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This research was conducted to see if using ChatGPT prompts students to think more deeply through reflection reports. The case study method and qualitative research methodology were used to carry out this study. Five graduate students in the Curriculum and Instruction department at Aksaray University's Social Sciences Institute who were teachers in various subjects and employed at various state school levels participated in the study. It was found that the majority of participants accepted all of the information presented by ChatGPT based on a citation as true, did not feel the need to control data reliability, and could be manipulated by ChatGPT while doing self-evaluation. Additionally, despite the fact that they prepared reflective reports in which they compared their essays with ChatGPT and included questions that prompted them to think critically and reflectively, as well as the fact that they had taken a graduate-level course on the teaching of higher order thinking skills, it was acknowledged that they could not demonstrate the expected performance in using higher order thinking skills other than to a limited extent. The onus should be on educators to pioneer positive examples of how to utilize ChatGPT and provide direction on how to harness its potential, supported by critical thinking, rather than to avoid using it and identify it as a tool to be avoided.

Since ChatGPT exploded onto the scene in October 2022, the media has been breathless with their discussion about how it is going to impact many aspects of life and work. In order to bring this new reality of generative AI into the "Introduction to Management Information Systems" classroom at both the undergraduate and graduate levels, we have developed two short cases that can be completed in or out of the classroom. These cases allow students to use generative AI for an interesting and useful purpose and develop prompts to deliver the output. Students can begin to learn what generative AI can do for them, and how it can shape their future careers. We tested the perceived effectiveness of the project on students using a pre/post survey. The results are analyzed using a paired t-test and demonstrate that students increased their understanding of generative AI and prompt engineering.

Still rebounding from the impact of the global pandemic, the higher education sector is being challenged even further by the next wave of Artificial Intelligence (AI) technologies. These technologies have the power to generate in a matter of seconds, quality text, images, music and coding responses to questions or prompts entered into an online chat box. Currently, one of the most accessible and popular text generators is OpenAI's ChatGPT which was released in November 2022. Early evaluation indicates that the quality of the responses exceed standard pass rates for comparable university assessments. Even if academic protocols mandate that text cited from AI sources should be acknowledged and referenced as any other source material, the speed, accessibility and high quality of the AI material justifies a rethink of the purpose of higher education and a redesign of curriculum, pedagogy and assessment. An initial suggestion being promoted in the sector is that learning outcomes and assessments should move away from a focus on content memorisation and recall, to development of higher order thinking skills such as critical analysis, evaluation, resilience, creativity, problem solving, appraising and mastery of verbal communication and computer literacy. This preliminary paper examines some of the literature to date, which discusses potential risks and threats, as well as the opportunities to enhance learning, embedded in this new wave of emerging AI technologies in higher education.

In this paper, we describe a teaching scenario using a virtual environment (known also in the context of the 'metaverse'). This is motivated by the challenges that arise during the pandemic. More and more teaching scenarios are transferred to online learning settings, which allow learning at any time and at any time. One of the possibilities are virtual 3D environment. These allow more intensive immersion than for example video conferences. Furthermore, they offer new didactic concepts, for example, for group activities. The benefit of using virtual 3D environments we demonstrate by a concrete learning scenario: the simulation of robot programming. A further advantage when using virtual 3D environments are personal assistants (conversational/ pedagogical agents), for example, to the ease the work load borne by teachers; meanwhile, this works well also with natural language due to advantage stage of artificial intelligence implementations.

The research is focused on a comprehensive analysis of digitalization as a prerequisite for higher education modernization. The authors of this article consider the digital divide as a component of information inequality, which has a technological nature and presupposes unequal opportunities for access, use, and production of information and knowledge or new technologies for their effective use in practice. The authors determined the digital divide is intensifying under pandemic and quarantine restrictions when the preference is given to blended learning technologies, collaborative learning, integrated learning, flipped classroom technology, storytelling, inquiry based learning (IBL), and project based learning (PBL). The research result is a unified information and communication ecosystem developed, which unites the scientific, technological, and educational potential of the network educational digital environment. The ecosystem also provides for the transformation from a lineal to a cluster model of competence cultivation, the formation of digital skills, growth in the volume of information, and creation of digital products.

