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CITATION.cff
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cff-version: 1.2.0
title: Athena
message: >-
If you want to reference Athena in your work, please cite
this article.
type: software
authors:
- given-names: Jan Philip
family-names: Bernius
email: [email protected]
affiliation: Technical University of Munich
orcid: 'https://orcid.org/0000-0001-8278-4598'
repository-code: 'https://github.com/ls1intum/Athena'
abstract: >-
The Athena system generates and suggests computer-aided
feedback for textual exercises based on machine learning.
Athena utilizes a segment-based grading concept, which
links feedback to text segments. Athena automates grading
based on topic modeling and an assessment knowledge
repository acquired during previous assessments. A
language model builds an intermediate representation of
the text segments. Hierarchical clustering identifies
groups of similar text segments to reduce the grading
overhead.
keywords:
- Software engineering
- Education
- Interactive learning
- Automatic assessment
- Grading
- Assessment support system
- Learning
- Feedback
license: MIT
preferred-citation:
type: article
authors:
- given-names: Jan Philip
family-names: Bernius
email: [email protected]
affiliation: Technical University of Munich
orcid: 'https://orcid.org/0000-0001-8278-4598'
- given-names: Stephan
family-names: Krusche
email: [email protected]
affiliation: Technical University of Munich
orcid: 'https://orcid.org/0000-0002-4552-644X'
- given-names: Bernd
family-names: Bruegge
email: [email protected]
affiliation: Technical University of Munich
orcid: 'https://orcid.org/0000-0001-8331-0490'
doi: "10.1016/j.caeai.2022.100081"
journal: "Computers and Education: Artificial Intelligence"
title: "Machine learning based feedback on textual student answers in large courses"
volume: 3
year: 2022