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ERIC Number: EJ1377776
Record Type: Journal
Publication Date: 2023
Pages: 17
Abstractor: As Provided
ISBN: N/A
ISSN: ISSN-1539-1523
EISSN: EISSN-1945-0818
Available Date: N/A
AI-Assisted Programming Question Generation: Constructing Semantic Networks of Programming Knowledge by Local Knowledge Graph and Abstract Syntax Tree
Journal of Research on Technology in Education, v55 n1 p94-110 2023
Creating practice questions for programming learning is not an easy job. It requires the instructor to diligently organize heterogeneous learning resources. Although educational technologies have been adopted across levels of programming learning, programming question generation (PQG) is still predominantly performed by instructors without advanced technological support. This study proposes a knowledge-based PQG model that aims to help the instructor generate new programming questions and expand the assessment items by the Local Knowledge Graph and Abstract Syntax Tree. A group of experienced instructors was recruited to evaluate the PQG model and expressed significantly positive feedback on the generated questions.
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Publication Type: Journal Articles; Reports - Research
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Grant or Contract Numbers: N/A
Author Affiliations: N/A