Background/Purpose: Integrating artificial intelligence tools within educational settings has generated considerable debate, yet empirical research that offers implications of its usage remains scarce. This study aims to qualitatively assess the perceptions and experiences of school principals and teachers regarding the use of ChatGPT in K-12 schools, focusing on the potential benefits and challenges.

Materials/Methods: Using a SWOT analysis framework, semi-structured interviews were conducted with 17 teachers and four school principals to explore participants’ insights and perceptions about the strengths, weaknesses, opportunities, and threats associated with using ChatGPT in education.

Results: The findings suggest that ChatGPT positively contributes to learning by providing personalized feedback, encouraging collaborative working, and supporting content-rich learning environments. It also contributes to the improvement of writing and language skills by providing continuous feedback to both students and teachers. However, concerns have been raised regarding ethical issues such as data privacy, security, plagiarism, bias, and the potential for commercial exploitation, as well as negative psychological impacts on users.

Background/purpose: The integration of ChatGPT in education shows great potential, but its success depends upon educators’ technological skills, their ability to adapt to new teaching tools, and a willingness to embrace AI as part of their instructional strategies. This qualitative study investigates the integration of AI, specifically ChatGPT, into lecture and lesson planning by faculty members in Kosovo. The study examines how ChatGPT contributes to their professional development and how it influences their higher education teaching practices.

Materials/methods: This study employed qualitative case study methodology, interviewing 10 faculty members (seven females, three males) from public and private universities in Kosovo to explore their use of AI in teaching. The participants, aged 38 to 52 years old, represent mid-career to late-career professionals with 3 to 13 years of teaching experience, and deemed likely more open to the adoption of new technologies. Data from email interviews were analyzed according to thematic analysis, with codes organized into broad themes to identify patterns and relationships.

Results: The findings indicate that faculty members view ChatGPT as a valuable tool for streamlining time-intensive teaching tasks, such as generating content ideas, creating engaging activities, and providing resources. This support was perceived to enhance their efficiency, contributing to more dynamic and interactive lectures. Faculty members raised concerns that ChatGPT’s integration may reduce student engagement in independent learning and critical thinking.

Background/Purpose – Technological pedagogical content knowledge (TPACK) emphasizes the effective integration of artificial intelligence (AI)-based tools in education, where specific knowledge is measured individually. This research determines the readiness of preservice teachers (PSTs) to integrate AI-based tools in education through the TPACK approach.

Materials/Methods – This descriptive study involves 429 PSTs from Don Mariano Marcos Memorial State University in the Philippines through a face-to-face survey. Exploratory factor analysis was employed using a minimum residual extraction method with oblimin rotation. Partial least squares structural equation modeling was performed, and goodness of fit indices (GFI, AGFI, PGFI, RMSEA, and TLI) were tested.  

Results – The PSTs’ readiness to integrate AI-based tools in education revealed their readiness based on their technical knowledge (TK), technical pedagogical knowledge (TPK), technical content knowledge (TCK), and TPACK, as well as their ethical readiness. The study found that the PSTs’ TK, TPK, TCK, and TPACK were positively related to their ethical readiness.

Background/Purpose. The integration of ChatGPT within higher education holds significant potential for enhancing learning through personalized, adaptive, and interactive educational experiences. This study’s aims were to investigate how academic engagement with ChatGPT in higher education has evolved within the Gulf Cooperation Council (GCC) countries. The objective was to identify key trends, benefits, challenges, and implications of adopting this technology in higher education systems across the region.

Materials/Methods. This study employed a bibliometric analysis of publications indexed in the Scopus database, focusing on those related to ChatGPT and higher education. VOSviewer software was used to generate network and overlay visualizations of key research topics and their co-occurrence patterns over time. Constructivist learning theory was applied as the theoretical framework to contextualize the findings and explore how ChatGPT can be used to support personalized learning in higher education.

Results. The analysis revealed that ChatGPT and artificial intelligence are central to the academic discourse on AI in higher education, particularly in GCC countries, with notable increases seen in research output over recent years. Key findings include the positive impact of ChatGPT on personalized learning and student engagement, as well as the growing focus on ethical concerns such as data privacy and bias. The study also identified strong interdisciplinary connections, with AI research in education intersecting with fields such as computer science, linguistics, and cognitive science.

Background/purpose. ChatGPT has become one of the groundbreaking examples of artificial intelligence-based chatbots with its capacity to produce texts and engage in human-like conversations. Therefore, it has garnered the attention of people with diverse backgrounds, including educational professionals. The current study aims to investigate how school principals and teachers perceived the use of ChatGPT in education and reveal their attitudes towards using AI-based tools to facilitate the teaching-learning experience.

Materials/methods. The study was designed using the qualitative case study method since it aimed to gather detailed information regarding school principals’ and teachers’ perceptions of ChatGPT. Data was collected from 80 teachers and school principals selected purposefully from public primary, secondary, and high schools. Data was analyzed using content analysis techniques by synthesizing codes into categories and themes.

