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Understanding Undergraduate Engineering Student Information Access and Needs: Results from a Scoping Review

Conference Session
Informing the Critical Understanding of Our Users: Using Data to Develop New and Diverse Services
Collection
2019 ASEE Annual Conference & Exposition
Authors
Kate Mercer, University of Waterloo; Kari D. Weaver, University of Waterloo; Ariel Jocelyn Stables-Kennedy, Western University
Tagged Topics
Diversity
Tagged Divisions
Engineering Libraries
Paper ID #24617Understanding Undergraduate Engineering Student Information Access andNeeds: Results from a Scoping ReviewMs. Kate Mercer, University of Waterloo Kate Mercer is the liaison librarian for Systems Design Engineering, Electrical & Computer Engineering and Earth & Environmental Sciences at the University of Waterloo. Kate’s main duties include providing instruction and research services to students, faculty and staff. Kate graduated with a MI from the Univer- sity of Toronto in 2011, and in addition to her job as a liaison librarian is a PhD Candidate at the University of Waterloo’s School of
Relevance Score: 0.59928423

Raising Algorithm Bias Awareness Among Computer Science Students Through Library and Computer Science Instruction

Conference Session
Engineering Libraries Division Technical Session 1: Diversity
Collection
2021 ASEE Virtual Annual Conference Content Access
Authors
Shalini Ramachandran, Boise State University; Steven Matthew Cutchin, Boise State University; Sheree Fu, California State University, Los Angeles
Tagged Topics
Diversity
Tagged Divisions
Engineering Libraries
responses from a range of computer science students from first year tograduate students. It should be mentioned that our study is not intended to be a completeformal quantitative investigation. Validation of the results with larger studies may berequired.The total number of raw data responses from all three institutions was 815. After cleaning theraw data to remove responses without signed consent, the total number of responses was 782.The full set of questions that were asked is included in Appendix A.Opinions of the respondents regarding the questions on search engine results and algorithm biaswere recorded in the form of a 7-point Likert scale ranging from “Strongly disagree” to“Strongly agree”. A sampling issue with the respondents was that
Relevance Score: 0.3507893