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The escalating integration of artificial intelligence (AI) technologies, particularly the widespread use of ChatGPT in higher education, necessitates a profound exploration of effective communication strategies. This paper addresses the critical role of prompt development as a skill essential for university instructors engaging with ChatGPT. While emphasizing the practical implications for higher education, the study introduces a novel two-layered AI prompt formula, considering both components and elements. In methodology, the research synthesizes insights from existing models and proposes a tailored approach for ChatGPT, addressing its unique characteristics and the contextual elements within higher education. The results highlight the formula's flexibility and potential applications in diverse fields, from syllabus planning to assessment. Moreover, the study identifies limitations inherent in ChatGPT, emphasizing the need for instructors to exercise caution in its usage. In conclusion, the paper underscores the evolving landscape of AI in education, envisaging specialized versions of ChatGPT for academic settings and advocating for the proactive adoption of ethical frameworks in the use of AI in higher education. This study serves as a foundational contribution to the discourse on effective AI communication in educational settings. [ABSTRACT FROM AUTHOR]

AI chatbots such as ChatGPT help people produce texts. According to media reporting, these texts are also used for educational purposes. Thus, AI influences people's knowledge and perception of current issues. This paper examines the narrative of ChatGPT's stories on climate change. Our explorative analysis reveals that ChatGPT's stories on climate change show a relatively uniform structure and similar content. Generally, the narrative is in line with scientific knowledge on climate change; the stories convey no significant misinformation. However, specific topics in current debates on global warming are conspicuously missing. According to the ChatGPT narrative, humans as a species are responsible for climate change and specific economic activities or actors associated with carbon emissions play no role. Analogously, the social structuration of vulnerability to climate impacts and issues of climate justice are hardly addressed. ChatGPT's narrative consists of de-politicized stories that are highly optimistic about technological progress. [ABSTRACT FROM AUTHOR]

Artificial Intelligence (AI) chatbots are increasingly becoming integral components of the digital learning ecosystem. As AI technologies continue to evolve, it is crucial to understand the factors influencing their adoption and use among students in higher education. This study is undertaken against this backdrop to explore the behavioral determinants associated with the use of the AI Chatbot, ChatGPT, among university students. The investigation delves into the role of ChatGPT's self-learning capabilities and their influence on students' knowledge acquisition and application, subsequently affecting the individual impact. It further elucidates the correlation of chatbot personalization with novelty value and benefits, underscoring their importance in shaping students' behavioral intentions. Notably, individual impact is revealed to have a positive association with perceived benefits and behavioral intention. The study also brings to light potential barriers to AI chatbot adoption, identifying privacy concerns, technophobia, and guilt feelings as significant detractors from behavioral intention. However, despite these impediments, innovativeness emerges as a positive influencer, enhancing behavioral intention and actual behavior. This comprehensive exploration of the multifaceted influences on student behavior in the context of AI chatbot utilization provides a robust foundation for future research. It also offers invaluable insights for AI chatbot developers and educators, aiding them in crafting more effective strategies for AI integration in educational settings. [ABSTRACT FROM AUTHOR]

Artificial intelligence (AI) has garnered considerable interest in the field of language education in recent times; however, limited research has focused on the role of AI in the specific context of register knowledge learning during English language writing. This study aims to address this research gap by examining the impact of ChatGPT, an AI-powered chatbot, on the acquisition of register knowledge across various writing tasks. The research design employed a one-case shot pre-experimental design, with 11 voluntary participants selected through convenience sampling. Preliminary results indicate that students found ChatGPT beneficial for acquiring formal register knowledge but perceived it as unnecessary for informal writing. Additionally, the effectiveness of ChatGPT in teaching neutral register was questioned by the participants. This research contributes to the existing literature by shedding new light on the effects of AI-generated chatbots in register learning during the writing process, offering insights into their potential as learning assistants. Further investigation is warranted to explore the broader implications and applications of AI in language learning contexts. [ABSTRACT FROM AUTHOR]

The GPT-4 large language model (LLM) and ChatGPT chatbot have emerged as accessible and capable tools for generating English-language text in a variety of formats. GPT-4 has previously performed well when applied to questions from multiple standardized examinations. However, further evaluation of trustworthiness and accuracy of GPT-4 responses across various knowledge domains is essential before its use as a reference resource. Here, we assess GPT-4 performance on nine graduate-level examinations in the biomedical sciences (seven blinded), finding that GPT-4 scores exceed the student average in seven of nine cases and exceed all student scores for four exams. GPT-4 performed very well on fill-in-the-blank, short-answer, and essay questions, and correctly answered several questions on figures sourced from published manuscripts. Conversely, GPT-4 performed poorly on questions with figures containing simulated data and those requiring a hand-drawn answer. Two GPT-4 answer-sets were flagged as plagiarism based on answer similarity and some model responses included detailed hallucinations. In addition to assessing GPT-4 performance, we discuss patterns and limitations in GPT-4 capabilities with the goal of informing design of future academic examinations in the chatbot era. [ABSTRACT FROM AUTHOR]