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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.

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.

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.

This paper explores recent advancements and implications of artificial intelligence (AI) technology, with a specific focus on Large Language Models (LLMs) like ChatGPT 3.5, within the realm of higher education. Through a comprehensive review of the academic literature, this paper highlights the unprecedented growth of these models and their widereaching impact across various sectors. The discussion sheds light on the complex issues and potential benefits presented by LLMs, providing a comprehensive overview of the field's current state. In the context of higher education, the paper explores the challenges and opportunities posed by LLMs. These include issues related to educational assessment, potential threats to academic integrity, privacy concerns, the propagation of misinformation, Equity, Diversity, and Inclusion (EDI) aspects, copyright concerns and inherent biases within the models. While these challenges are multifaceted and significant, the paper emphasises the availability of strategies to address them effectively and facilitate the successful adoption of LLMs in educational settings. Furthermore, the paper recognises the potential opportunities to transform higher education. It emphasises the need to update assessment policies, develop guidelines for staff and students, scaffold AI skills development, and find ways to leverage technology in the classroom. By proactively pursuing these steps, higher education institutions (HEIs) can harness the full potential of LLMs while managing their adoption responsibly. In conclusion, the paper urges HEIs to allocate appropriate resources to handle the adoption of LLMs effectively. This includes ensuring staff AI readiness and taking steps to modify their study programmes to align with the evolving educational landscape influenced by emerging technologies.

We propose a novel model, Wide & Deep Item Response Theory (Wide & Deep IRT), to predict the correctness of students' responses to questions using historical clickstream data. This model combines the strengths of conventional Item Response Theory (IRT) models and Wide & Deep Learning for Recommender Systems. By leveraging clickstream data, Wide & Deep IRT provides precise predictions of answer correctness while enabling the exploration of behavioral patterns among different ability groups. Our experimental results based on a real-world dataset (EDM Cup 2023) demonstrate that Wide & Deep IRT outperforms conventional IRT models and state-of-the-art knowledge tracing models while maintaining the ease of interpretation associated with IRT models. Our model performed very well in the EDM Cup 2023 competition, placing second on the public leaderboard and third on the private leaderboard. Additionally, Wide & Deep IRT identifies distinct behavioral patterns across ability groups. In the EDMCup2023dataset, low-ability students were more likely to directly request an answer to a question before attempting to respond, which can negatively impact their learning outcomes and potentially indicates attempts to game the system. Lastly, the Wide & Deep IRT model consists of significantly fewer parameters compared to traditional IRT models and deep knowledge tracing models, making it easier to deploy in practice. The source code is available via Open Science Framework.

When studying grammar, students must not only focus on its structure but also on its form. Form-focused activities are integral to this process, requiring students to identify and manipulate language forms. A well-established technique for facilitating language acquisition is the consciousness-raising task (CR), which aims to heighten learners' awareness of language form. By prioritizing the language input, students can cultivate a more precise comprehension of grammar structures, thereby enhancing their own language proficiency. This approach entails various strategies, such as inferring grammatical rules from examples, comparing different forms of expression, and examining differences between a learner's usage of a grammar item and that of native speakers. However, designing effective CR tasks is cognitively demanding, time-intensive, and laborious for teachers, as it entails accommodating numerous requirements, including the definition of clear objectives, task relevance, and task engagement. To address these challenges, it is worth utilizing ChatGPT which is an advanced conversational AI system with the capability to process and generate various modalities of language. It has access to extensive databases and can produce written content that is frequently indistinguishable from human-written text. Accordingly, ChatGPT can be utilized to generate CR tasks or materials that may be applied in class. The present study endeavors to offer a range of CR tasks for grammar teaching that have been generated by ChatGPT. The tasks include identification tasks, text correction tasks, word choice tasks, and others.

The Chat Generative Pretrained Transformer (ChatGPT) is a state-of-the-art artificial intelligence (AI) language model developed by OpenAI. It employs advanced deep-learning algorithms to generate text that mimics human language. ChatGPT, launched on November 30, 2022, has rapidly gained widespread recognition. Its influence on the future of technology and artificial intelligence is anticipated to grow even more, considering it has achieved such significance in less than two years since its release. This study investigated the potential of ChatGPT as a tool for enhancing the learning of Maltese for adult international students. This study involved 41 participants who embarked on a journey of exploration and employed ChatGPT for two weeks to support their Maltese learning. The study evaluated the effectiveness of ChatGPT through surveys and focus group discussions and revealed that while ChatGPT was convenient and accessible, its ability to provide accurate responses to students' questions and support Maltese grammar, vocabulary, and conversational practice was limited. The participants expressed frustration with the ChatGPT's limitations in understanding and responding to the Maltese language. This study emphasizes the need to fully unleash the potential of ChatGPT by improving its training on the Maltese language and collaborating with Maltese language and AI experts to better support Maltese language learning. These findings have important implications for the development of ChatGPT for less widely spoken languages such as Maltese.

