Artificial Intelligence and Educational Psychology

Dear Colleagues,

As the Guest Editor of this Special Issue, I present a collection of thought-provoking articles that delve into the intersection of artificial intelligence (AI) and educational psychology, with a particular focus on behavior analysis. This compilation aims to explore how AI can be leveraged to enhance our understanding of student behavior, personalize learning experiences, and improve educational outcomes.

This Special Issue begins with an overview of AI's role in shaping educational psychology, highlighting advancements in data-driven insights and predictive analytics. Subsequent articles examine the ethical implications of AI in educational settings, ensuring that the technology is used responsibly and with respect for student privacy.

Contributors from various disciplines discuss the practical applications of AI in behavior analysis, including the use of machine learning algorithms to identify patterns in student engagement and the development of adaptive learning systems that respond to individual needs. Case studies showcase successful implementations of AI in classrooms, demonstrating improved student performance and teacher satisfaction.

This Special Issue concludes with a forward-looking discussion on the future of AI in education, considering the potential for AI to revolutionize pedagogical approaches and the challenges that lie ahead in integrating these technologies into the educational landscape.

This Special Issue is a must-read for educators, researchers, and policymakers interested in the transformative potential of AI in shaping the future of education and behavior analysis.

Prof. Dr. Manli Li
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Behavioral Sciences is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2200 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

• educational artificial intelligence
• educational data mining
• AI tutoring systems
• collaborative learning
• learning analytics
• personalized learning
• educational governance with AI
• intelligent recommender systems
• self-adaptive learning
• affective computing
• value sensitive design

Title: An Examination of Generative AI in Higher Education Pedagogy: A Systematic Literature Review
Authors: Li Manli Wufan Dang Yang
Affiliation: Institute of Education, Tsinghua University, Beijing 100084, China
Abstract: The deployment of Generative AI(GenAI) has garnered considerable scholarly attention within the realm of higher education. This study aims to delineate the transformative implications of GenAI on teaching methodologies and the educational experiences of students within the higher education milieu. The present systematic review synthesizes relevant literature published between 2016 and 2024, drawing from databases including Scopus, Web of Science, and educational repositories within EBSCOhost. An initial corpus of 1544 articles was identified, with a final selection of 130 studies informed by the PRISMA Statement guidelines. The findings indicate that Gen AI is predominantly utilized in higher education settings for facilitating the creation of assessment items by educators and aiding students in the completion of project-based assignments. Beyond applications such as ChatGPT，Gemini and Chat-GLM，a multitude of specialized tools and platforms tailored for specific pedagogical tasks have emerged. The application of GenAI is posited to augment student learning outcomes, including knowledge acquisition, problem-solving, critical thinking, and communicative proficiency. Additionally, GenAI is shown to foster students' behavioral intention towards its adoption and utilization. The integration of GenAI in educational settings presents increasing opportunities for AI-mediated teacher-student collaboration, significantly enhancing classroom interaction, personalized learning, and student engagement. Notably, GenAI is recognized for its potential to revolutionize teacher professional development, particularly in guiding students in the effective and responsible use of GenAI tools. The review underscores the imperative transition from broad thematic investigations to nuanced inquiries into the specific instructional practices involving GenAI. Moreover, it advocates for a robust body of empirical research examining the multifaceted impact of GenAI on teaching and learning from an interdisciplinary and multidimensional standpoint.