Intelligent diagnostic feedback for online multiple-choice questions
- Submitting institution
-
University of East London
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 26
- Type
- D - Journal article
- DOI
-
10.1007/s10462-013-9419-6
- Title of journal
- Artificial Intelligence Review
- Article number
- -
- First page
- 369-383
- Volume
- 42
- Issue
- 3
- ISSN
- 0269-2821
- Open access status
- Out of scope for open access requirements
- Month of publication
- October
- Year of publication
- 2014
- URL
-
https://link.springer.com/article/10.1007/s10462-013-9419-6
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
3
- Research group(s)
-
1 - Intelligent Systems
- Citation count
- 11
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- The research provides guided learning to students and enables them to progress through the learning journey based on their learning styles. The approach has been successfully implemented at London Metropolitan University [1], and in China at JinQiao University (JQU) [2] and Kunming Technology University (KTU) [2], providing an automated guided learning tool for students studying in various modules. The results from this work also led to a PhD completion [3].
[1] https://aru.ac.uk/people/fang-fang-cai
[2] linkedin.com/in/dominic-palmer-brown-5a449613
[3] https://repository.londonmet.ac.uk/5220/
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -