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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.

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.

The rapid advancement of artificial intelligence technologies, exemplified by systems including Open AI's ChatGPT, Microsoft's Bing AI, and Google's Bard (now Gemini 1.5Pro), present both challenges and opportunities for the academic world. Higher education institutions are at the forefront of preparing students for this evolving landscape. This paper examines the current state of AI education in universities, highlighting current obstacles and proposing avenues of exploration for researchers. This paper recommends a holistic approach to AI integration across disciplines, fostering industry collaborations and emphasizing the ethical and social implications of AI. Higher education institutions are positioned to shape an educational environment attuned to the twenty-first century, preparing students to be informed and ethical contributors in the AI-driven world.

Since the advent of computer-mediated communication (CMC) technologies, the landscape of education, especially in English Language Teaching and learning, has undergone significant transformations. Academic writing, a key skill in this context, has witnessed notable benefits from technological advancements, particularly in the contemporary era. One prominent technology reshaping the academic landscape is ChatGPT. While it offers abundant learning opportunities for second language learners and teachers, it also poses significant ethical challenges. This paper provides an overview of the opportunities and challenges presented by ChatGPT and other AI-based technologies concerning writing skills, specifically academic writing in English as a second language. The study includes a descriptive account of my interview with ChatGPT regarding the opportunities that it has presented and the challenges posed for L2 students and teachers. The interview results indicate that ChatGPT can be employed in various ways to enhance the second language writing process for both students and teachers, notwithstanding the latter's reservations about its ethical implications. In addition, the paper offers some practical activities that can be implemented in L2 academic writing classes.

This study aims to investigate students' self-regulation skills, confidence to learn online, and perception of satisfaction and usefulness of online classes in three learning environments that integrates ChatGPT. In this study, a quasi-experiential design was used to compare three online learning environments that integrate ChatGPT (independent, peer, and group). A total of 100 undergraduate students were randomly assigned to these three groups. Three questionaries' were used for data collection. The results showed that the self-regulation levels were high among the participants in these three online ChatGPT groups. However, learning in peer and group environments were more effective in developing self-regulation skills than learning independently. This research also found that the participants in the peer and group learning environments had high levels of confidence to learn online compared to the participants in the independent group. The results also showed that the participants in the peer learning group had the highest scores of perception of satisfaction and usefulness of online classes compared to the participants in the independent and group learning environments. The findings of this study support the notion that integrating ChatGPT within peer groups can enhance students' perception of satisfaction and usefulness of online classes. Educators should explore ways to leverage ChatGPT to facilitate meaningful interactions and collaboration among students, thereby increasing their satisfaction and engagement with online learning materials and activities.

Artificial intelligence (AI) has been evolving since the mid-twentieth-century when luminaries such as Alan Turing, Herbert Simon, and Marvin Minsky began developing rudimentary AI applications. For decades, AI programs remained pretty much in the realm of computer science and experimental game playing. This changed radically in the 2020s when commercial vendors such as OpenAI and Google developed generative AI programs (ChatGPT and Bard) using large language modelling (LLM). As a result, generative AI is now being considered for use in all walks of life, including education. In spring 2023, when ChatGPT burst into the public psyche, twenty-five education students in the author's graduate seminar were invited to participate in a qualitative study using ChatGPT as an essay-writing tool. Fifteen accepted the offer. The purpose in doing this was to give students in this seminar the opportunity to use ChatGPT in a supportive environment and to collect qualitative data via descriptive written evaluation and a focus group to comment on their experiences using ChatGPT. All of these students have master's degrees in education and experience as teachers in New York City schools. Their training and experience give them keen insights into pedagogical practice making them ideally suited to evaluate ChatGPT as an essay-writing tool. This article reports on the results of this study. Key findings indicate that the vast majority of these students had a good experience in using ChatGPT for their essays. Many, especially the secondary school teachers, would use it in their own classes.

This paper shares the reflections of a small group of graduate students and faculty members in the United Arab Emirates (UAE) on the challenges and affordances of using large language model (LLM) tools to assist with academic writing in an English Medium Education (EME) context. The influence of interpretive grounded theory afforded the authors the opportunity to engage with emerging data from a focus group interview. Ethical issues including academic integrity and maturity formed a major theme of this study, as well as the future-thinking affordances of LLMs in facilitating and democratizing academic writing for all, including those in EME programs. Considering that LLMs are here to stay and will be used by students and faculty alike, the authors consider that the nature of assessment is likely to change and indeed will require higher education institutions to consider the types of assessments in place, with a view to potentially modifying them in light of these technological advances. We recommend the use of deeply personalized, critically reflective writing assignments where students demonstrate how the topic has meaning in their individual context and personal life story, that will ensure academic integrity and maturity while still embracing these new technologies to widen the scope of academic writing.

