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Behavioral Sciences
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Artificial Intelligence and Educational Psychology
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Artificial Intelligence and Educational Psychology

A special issue of Behavioral Sciences (ISSN 2076-328X). This special issue belongs to the section "Educational Psychology".

Deadline for manuscript submissions: 31 May 2025 | Viewed by 12100

Special Issue Editor

Prof. Dr. Manli Li

E-Mail Website
Guest Editor
Institute of Education, Tsinghua University, Beijing 100084, China
Interests: higher education; curriculum & instruction in HE; teaching &learning in HE; liberal arts education in digital era; high-achieving students; languange & education; K-12 school reform; online education & online learning

Special Issue Information

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.

Keywords

  • 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

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Further information on MDPI's Special Issue policies can be found here.

Published Papers (5 papers)

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Research

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22 pages, 314 KiB  
Article
AI as the Therapist: Student Insights on the Challenges of Using Generative AI for School Mental Health Frameworks
by Cecilia Ka Yuk Chan
Behav. Sci. 2025, 15(3), 287; https://doi.org/10.3390/bs15030287 - 28 Feb 2025
Cited by 2 | Viewed by 3782 | Correction
Abstract
The integration of generative AI (GenAI) in school-based mental health services presents new opportunities and challenges. This study focuses on the challenges of using GenAI chatbots as therapeutic tools by exploring secondary school students’ perceptions of such applications. The data were collected from [...] Read more.
The integration of generative AI (GenAI) in school-based mental health services presents new opportunities and challenges. This study focuses on the challenges of using GenAI chatbots as therapeutic tools by exploring secondary school students’ perceptions of such applications. The data were collected from students who had both theoretical and practical experience with GenAI. Based on Grodniewicz and Hohol’s framework highlighting the “Problem of a Confused Therapist”, “Problem of a Non-human Therapist”, and “Problem of a Narrowly Intelligent Therapist”, qualitative data from student reflections were examined using thematic analysis. The findings revealed that while students acknowledged AI’s benefits, such as accessibility and non-judgemental feedback, they expressed significant concerns about a lack of empathy, trust, and adaptability. The implications underscore the need for AI chatbot use to be complemented by in-person counselling, emphasising the importance of human oversight in AI-augmented mental health care. This study contributes to a deeper understanding of how advanced AI can be ethically and effectively incorporated into school mental health frameworks, balancing technological potential with essential human interaction. Full article
(This article belongs to the Special Issue Artificial Intelligence and Educational Psychology)
14 pages, 472 KiB  
Article
How Epistemic Curiosity Influences Digital Literacy: Evidence from International Students in China
by Shaojun Ma, Xuan Jin, Xin Li, Hongming Dong, Xuehang Dong and Bowen Tang
Behav. Sci. 2025, 15(3), 286; https://doi.org/10.3390/bs15030286 - 28 Feb 2025
Cited by 1 | Viewed by 746
Abstract
Digital literacy is the core competitiveness and necessary ability that international students should cultivate while studying in China in the context of education digitalization, and this paper mainly explores whether epistemic curiosity can affect the digital literacy of international students in China. Based [...] Read more.
Digital literacy is the core competitiveness and necessary ability that international students should cultivate while studying in China in the context of education digitalization, and this paper mainly explores whether epistemic curiosity can affect the digital literacy of international students in China. Based on the Technology Acceptance Model, this paper introduces the variable of epistemic curiosity, uses questionnaire survey method and quantitative tools (SPSS and AMOS software) to construct a model of the cognition–perception–formation mechanism of international students’ digital literacy in China, and obtains the following conclusions: Firstly, both interest- and deprivation-type epistemic curiosity can directly promote the digital literacy of international students in China. Secondly, this paper discusses how interest- and deprivation-type epistemic curiosity can affect digital literacy under the mediating effect of perceived usefulness. Finally, perceived ease of use can also indirectly promote the relationship between epistemic curiosity and digital literacy of international students in China. The contribution of this paper is to highlight the formation mechanism of digital literacy in cross-cultural contexts and to explore how interest- and deprivation-type epistemic curiosity affect the digital literacy of international students in China. To a certain extent, this paper reveals the potential process of international students in China to use digital resources to transform into digital literacy and also provides useful evidence for the further development of attractive digital resources. Full article
