328
Views
0
CrossRef citations to date
0
Altmetric
Articles

Developing A Controlled Vocabulary for Curriculum Mapping: A Case Study

ORCID Icon, &
Pages 214-223 | Published online: 04 Jan 2021
 

ABSTRACT

The University of North Dakota (UND) School of Medicine & Health Sciences (SMHS) Medical Curriculum Committee (MCC) created the Curriculum Evaluation and Management Subcommittee (CEMS) in 2018. The committee was created to facilitate medical education curriculum content review and revision as discussed in Standard 8.3 of the Liaison Committee on Medical Education (LCME) accreditation standards. The subcommittee consisted of librarians, instructional designers, academic faculty, curriculum team leaders, and a curriculum database manager. The purpose of the group was to recommend policies and best practices to guide writing of learning objectives. The secondary goal for the group was to create a framework for mapping learning objectives within the curriculum and promote detailed mapping of curricular objectives for assessment and continued program accreditation. From the subcommittee’s inception, medical librarians advised the group to develop a controlled vocabulary to make curriculum mapping more efficient and led the group in developing one that matched the school’s mission and programming.

Acknowledgments

The authors would like to also acknowledge Dawn Hackman, MS, AHIP Medical School Librarian at the University of Minnesota Health Sciences Library who was part of the CEMS group at UND prior to changing positions.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 53.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 311.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.