In this paper we describe a framework for teaching students when they should, or should not use generative AI such as ChatGPT. Generative AI has created a fundamental shift in how students can complete their class assignments, and other tasks such as building resumes and creating cover letters, and we believe it is imperative that we teach students when the use of generative AI is appropriate, and when it is not appropriate (i.e., considered cheating). Framework development is based off the 2x2 Product-Market matrix introduced by Ansoff in 1965. Our initial pass at the framework was piloted with colleagues, and then followed with a focus group of students to refine the framework. We then used the framework in an MBA class to test its efficacy and gather qualitative feedback. Using the results, we further refined the framework and then used it to teach two general undergraduate business classes as a rudimentary test of generalizability across students. The qualitative results were positive. The framework helps educators understand when to use, or not use ChatGPT, and provides a way to teach students about the same. We have found that using the framework in class generates interesting discussions about the use of generative AI.

This study delves into the opportunities and challenges associated with the deployment of AI tools in the education sector. It systematically explores the potential benefits and risks inherent in utilizing these tools while specifically addressing the complexities of identifying and preventing academic dishonesty. Recognizing the ethical dimensions, the paper further outlines strategies that educational institutions can adopt to ensure the ethical and responsible use of AI tools. Emphasizing a proactive stance, the paper suggests that by implementing these strategies, schools can harness the benefits of AI tools while mitigating the risks associated with potential misuse. As the adoption of AI tools in education continues to expand, all stakeholders must stay abreast of the latest developments in the field. This knowledge equips educators to navigate the opportunities and challenges posed by AI tools, fostering a learning environment that is both secure and conducive to empowering students to realize their full potential.

This study aimed to investigate the impact of artificial intelligence (AI) anxiety on multi-dimensional 21st-century skills and lifelong learning among undergraduates. A quantitative method using a correlational research model was used to examine the relationships between AI anxiety, 21st-century skills, and lifelong learning levels, considering various demographic and educational variables. Data were collected from undergraduates in educational faculty programs in Kyrenia, Turkish Republic of Northern Cyprus (TRNC) during the 2023-2024 academic year. Findings revealed a moderate level of AI anxiety among students, a strong perception of possessing relevant 21st-century skills, and a moderate recognition of the importance of lifelong learning. Significant differences in AI anxiety were observed based on gender, with females reporting higher anxiety levels. Age, country of origin, university, faculty program, class level, GPA, use of AI-based products or services, and daily internet use for professional development also influenced students' 21st-century skills and lifelong learning levels. No significant correlations were found between AI anxiety and the other constructs, while a moderate positive correlation was identified between 21st-century skills and lifelong learning. These findings emphasize the importance of fostering 21st-century skills for lifelong learning and suggest that AI anxiety may not significantly impact students' skill acquisition or learning behaviours.

Artificial Intelligence (AI) is a highly discussed subject, and its integration into our daily lives has grown significantly. This research evaluated how dental students in North Cyprus perceive and feel about artificial intelligence, with a focus on identifying educational needs to enhance their professional skills. A self-administered multiple-choice questionnaire with 24 questions was conducted. 5 questions focused on gathering basic demographic information, such as gender, age, academic year, AI knowledge self-assessment, dental news sources, and experience in AI development. The remaining 16 questions pertained to AI-related topics. In general, students stated that they have little knowledge about AI (71.4%), and usually get the latest medical and dental news and information through the Internet (65.7%). 43,6% of the participants were strongly agree that AI-related lectures should be included in the regular curriculum for dental hygiene. Male students showed that they have significantly more knowledge about AI than female students. (p<0.05) In general, participants demonstrated diminished confidence in AI. It is seen that the dental education curriculum provided minimal information about AI and most of the students stated that AI-related lectures should be included in the regular curriculum for dental hygiene. Based on these findings, it is important to arrange lectures and seminars aimed at enhancing dental students' comprehension of AI.

The main aim of this mixed methods study is to determine the evaluations made by academics on an academic text generated with ChatGPT and get their general views on ChatGPT. The convergent parallel design is utilized where the qualitative and quantitative methods are combined to produce triangulated results. Data were collected via an online form from 45 academics. Academics were asked to read and rate the sample text generated by ChatGPT. The titles "Writing rules," "Language and expression," and "Subject integrity" of the text generated by ChatGPT received the highest ratings from the academics. The qualitative findings obtained were interpreted within the framework of the "Diffusion of Innovations" and "Uses and Gratifications" theories, and the related themes were formed. As a result, the participants were asked about their feelings about using ChatGPT, and the themes of astonishment, pessimism, anxiety, and hopefulness emerged. Participants were asked their opinions about the benefits and negative aspects of using ChatGPT. Themes emerged under the benefits, and negative aspects titles were evaluated. Finally, the other themes that emerged under the satisfaction with ChatGPT and making ChatGPT widespread titles were assessed.

