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ERIC Number: ED621737
Record Type: Non-Journal
Publication Date: 2022
Pages: 24
Abstractor: As Provided
ISBN: N/A
ISSN: N/A
EISSN: N/A
Available Date: N/A
Exploring Automated Classification Approaches to Advance the Assessment of Collaborative Problem Solving Skills
Jessica Andrews-Todd; Jonathan Steinberg; Michael Flor; Carolyn M. Forsyth
Grantee Submission, Journal of Intelligence v10 Article 39 2022
Competency in skills associated with collaborative problem solving (CPS) is critical for many contexts, including school, the workplace, and the military. Innovative approaches for assessing individuals' CPS competency are necessary, as traditional assessment types such as multiple-choice items are not well suited for such a process-oriented competency. In a move to computer-based environments to support CPS assessment, innovative computational approaches are also needed to understand individuals' CPS behaviors. In the current study, we describe the use of a simulation-based task on electronics concepts as an environment for higher education students to display evidence of their CPS competency. We further describe computational linguistic methods for automatically characterizing students' display of various CPS skills in the task. Comparisons between such an automated approach and an approach based on human annotation to characterize student CPS behaviors revealed above average agreement. These results give credence to the potential for automated approaches to help advance the assessment of CPS and to circumvent the time-intensive human annotation approaches that are typically used in these contexts.
Related Records: EJ1354059
Publication Type: Journal Articles; Reports - Research
Education Level: Higher Education; Postsecondary Education
Audience: N/A
Language: English
Sponsor: Institute of Education Sciences (ED)
Authoring Institution: N/A
IES Funded: Yes
Grant or Contract Numbers: R305A170432
Author Affiliations: N/A