The Practical Value of Information Literacy in the Workplace
Bibliographic record
Abstract
This video was produced for an information literacy course at the University of Ottawa's École School of Information Studies (ÉSIS). It is shared as an open education resource to be (re)used to teach viewers about the value of information literacy in the workplace. The video aims to briefly outline workplace literacy expectations for novice job seekers wanting to increase their employability. The video’s objective is to make (under)graduate students aware of the key information literacy skills that employers are looking for in new hires, and provide some suggested resources to improve or acquire these skills. The video is meant to be a starting point to build on students' awareness of information literacy skills and how these skills will be valuable in the workplace. This builds on the core concept of "Information Has Value" from the Association of College & Research Libraries' <em>Framework for Information Literacy for Higher Education</em> (2015).<strong> </strong> Learning objectives include knowing why an employee needs information, where and how information can be found, and how information is used and presented in the workplace. The video was produced using Microsoft PowerPoint, Canva, Slidesgo and Screencast-o-matic. The following references were used to inform the video content: Cheuk, B. (2008). Delivering business value through information literacy in the workplace. <em>Libri, 58</em>(3), 137–143. https://doi.org/10.1515/libr.2008.015 Geisinger, K. F. (2016). 21st century skills: What are they and how do we assess them? <em>Applied Measurement in Education, 29</em>(4), 245–249. https://doi.org/10.1080/08957347.2016.1209207 Hamlett, A. (2021). Getting to work. <em>Journal of Information Literacy, 15</em>(2), 166–177. https://doi.org/10.11645/15.2.2857 Hart Research Associates. (2015). <em>Falling short? College learning and career success. Selected findings from online surveys of employers and college students conducted on behalf of the Association of American Colleges & Universities</em>. https://dgmg81phhvh63.cloudfront.net/content/user-photos/Research/PDFs/2015employerstudentsurvey.pdf Head, A. J. (2012). Learning curve: How college graduates solve information problems once they join the workplace. <em>SSRN Electronic Journal</em>. https://doi.org/10.2139/ssrn.2165031 Head, A. J. (2016). Staying smart: How today’s graduates continue to learn once they complete college. <em>SSRN Electronic Journal</em>. https://doi.org/10.2139/ssrn.2712329 Head, A. J., Hoeck, M. V., Eschler, J., & Fullerton, S. (2013). What information competencies matter in today’s workplace? <em>Library and Information Research, 37</em>(114), 74–104. https://doi.org/10.29173/lirg557 Hoffman, N. (2016). Guttman Community College puts “work” at the center of learning: An approach to student economic mobility. <em>Change, 48</em>(4), 14–23. https://doi.org/10.1080/00091383.2016.1198167 Jewell, P., Reading, J., Clarke, M., & Kippist, L. (2020). Information skills for business acumen and employability: A competitive advantage for graduates in Western Sydney. <em>Journal of Education for Business, 95</em>(2), 88–105. https://doi.org/10.1080/08832323.2019.1610346 Rainie, L., & Anderson, J. (2017). <em>The future of jobs and jobs training.</em> Pew Research Center. https://www.proquest.com/docview/1904675911?parentSessionId=ZC%2F3xfG3CZGmYbJM0fE4NhuW5HQPbFkfieMUZFD57mU%3D&pq-origsite=primo&
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.060 | 0.003 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".