This article examines the effects of technology in the field of education and management and focuses especially on the effects of technologies used in distance education activities on transformation processes. Based on research conducted, the article explains how technological developments affect education and management processes, according to the findings obtained as a result of the interviews. The technologies used in the digitalization processes of higher education institutions that provide distance education services and the effects of these technologies on the transformation processes were examined. How artificial intelligence, blockchain, metaverse, brain-computer interfaces and similar technologies can be used in education and organizational management processes and how this use affects management processes are discussed. Findings show that technological developments have profound effects on the processes in educational environments and transform management processes. As a result, the research emphasizes the need for further research and application to effectively use technologies such as artificial intelligence, blockchain, and metaverse in education and management processes. It is stated that advances in this field can cause significant transformations in education and management.

In an era of major advances in the digital world, artificial intelligence has been a part of programs, tools, applications, and platforms. It has also been integrated into fields of education including language teaching and learning. To this end, ChatGPT, one of the most recent AI-driven systems, has been proposed to support language learners' personalized studies. Thus, this paper presents a qualitative study aiming to explore how Turkish EFL learners in higher education use ChatGPT for speaking. For a deeper understanding, the study was designed as a case study which used multiple sources to collect qualitative data. In this sense, semi-structured interviews were held with the participants, and through open-ended questions, they were asked about their study habits and any background knowledge about ChatGPT. In a following session, they were introduced the chatbot and instructed on possible ways to use it for speaking practice. Screen recordings of the usage by the participants were another source to observe and later describe the process for the researcher. A final session of the interviews planned as a stimulated recall was held to explore the participants' ChatGPT use experience through their reflection. The thematic analysis of the data revealed codes and themes leading to language teaching implications about learner characteristics and use of AI for language studies.

The limitations of traditional education models and the advancement of technology have revealed the need to transform the learning experience. The "Flipped Learning" approach, born out of this need, is a model where students study learning materials in advance and participate in more interactive and hands-on activities in the classroom. This research discusses how the Flipped Learning model can be combined with ChatGPT. ChatGPT is a language model developed by OpenAI, and it can interact with students thanks to its natural language processing capability. In this way, combined with the Flipped Learning model, it can provide students with a more individualized and interactive learning experience. From this viewpoint, in this research, a model called "ChatGPT Aided Flipped Learning Model (CAFLM)" has been developed, which enables ChatGPT to be used in the "Flipped Learning" learning environment. CAFLM has three main phases: 1) Preparation, 2) Outside classroom teaching, and 3) inside classroom teaching. At these phases, the tasks of the student and the teacher are explained in detail. Sample activities and use cases are provided on how ChatGPT can be integrated into the Flipped Learning model and help students. To experience the model, activities developed for mathematics and science lessons were carried out using ChatGPT. The experiences have shown that the Flipped Learning model can be combined with Chatbots such as ChatGPT to provide students with a more effective and personalized learning experience. CAFLM can enable students to be more active in the learning process and contribute to innovative approaches in education.

Artificial Intelligence (AI) brings enormous opportunities into learning, teaching, and assessment processes. Among them, it is convenient to explore its ability to channel students' creativity, which is described as a basic competence in the training of people with both the OECD and the recent Spanish LOMLOE law pointing to the need to foster it in educational settings. In this context, the objective of this research is to explore the creative potential of prospective elementary school teachers related to storytelling, via a project including the rational use of AI generative tools. A combination of qualitative and quantitative instruments was used to get insight on the implications of those AI tools in the creative process and to gain understanding on the concerns of prospective teachers about AI at both their training and future teaching practice. The results show the potential of AI from an educational point of view, specially in self-assessment and co-evaluation processes, since it allows confronting not only the result of the creative task, but also the process itself by reflecting on the asked questions. Finally, the importance of continuing research on the ability to ask questions (a creative skill in itself) in the new context of AI is discussed.

