Classification of open-ended responses to a research-based assessment using natural language processing-Reference-Cited by-同舟云学术

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Classification of open-ended responses to a research-based assessment using natural language processing

Published:2022-06-02 Issue:1 Volume:18 Page:
ISSN:2469-9896
Container-title:Physical Review Physics Education Research
language:en
Short-container-title:Phys. Rev. Phys. Educ. Res.

Author:

Wilson Joseph^ORCID,Pollard Benjamin^ORCID,Aiken John M.,Caballero Marcos D.^ORCID,Lewandowski H. J.

Funder

National Science Foundation

Norges Forskningsråd

Olav Thon Stiftelsen

Direktoratet for internasjonalisering og kvalitetsutvikling i høgare utdanning

Lappan-Philips Foundation

Publisher

American Physical Society (APS)

Subject

General Physics and Astronomy,Education

Link

http://harvest.aps.org/v2/journals/articles/10.1103/PhysRevPhysEducRes.18.010141/fulltext

Reference42 articles.

1. Resource Letter RBAI-1: Research-Based Assessment Instruments in Physics and Astronomy

2. Resource Letter RBAI-2: Research-based assessment instruments: Beyond physics topics

3. Theoretical perspectives of quantitative physics education research

4. Human vs. Computer Diagnosis of Students’ Natural Selection Knowledge: Testing the Efficacy of Text Analytic Software

5. A Learning Analytics Methodology for Detecting Sentiment in Student Fora: A Case Study in Distance Education

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1. Evaluating IBM’s Watson natural language processing artificial intelligence as a short-answer categorization tool for physics education research;Physical Review Physics Education Research;2024-03-22

2. Method to assess the trustworthiness of machine coding at scale;Physical Review Physics Education Research;2024-03-06

3. Physics language and language use in physics—What do we know and how AI might enhance language-related research and instruction;European Journal of Physics;2024-01-29

4. Toward AI grading of student problem solutions in introductory physics: A feasibility study;Physical Review Physics Education Research;2023-11-29

5. Toward intelligent open-ended questions evaluation based on predictive optimization;Expert Systems with Applications;2023-11

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