(This article belongs to the Special Issue Artificial Intelligence and Educational Psychology)
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25 pages, 1238 KiB  
Article
Latent Profile Analysis of AI Literacy and Trust in Mathematics Teachers and Their Relations with AI Dependency and 21st-Century Skills
by Tommy Tanu Wijaya, Qingchun Yu, Yiming Cao, Yahan He and Frederick K. S. Leung
Behav. Sci. 2024, 14(11), 1008; https://doi.org/10.3390/bs14111008 - 30 Oct 2024
Cited by 5 | Viewed by 4862
Abstract
Artificial Intelligence (AI) technology, particularly generative AI, has positively impacted education by enhancing mathematics instruction with personalized learning experiences and improved data analysis. Nonetheless, variations in AI literacy, trust in AI, and dependency on these technologies among mathematics teachers can significantly influence their [...] Read more.
Artificial Intelligence (AI) technology, particularly generative AI, has positively impacted education by enhancing mathematics instruction with personalized learning experiences and improved data analysis. Nonetheless, variations in AI literacy, trust in AI, and dependency on these technologies among mathematics teachers can significantly influence their development of 21st-century skills such as self-confidence, problem-solving, critical thinking, creative thinking, and collaboration. This study aims to identify distinct profiles of AI literacy, trust, and dependency among mathematics teachers and examines how these profiles correlate with variations in the aforementioned skills. Using a cross-sectional research design, the study collected data from 489 mathematics teachers in China. A robust three-step latent profile analysis method was utilized to analyze the data. The research revealed five distinct profiles of AI literacy and trust among the teachers: (1) Basic AI Engagement; (2) Developing AI Literacy, Skeptical of AI; (3) Balanced AI Competence; (4) Advanced AI Integration; and (5) AI Expertise and Confidence. The study found that an increase in AI literacy and trust directly correlates with an increase in AI dependency and a decrease in skills such as self-confidence, problem-solving, critical thinking, creative thinking, and collaboration. The findings underscore the need for careful integration of AI technologies in educational settings. Excessive reliance on AI can lead to detrimental dependencies, which may hinder the development of essential 21st-century skills. The study contributes to the existing literature by providing empirical evidence on the impact of AI literacy and trust on the professional development of mathematics teachers. It also offers practical implications for educational policymakers and institutions to consider balanced approaches to AI integration, ensuring that AI enhances rather than replaces the critical thinking and problem-solving capacities of educators. Full article
(This article belongs to the Special Issue Artificial Intelligence and Educational Psychology)
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26 pages, 711 KiB  
Systematic Review
A Systematic Review of Responses, Attitudes, and Utilization Behaviors on Generative AI for Teaching and Learning in Higher Education
by Fan Wu, Yang Dang and Manli Li
Behav. Sci. 2025, 15(4), 467; https://doi.org/10.3390/bs15040467 - 4 Apr 2025
Viewed by 978
Abstract
The utilization of Generative AI (GenAI) in higher education classrooms has significantly increased in recent years. Studies show that GenAI holds promise in impacting the learning experiences of both students and teachers, offering personalized learning and assessment opportunities. This study conducts a systematic [...] Read more.
The utilization of Generative AI (GenAI) in higher education classrooms has significantly increased in recent years. Studies show that GenAI holds promise in impacting the learning experiences of both students and teachers, offering personalized learning and assessment opportunities. This study conducts a systematic review of the responses, attitudes, and behaviors related to the application of GenAI within higher education classrooms. To this end, we synthesized 99 papers published between 2020 and August 2024, focusing on the utilization of GenAI in higher education settings. The analysis addresses three key inquiries: responses, attitudes, and behaviors. This systematic review provides an updated understanding from psychological perspectives of GenAI’s role in the teaching and learning processes of higher education, with a particular emphasis on GenAI technologies. Full article
(This article belongs to the Special Issue Artificial Intelligence and Educational Psychology)
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1 pages, 131 KiB  
Correction
Correction: Chan (2025). AI as the Therapist: Student Insights on the Challenges of Using Generative AI for School Mental Health Frameworks. Behavioral Sciences, 15(3), 287
by Cecilia Ka Yuk Chan
Behav. Sci. 2025, 15(3), 375; https://doi.org/10.3390/bs15030375 - 17 Mar 2025
Viewed by 375
Abstract
In the original publication (Chan, 2025), “(Gaffney et al [...] Full article
(This article belongs to the Special Issue Artificial Intelligence and Educational Psychology)
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