Educators are faced with the sudden infiltration of AI, including artificially intelligent tools that generate content far more sophisticated than any prior technological advancement. In this study, the researchers investigated the use of ChatGPT (currently the most used generative AI tool) as a means of learning Calculus. The study examined student perceptions toward the use of ChatGPT in their learning of mathematical concepts in Calculus and their perceptions of the advantages and disadvantages of its use in the classroom. The participants in this study were 64 undergraduate students enrolled in a Calculus course. Participants completed a 5-point Likert-type questionnaire with two open-ended questions. The collected data were analyzed both quantitatively and qualitatively. Results of the study indicated that most students supported the use of ChatGPT in learning Calculus; they believed that ChatGPT had a positive impact on their learning, and even increased their classroom participation and engagement.

Adapting the Technology Acceptance Model (TAM) framework, this study investigates English teachers' perspectives on the intention to adopt and integrate ChatGPT in their classrooms. This study utilizes quantitative cross-sectional research with 114 respondents answering the online questionnaire. The Structural Equation Modeling (SEM) statistical analysis through SmartPLS 3.0 was employed to analyze the collected data. The result indicates that the proposed TAM model in this study can predict ChatGPT acceptance in English language teaching. Additionally, the structural model showed that perceived usefulness, ease of use, and attitude toward using significantly and positively influenced behavioral intention. Furthermore, attitude toward using and behavioral intention significantly and positively impacted actual system use. Teachers' perspectives on ChatGPT uptake and integration into English language learning are critical to technological innovation. This paper could assist teachers in Indonesia and comparable regions in understanding and adopting ChatGPT in English language teaching.

Artificial Intelligence (AI) has relatively become a part of our lives in many fields including education. As a recent AI tool generated by OpenAI, ChatGPT offers numerous opportunities and challenges for language learners and teachers. Therefore, the purpose of this study was to investigate the experiences of language learners and teachers in the use of ChatGPT during the language learning and teaching process. Phenomenological design, which is a type of qualitative research, was used in this study. Participants in the study were 8 English language learners with a background in English language learning and 3 English Language teachers with teaching experience at different levels. The participants were voluntarily selected through a purposive sampling and the interview technique was used as the data collection instrument. The findings of the study revealed that ChatGPT and AI were considered to be useful tools for language learning and teaching, although they presented some challenges that can be overcome with the advancement of technology. It is believed that students and teachers will be more involved in ChatGPT and AI in the future with its introduction into the language teaching curriculum, pre-service and in-service teachers' curriculum and the improvement of teachers' technological and pedagogical content knowledge.

In November 2022, ChatGPT, an Artificial Intelligence (AI) large language model (LLM) capable of generating human-like responses, was launched. ChatGPT has a variety of promising applications in education, such as using it as thought-partner in generating curricular resources. However, scholars also recognize that the use of ChatGPT raises concerns, such as outputs that are inaccurate, nonsensical, or vague. We, two mathematics teacher educators, engaged in a collaborative self-study using qualitative descriptive approaches to investigate the procedures, concepts, and cognitive demand of ChatGPT-generated mathematical tasks focused on fraction multiplication using the area model approach. We found that the ChatGPT-generated tasks were mostly procedural and not cognitively demanding. Moreover, despite ten variations of input prompts, ChatGPT did not produce any tasks that used the area model approach for fraction multiplication. Rather, it generated tasks focused on procedural approaches. Alarmingly, some tasks were conceptually and/or procedurally inaccurate and vague. We suggest that educators cannot fully rely on ChatGPT to generate cognitively demanding fraction multiplication tasks using the area model. We offer recommendations for educators' strategic use of ChatGPT to generate cognitively demanding mathematical tasks.

ChatGPT, an AI-powered service known for its effective delivery of information and solutions, has the potential to transform education, scientific problem-solving, and student learning. However, to fully harness its advantages, understanding the pedagogical approach needed is essential. This study explores teachers' awareness of ChatGPT and the inquiry-based learning (IBL) 5E model, examines ChatGPT's effective use within IBL, and investigates teachers' perceptions and experiences when integrating ChatGPT into the IBL framework. Employing an exploratory qualitative approach, this research gains insight into teachers' perspectives on ChatGPT's integration into IBL. The study involves two distinct focus groups comprising Junior Secondary School (JSS) and Senior Secondary School (SSS) science teachers in Nigeria. The findings highlight that while some teachers have actively integrated ChatGPT into the IBL 5E model and are already experiencing its benefits, others are at varying stages of awareness and adoption. The interest and curiosity expressed by some teachers suggest a potential for broader adoption as educators become more familiar with ChatGPT's capabilities within the context of IBL. This aligns with the idea that technology integration often involves a phased approach, with early adopters paving the way for broader usage.

