User interactions with chatbot interfaces vs. Menu-based interfaces: An empirical study

TL;DR: In this paper , a meta-analysis of 24 randomized studies utilizing Stata software (version 14) was performed to examine the effects of AI chatbots on students' learning outcomes and the moderating effects of educational levels and intervention duration.

TL;DR: This paper conducted a systematic literature review (SLR) of published work indexed in the Clarivate Web of Science and Elsevier Scopus databases and identified four dominant topical areas through bibliographic coupling.

Abstract: Artificial intelligence technologies are rapidly advancing. As part of this development, large language models (LLMs) are increasingly being used when humans interact with systems based on artificial intelligence (AI), posing both new opportunities and challenges. When interacting with LLM-based AI system in a goal-directed manner, prompt engineering has evolved as a skill of formulating precise and well-structured instructions to elicit desired responses or information from the LLM, optimizing the effectiveness of the interaction. However, research on the perspectives of non-experts using LLM-based AI systems through prompt engineering and on how AI literacy affects prompting behavior is lacking. This aspect is particularly important when considering the implications of LLMs in the context of higher education. In this present study, we address this issue, introduce a skill-based approach to prompt engineering, and explicitly consider the role of non-experts ’ AI literacy (students) in their prompt engineering skills. We also provide qualitative insights into students ’ intuitive behaviors towards LLM-based AI systems. The results show that higher-quality prompt engineering skills predict the quality of LLM output, suggesting that prompt engineering is indeed a required skill for the goal-directed use of generative AI tools. In addition, the results show that certain aspects of AI literacy can play a role in higher quality prompt engineering and targeted adaptation of LLMs within education. We, therefore, argue for the integration of AI educational content into current curricula to enable a hybrid intelligent society in which students can effectively use generative AI tools such as ChatGPT.

TL;DR: This study investigates ChatGPT users' satisfaction, loyalty, and ethical concerns, revealing that information quality, perceived usefulness, and coolness positively impact satisfaction and loyalty, while user ethical perceptions and beliefs negatively moderate this relationship.

TL;DR: Cognitive dissonance theory links actions and attitudes as discussed by the authors, which holds that dissonance is experienced whenever one cognition that a person holds follows from the opposite of at least one other cognition that the person holds.

TL;DR: This review revisits the classic definitions of intrinsic and extrinsic motivation in light of contemporary research and theory and discusses the relations of both classes of motives to basic human needs for autonomy, competence and relatedness.

TL;DR: The Second Edition of this practical guide to partial least squares structural equation modeling is designed to be easily understood by those with limited statistical and mathematical training who want to pursue research opportunities in new ways.

TL;DR: Although structural equation modelling (SEM) is a popular statistical technique for multivariate data analysis in social and behavioural sciences, its use in education has massified more recently as mentioned in this paper.