov, Maria O. Timofeeva, Roza L. Budkevich
CONT ED TECHNOLOGY, Volume 15, Issue 4, Article No: ep460
ABSTRACT
A descriptive bibliometric analysis of works on artificial intelligence (AI) in science education is provided in this article to help readers understand the state of the field’s research at the time. This study’s main objective is to give bibliometric data on publications regarding AI in science education printed in periodicals listed in the Scopus database between 2002 and 2023 end of May. The data gathered from publications scanned and published within the study’s parameters was subjected to descriptive bibliometric analysis based on seven categories: number of articles and citations per year, countries with the most publications, most productive author, most significant affiliation, funding institutions, publication source and subject areas. Most of the papers were published between 2016 and 2022. The United States of America, United Kingdom, and China were the top-3 most productive nations, with the United States of America producing the most publications. The number of citations to the publications indexed in Scopus database increased in a progressive way and reached to maximum number in 2022 with 178 citations. Most productive author on this topic was Salles, P. with four publications. Moreover, Carnegie Mellon University, University of Memphis, and University of Southern California have the maximum number of publications as affiliations. The National Science Foundation was the leader funding institution in terms of number of publications produced. In addition, “Proceedings Frontiers in Education Conference Fie” have the highest number of publications by year as a publication source. Distribution of the publications by subject area was analyzed. The subject areas of the publications were computer sciences, social sciences, science education, technology and engineering education respectively. This study presents a vision for future research and provides a global perspective on AI in science education.
Keywords: artificial intelligence, science education, STEM, bibliometric review
Review Article
Tufan Adiguzel, Mehmet Haldun Kaya, Fatih Kürşat Cansu
CONT ED TECHNOLOGY, Volume 15, Issue 3, Article No: ep429
ABSTRACT
Artificial intelligence (AI) introduces new tools to the educational environment with the potential to transform conventional teaching and learning processes. This study offers a comprehensive overview of AI technologies, their potential applications in education, and the difficulties involved. Chatbots and related algorithms that can simulate human interactions and generate human-like text based on input from natural language are discussed. In addition to the advantages of cutting-edge chatbots like ChatGPT, their use in education raises important ethical and practical challenges. The authors aim to provide insightful information on how AI may be successfully incorporated into the educational setting to benefit teachers and students, while promoting responsible and ethical use.
Keywords: artificial intelligence, education, chatbots, ChatGPT, personalized learning
Review Article
Andres F. Mena-Guacas, Jairo Alonso Urueña Rodríguez, David Mauricio Santana Trujillo, José Gómez-Galán, Eloy López-Meneses
CONT ED TECHNOLOGY, Volume 15, Issue 3, Article No: ep428
ABSTRACT
The diversity of topics in education makes it difficult for artificial intelligence (AI) to address them all in depth. Therefore, guiding to focus efforts on specific issues is essential. The analysis of competency development by fostering collaboration should be one of them because competencies are the way to validate that the educational exercise has been successful and because collaboration has proven to be one of the most effective strategies to improve performance outcomes. This systematic review analyzes the relationship between AI, competency development, and collaborative learning (CL). PRISMA methodology is used with data from the SCOPUS database. A total of 1,233 articles were found, and 30 passed the inclusion and exclusion criteria. The analysis of the selected articles identified three categories that deserve attention: the objects of study, the way of analyzing the results, and the types of AI that could be used. In this way, it has been possible to determine the relationship offered by the studies between skill development and CL and ideas about AI’s contributions to this field. Overall, however, the data from this systematic review suggest that, although AI has great potential to improve education, it should be approached with caution. More research is needed to fully understand its impact and how best to apply this technology in the classroom, minimizing its drawbacks, which may be relevant, and making truly effective and productive use of it.
Keywords: artificial intelligence, collaborative learning, skills development, educational development
Research Article
Mohanad Halaweh
CONT ED TECHNOLOGY, Volume 15, Issue 2, Article No: ep421
ABSTRACT
Since the launch of ChatGPT for public use, educators have expressed a variety of concerns about its integration into educational settings. This paper has been written to provide an in-depth examination of these issues and explore the potential use of ChatGPT in educational contexts. Specifically, it aims to (i) present an argument in favor of incorporating ChatGPT into education and (ii) provide educators with a set of strategies and techniques to ensure responsible and successful implementation of ChatGPT in teaching or research. By doing so, this paper aims to promote a more informed discussion around the use of ChatGPT in education.
Keywords: ChatGPT, artificial intelligence (AI), education, educational technologies