This exploratory study focuses on the use of ChatGPT, a generative artificial intelligence (GAI) tool, by undergraduate engineering students in lab report writing in the major. Literature addressing the impact of ChatGPT and AI on student writing suggests that such technologies can both support and limit students' composing and learning processes. Acknowledging the history of writing with technologies and writing as technology, the development of GAI warrants attention to pedagogical and ethical implications in writing-intensive engineering classes. This pilot study investigates how the use of ChatGPT impacts students' lab writing outcomes in terms of rhetorical knowledge, critical thinking and composing, knowledge of conventions, and writing processes. A group of undergraduate volunteers (n = 7) used ChatGPT to revise their original engineering lab reports written without using ChatGPT. A comparative study was conducted between original lab report samples and revisions by directly assessing students' lab reports in gateway engineering lab courses. A focus group was conducted to learn their experiences and perspectives on ChatGPT in the context of engineering lab report writing. Implementing ChatGPT in the revision writing process could result in improving engineering students' lab report quality due to students' enhanced lab report genre understanding. At the same time, the use of ChatGPT also leads students to provide false claims, incorrect lab procedures, or extremely broad statements, which are not valued in the engineering lab report genre.

The emergence of ChatGPT, an AI-powered language model, has sparked numerous debates and discussions. In educational research, scholars have raised significant questions regarding the potential, limitations, and ethical concerns around the use of this technology. While research on the application and implications of ChatGPT in academic settings exists, analysis of the perspectives of high-school students are limited. In this study, we use qualitative content analysis to explore the perspectives of high-school students regarding the integration or ban of ChatGPT in their schools through the lens of the Technology Acceptance Model (TAM2). Data was sourced from students' comments to a New York Times Learning Network article. Findings revealed that students' perceptions about integrating or banning ChatGPT in schools are influenced by their assessments of the technology's usefulness, personal experiences, societal technology trends, and ethical considerations. Our findings suggest that student perspectives in this study align with those of educators and policymakers while also possessing unique perspectives that cater to their specific needs and experiences. Implications emphasize the significance of an inclusive decision-making process around the integration of AI schools in educational contexts, including students alongside other stakeholders.

This paper provides a thorough examination of the role of Artificial Intelligence (AI), particularly ChatGPT and other AI language models, in the realm of education. Drawing insights from existing literature and a novel study on educator perspectives, the paper delves into the potential advantages, ethical dilemmas, and factors shaping educators' attitudes towards AI integration in education. AI language models have the potential to revolutionize educational content creation, personalize learning experiences, and streamline assessment and feedback processes. These capabilities hold the potential to enhance teaching and learning outcomes while catering to the diverse needs of students. However, ethical concerns loom large in the adoption of AI in education. Bias in generated content is a chief concern, as it can perpetuate societal biases and lead to unfair treatment or the dissemination of inaccurate information. The solution lies in rigorous data curation to ensure equitable educational experiences for all students. Moreover, the potential for generating inappropriate or misleading content poses a significant ethical challenge, impacting students' well-being, civic understanding, and social interactions. Safeguards must be implemented to detect and rectify biased or inappropriate content, fostering inclusive and unbiased learning environments. Transparency emerges as a crucial ethical consideration. The opacity of AI models like ChatGPT makes it difficult to comprehend their decision-making processes. Enhancing model interpretability and explainability is vital for accountability and addressing embedded ethical issues. Privacy concerns related to data collection and usage are emphasized in the literature. Clear policies and guidelines must govern data collection, use, and protection, ensuring data is solely employed for educational purposes and maintaining robust data security measures. Our study expands upon these insights by exploring socio-demographic factors, motivations, and social influences affecting educators' AI adoption in higher education. These findings inform institutions on tailoring AI integration strategies, emphasizing responsible usage through training, and assessing the impact on learning outcomes. As educational institutions increasingly embrace AI, including advanced models like GPT-4, a cautious and thoughtful approach is vital. Balancing potential benefits with ethical challenges ensures that AI enhances teaching and learning while upholding fairness, equity, and accountability. In summary, this paper illuminates the potential of AI in education, accentuates ethical concerns, and highlights the significance of understanding educators' perspectives. Collaboration between educators and policymakers is essential to navigate the complexities of AI integration, ensuring that education remains a realm of equitable, efficient, and accountable learning experiences.

There is a current debate about the extent to which ChatGPT, a natural language AI chatbot, can disrupt processes in higher education settings. The chatbot is capable of not only answering queries in a human-like way within seconds but can also provide long tracts of texts which can be in the form of essays, emails, and coding. In this study, in the context of higher education settings, by adopting an experimental design approach, we applied ChatGPT-3 to a traditional form of assessment to determine its capabilities and limitations. Specifically, we tested its ability to produce an essay on a topic of our choice, created a rubric, and assessed the produced work in accordance with the designed rubric. We then evaluated the chatbot's work by assessing ChatGPT's application of its rubric according to a modified version of Paul's (2005) Intellectual Standards rubric. Using Christensen et al.'s (2015) framework on disruptive innovations, our study found that ChatGPT was capable of completing the set tasks competently, quickly, and easily, like a "magic wand". However, our findings also challenge the extent to which all of the ChatGPT's demonstrated capabilities can disrupt this traditional form of assessment, given that there are aspects of its construction and evaluation that the technology is not yet able to replicate as a human expert would. These limitations of the chatbot can provide us with an opportunity for addressing vulnerabilities in traditional forms of assessment in higher education that are subject to academic integrity issues posed by this form of AI. We conclude the article with implications for teachers and higher education institutions by urging them to reconsider and revisit their practices when it comes to assessment.

