Computer-Assisted Learning and Teaching Tools in the AI Era
A Special Issue of Computers (ISSN 2073-431X) belonging to the section "AI-Driven Innovations".
Deadline for manuscript submissions: 15 July 2027 | Viewed by 421
Editor
Interests: industrial internet of things; algorithms; web programming; instrumentation; data mining; engineering education
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The rapid emergence of generative artificial intelligence is transforming the role of computer-assisted tools in learning and teaching across schools, higher education, vocational education, professional training and lifelong learning settings. Traditional educational technologies, such as learning management systems, digital assessment platforms, simulation environments, multimedia resources and computer-based tutoring systems, are now being extended through intelligent automation, natural language interaction, adaptive feedback and data-driven personalization.
Relevant topics include computational tools and relevant practices for students' self-learning, teaching support, AI-assisted feedback, automated assessment, learning analytics, educational data mining, virtual and augmented reality, simulation-based learning, accessibility technologies, academic integrity, teacher workload reduction and human–AI collaboration in educational practice.
The Special Issue also encourages critical studies that address the risks and limitations of these tools, including bias, privacy, transparency, reliability, digital inequality, student overreliance and the changing role of educators. By bringing together current research and practical innovations, this issue aims to advance understanding of how computer-assisted tools can be responsibly designed and used to improve learning outcomes, strengthen teaching practice and support human-centered education in the generative AI era.
Topics of interest include, but are not limited to, the following:
- Applications of artificial intelligence to education;
- Computer-assisted blended learning;
- Impact of large language models on learning and assessments;
- Adaptive learning systems;
- Gamification in education;
- Virtual and augmented reality in education;
- Mobile learning;
- Collaborative learning platforms;
- Smart classroom technologies;
- Cloud-based learning environments;
- Wearable technology for learning.
We welcome submissions that investigate the pedagogical, ethical and technological challenges and opportunities posed by these developments, with the aim of understanding their impact on educational outcomes and the future of teaching.
Dr. Ananda Maiti
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 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 single-anonymized peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Computers 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 1800 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
- generative artificial intelligence (generative AI)
- artificial intelligence in education (AIED)
- computer-assisted learning
- computer-assisted teaching
- intelligent tutoring systems
- adaptive learning
- large language models (LLMs) in Education
- learning analytics
- educational data mining
- automated assessment and feedback
- blended learning
- online learning
- virtual reality (VR) and augmented reality (AR) in education
- gamification
- smart classrooms
- mobile learning
- collaborative learning
- academic integrity
- human–AI collaboration
- educational technology
- wearable technology for learning
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