ChatGPT, a generative AI program developed by OpenAI, has raised serious questions about the future of education since its launch in November 2022. This paper argues that ChatGPT has the potential to redefine existing educational theories and the role of teachers in language education. Specifically, the paper examines ChatGPT's impact on language education and suggests ways to incorporate it into teaching practice. Since people have been proclaiming that AI would replace teachers since the 1970s, the history of AI in education is relevant to this paper. Therefore, the paper first discusses the history of AI in education to provide context and highlight how ChatGPT fits into this larger conversation. Afterwards, the paper then explores how ChatGPT might redefine existing learning theories such as Constructivism and Self-Determination Theory using the AIED framework. ChatGPT has the potential to provide learners with personalized and adaptive learning experiences that align with these learning theories. For this reason, the paper will investigate how ChatGPT may impact the role of learners through the lens of Learner Autonomy before looking at how it might also redefine the role of the teacher in the classrooms of the near future. While ChatGPT has the potential to automate certain aspects of language education, the role of the teacher as a mentor and guide in the learning process is still essential. Finally, the paper offers suggestions for how educators can effectively incorporate generative AI programs like ChatGPT into their teaching practice and curriculum. The paper concludes by emphasizing the importance of approaching the integration of AI in education with caution and a critical perspective.

The National Board of Certification and Recertification for Nurse Anesthetists (NBCRNA) conducted a one-year research study comparing performance on the traditional continued professional certification assessment, administered at a test center or online with remote proctoring, to a longitudinal assessment that required answering quarterly questions online on demand. A randomized controlled trial of 1,000 certified registered nurse anesthetists (500 randomly assigned to the traditional assessment group and longitudinal assessment group) aimed to 1) compare assessment performance between groups, 2) compare perceptions and user experience between groups; and 3) describe participant feedback about usability of the longitudinal assessment platform. The mean scaled score for the traditional assessment group exceeded that of the longitudinal assessment group when scoring the first responses; however, upon scoring the longitudinal assessment group's most recent responses on repeat questions previously answered incorrectly, the mean scaled score was higher than the traditional assessment group. Both groups were satisfied with their experience, with slightly higher feedback ratings for the longitudinal assessment group who also found the platform easy to use and navigate. Overall results suggest the longitudinal assessment is a feasible, acceptable, and usable format to assess specialized knowledge for continued healthcare professional certification.

Artificial intelligence (AI) first made its entry into higher education in the form of paraphrasing tools. These tools were used to take passages that were copied from sources, and through various methods, disguised the original text to avoid academic integrity violations. At first, these tools were not very good and produced nearly incomprehensible output. However, through the use of generative artificial intelligence and natural language processing, the current engines supporting these tools have become better and more efficient at producing quality output. Recently, the artificial intelligence research company, OpenAI, developed a groundbreaking artificial intelligence engine to drive a conversational chat frontend application called ChatGPT. Backed by an expansive knowledge base that could rival any university library in volume, this AI-driven conversational application can produce well-written, seemingly academic, responses to questions. This paper examines text-based artificial intelligence tools that can be used for both ethical and unethical purposes and what simple methods can be used to recognize AI-generated output whose use may indicate plagiarism.

This study explores the perceptions of second language (L2) educators on the surge of Large Language Models (LLMs) like ChatGPT, and their potential impact on language education. We surveyed over 100 L2 instructors, asking questions about their ideas for AI-proofing assignments, their policies, and their perceptions of how this tool will impact the profession. Data was collected through an anonymous survey and analyzed with a mixed-method approach through a constructivist lens. The results show mixed feeling: ranging from excitement for the pedagogical potential of ChatGPT to fear for potential academic dishonesty and job security in some. The results analysis provides insight into L2 educators use and policies of ChatGPT. The quantitative data highlighted that instructors' levels of excitement or concern about the adoption of ChatGPT in language education correlate with their personal experience with the tool, in line with Bax's (2003) normalization framework. Those with prior interaction with ChatGPT showed more enthusiasm for its educational potential than those without. Interestingly, this study found no significant difference in attitudes across different age groups or years of teaching experience. The qualitative data show that L2 educators anticipate wide use of ChatGPT in their students' assignments, yet a large majority (90%) is confident in their ability to identify students use of Chat GPT and Google Translate in their work. This study also reviews the current use and policies regarding MT and ChatGPT, highlighting a significant number of instructors prohibiting their uses. The results also highlight different ways instructors have been AI proofing their assignments and how they are currently using ChatGPT in their professions. In conclusion, this study advocates for a proactive use of these tools emphasizing the importance of adopting innovative pedagogies, a student-centered classroom approach, and certain ethical considerations.

Artificial Intelligence (AI), as an innovation in technology, has greatly affected human life. AI applications such as ChatGPT have been used in different fields, particularly education. However, the use of AI applications to enhance undergraduate students' academic emotions and test anxiety has not been appropriately investigated. This study addresses the effects of undergraduate students' test anxiety and academic emotions. A total of 160 undergraduate students majoring in different fields of study were selected through convenience sampling and divided into control and experimental groups. Both groups received test anxiety and academic emotions scales at the onset of the treatment. The students assigned to the experimental group were trained to use ChatGPT and monitored for learning and doing their assignments outside the classroom during the semester. The two groups received the scales at the end of the semester, which lasted 16 weeks. Independent samples t-tests were used for analyzing the data. Results revealed that using AI-empowered applications significantly reduced the students' test anxiety and negative academic emotions but enhanced their positive academic emotions. Students can use ChatGPT as an auxiliary instrument to overcome their negative emotions and enhance their educational attainment. Findings affect teachers, educational technologists, educational psychologists, and students.

In education, the integration of artificial intelligence (AI) has presented opportunities to transform the dynamics of online learning. This study investigated the impact of an AI-powered application, namely ChatGPT, on the autonomy of Saudi Arabian primary students participating in online classes. It also explored how the implementation of Chat GPT influenced Saudi Arabian primary students' autonomy. In this mixed-methods study, a quasi-experimental design assessed the impact of ChatGPT on learner autonomy among 250 Saudi Arabian primary students from six primary schools in Riyadh, Saudi Arabia. The quantitative analysis employed descriptive statistics and t-tests, while the qualitative data underwent interpretative phenomenological analysis. To ensure coding reliability, 20% of the codes were independently reviewed by an external coder, with a 94% inter-coder agreement coefficient reached through consensus. Findings revealed that ChatGPT significantly affected the participants' perceptions of autonomy and its different dimensions. Qualitative data showed that AI-powered applications contributed to the students' autonomy in 10 different ways. Participants also mentioned that AI-powered apps might have some negative consequences. This study has theoretical implications for redefining learner autonomy in the digital age and calls for the exploration of many facets of autonomy. Practical applications from this study include strategic integration of AI into online education, data security, and the need for orientation programs.

The rapid advancement of artificial intelligence (AI) in education underscores transformative prospects for open and distributed learning, encompassing distance, hybrid, and blended learning environments. This qualitative study, grounded in narrative inquiry, investigates the experiences and perceptions of 141 preservice teachers engaged with AI, mainly through ChatGPT, over a 3-week implementation on Zoom to understand its influence on their evolving professional identities and instructional methodologies. Employing Strauss and Corbin's methodological approach of open, axial, and selective coding to analyze reflective narratives, the study unveils significant themes that underscore the dual nature of AI in education. Key findings reveal ChatGPT's role in enhancing educational effectiveness and accessibility while raising ethical concerns regarding academic integrity and balanced usage. Specifically, ChatGPT was found to empower personalized learning and streamline procedures, yet challenges involving information accuracy and data security remained. The study significantly contributes to teacher education discourse by revealing AI's complex educational impacts, highlighting an urgent need for comprehensive ethical AI literacy in teacher training curricula. However, critical ethical considerations and practical challenges involving academic integrity, information accuracy, and balanced AI use are also brought to light. The research also spotlights the need for responsible AI implementation in open and distributed learning to optimize educational outcomes while addressing potential risks. The study's insights advocate for future-focused AI literacy frameworks that integrate technological adeptness with ethical considerations, preparing teacher candidates for an intelligent digital educational landscape.