Artificial intelligence (AI) in higher education is a complex issue that can be discussed from many different perspectives. There is currently a great need for ethical discussions about the use of AI in universities. For example, educational researchers and teachers are already talking a lot about fairness, accountability, transparency, bias, autonomy, agency and inclusion of AI applications, and discussing these in terms of concrete teaching-learning settings. However, less explored are the implications of AI-enhanced teaching and learning in relation to fundamental educational ideals and goals. The article takes this research desideratum as a starting point by relating the use of AI in universities to Kant's reflections on enlightenment. The aim of this article is to theoretically analyse the compatibility of various AI tools with the ideal of maturity on an educational philosophical level and to formulate recommendations for action based on the results. Through a comprehensive literature review, the article analyses the impact of intelligent tutoring systems, ChatGPT and AI-supported research tools on students' maturity and discusses both opportunities and challenges for higher education. The theoretical analysis shows that intelligent tutoring systems and ChatGPT threaten student maturity, while AI-supported research tools can have a positive effect. In addition, the analysis provides several recommendations that can help to minimise the risks of AI applications in terms of student maturity. The educational principle of research-based learning is of particular importance in this context, illustrating how students can learn to use AI tools responsibly and maturely. In this sense, the paper presents a theoretical study that fundamentally reflects on the maturity ofstudentsin the age of AI and thus both encourages teachers in the field of e-teaching to critically reflect on AI-based tools and provides a basis for further empirical research.

This study explores the transformative potential of Generative AI (GenAI) and ChatBots in educational interaction, communication, and the broader implications of human-GenAI collaboration. By examining the related literature through data mining and analytical methods, the paper identifies three main research themes: the revolutionary role of GenAI-powered ChatBots in educational interactions, their capability to enrich social learning, and their dual role as both support and assistance within educational settings. This research further highlights the impact of human-GenAI interaction in education from social, psychological, and cultural perspectives, focusing on social presence as a fundamental component of the teaching and learning process. It discusses the integration of GenAI and ChatBots into education and considers whether this marks the dawn of an algorithmic renaissance that elevates educational experiences or an apocalypse that threatens the very essence of human learning and interaction.

Evaluation is an essential component of the learning process when discerning learning situations. Assessing natural language responses, like short answers, takes time and effort. Artificial intelligence and natural language processing advancements have led to more studies on automatically grading short answers. In this review, we systematically analyze short-answer evaluation studies. We present the development of the field in terms of scientific production features, datasets, and automatic evaluation features. The field has developed with pioneering studies in the US. Researchers generally conduct applications with English datasets. There has been a significant increase in research in recent years with large language models that support many different languages. These models have applications that achieve accuracy close to that of human evaluators. In addition, deep learning models do not require traditional approaches' detailed preprocessing and feature engineering processes. The dataset size trend is 1000 and above regarding the number of responses. It was observed that metrics such as accuracy, precision, and F1 score were used in performance determination. It is seen that the majority of the studies focus on scoring or rating. In this context, there needs to be more literature on the context of evaluation system applications that can provide descriptive and formative feedback. In addition, the developed assessment systems must be actively used in learning environments.

This study aimed at examining the performance of generative artificial intelligence to extract argumentation elements from text. Thus, the researchers developed a web-based framework to provide automated assessment and feedback relying on a large language model, ChatGPT. The results produced by ChatGPT were compared to human experts across scientific and non-scientific contexts. The findings revealed marked discrepancies in the performance of AI for extracting argument components, with a significant variance between issues of a scientific nature and those that are not. Higher accuracy was noted in identifying claims, data, and qualifiers, as opposed to rebuttals, backing, and warrants. The study illuminated AI's promise for educational applications but also its shortcomings, such as the increased frequency of erroneous element identification when accuracy was low. This highlights the essential need for more in-depth comparative research on models and the further development of AI to enhance its role in supporting argumentation training.

The aim of the research is to investigate the academic achievement of ChatGPT, an artificial intelligence based chatbot, in a national mathematics exam. For this purpose, 3.5 and 4 versions of ChatGPT were asked mathematics questions in a national exam. The method of the research is a case study. In the research, 3.5 and 4 versions of ChatGPT were used as data collection tools. The answers given by both versions of ChatGPT were analyzed separately by three researchers. As a result of the analysis of the data, it was found that ChatGPT-4 was more successful in the exam compared to ChatGPT-3,5 version, was better at understanding the questions asked, understood the instructions better and included more details in the question solution, and at the same time, both versions made common and different mistakes. According to the findings of the study, it was concluded that ChatGPT sometimes worked very well, sometimes only worked well and sometimes failed. In the light of the findings of the study, it can be suggested to use ChatGPT versions in mathematics education to obtain basic information and to get supervised help.

