Impact – Quasi–experimental

This study investigates the potential of using ChatGPT as a teachable agent to support students learning by teaching process, specifically in programming education. While learning by teaching is an effective pedagogical strategy for promoting active learning, traditional teachable agents have limitations, particularly in facilitating natural language dialogue. Our research explored whether ChatGPT, with its ability to engage learners in natural conversations, can support this process.

This study investigated the impact of AI-powered personalized learning tools on the academic performance and perceptions of pre-service student teachers enrolled in the Educational Technology course, a compulsory component of the Professional Postgraduate Diploma in Teaching program at Ajman University. A quasi-experimental design was employed with 55 students in the experimental group and 55 in the control group. The experimental group utilized AI-powered tools within the Moodle platform, while the control group received traditional instruction.

In this paper, we study how generative AI and specifically large language models (LLMs) impact learning in coding classes. We show across three studies that LLM usage can have positive and negative effects on learning outcomes. Using observational data from university-level programming courses, we establish such effects in the field. We replicate these findings in subsequent experimental studies, which closely resemble typical learning scenarios, to show causality. We find evidence for two contrasting mechanisms that determine the overall effect of LLM usage on learning.

App Planner is an interactive support tool for K-12 students, designed to assist in creating mobile applications. By utilizing generative AI, App Planner helps students articulate the problem and solution through guided conversations via a chat-based interface. It assists them in brainstorming and formulating new ideas for applications, provides feedback on those ideas, and stimulates creative thinking.

Gender discrimination in education hinders women's representation in various fields. How to create a gender-neutral learning environment when teachers' gender composition and mindset are slow to change? Artificial Intelligence (AI)'s recent development provides a way to achieve this goal, as engineers can make AI trainers gender-neutral and not take gender-related information as input. We use data from a natural experiment where such AI trainers replace some human teachers for a male-dominated strategic board game to test the effectiveness of AI training.

The study aimed to examine the influence of ChatGPT on the academic performance and learning perception of eleventh-grade students in a United Arab Emirates school in the field of electronic magnetism. The participants were randomly divided into two groups: an experimental group granted access to ChatGPT and a control group without access to ChatGPT. The research spanned four weeks, during which the experimental group was instructed to utilize ChatGPT whenever they required assistance with the course content.

This study evaluates the impact of students' usage of generative artificial intelligence (GenAI) tools such as ChatGPT on their exam performance. We analyse student essays using GenAI detection systems to identify GenAI users among the cohort. Employing multivariate regression analysis, we find that students using GenAI tools score on average 6.71 (out of 100) points lower than non-users. While GenAI may offer benefits for learning and engagement, the way students actually use it correlates with diminished exam outcomes.

Despite a rising interest in artificial intelligence (AI) technology, research in services marketing has not evaluated its role in helping firms learn about customers needs and increasing the adaptability of service employees. Therefore, the authors develop a conceptual framework and investigate whether and to what extent providing AI assistance to service employees improves service outcomes.

The purpose of this study is twofold: 1) to develop a service-learning-based module training artificial intelligence (AI) subject (SLBM-TAIS), and 2) to evaluate the effect of SLBM-TAIS on preservice teachers practical knowledge and motivation, as well as primary school students' attitude towards AI in China. Participants of this study comprised 60 PSTs and 107 primary school students. The experimental research in this study followed the quasi-experimental non-randomized pretest and post-test control group design.

Artificial intelligence (AI) applications to support human tutoring have potential to significantly improve learning outcomes, but engagement issues persist, especially among students from lowincome backgrounds. We introduce an AI-assisted tutoring model that combines human and AI tutoring and hypothesize this synergy will have positive impacts on learning processes.