Mastering academic writing skills in English is essential for future researchers. At present, AI language processing tools provide high-quality, accessible, and fast assistance for translation, editing, and stylistic enhancement of scientific texts. However, their use within English for Academic Purposes (EAP) courses generates mixed reactions among educators and raises ethical concerns. Our study aimed to explore the predominant perceptions of AI language processing tools by PhD students of the National Academy of Sciences of Ukraine (NASU) from the viewpoint of their integration into the academic English course taught in the first year of their PhD studies. The study involved 52 PhD students from various NASU institutes. They completed a survey with both closed-ended and open-ended questions regarding their previous and expected use of online translators, writing enhancement tools, and ChatGPT for research writing purposes. The results of the survey show that NASU PhD students have extensive experience with online translators, but are less familiar with writing enhancement tools and less certain about their potential use in the future. Almost a third of the respondents expressed reservations about using ChatGPT for academic writing due to academic integrity concerns. Most of the respondents (66%) agree that the basics of ethical use of AI writing and editing tools should be incorporated into EAP courses. One subgroup of the participants (n = 11) took part in a small-scale additional intervention focused on writing enhancement tools. They were asked to apply Grammarly, QuillBot, and ChatGPT to edit their course projects (presentations of the current state of their dissertation research) and compare these tools according to various criteria. The feedback provided by this subgroup indicates that they were most satisfied with the quality of editing provided by ChatGPT but found Grammarly and QuillBot easier to use and more suitable for superficial grammar checks. We found out that the AI tools helped participants achieve improvements primarily in such aspects as the use of articles, punctuation, use of prepositions, and elimination of redundancy. The study has significant pedagogical implications, promoting the wider use of AI tools in the context of teaching English for Academic Purposes and addressing appropriate teaching techniques and methods.

In postsecondary education institutions, where innovative technologies continually reshape research and pedagogical approaches, the integration of generative artificial intelligence (GenAI) tools presents promising avenues for enhancing student learning experiences. This study assesses the efficacy of integrating GenAI tools, specifically chatbots, to ameliorate learning outcomes and mitigate test anxiety among postsecondary students. Within the context of an introductory psychology course, 40 participants engaged with chatbots as supplementary "study confidantes" for exam preparation and as facilitators for an essay grading task. The results from surveys administered to the participants indicated that most students found the chatbots helpful in aiding comprehension of course materials. Moreover, a substantial proportion of respondents reported an enhanced understanding of how to structure an academic paper because of their essay grading activity. Despite the favourable perception of chatbot assistance with learning course material and fostering insights into structuring scholarly essays, no discernible alterations in the levels of test anxiety among students were observed. Overall, this research underscores the latent potential of chatbots as pedagogical adjuncts, furnishing instructive insights for educators aiming to innovate instructional methodologies and optimize student learning paradigms within the domain of postsecondary education.

Despite existing research on AI applications in education (AIEd), the release of ChatGPT has disrupted the status quo in the educational landscape. Although this technology can personalize learning, decrease teacher workload, and offer access to a wealth of information, concerns around generative AI (GenAI) tools have emerged, including academic integrity, data accuracy, and bias in information. Given research highlights and acknowledging educators' varied levels of awareness and conflicting views toward AIEd, two teacher educators (also authors of this paper) in the Faculty of Education at Brock University facilitated three workshops among different groups of teacher educators. The workshops focused on the emerging nature of GenAI tools, their affordances, and their implications for educators' practices. Adopting a narrative inquiry approach, the authors describe the details of these workshops and present their reflections on the process of preparing for and facilitating them. Implications for teacher education research and practice are also presented and discussed.

The introduction of ChatGPT into basic education is progressing rapidly, generating impacts that, in many cases, are unknown. Its impressive capability profiles it as a tool that will revolutionize teaching and learning processes, creating gaps that need to be understood and evaluated. The research aims to explore the advantages, disadvantages, and its impact on school tasks. It is an exploratory qualitative study; data were collected through semi-structured interviews with 110 participants from five schools in Tacna, Peru. The results reveal that ChatGPT provides information quickly and easily, with a variety of content and pedagogical strategies. Additionally, it serves for evaluation, knowledge consultation, and scheduling school tasks. Eight related disadvantages were identified: Easy access to information may encourage the habit of copying and pasting, fostering academic dependence that would affect the development of skills, such as inquiry, argumentation, analysis, and critical thinking. Also, students may misuse information, cheating on school tasks and affecting their quality and suitability, making them no longer useful for education, including synthesis, essays, monographs, organizers, summaries, and mathematical exercises.

The realm of online international Chinese language teaching is undergoing significant transformations propelled by the internet and the pandemic. The digital teaching is the way forward for online international Chinese language teaching. There are significant differences between online international Chinese language teaching and traditional Chinese language teaching. To improve online teaching activities and guide future research, this growing field aims to analyze Chinese international online education research. Specifically, the goal is to develop a sustainable teaching model. By utilizing Preferred Reporting Items for Systematic Review and Meta-Analysis Protocol (PRISMA-P), the authors analyzed 27 articles proposing a viable teaching model. The review identifies six models of online Chinese language teaching: flipped classroom, APP software, open online platform, online interaction, blended learning, and ChatGPT. The blended learning model is considered the most effective but still faces limitations such as technical issues, demanding teachers, lack of motivation, limited face-to-face interaction, and limited assessment options. Scholars suggest solutions including technical support, teacher training, motivation, improving face-to-face interaction, and using multiple assessment methods. Overall, the blended teaching model has the potential to advance online international Chinese language teaching in the future.

