Competency-Based Education/Training (CBE/CBT) in data services: Data Service Continuing Professional Education (DSCPE) and learning outcomes
Tang, Rong; Hu, Zhan; Martin, Elaine; Thomas, Ashley M.; Shahvar, Shabnam S.
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https://hdl.handle.net/2142/123058
Description
Title
Competency-Based Education/Training (CBE/CBT) in data services: Data Service Continuing Professional Education (DSCPE) and learning outcomes
Author(s)
Tang, Rong
Hu, Zhan
Martin, Elaine
Thomas, Ashley M.
Shahvar, Shabnam S.
Issue Date
2023-09
Keyword(s)
Comparative Analysis
Competency-based Education
Curriculum
Data Services Training
Education
Education Programs/schools
Pedagogy
Pre-program and Post-program Learning Outcomes
Knowledge, Skills and Abilities (KSA)
Students
Abstract
In this paper, we report the findings of the evaluation data from the Data Services Continuing Professional Education (DSCPE) program. Using the Competency-Based Education/Training (CBE/CBT) approach, the DSCPE program fills a much-needed gap in data services training of working librarians. Our analysis focuses on the Knowledge, Skills, and Abilities (KSAs) as learning outcomes expressed by students via a pre-program survey and personal statement, and learning outcomes achieved based on students’ post-program survey, the focus group session, and their capstone presentation. Seventeen KSAs identified by participants pre-program matched the KSAs that participants reported they obtained through DSCPE. There were four matched items between mentors' feedback and students expected or achieved KSAs. The focus on competencies is one of the key factors that led to the success of DSCPE, and specific program evaluation data zero in on KSAs also helped to highlight the matched learningoutcomes and identify areas where the DSCPE can improve for future cohorts.
Series/Report Name or Number
Proceedings of the ALISE Annual Conference, 2023
Type of Resource
text
Language
eng
Handle URL
https://hdl.handle.net/2142/123058
DOI
https://doi.org/10.21900/j.alise.2023.1276
Copyright and License Information
Copyright 2023 Rong Tang, Zhan Hu, Elaine Martin, Ashley M. Thomas, Shabnam S. Shahvar
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License (https://creativecommons.org/licenses/by-sa/4.0/).
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