Since artificial intelligence (AI) is extensively used in the field of education, it presents various opportunities in teaching and learning. In education, AI is chiefly used to impart knowledge, stimulate comprehension, heighten intelligence, and is treasured as support in learning. It is also instrumental in empowering and inspiring students. The emergence of AI also has a positive impact on inclusive education. Because these technologies can potentially transform teaching and learning, it is important to understand how they can be used to further support inclusive education. This non-empirical research analyzed some advantages and challenges of incorporating AI in teaching and learning and highlighted how it influences inclusion. Based on the literature, some of the advantages of AI are improved performance of students, motivation, and encouragement of students. This review also identified some challenges associated with the use of AI for inclusive education, such as technological difficulties, poor connectivity, pedagogical issues, and limitations of the database. Some recommendations are proposed to address these challenges. This research can assist educators, parents, students, government officials, and policymakers in making proper decisions on the effective use of AI and inclusion.

India's growing economy and population proves its significant stake in the Artificial Intelligence (AI) revolution. India's education and technology sector has grown exponentially over the last few years, particularly in times of COVID-19 pandemic but owing to various reasons, it is accessible to only one in four students in India. AI has proven to be of benefit to all stakeholders alike by (a) enhancing teachers' efficiency and effectiveness in managing Multi Levelled or Multi Graded Learning Units and enabling automated development of customised teaching content; (b) using Intelligent Tutoring Systems to tailor the learning materials to a child's level of competence, style and pace of learning for improving student interactivity and attention rates; and (c) for effective teacher posting and transfer systems and predicting likely student activities such as dropout rates in government schools. The research provides a comprehensive review of the rigorous inclusion of AI in India's education sector through various policy measures. According to the findings, AI increases the efficiency of grading and encourages critical thinking and analytical skills among students. Further studies can assess effective integration of AI with educational practices and policies to increase learning needs.

This study aims to examine the potential differences between teacher evaluations and artificial intelligence (AI) tool-based assessment systems in university examinations. The research has evaluated a wide spectrum of exams including numerical and verbal course exams, exams with different assessment styles (project, test exam, traditional exam), and both theoretical and practical course exams. These exams were selected using a criterion sampling method and were analyzed using Bland-Altman Analysis and Intraclass Correlation Coefficient (ICC) analyses to assess how AI and teacher evaluations performed across a broad range. The research findings indicate that while there is a high level of proficiency between the total exam scores assessed by artificial intelligence and teacher evaluations; medium consistency was found in the evaluation of visually based exams, low consistency in video exams, high consistency in test exams, and low consistency in traditional exams. This research is crucial as it helps to identify specific areas where artificial intelligence can either complement or needs improvement in educational assessment, guiding the development of more accurate and fair evaluation tools.

After the pandemic, research on Artificial Intelligence (AI) in the field of education has seen a significant increase globally. However, a few studies conducted before the pandemic addressed the problem of supporting intrinsic motivation in students, crucial for the quality of learning and knowledge retention. This study explores how this topic is covered in recent research, by conducting a cross-disciplinary literature review and critical discourse analysis under the theoretical framework of Activity Theory (AT). It aims to identify the coverage extension of all types of relationships between nodes in the educational activity system, with special attention to Subject (students) and Object, as this central relationship embodies the motive-driven nature of human activity. The analysis incorporated 69 articles from Scopus published from 2020 until now. The results demonstrate the coverage about only some relationships like: Subject-Tools (students' interaction with AI technology), Tools-Object (AI technologies development), and Tools-Community (adapting AI within an educational community). The Subject-Object relationship remains unexplored. Practical implications include refocusing on intrinsic motivation, emphasising epistemological needs, meaning, and choice. This involves evaluating the benefits and risks of AI in specific educational cases. Theoretical implications involve exploring how to sustain students' intrinsic motivation in the context of AI implementation.

The technology-supported education systems seamlessly integrated throughout the globe in response to the demands of post COVID-19 pandemic. The swift developments of the digital tools with Artificial Intelligence (AI) support are also readily diffused among the educational communities. This research paper investigates the synergistic impact of digital literacy, the incorporation of AI tools, and Peer Supported Collaborative Learning (PSCL) on the learning perceptions of university students. The research aims to discern the implications of these technological and social facets on students' attitudes towards AI assisted learning process. Structured questionnaire-based survey among the University students were done for this descriptive research. 409 responses collected were analysed with SPSS, Excel and Process Macro. It is found that the students' Digital Literacy, Use of AI tools and PSCL on AI assisted learning were positively correlated. The partial mediatory path through the PSCL and AI tool usage has a significant positive influence on students learning process. The insights gathered from this study can inform educators, policymakers, and institutions on optimizing the amalgamation of digital literacy, AI tools and PSCL to enhance the contemporary learning environment. As universities navigate the digital age, this research provides a nuanced understanding of the dynamics shaping students' perceptions, offering valuable insights into the multifaceted aspects of AI influencing the educational landscape.