This study explores Arab university faculty's views on fully AI-generated assignments and research papers submitted by students, what reasons they give for their stance and how they react in this case. Surveys with a sample of 45 Arab instructors revealed that 98% do not accept AI-generated assignments and research papers from students at all. They gave numerous reasons for their position. If students submit AI-generated assignments or research papers, they would ask them to re-write them. The study recommends raising students' awareness of university policies regarding AI-generated content and introducing faculty and students to AI plagiarism detection tools. Faculty views and recommendations are reported in detail.

This study explores how discussing metaphors for AI can help build awareness of the frames that shape our understanding of AI systems, particularly large language models (LLMs) like ChatGPT. Given the pressing need to teach "critical AI literacy", discussion of metaphor provides an opportunity for inquiry and dialogue with space for nuance, playfulness, and critique. Using a collaborative autoethnographic methodology, we analyzed metaphors from a range of sources, and reflected on them individually according to seven questions, then met and discussed our interpretations. We then analyzed how our reflections contributed to the three kinds of literacies delineated in Selber's multiliteracies framework: functional, critical and rhetorical. These allowed us to analyze questions of ethics, equity, and accessibility in relation to AI. We explored each metaphor along the dimension of whether or not it was promoting anthropomorphizing, and to what extent such metaphors imply that AI is sentient. Our findings highlight the role of metaphor reflection in fostering a nuanced understanding of AI, suggesting that our collaborative autoethnographic approach as well as the heuristic model of plotting AI metaphors on dimensions of anthropomorphism and multiliteracies, might be useful for educators and researchers in the pursuit of advancing critical AI literacy.

This study compared the problem-solving abilities of ChatGPT and 58 pre-service teachers (PSTs) in solving a mathematical word problem using various strategies. PSTs were asked to solve a problem individually. Data was collected from PSTs' submitted assignments, and their problem-solving strategies were analyzed. ChatGPT was also given the same problem to solve with various prompts, and the correctness of its solutions and problem-solving strategies were assessed alongside those of PSTs. The results indicated that PSTs used diverse strategies and achieved accurate solutions, but not always relevant strategies to children's level of understanding. ChatGPT employed similar strategies to PSTs but mostly produced incorrect solutions, and its performance needed to be contextualized in the primary school context. The study highlights the potential of ChatGPT in mathematics teaching and informs teacher education programs about the possibility of using it in teaching problem-solving strategies.

In this research, we aimed to determine whether students' math achievements improved using ChatGPT, one of the chatbot tools, to prepare lesson plans in primary school math courses. The research was conducted with a pretest-posttest control group experimental design. The study comprises 39 third-grade students (experimental group = 24, control group = 15). The implementation process lasted five weeks and 25 lesson hours. In the experimental group, lessons were taught according to plans prepared using ChatGPT, while in the control group, existing lesson plans were used. Students' academic achievement was measured with a multiple-choice achievement test of 25 questions with two separate questions for each learning objective. According to the results, students' academic achievement increased significantly (d = 1.268) in math lessons taught according to lesson plans prepared using the ChatGPT. Although there was a difference between the posttest scores of the experimental group and the control group in favor of the experimental group, it was determined that this difference was not significant. These results show that teaching primary school math according to lesson plans prepared using ChatGPT is effective in academic achievement. Teachers should consider ChatGPT and their plans, combining them and benefiting from both in the implementation process.

From personalized advertising to economic forecasting, artificial intelligence (AI) is becoming an increasingly important element of our daily lives. These advancements raise concerns regarding the transhumanist perspective and associated discussions in the context of technology-human interaction, as well as the influence of artificial intelligence (AI) on education and critical pedagogy. In this regard, the purpose of this research paper was to investigate the intersection of AI and critical pedagogy by critically assessing the potential of AI to promote or hamper critical pedagogical practices in the context of transhumanism. The article provides an overview of the concepts of transhumanism, artificial intelligence, and critical pedagogy. In order to seek answers to research questions, qualitative research design was adopted, and GPT-3 was used as a data collection resource. Noteworthy findings include the similarity of the dialogue with the GPT-3 davinci model to a conversation between two human beings, as well as its difficulty in understanding some of the questions presented from a critical pedagogy perspective. GPT-3 draws attention to the importance of the relationship between humans in education and emphasizes that AI applications can be an opportunity to ensure equality in education. The research provides suggestions indicating the relationship between AI applications and critical pedagogy.

ChatGPT has become a prominent tool for fostering personalized and interactive learning with the advancements in AI technology. This study analyzes 212 academic research articles indexed in the Scopus database as of July 2023. It maps the trajectory of educational studies on ChatGPT, identifying primary themes, influential authors, and contributing institutions. By employing bibliometric indicators and network analysis, the study explores collaboration patterns, citation trends, and the evolution of research interests. The findings show the exponential growth of interest in leveraging ChatGPT for educational purposes and provide insights into the specific educational domains and contexts that have garnered the most attention. Furthermore, the study reveals the collaborative dynamics and intellectual foundations shaping the field by examining co-authorship and citation networks. This bibliometric analysis contributes to a comprehensive understanding of the current state of ChatGPT research in education, offering researchers and practitioners valuable insights into evolving trends and potential future directions for this innovative aspect of AI and learning.

