From Educational Data to Pedagogical Action: AI-Driven Insights for Teaching and Learning
A Special Issue of Education Sciences (ISSN 2227-7102) belonging to the section "Technology Enhanced Education".
Deadline for manuscript submissions: 30 April 2027 | Viewed by 32
Editors
Interests: AI-enhanced simulations; AI literacy for educators
Special Issue Information
Dear Colleagues,
Artificial intelligence is rapidly changing how students learn, how instructors teach, and how educational experiences are designed. At the same time, the growing use of AI in educational settings creates new opportunities to examine learners’ behaviors, experiences, interactions, and outcomes and to use these insights to improve teaching and learning.
This Special Issue invites research exploring how data, evidence, and analytics can help us better understand and improve teaching and learning in the age of AI. We welcome studies examining how students and instructors use AI in authentic educational settings, including classrooms, online courses, professional preparation, simulations, and other learning environments. Topics may include patterns of student AI use, learning and engagement, instructional practices, assessment and feedback, personalized learning, collaboration, learning design, and emerging forms of human-AI interaction.
Contributions may employ quantitative, qualitative, mixed-methods, learning analytics, or design-based approaches. We particularly encourage studies that move beyond whether AI is simply used or accepted to investigate how AI shapes learning processes, learner experiences, instructional practices, and educational outcomes. Research addressing responsible, equitable, and effective uses of AI across diverse educational contexts is also welcome.
Topics of interest for publication include, but are not limited to, the following:
- Students’ use of AI in classroom and course-based learning
- AI-supported learning behaviors, strategies, and experiences
- AI and student engagement, participation, motivation, and performance
- AI-supported teaching practices and instructional decision making
- AI for assessment, feedback, and learning support
- AI-supported personalized and adaptive learning experiences
- Human-AI interaction and collaboration in learning
- AI use in authentic, experiential, professional, and simulation-based learning
- Data- and evidence-informed understanding of AI-supported teaching and learning
- Responsible and effective integration of AI into teaching and learning
Dr. Jie Lu
Dr. Xiaoman Wang
Guest Editors
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 250 words) can be sent to the Editorial Office for assessment.
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 double-anonymized peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Education 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 2000 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
- artificial intelligence in education
- teaching and learning
- learning analytics
- student AI use
- AI-supported learning
- instructional practices
- human–AI interaction
- learning design
- assessment and feedback
- educational innovation
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