Revealing essential notions: an algorithmic approach to distilling core concepts from student and teacher responses in computer science education

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F70883521%3A28140%2F24%3A63587239" target="_blank" >RIV/70883521:28140/24:63587239 - isvavai.cz</a>
Result on the web
<a href="https://www.emerald.com/insight/content/doi/10.1108/aci-12-2023-0207/full/html" target="_blank" >https://www.emerald.com/insight/content/doi/10.1108/aci-12-2023-0207/full/html</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1108/ACI-12-2023-0207" target="_blank" >10.1108/ACI-12-2023-0207</a>

Result language
angličtina
Original language name
Revealing essential notions: an algorithmic approach to distilling core concepts from student and teacher responses in computer science education
Original language description
PurposeThis study aims to assess subjective responses in computer science education to understand students' grasp of core concepts. Extracting key ideas from short answers remains challenging, necessitating an effective method to enhance learning outcomes.Design/methodology/approachThis study introduces KeydistilTF, a model to identify essential concepts from student and teacher responses. Using the University of North Texas dataset from Kaggle, consisting of 53 teachers and 1,705 student responses, the model's performance was evaluated using the F1 score for key concept detection.FindingsKeydistilTF outperformed baseline techniques with F1 scores improved by 8, 6 and 4% for student key concept detection and 10, 8 and 6% for teacher key concept detection. These results indicate the model's effectiveness in capturing crucial concepts and enhancing the understanding of key curriculum content.Originality/valueKeydistilTF shows promise in improving the assessment of subjective responses in education, offering insights that can inform teaching methods and learning strategies. Its superior performance over baseline methods underscores its potential as a valuable tool in educational settings.
Czech name
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Czech description
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Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project
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Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year
2024
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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