ChatGPT is taking the world and the education sector by storm. Many educators are still hesitant to integrate it within their curricula, owing to the limited practical and theoretical guidance on its applications, despite early conceptual studies advocating for its potential benefits. This pedagogical innovation applied an effectual logic to implement ChatGPT for a founding team activity within an entrepreneurship course. Composing a founding team is an inundating task in venture creation, with long-lasting consequences. So far, there is yet to be an ideal approach proposed in literature or observed in real-life for doing it. In this pedagogical innovation, three student teams with varying business ideas prompted ChatGPT using different keywords and levels of details, to get recommendations on essential team members, their roles and equity split. Each team presented their findings, and then the classroom engaged in a collective discussion. The students were surveyed afterwards to assess the reception and effectiveness of the intervention. Their feedback showed an overwhelming favoritism of ChatGPT, as a convenient and resourceful learning tool. The study establishes the potential value of ChatGPT as a heutagogical tool that supports student-centric entrepreneurial learning across educational institutions and the entrepreneurship ecosystem that extends to the venture creation process.

This study investigates the perceptions of English language teachers regarding the use of ChatGPT in English Language Teaching (ELT). The study aims to fill the research gap by exploring teachers' perspectives on the integration of ChatGPT as an instructional tool and its implications for ELT practices. Using a mixed methods approach, the study employed focus group discussions and an online survey to gather insights from a sample of 115 English language teachers in Metro Manila, Philippines. Findings revealed English language teachers' perspectives on the use of ChatGPT in ELT including potential use of ChatGPT in ELT (e.g., integration for vocabulary expansion and writing practice and enhancing language fluency and communication), potential benefits of ChatGPT to English languge learners (e.g., translation and language comprehension support, conversational practice and language development, access to information and cultural understanding), and potential limitations of using ChatGPT in ELT (e.g., cheating and plagiarism, lack contextual understanding and nuance, reliability and accuracy of information). These findings shed light on teachers' perceptions of ChatGPT as a language teaching tool including ChatGPT's integration into ELT, use of ChatGPT in writing activities, use of ChatGPT in improving language skills, and other benefits of using ChatGPT, including teachers' concerns regarding the authenticity of AI-generated content and the potential impact on language learning outcomes. The findings of this research contribute to the existing literature on the integration of AI technology in ELT and offer practical recommendations for educators seeking to leverage the potential of ChatGPT in language teaching. By giving voice to teachers' perspectives, this study underscores the importance of considering teachers' perceptions and experiences when incorporating emerging technologies like ChatGPT into the ELT classroom. Ultimately, this research aims to foster a deeper understanding of the complex dynamics between AI technology and language teaching, paving the way for informed decision-making and effective implementation in the field of ELT.

Artificial intelligence in education (AIEd) is a fast-growing field of research. In previous work, we described efforts to explore the possible futures of AIEd by identifying key variables and their future prospects. This paper re-examines our discussions on the governance of data and the role of students and teachers by considering the implications of (1) a recent case related to the General Data Protection Regulation (GDPR) and (2) the release of ChatGPT, a generative AI model capable to producing 'human-like' text. These events raise questions for the future of AIEd and the underlying function of assessment, and highlight the importance of active student participation in the integration of AI in education. [This article has been presented in the 5th International Open & Distance Learning Conference-IODL 2022.]

This study investigated the usage of conversational artificial intelligence (CAI) to support learners in foreign language classrooms. It employed Google Assistant and focused on the interactions between the teacher, learners, and CAI, as well as the teacher's collaboration with CAI. Using social network and content analyses of two 50-minute language classes and group interviews, this study revealed that the teacher and CAI played a significant role during classroom interactions. The teacher employed various talk moves to facilitate interactions between the students and CAI. There were several instances of collaboration between the teacher and CAI during classroom facilitation. This study highlights the implications of the collaboration between human teachers and CAI in classrooms for teaching foreign languages and suggests avenues for future research.

Differentiated instruction is much demanded yet quite challenging in face of the growing student diversity in today's K-12 classrooms. One major challenge is the provision of differentiated materials to students. Automated text simplification (ATS) tools fueled by natural language processing may serve as a useful assistant for teachers. However, little is known about teachers' contextualized use of ATS over time. This case study traced two teachers' use of ATS systems over a semester. Drawing upon three semi-structured interviews and teacher-generated materials with ATS, we identified an evolving pattern of teachers' engagement with ATS systems, a progression from a blind reliance on the tool to a more critical and coordinated use of the tool over time. We further revealed that teachers' evolving understanding of DI, positioning of the role of ATS systems and human instructors, and interpretation of DI need in specific teaching situations interplayed to shape their particular ways of engagement. Overall, this study contributes to the understanding of teachers' contextualized use of ATS technology for DI. By revealing the influencing factors, the findings hold significant pedagogical implications to inform the design of ATS tools and the creation of favorable conditions to maximize the potential of ATS tools for DI and language teaching and learning in general.

Many universities have, or are facing, the task of providing high quality essential customer services with fewer financial and human resources. The growing diversity of students, their needs and proficiencies, along with the increasing variety of university program offerings, make providing customized, ondemand, automated solutions crucial to delivering high quality customer service. In this paper, the authors describe the development of an artificial intelligence-backed chatbot to aid in answering student advisement questions. The main objective of the chatbot is to provide 24/7 supplemental program specific advising assistance to graduate computer science majors to lessen the advising load of university faculty. In this paper, the authors describe the development of a chatbot prototype using IBM Watson Assistant running on a specially designed website and Slack platform to address frequently asked questions of computer science graduate students. Results of a pilot study conducted on 99 graduate students indicate that the prototype is a positive step forward in making student advising accessible, usable, and scalable to a broader audience.

Technological advancements, particularly in the field of artificial intelligence (AI) have played an increasingly important role in transforming education. More recently, ground-breaking AI applications like ChatGPT have demonstrated the potential to bring radical changes to the educational landscape due to their capability to understand complex questions, generate plausible responses and human-like writing, and assist with the completion of complex tasks. However, ChatGPT has limitations in the quality of its output, such as the inclusion of inaccurate, fabricated and biased information and the lack of critical thinking and in-depth understanding. The combinations of these capabilities and limitations along with external factors (e.g., the growing demand for personalized learning support, the irresponsible and unethical use of AI) presents a range of opportunities and challenges to the potential use of ChatGPT in education. This paper presents a thorough SWOT (strength, weakness, opportunity, threat) analysis of ChatGPT, based on which we propose how ChatGPT can be properly integrated into teaching and learning practice to harness its potential in education.

Debate is a universally acknowledged competency for its vital role in fostering essential skills such as analytical reasoning, eloquent communication, and persuasive argument construction. This is relevant in both formal educational settings like classrooms and informal venues such as after-school clubs. Traditional debate training methods often face challenges in facilitating personalized learning, primarily due to the difficulty of securing a debate partner. However, the emerging field of generative AI offers a promising alternative. This study evaluates the effectiveness of DEBO, a debate education application that utilizes ChatGPT, an advanced language model by OpenAI. Focusing on university students actively involved in a debate club, six volunteers tested DEBO and participated in interviews to provide insights. The findings reveal that DEBO notably enhances divergent thinking and features a comprehensive analytics dashboard for in-depth performance analysis. However, there are few limitations including occasional shortcomings in debate quality, minor inaccuracies, and the need for faster response times. The study underscores the transformative potential of advanced language models like ChatGPT in reshaping debate education, while also identifying areas for further improvement.

This paper describes the results of an archival desk-study that analyzed worksheets produced by four students using ChatGPT as a coach. ChatGPT is a Generative Pre-Trained Large Language model that can write comprehensively in various languages and styles. It was discovered that it could pass university level physics exams and perform at the level of a third-year medical student. Fourth-year students in Information Technology are required to produce a 3000-to-5000-word research report as part of the requirements for graduation, and their first meeting of the year consists of a workshop following the GROW (Goal, Reality, Opportunities, Will) coaching process. Logistical considerations in this predominantly e-learning based course prevented such teamwork. The two-month-old ChatGPT, however, presented an opportunity to determine the extent to which a chatbot could be used as a peer coach. This paper reports on the outcome of an exercise that was given to students as an introduction to their research methodology course. It was found that well-designed prompts were essential and that students should be encouraged to reflect on their interaction with artificial intelligence. Three clear issues emerged from the study: the quality of feedback given by the chatbot, the value of the prompt, and the importance of student reflection. The chatbot, ChatGPT, displays the traditional computer characteristic of garbage in, garbage out and gives the feedback it is programmed to give. The dialogue shows how a student can build up mutual rapport with the chatbot when they adapt their responses to the feedback provided. The critical reflection in shows that it is still the user who should oversee the process and evaluate the feedback. It is recommended that novice research students be given some training in reacting to feedback, developing useful prompts, and engaging in meaningful reflection. Future research would include developing a reflective coach.

The proliferation of large language models represents a paradigm shift in the landscape of automated essay scoring (AES) systems, fundamentally elevating their accuracy and efficacy. This study presents an extensive examination of large language models, with a particular emphasis on the transformative influence of transformer-based models, such as BERT, mBERT, LaBSE, and GPT, in augmenting the accuracy of multilingual AES systems. The exploration of these advancements within the context of the Turkish language serves as a compelling illustration of the potential for harnessing large language models to elevate AES performance in in low-resource linguistic environments. Our study provides valuable insights for the ongoing discourse on the intersection of artificial intelligence and educational assessment.

While ChatGPT has recently become very popular, AI has a long history and philosophy. This paper intends to explore the promises and pitfalls of the Generative Pre-trained Transformer (GPT) AI and potentially future technologies by adopting a speculative methodology. Speculative future narratives with a specific focus on educational contexts are provided in an attempt to identify emerging themes and discuss their implications for education in the 21st century. Affordances of (using) AI in Education (AIEd) and possible adverse effects are identified and discussed which emerge from the narratives. It is argued that now is the best of times to define human vs AI contribution to education because AI can accomplish more and more educational activities that used to be the prerogative of human educators. Therefore, it is imperative to rethink the respective roles of technology and human educators in education with a future-oriented mindset.

