Trends in Teaching and Learning Technologies for Enhancing Assessment and Feedback
A special issue of Education Sciences (ISSN 2227-7102). This special issue belongs to the section "Technology Enhanced Education".
Deadline for manuscript submissions: 30 November 2025 | Viewed by 103
Special Issue Editors
Interests: educational robotics; research methodologies; data analysis
Special Issue Information
Dear Colleagues,
The rapid advancements in teaching and learning technologies are reshaping how educators design assessment and deliver feedback, which is vital for effective learning. Feedback serves as a cornerstone for guiding learners, fostering engagement, and improving outcomes. Technologies such as artificial intelligence, data analytics, and gamification offer unprecedented potential to enhance feedback by making it more personalized, timely, and impactful. However, their successful implementation depends on aligning these innovations with sound pedagogical principles, creating a cohesive approach that integrates technology and teaching methodologies.
This Special Issue explores how the integration of technology and pedagogy can transform assessment and feedback practices in education. It seeks to highlight cutting-edge research, innovative tools, and strategies that demonstrate the seamless collaboration of teaching methods and technological advancements. By bringing together researchers, educators, and practitioners, this Special Issue aims to showcase impactful practices, share insights on effective implementation, and critically examine how technology, when harmonized with pedagogy, can reshape the way feedback supports learning.
We invite submissions of original research articles, reviews, and case studies that present innovative tools, practices, and results. Submissions may address, but are not limited to, the following themes:
- Innovative digital tools and platforms for assessment and feedback;
- Artificial intelligence and machine learning applications in education;
- Data analytics and learning dashboards for personalized feedback;
- Digital twins and cyber-physical systems in education;
- Designing equitable and inclusive assessment technologies ;
- Case studies on the implementation of technology-enhanced assessment practices;
- Challenges and barriers to adopting new technologies in assessment;
- Theoretical frameworks and models for technology-enhanced assessment;
- Ethical considerations and data privacy in educational technologies.
Dr. Laura Screpanti
Prof. Dr. Lorella Giannandrea
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 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 double-blind 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 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
- technology-enhanced pedagogy
- personalized feedback
- assessment as learning
- automated assessment
- intelligent tutoring systems
- artificial intelligence in education
- learning analytics
- cyber physical human systems
- transformative and adaptive feedback
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