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Unravelling language use of narrative comments in ePortfolios : a text analysis approach

Sofie Van Ostaeyen (UGent) , Orphée De Clercq (UGent) , Mieke Embo (UGent) , Tammy Schellens (UGent) and Martin Valcke (UGent)
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Abstract
Narrative comments reported in ePortfolios allow to ground competency assessment and development during workplace learning in healthcare education. However, not all narrative comments are considered effective. The present study is a first step in exploring whether automatic text analysis could support the authors of narrative comments. Therefore, the aim of this study was to determine whether high-quality narrative comments can be characterised by certain language use. First, 2,348 narrative comments retrieved from ePortfolios of 149 Flemish healthcare students were manually labelled to determine their quality. Subsequently, these comments were analysed using the Linguistic Inquiry and Word Count (LIWC) tool. The results reveal that word count is the single lexical dimension which can be associated with quality differences. The LIWC dictionary categories did not vary across low-, moderate- or high-quality comments. This suggests potential shortcomings in the currently available LIWC dictionary categories. More specialized dictionary categories might be required.
Keywords
Assessment methods and tools, Feedback, Higher education, Workplace learning

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Citation

Please use this url to cite or link to this publication:

MLA
Van Ostaeyen, Sofie, et al. “Unravelling Language Use of Narrative Comments in EPortfolios : A Text Analysis Approach.” Book of Abstracts EARLI 2022, 2022.
APA
Van Ostaeyen, S., De Clercq, O., Embo, M., Schellens, T., & Valcke, M. (2022). Unravelling language use of narrative comments in ePortfolios : a text analysis approach. Book of Abstracts EARLI 2022. Presented at the EARLI SIG 1 & 4 Joint Conference 2022, Cádiz, Spain.
Chicago author-date
Van Ostaeyen, Sofie, Orphée De Clercq, Mieke Embo, Tammy Schellens, and Martin Valcke. 2022. “Unravelling Language Use of Narrative Comments in EPortfolios : A Text Analysis Approach.” In Book of Abstracts EARLI 2022.
Chicago author-date (all authors)
Van Ostaeyen, Sofie, Orphée De Clercq, Mieke Embo, Tammy Schellens, and Martin Valcke. 2022. “Unravelling Language Use of Narrative Comments in EPortfolios : A Text Analysis Approach.” In Book of Abstracts EARLI 2022.
Vancouver
1.
Van Ostaeyen S, De Clercq O, Embo M, Schellens T, Valcke M. Unravelling language use of narrative comments in ePortfolios : a text analysis approach. In: Book of Abstracts EARLI 2022. 2022.
IEEE
[1]
S. Van Ostaeyen, O. De Clercq, M. Embo, T. Schellens, and M. Valcke, “Unravelling language use of narrative comments in ePortfolios : a text analysis approach,” in Book of Abstracts EARLI 2022, Cádiz, Spain, 2022.
@inproceedings{8765434,
  abstract     = {{Narrative comments reported in ePortfolios allow to ground competency assessment and development during workplace learning in healthcare education. However, not all narrative comments are considered effective. The present study is a first step in exploring whether automatic text analysis could support the authors of narrative comments. Therefore, the aim of this study was to determine whether high-quality narrative comments can be characterised by certain language use. First, 2,348 narrative comments retrieved from ePortfolios of 149 Flemish healthcare students were manually labelled to determine their quality. Subsequently, these comments were analysed using the Linguistic Inquiry and Word Count (LIWC) tool. The results reveal that word count is the single lexical dimension which can be associated with quality differences. The LIWC dictionary categories did not vary across low-, moderate- or high-quality comments. This suggests potential shortcomings in the currently available LIWC dictionary categories. More specialized dictionary categories might be required.}},
  author       = {{Van Ostaeyen, Sofie and De Clercq, Orphée and Embo, Mieke and Schellens, Tammy and Valcke, Martin}},
  booktitle    = {{Book of Abstracts EARLI 2022}},
  keywords     = {{Assessment methods and tools,Feedback,Higher education,Workplace learning}},
  language     = {{eng}},
  location     = {{Cádiz, Spain}},
  title        = {{Unravelling language use of narrative comments in ePortfolios : a text analysis approach}},
  url          = {{https://ssl.earli.org/SIG1andSIG4-Cadiz2022}},
  year         = {{2022}},
}