The burgeoning role of Artificial Intelligence (AI) in education prompts crucial discussions regarding its implications for teaching and learning. This qualitative study probes the argumentative perspectives of 118 teacher candidates from Igdir University on the integration of AI into educational practices. Employing Toulmin's (1958) model, we analyzed their arguments, which encompass claims, evidence, warrants, backings, rebuttals, and conclusions, to ascertain their stance on AI's pedagogical integration. Utilizing four distinct AI chatbots--GPT-4, Gemini AI, Claude 3 Haiku, and Mistral AI--the research deciphers thematic undercurrents within these dimensions. Moreover, a novel methodological contribution is made through 'negative space exploration', focusing on the unmentioned themes to identify latent biases and assumptions in the argumentation. The study's dual analytical approach, combining AI-driven theme identification and negative space exploration, resulted in an enriched understanding of the content. Key findings suggest a nuanced perception among participants: while AI chatbots are acknowledged for enhancing educational efficiency and enabling personalized learning, concerns regarding diminished human interaction, potential erosion of critical thinking skills, and ethical use persist. The analyses also highlight the need for a balanced AI implementation that supports, not supplants, traditional educational methods. This research contributes to the ongoing debate on effective AI integration in education and calls for responsible pedagogical adoption of AI technologies.

The article reviews some of the relationships between AI and education, emphasizing the metaphors used, the difficulties in finding points of agreement, as well as aspects of the social criticism that is made of AI (e.g. considering that it can be a form of unwanted deviation). AI appears as one more case of technology that comes to improve education, as happened in the past with other less "intelligent" technologies, although now with more arguments in its favor. Secondly, it explores the logical mechanisms (abduction) that are widely used in human reasoning but also in AI, showing how their uncontrolled use can lead to certain conversation algorithms being able to lie, something that teachers would not do. An ethical rather than logical question is raised that deserves to be explored later.

Artificial Intelligence (AI) has been part of every citizen's life for several years. Still, the emergence of generative AI (GenAI), accessible to all, has raised discussions about the ethical issues they raise, particularly in education. GenAI tools generate content according to user requests, but are students using these tools ethically and safely? Can teachers guide students in this use and use these tools in their teaching activities? This paper argues that teacher professional development (TPD) is an essential key trigger in adopting these emerging technologies. The paper will present an integrative literature review that discusses the components of TPD that may empower teachers to guide their students towards the ethical and safe use of GenAI. According to the literature review, one key component of TPD should be AI literacy, which involves understanding AI, its capabilities and limitations, and its potential benefits and drawbacks in education. Another essential component is hands-on activities that engage teachers, their peers, and students in actively using these tools during the training process. The paper will discuss the advantages of working with GenAI tools and designing lesson plans to implement them critically in the classroom.

After years of development in the background, Artificial Intelligence (AI) has burst onto the global stage thanks to open tools for generating textual, visual, auditory, and audiovisual content. In this emerging context, AI is not only emerging as a technological phenomenon but also as a catalyst for innovation in the artistic and educational fields. Although we are only at the dawn, AI is rapidly evolving and leading us towards a revolution, opening a new field of possibilities in creative domains that will transform current aesthetic, procedural, and authorial conceptions. Its potential as a creative tool is currently limited to being a support that facilitates obtaining results of great formal quality and style quickly, but without human intervention based on clear objectives, it becomes an empty generator. Artistic Education must embrace this technology not as an intruder or rival, but as a tool to be known and integrated as another means of creation, developing skills that allow students not only to use these tools effectively but also to reflect on their implications in society and culture. Promoting a conscious, responsible, safe, and ethical use that ensures a critical stance towards generative AI. Understand that it is not a creative tool. It is for creators.

This article proposes a comprehensive AI curriculum tailored for young learners aged 11 to 14, emphasizing a humanistic approach. We review other AI curricula proposals for children and young people and underline that they focus primarily on AI's technological benefits and on learning coding and logic. Our curriculum explores human cognition that is often overlooked in existing AI curriculum. Our proposal combines learning through construction, reflective discussions and project-based learning in order to approach AI from variety of angles. Implemented by CreaTIC Academy during 2023/24 school year as an out-of-school activity in a secondary (middle) school in Barcelona, Spain, this curriculum integrates technological, philosophical, cognitive, and cultural dimensions. It draws from diverse fields, including Philosophy of Mind, Cognitive Psychology and Philosophy of Children, and includes practical coding with tools like Scratch and AppInventor, as well as Machine Learning for Kids. Designed to be adaptable across various socio-economic contexts, our approach aims to promote a broader liberal education for children and help teachers implement AI activities in their classrooms.

This research explores university educators' perspectives on the opportunities, concerns, and considerations associated with Generative Artificial Intelligence (GenAI) in the training of professional communicators. Positioned at the early stages of ChatGPT's integration into educational settings, the study examines teachers' assignment instructions, assessments of ChatGPT's responses, and reflections on these outcomes. Employing a cross-sectional, qualitative methodology, the research involves a sample of 22 teachers from communication faculties in Mexico, Peru, and Spain. Utilizing Bloom's taxonomy and an inductive approach for data analysis, the findings unveil nuanced views on GenAI's role in teaching practice. Teachers perceive ChatGPT as a tool with varying impacts depending on its application. They articulate distinct roles for ChatGPT, viewing it as either an ally or a rival, prompting discussions on anthropomorphizing technologies and emphasizing the need to empower students in GenAI tool usage, establish ethical protocols, and reconsider assessment methods, among other key considerations.

In higher education, generative chatbots have infiltrated teaching and learning. Concerns about how and if to utilize chatbots in the classroom are at the forefront of scholarly discussion. This quick-hit article presents a plan to teach learners about generative AI writing tools and their ethical use for writing purposes. As generative AI tools continue to emerge, this guide can support instructors from all disciplines to engage learners in getting the most accurate information.

Learning is an integral part of being human. How people learn has long been discussed, revealed in many learning theories, investigated in numerous studies, and demonstrated in extensive practices. The goal of this article is to rethink how people learn from four fundamental perspectives, that is, learning by interaction with content (C), learning by interaction with other people (O), learning by interaction with self (S), and learning by interaction with tasks or practices (T), so-called COST model. This framework offers a high-level view of human learning and the role of technology in human learning. Moreover, it serves as a guide for effective design of learning experiences, learning environments, and learning approaches, where technology has become a crucial component.

AI-generated paraphrasing tools, especially QuillBot and Paraphrasing Tool, play a crucial role in preventing plagiarism in academic writing. However, their effectiveness and proficiency have been questioned, particularly regarding the adequacy of their strategies. This qualitative study analyzed the paraphrasing strategies and proficiency levels of QuillBot and Paraphrase Tool. Using a purposive sampling technique, all 30 abstracts from one issue of the "Journal of Second Language Writing" were paraphrased using the two paraphrasing tools in their standard modes, and the results were analyzed using the frameworks of Keck (2014) and Nabhan et al. (2021). The results of the study indicated that both tools primarily used synonym substitution, with QuillBot favoring word-level changes and Paraphrase Tool emphasizing sentence restructuring. QuillBot tended to show minimal revision, followed by moderate revision, while Paraphrase Tool exhibited more moderate revision, followed by minimal and substantial revision. Paraphrase Tool exhibited broader paraphrasing capability than QuillBot, but both tools show some paraphrasing limitations. Overall, while these tools may enhance some writing, writers should thoroughly review the core concepts of the original texts and grammatical structures in specific contexts. For novice writers, paraphrasing practice in classrooms should be conducted under teachers' guidance. AIgenerated tools should be secondary.

Building on previous research, this qualitative exploratory study investigates the impact of ChatGPT on English language classes among Korean university students. The researcher uses pre- and post-training surveys, in-class observations, and interviews to explore 120 students' perceptions of their experiences over a 15-week semester. Results indicate largely positive attitudes, with students expressing optimism about ChatGPT's potential to enhance language skills. Classroom engagement was high, fostering collaboration and active participation. Post-training interviews revealed improved confidence, collaborative learning experiences, and a shift toward metacognitive awareness in learners and autonomous learning. Some technical and language challenges surfaced, as well as skepticism from a small number of learners. Long-term post-training surveys highlight sustained engagement and real-world applications. The findings provide insights for educators and policymakers considering the integration of AI tools in language education, emphasizing the importance of ongoing support and flexibility in implementation strategies.

A posttest-only control group experimental design compared novice Arduino programmers who developed their own programs (self-programming group, n = 17) with novice Arduino programmers who used ChatGPT 3.5 to write their programs (ChatGPT-programming group, n = 16) on the dependent variables of programming scores, interest in Arduino programming, Arduino programming self-efficacy, Arduino programming posttest scores, and types of programming errors. Students were undergraduates in an introductory agricultural systems technology course in Fall 2023. The results indicated no significant (p < 0.10) differences between groups for programming rubric scores (p = 0.50) or interest in Arduino programming (p = 0.50). There were significant differences for Arduino programming self-efficacy, (p = 0.03, Cohen's d = 0.75) and Arduino posttest scores, (p = 0.03, Cohen's d = 0.76); students in the self-programming group scored significantly higher on both measures. Analysis of students' errors indicated the ChatGPT group made significantly (p < 0.01) more program punctuation errors. These results indicated novice students writing their own programs developed greater Arduino programming self-efficacy and programming ability than novice students using ChatGPT. Nevertheless, ChatGPT may still play an important role in assisting novices to write microcontroller programs.

Adaptive online learning can be realized through the evaluation of the learning process. Monitoring and supervising learners' cognitive levels and adjusting learning strategies can increasingly improve the quality of online learning. This analysis is made possible by real-time measurement of learners' cognitive levels during the online learning process. However, most of the currently used techniques for evaluating cognitive levels rely on labour-intensive and time-consuming manual coding. In this study, we explore the machine learning (ML) algorithms and taxonomy of Bloom's cognitive levels to explore features that affect learner's cognitive level in online assessments and the ability to automatically predict learner's cognitive level and thus, come up with a recommendation or pedagogical intervention to improve learner's acquisition. The analysis of 15,182 learners' assessments of a specific learning concept affirms the effectiveness of our approach. We attain an accuracy of 82.21% using ML algorithms. These results are very encouraging and have implications for how automated cognitive-level analysis tools for online learning will be developed in the future.

Artificial intelligence (AI) has recently been gaining ground, particularly since November 2022, with the introduction of generative tools based on natural language processing and neural network algorithms. These kinds of tools have great potential for creators and users of Open Educational Resources (OER) and the Open Movement itself but they also represent risks. The International Council for Open and Distance Education OER Advocacy Committee (OERAC) developed two workshops to present the role of AI in OER at two international conferences in the fall of 2023. The workshops presented the features, benefits, key challenges, and practical issues related to using AI technologies from professional, ethical, sustainable, and equitable perspectives, while also focusing on the five areas of the UNESCO OER Recommendation. Participants were dynamically engaged in discussions, and documented their ideas in formats that could be used as OER in themselves. The OERAC noted and categorized the results, and developed short summaries and drafts for further work. Finally, drawing on the findings from the workshops, we asked ChatPDF for a second opinion on further suggestions for AI in connection with OER, which in turn related to the five areas of the recommendation. We conclude that, while there is great potential for the use of AI in the context of the Open Movement, there is also a need for professional ethics, equity, and sustainable capacity building, access, inclusion, policy, models, and international collaboration.

Recent advancements in generative artificial intelligence (GAI) have sparked debates and research on its transformative potential in education. This study explored how a specific group of educators partner with GAI tools, particularly ChatGPT, to complement and enhance their teaching. Within an interpretative paradigm, the study used an exploratory case study design to investigate how 13 educators enrolled as students in a structured master's programme at an open distance learning university in South Africa use GAI tools in their teaching. Their posts on a discussion forum were used to collect data. Findings reveal that they actively employ GAI to streamline their teaching practices, specifically to personalized tutors, simplifying English texts and translations, assessments, lesson planning, and critical thinking tasks. The study also highlights the need to understand the limitations and boundaries of GAI, including concerns about accuracy, biases and reliability. Importantly, the absence of institutional guidelines on GAI raises questions about the necessity for clear guidelines and policies to ensure responsible and ethical integration in educational contexts. The paper concludes by emphasizing the transformative potential of GAI and the fact that it will increasingly act as a partner in teaching and influence modern teaching practices. Ultimately, GAI's foothold in education is undeniable, challenging educators and policymakers to navigate its implications while maximizing its potential to support effective teaching.