Generative AI, specifically ChatGPT, represents a significant technological advancement in natural language processing (NLP) large language models (LLM) with far-reaching implications in many dimensions of our lives, including education. This paper discusses the prospects of generative AI in utilizing language and its potential role as a conversational agent within the educational realm. Emulating the most advanced human technology, language, generative AI's success relies on understanding and generating human-like text. However, its comprehension is solely based on patterns and structures it learns from its training data. With the advent of AI-driven conversational agents, prompt engineering emerges as a vital form of digital literacy. The convergence of general and educational technologies necessitates preparedness for a future dominated by AI. This paper highlights the importance of vigilance and prudence in harnessing the potential of generative AI technologies, emphasizing the responsibility of humans, as creators, in mitigating any potential mishaps. In conclusion, this paper suggests that preparedness for a future dominated by AI is essential, as generative AI technologies have the potential to profoundly impact teaching and learning methods, and necessitate new ways of thinking.

An educational customer relationship management (CRM) Chatbot is a learner support service automation tool that enhances the human computer interaction and user experience in higher education institutions through effective online conversation and information exchange. The machine with embedded knowledge is trained to identify the sentences and taking a right decision itself in response to answer a question. An E-learning platform is a web-based platform designed to streamline the administration, delivery of online educational courses and training programs. It serves as a centralized hub where educators, learners, and administrators can interact, collaborate, and access learning resources anytime, anywhere. The research objective is to design and build a E-Learning Management System with CRM chatbot for effective user interaction. A website is developed for managing course materials in the form of videos, flip-books and quiz using HTML, CSS, JavaScript, PHP, and MySQL. Students can access the course materials from anywhere and anytime. The queries may arise from user at any moment. In this case, the chat bot will primarily assist students and will respond to queries by guiding them through the functionalities and features of this application at any time. Chatbot will enhance customer service. This proposed CRM-chatbot uses natural language processing (NLP) and Feed forward Neural Network model to understand students questions and automate responses to them.

This research is part of the Artificial Intelligence Virtual Trainer (AI-VT) project which aims to create a system that can identify the user's skills from a text by means of machine learning. AI-VT is a case-based reasoning learning support system can generate customized exercise lists that are specially adapted to user needs. To attain this outcome, the relevance of the first proposed exercise must be optimized to assist the system in creating personalized user profiles. To solve this problem, this project was designed to include a preliminary testing phase. As a generic tool, AI-VT was designed to be adapted to any field of learning. The most recent application of AI-VT was in the field of computer science specifically in the context of the fundamentals of algorithmic learning. AI-VT can and will also be useful in other disciplines. Developed in Python with the Keras API and the Tensorflow framework, this artificial intelligence-based tool encompasses a supervised learning environment, multi-label text classification techniques and deep neural networks. This paper presents and compares the performance levels of the different models tested on two different data sets in the context of computer programming and algorithms.

With recent public access to large language models via chatbots, the field of language education is seeing unprecedented levels of interest in how AI will affect language learning and teaching. As attention is primarily focused on student misuse of the technology, the potential affordances of generative AI tools may often be overlooked. In this paper we highlight potential affordances of AI generative tools, such as ChatGPT, for creating language learning and teaching materials and assessments. We offer suggestions on crafting prompts as well as provide example prompts and the materials and assessments generated by ChatGPT in response. We also present a framework for evaluation that combines both of Hubbard's (1988) framework for CALL evaluation and The Douglas Fir Group's (2016) transdisciplinary framework that may assist language educators in determining when it is appropriate to leverage generative AI tools. We then briefly illustrate how the framework has been used in our own evaluations. Finally, we suggest language educators consider how the concerns and opinions of using AI-based tools held by individuals and institutions within their own micro, meso, and macro sociocultural levels align or conflict with those of the individuals and institutions of their students' micro, meso, and macro sociocultural levels.

Background/purpose: ChatGPT is an artificial intelligence program released in November 2022, but even now, many studies have expressed excitement or concern about its introduction into academia and education. While there are many questions to be asked, the current study reviews the literature in order to reveal the potential effects of ChatGPT on education as a whole. The potential implications, possibilities, and concerns about the use of ChatGPT in education are disclosed as mentioned in the literature. Materials/methods: The data of the study were collected and then subjected to a systematic review. Research findings were analyzed according to the themes and categories identified. Results: The results of this research were examined under themes according to the positive and negative aspects of ChatGPT. The positive categories and sub-categories of ChatGPT's integration into education were determined, and the relationship between education and artificial intelligence determined. Similarly, the negative category highlighted the potential negative impact of artificial intelligence on educational processes. Conclusion: The reviewed research evaluated and discussed the impact of AI on education and training processes. In conclusion, this review revealed the critical applications of ChatGPT for educational settings and the potential negative impact of its application. The findings established how ChatGPT and its derivatives would create a new paradigm in education as a whole.