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Using Decision-based Learning to Develop Expert Information Literacy Behaviors in Engineering Undergraduates

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Conference

2023 ASEE Annual Conference & Exposition

Location

Baltimore , Maryland

Publication Date

June 25, 2023

Start Date

June 25, 2023

End Date

June 28, 2023

Conference Session

Engineering Libraries Division (ELD) Technical Session 3: Instruction & Information Literacy

Tagged Division

Engineering Libraries Division (ELD)

Page Count

18

DOI

10.18260/1-2--44571

Permanent URL

https://peer.asee.org/44571

Download Count

178

Paper Authors

biography

David Pixton Brigham Young University Orcid 16x16 orcid.org/0000-0001-8128-628X

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David Pixton is a subject liaison at the Harold B. Lee Library at Brigham Young University. In this role, he is responsible for providing research training and assistance to students and faculty within the majority of engineering and technology fields offered at the university. He holds degrees in Mechanical Engineering and Library & Information Science. David’s current research is focused on improving learning in a library environment, including the use of augmented reality for educational purposes, and the pedagogical method described herein, namely, Decision-based Learning.
Prior to coming to BYU, David served in industry as a mechanical engineer and engineering leader for more than 30 years, serving the energy and diamond manufacturing industries. He has spearheaded several collaborations with members of industry, government, and academia, which have led to the development of advanced products ranging from downhole drilling tools and services to technology enablers such as engineered polycrystalline diamond composites. David is an original co-inventor of the IntelliServ wired drill pipe technology and holds more than 30 patents in this and other technical areas.
David is a member of the American Society for Engineering Education, where he serves on the Publications and Scholarly Communication committees in the Engineering Libraries Division. He is also a member of the Special Libraries Association, serves the Utah Library Association as chair of the Copyright Education Roundtable, and is chair of the Scholarly Communications committee at the Harold B. Lee Library.

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Abstract

The ACRL Framework for Information Literacy in Higher Education describes desirable information literacy competencies in terms of novice and expert behaviors. One may reasonably argue that it is outside of the scope of a university education to fully achieve the expert level of behavior described. However, choices in designing information literacy instruction can improve chances of a measure of expertise being developed even prior to graduation. One element of expertise that is often overlooked in instructional programs is the framing of the conditions under which certain methods of inquiry or analysis are to be used. Often, the conditions of use are obvious inside of the academy, given the context of the assignment or unit of study. However, when that context is removed and students are given a real-world problem, they may struggle to identify the proper tools to use because they have yet to develop a schema that guides this kind of decision making. This understanding or “conditional knowledge” – knowledge of when to use the tools at one’s disposal – is one of the key distinguishing attributes of experts. One method for helping students explicitly develop conditional knowledge is called Decision-based Learning (DBL). This paper describes continuing efforts to employ DBL techniques in undergraduate information literacy instruction, in furtherance of expert literacy skill levels identified in ACRL’s Framework (a work-in-progress). It summarizes results of recently published studies in this area and explores different areas within the domain of college-level information literacy where developing conditional knowledge may provide the largest gains in information literacy education. Focus is placed on concepts of particular interest to engineering undergraduate students. Finally, the paper provides examples of possible ways of incorporating DBL to teach these principles and provides observations from a pilot implementation of these example DBL models.

Pixton, D. (2023, June), Using Decision-based Learning to Develop Expert Information Literacy Behaviors in Engineering Undergraduates Paper presented at 2023 ASEE Annual Conference & Exposition, Baltimore , Maryland. 10.18260/1-2--44571

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