This qualitative study explores the potential of generative artificial intelligence (AI) to improve the academic writing skills of a large student cohort within the context of a distance learning institution. Utilising qualitative methods, the research explores diverse approaches and applications of generative AI to elevate teaching and learning experiences. Grounded in socio-cultural theory and a human-AI collaboration framework, the study highlights the synergistic interplay between human intelligence and generative AI capabilities. Email interviews with lecturers, focus group discussions with students, and informal discussions with markers on a WhatsApp group helped researchers to (1) understand lecturers' perceptions of generative AI integration in the Academic Writing module, (2) explore students' perspectives on the potential of generative AI as a guide in the Academic Writing module, and (3) examine the potential of generative AI on students' motivation to enhance their academic writing skills. Findings from the study reveal that the potential of generative AI has a positive impact on teaching and learning experiences, providing innovative opportunities for academics. This research contributes to the discourse on the intersection of generative AI and education, reiterating the innovative potential of generative AI in redefining pedagogical strategies and shaping the future of distance learning.

This study tried to design a WhatsApp bot to be implemented in English language vocabulary learning context in Oman. 150 Omani English as a Foreign Language (EFL) students from three different proficiency levels were selected based on random sampling. To measure the effectiveness of the treatment, pretests, posttests, and delayed posttests were conducted, respectively. The TAM 2 extended questionnaire was also used to understand learners' perceptions regarding the use of the WhatsApp bot in the learning process. The results of the study revealed that the WhatsApp bot, on all three levels, works nicely and practically. Although experimental groups, who used WhatsApp bot, at elementary and intermediate levels showed significant differences from the traditional face-to-face classes, pre-intermediate students showed no significant difference between the two mentioned terms. It was also understood that chatbots could be the best supplementary materials assisting teaching in delivering materials.

Intelligent systems of essay grading constitute important tools for educational technologies. They can significantly replace the manual scoring efforts and provide instructional feedback as well. These systems typically include two main parts: a feature extractor and an automatic grading model. The latter is generally based on computational and artificially intelligent methods. In this work, we focus on the feature extraction part. More precisely, we focus on argumentation and discourse-related features, which constitute high-level features. We discuss some state-of-the-art systems and analyze how argumentation and discourse analysis are used for extracting features and providing feedback.

As a major shift in education technologies, Adaptive Learning Systems (ALS) use artificial intelligence and similar technologies, adapting the lessons to the needs of individual students. Emphasizing transformative pedagogy and teaching strategies that transform the learners' cognitive and interactive patterns, this study presents a comprehensive bibliometric analysis of ASL. Contrary to conventional teaching methods, ALS alters dramatically the way students think and interact with their environment. This research has utilized an all-inclusive bibliometric analysis to analyze the evolution, trends, and themes in ALS by using an extensive set of data from the Web of Science (WoS) and Scopus. The primary objective of Bibliometric analysis is to map the development of ALS in teaching and learning while marking the important trends, models, and thematic priorities. The relevance of this research lies in its comprehensive analysis of the Adaptive Learning Systems (ALS) field through bibliometric methods, offering critical insights into the trends, key contributors, and thematic developments over time. The systematic evaluation enables the appraisal of the impact created by major contributors like authors, organizations, journals, etc. The study also examines, using the advanced data collection technique, influential articles, and publications that enormously contributed to shaping ALS. Similarly, it does the rating effectively upon evaluating the mutual relationships among important terms, concepts, and factors through co-references and co-occurrences. It highlights the increasing scholarly output and identifies key contributors and influential works, underscoring the growing recognition of ALS's importance due to technological advancements. The study's findings on global research contributions, thematic analyses, and collaboration networks offer new insights into the field's dynamics, setting a foundation for future research directions. To visually represent bibliometric data, web analytic tools are used, explaining intricate relationships and thematic clusters. Identifying the unexplored areas and discussing the practical implications of ASL development, research, and analysis of combined data taken from WoS and Scopus provides a unique perspective. Consequently, researchers, educators, policymakers, etc., get valuable insights that enable advancing and understanding the area. This bibliometric analysis will undoubtedly guide future research in the area of transformative pedagogy as it is the most sought-after method in understanding the scholarly landscape of ALS.