Adapting progress feedback and emotional support to learner personality
- Submitting institution
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University of Portsmouth
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 11379873
- Type
- D - Journal article
- DOI
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10.1007/s40593-015-0059-7
- Title of journal
- International Journal of Artificial Intelligence in Education
- Article number
- -
- First page
- 877
- Volume
- 26
- Issue
- 3
- ISSN
- 1560-4292
- Open access status
- Out of scope for open access requirements
- Month of publication
- August
- Year of publication
- 2015
- URL
-
-
- 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
- Yes
- Number of additional authors
-
2
- Research group(s)
-
B - Computational Intelligence
- Citation count
- 15
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- The categorised emotional support statements developed in this research have been used by others (e.g. Okpo et al., ACM UMAP'17, pp. 140–147; Sidi-Ali et al., ACM UMAP'19, pp. 318–326) when investigating appropriate feedback strategies to use. Kindness et al. (International Journal of Human-Computer Studies, 2017, pp. 1-22) used the same methodology to create categorised statements tailored to community first responders. The methodology for generating stories that express a trait was generalised and led to the further research reported in Smith et al. (User Modeling and User-Adapted Interaction, 2019, pp. 573–618).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -