Margaret Phillips, Amy Van Epps, Nastasha Johnson, and Dave Zwicky. 11/23/2018. “
Effective Engineering Information Literacy: A Systematic Literature Review.” Journal of Academic Librarianship, 44, 6, Pp. 705-711.
Publisher's VersionAbstractThe objective of this study was to investigate effective methods of teaching information literacy to engineering undergraduate students. The authors searched several databases (e.g., Compendex, Scopus, ERIC) for English language studies published between January 2000 and January 2016 that contained both an information literacy intervention for engineering undergraduate students and an assessment method for evaluating the intervention's effectiveness. Thirteen studies were included in the final data set, of which eleven studies reported effective results based largely upon descriptive statistical analysis. The strongest indicator of effectiveness that emerged in the data was collaboration with disciplinary faculty. With few articles in the final results set containing inferential statistics, the authors were only able to draw limited conclusions regarding effectiveness. The low use of such statistical methods highlights a need for librarian researchers to develop skills with research design and statistical analysis. This study is one of few systematic reviews on the topic of information literacy and the first systematic review on engineering information literacy effectiveness. It intends to serve as a baseline for future work.
Michael Fosmire and Amy S. Van Epps. 2018. “
Competency-Based Education, Badging, and the Library.” In Teaching with Digital Badges: Best Practices for Libraries, Pp. 131-146. Lanham, MD: Rowman & Littlefield.
Kerrie A. Douglas, Todd M. Fernandez, Şenay Purzer, Michael Fosmire, and Amy S. Van Epps. 2018. “
The Critical-Thinking Engineering Information Literacy Test (CELT): A Validation Study for Fair Use Among Diverse Students.” International Journal of Engineering Education, 34, 4, Pp. 1347–1362.
Publisher's VersionAbstractInformation literacy and lifelong learning are essential for engineers as they constantly renew and expand their knowledge and skills to keep abreast with the development of new technologies. However, the lack of validated information literacy assessments relevant for engineering students makes it difficult to determine how well those students are acquiring needed information literacy skills. We describe validity evidence for the Critical-Thinking Engineering Information Literacy Test (CELT), an instrument designed to assess students’ information literacy associated with critical thinking in an engineering context. By examining psychometric properties of CELT through Rasch modeling applications, we present evidence of appropriate and fair use of CELT among first-year engineering student populations. From our analysis, we find that CELT is appropriate for use in the classroom to assess information skills associated with critical thinking among first-year engineering students, when students’ experience with English language is part of their score interpretation. We discuss specific recommendations for use with students who have little experience learning in an English language environment.
Margaret Phillips, Amy S. Van Epps, Dave Zwicky, and Nastasha Johnson. 2018. “
Effective Methods of Engineering Information Literacy: Initial Steps of a Systematic Literature Review and Observations about the Literature.” ASEE Annual Conference and Exposition. Salt Lake City, UT: ASEE.
Publisher's VersionAbstractBackground – There is a body of information literacy (IL) literature applied to undergraduate engineering students, much of which discusses different methods for teaching, such as classes/one-shots, online tutorials, gaming, and other interventions. It is important for librarians to know which methods of teaching engineering information literacy (EIL) are most effective for student learning, in order to make efficient and effective use of student and librarian time.
Purpose/Hypothesis – The authors reviewed the existing literature to find indications of the most effective methods for teaching and/or integrating EIL, both in face-to-face and online instruction.
Design/Method – The authors have completed the first stages of a systematic literature review (SLR), through the creation of the final dataset. The initial searches generated a set of 1224 papers prior to duplicate removal. Duplicate removal and multiple rounds of review, using authors-created inclusion and exclusion criteria, narrowed the final dataset to 13 papers.
Scope/Method – The lessons learned in the process around searching, tools for data evaluation, and articulation of criteria are presented. As a result of this portion of the SLR process, the authors identified characteristics of the undergraduate-focused EIL literature that are shared.
Results/Discussion – A brief summary of the process to arrive at a final dataset of 13 papers, the challenges in the process, and the refinements made at each step how many showed an effective intervention, and typical types of assessment are outlined.
Conclusion – There are several preliminary conclusions to be drawn, many of which will not be surprising to the engineering librarian community. The dataset came down to just 13 items because much of the EIL literature is based on student self-report data on how the class went, or was it enjoyable, rather than on actual student learning gains. As such, these papers did not meet the criteria for demonstrated learning gains as a measure of effectiveness. In addition, some papers were excluded for lack of clarity about methods. In these studies it is not evident how either the intervention and/or the assessment was conducted, with regard to timing, instrument used, etc. Some additional papers were excluded because a control or comparison group was not included to establish “effectiveness” of the intervention. Overall, the authors note the EIL literature frequently reports descriptive statistics, showing that data has been gathered, but sometimes falls short of a full analysis that allows the researchers to draw meaningful/well grounded conclusions from the data.