Results. The study revealed four major themes regarding school principals’ and teachers’ perceptions of ChatGPT: overall perceptions, perceived opportunities, perceived risks, and the effective use of ChatGPT. The participants referred to several advantages of using ChatGPT in education such as lesson planning, offering customized learning, and enabling easy and fast access to information. They were also cautious about some risks such as ethical and responsible use, the likelihood of encouraging dishonesty, free-riding, cheating, or plagiarism as well as weakening students’ cognitive skills. Due to its potential to provide inaccurate information depending on the reliability of its data source, they were also doubtful that it could provide students with false guidance in its current form. The participants also made some recommendations to make better and more effective use of ChatGPT in education such as providing ongoing training for both teachers and students on recent developments, increasing the reliability of its data sources through continuous tests, and aligning its capacity with the readiness and age of students.

Background/Purpose. This study investigates the integration of neuropedagogy, neuroimaging, artificial intelligence (AI), and deep learning in educational systems. The research aims to elucidate how these technologies can be synergistically applied to optimize learning processes based on individual neurocognitive profiles, thereby enhancing educational effectiveness.

Materials/Methods. A mixed-methods approach was employed, incorporating both quantitative and qualitative analyses. The study involved 297 students and 59 teachers. Quantitative methods included exploratory factor analysis (EFA) to validate the Neuropedagogy, Neuroimaging, Artificial Intelligence, and Deep Learning Scale, and Spearman correlations to examine inter-variable relationships. Qualitative data were collected through focus groups and analyzed using selective coding. Additionally, a comparative case study using portable electroencephalography (EEG) was conducted to observe direct neurological effects of different learning approaches.

Results. EFA confirmed the construct validity of the scale (KMO = .89, p < .001). Spearman correlations revealed significant positive relationships between all dimensions (.65-.72, p < .01). Multiple regression analysis indicated that AI was the strongest predictor of deep learning (β = 0.39, p < .001). The neuroimaging case study demonstrated increased frontal and prefrontal lobe activation and enhanced theta-gamma wave synchronization in AI-supported learning tasks, suggesting more integrated information processing.

Background/purpose. Widespread adoption of e-learning was triggered worldwide during the COVID-19 pandemic and modern higher education institutions dedicated significant resources to the use of diverse e-learning systems. However, to maximize the benefits of these investments, it is crucial that the degree to which end-users accept and continue using these systems is evaluated. Employing an integrative theoretical framework based on the extended Technology Acceptance Model (TAM) and Expectation Confirmation Model (ECM), this study aimed to scrutinize factors affecting students’ continuance intention to use an e-learning platforms following the pandemic.

Materials/methods. The research employed a cross-sectional design, and 343 university students were surveyed. Partial least squares structural equation modeling (PLS-SEM) was employed in the data analysis.

Results. The findings indicate perceived usefulness and satisfaction to be direct predictors of e-learning system usage, whilst confirmation of expectation, perceived usefulness, perceived ease of use, and system interactivity were shown as indirect predictors.

Background/Purpose. The study aimed to develop a rubric to measure students’ critical-thinking skills within a multicultural education scope.

Materials/Methods. The study’s participants were faculty members, teachers, and students, determined according to convenience sampling based on predetermined criterion. Initially, a story-based test and critical-thinking rubric were prepared and then validity studies conducted on these products. Subsequently, the prepared test and rubric were applied to fourth-grade elementary school students, with the data scored by their teachers, and reliability studies were then conducted. During the study’s analysis, scope, validity index and ratio, agreement percentage, correlation coefficient, Kendall’s concordance coefficient, and Cronbach’s alpha coefficient were all examined.

Results. The collected data were evaluated according to statistical analysis and the obtained findings showed the developed rubric to be both valid and reliable. The results revealed that the rubric developed to evaluate critical-thinking skills in a multicultural education scope was deemed to be an effective tool to assist teachers in measuring and evaluating students’ critical-thinking skills. In addition, use of the rubric can contribute to identifying and implementing strategies to improve students’ critical-thinking skills.

Background/purpose. Student mentoring aims to contribute to learner development beyond that of their academic program. In this study, we focus on a student mentoring program (SMP) consisting of mentors, communities, and peers, which aimed to promote students’ seven dimensions of well-being (Emotional, Social, Physical, Intellectual, Occupational, Spiritual, and Financial). The purpose of the study was to examine the mentoring program’s perceived influence according to these seven dimensions.

Materials/methods. The study was conducted according to a mixed QUAL-Quan methodology approach and was carried out within a multi-campus private university in México. Data were collected using a Likert-type scale that was responded to by 996 participant students, plus four focus groups (with 24 mentors) were held.

Results. The results show that the SMP contributed to the students well-being. Specifically, the mentors contributed to the students’ Emotional dimension, while the student communities contributed to the Social dimension.

Background/purpose. The study investigated the role of intercultural sensitivity as a mediator variable between cultural intelligence and attitudes towards multicultural education.

Materials/methods. The design of the research was a predictive correlational study. A total of 287 preservice teachers (PSTs) from different departments at a state university participated in the study. Data were collected by means of a personal information form, the Cultural Intelligence scale, the Intercultural Sensitivity scale, and Attitudes Towards Multicultural Education scale. The theoretical model, created to reveal the mediating role of intercultural sensitivity in the relationship between cultural intelligence and the variable of attitude towards multicultural education, was tested with the help of path analysis.

Results. Findings showed that while cultural intelligence significantly predicted attitudes towards multicultural education, when intercultural sensitivity was included in the model as a mediator variable, cultural intelligence did not significantly predict attitudes towards multicultural education.