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programming concepts in programming assignments in a CS1 course. We seek to answer the following research questions: RQ1. How effectively can large language models identify knowledge components in a CS1 course from programming assignments? RQ2. Can large language models be used to extract program-level knowledge components, and how can the information be used to identify students’ misconceptions? Preliminary results demonstrated a high similarity between course-level knowledge components retrieved from a large language model and that of an expert-generated list.
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From "Hello, World!" to Fourier transformations: Teaching linguistics undergraduates to code in ten weeks or less
I used Backward Design to scaffold ten weeks of assignments that taught students how to perform sine wave vowel synthesis and a Fourier transformation approximation using just a few fundamental programming concepts. This strategy gave all students, regardless of their previous programming experience, the opportunity to implement algorithms related to core concepts in phonetics and speech technology. Reflecting on the course, it seems that the coding assignments were generally well-received by students and contributed to students programming something complex and meaningful.
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- Award ID(s):
- 1924593
- PAR ID:
- 10357080
- Date Published:
- Journal Name:
- Proceedings of the Linguistic Society of America
- Volume:
- 6
- Issue:
- 2
- ISSN:
- 2473-8689
- Page Range / eLocation ID:
- 5135
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.3765/plsa.v6i2.5135