This paper addresses the pedagogical implications of incorporating ChatGPT into the college English classroom specifically and, more broadly, into any college course with a focus on writing and research. Historically, advances in technology in the college classroom have characteristically promoted two juxtaposed reactions: relief and anxiety. Students customarily exhibit relief that a new technology will lessen their workload and embrace it wholeheartedly. Conversely, faculty often experience anxiety at how some newfangled computerized application will impact student learning. This juxtaposition creates barriers to an effective integration of new technology into the classroom. What students view as a cool new tool faculty see as a platform that promotes student slacking or, at worst, cheating. Such is the case with ChatGPT. I review generally the ethics of using ChatGPT as a classroom tool to conclude that the potential for advancing educational equity among students outweighs any potential for misuse of this quickly evolving technology. Relying upon established principles of classroom instruction as well as significant trial-and-error experience, I propose a pedagogical framework that allows for limited application of ChatGPT in selected scaffolded assignments. I further offer specific lesson plans to show how incorporation of ChatGPT into the college composition classroom can align with universally accepted goals, objectives, and student learning targets in both freshman composition and traditional literature courses, all while removing barriers and promoting equity. This paper provides faculty who are not already well-versed in ChatGPT with information to evaluate its efficacy for their courses and a flexible framework to include into their pedagogy easily modifiable ChatGPT-based lesson plans that present challenging yet fun scaffolded assignments for any writing or research curriculum.

The advent of generative AI (GenAI) technology has impacted second language (L2) learning and assessment, offering new opportunities for learners to practice and improve their skills. One approach gaining interest is employing GenAI tools as writing or speaking partners to provide personalized, real-time feedback and assistance to learners. These interactions allow learners to practice their writing and speaking skills while receiving assessment information on various aspects of language, including grammar, vocabulary, and pronunciation. Considering the potential of GenAI tools to enrich assessment and learning experiences, it is worth examining recent research on the use of this technology for this purpose. This paper reviews the literature on the use of GenAI as writing and speaking partners through the lens of the Learning-Oriented Assessment (LOA) framework (Purpura, 2024; Turner & Purpura, 2016) to explore how assessment data from GenAI tools could be leveraged to further learning.

In the realm of language acquisition, the integration of Artificial Intelligence (AI) presents a promising frontier. However, gaps exist in understanding the practical application of AI-driven tools, particularly in second language learning contexts. This study delves into the usability of ChatGPT, an advanced AI language model, within the domain of second language acquisition. This paper synthesizes existing literature on ChatGPT's multifaceted capabilities, its effectiveness, its associated challenges, and the potential solutions to these challenges in language learning environments. This review demonstrates ChatGPT's substantial potential in enhancing language learning outcomes, including fostering learner autonomy, improving motivation, and developing language proficiency. Yet, nuanced challenges such as preserving academic integrity and difficulties in crafting effective prompts emerge as crucial considerations. To address these issues, possible solutions including enhancing AI literacy among learners and educators are discussed. This paper sheds light on the complex dynamics of AI-assisted language education, urging ongoing research and refinement to fully utilize these technologies in enhancing second language learning.

This research aimed to develop and validate a rubric to assess Artificial Intelligence (AI) chatbots' effectiveness in accomplishing tasks, particularly within educational contexts. Given the rapidly growing integration of AI in various sectors, including education, a systematic and robust tool for evaluating AI chatbot performance is essential. This investigation involved a rigorous process including expert involvement to ensure content validity, as well as the application of statistical tests for assessing internal consistency and reliability. Factor analysis also revealed two significant domains, "Quality of Content" and "Quality of Expression", which further enhanced the construct validity of the evaluation scale. The results from this investigation robustly affirm the reliability and validity of the developed rubric, thus marking a significant advancement in the sphere of AI chatbot performance evaluation within educational contexts. Nonetheless, the study simultaneously emphasizes the requirement for additional validation research, specifically those entailing a variety of tasks and diverse AI chatbots, to further corroborate these findings. The ramifications of this research are profound, offering both researchers and practitioners engaged in chatbot development and evaluation a comprehensive and validated framework for the assessment of chatbot performance.

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.

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.

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.

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.

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.

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.

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.

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.

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.