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Record W2434034758 · doi:10.18438/b8h059

Information Literacy Course Yields Mixed Effects on Undergraduate Acceptance of the University Library Portal

2016· article· en· W2434034758 on OpenAlexvenueno aff
Heather Coates

Bibliographic record

VenueEvidence Based Library and Information Practice · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicLibrary Science and Information Literacy
Canadian institutionsnot available
Fundersnot available
KeywordsInformation literacyMedical educationPsychologyAcademic yearLibrary instructionMathematics educationMedicinePedagogy

Abstract

fetched live from OpenAlex

Objective – To determine the effects over time of a 3-credit semester-long undergraduate information literacy course on student perception and use of the library web portal. Design – Mixed methods, including a longitudinal survey and in-person interviews. Setting – Information literacy course at a comprehensive public research institution in the northeastern United States of America. Subjects – Undergraduates at all levels enrolled in a 3-credit general elective information literacy course titled “The Internet and Information Access.” Methods – A longitudinal survey was conducted by administering a questionnaire to students at three different points in time: prior to instruction, near the end of the course (after receiving instruction on the library portal), and three months after the course ended, during the academic year 2011-2012. The survey was created by borrowing questions from several existing instruments. It was tested and refined through pre-pilot and pilot studies conducted in the 2010-2011 academic year, for which results are reported. Participation was voluntary, though students were incentivized to participate through extra credit for completing the pre- and post-instruction questionnaire, and a monetary reward for completing the follow-up questionnaire. Interviews were conducted with a subset of 14 participants at a fourth point in time. Main Results – 239 of the 376 (63.6%) students enrolled in the course completed the pre- and post-instruction questionnaire. Fewer than half of those participants (111 or 30% of students enrolled) completed the follow-up questionnaire. Participants were primarily sophomores and juniors (32% each), with approximately one-quarter (26%) freshman, and only 10% seniors. Student majors were concentrated in the social sciences (62%), with fewer students from science and technology (13%), business (13%), and the humanities (9%). The 14 participants interviewed were drawn from both high- and low-use students. Overall, the course had a positive effect on students’ perception of usefulness (PU) and ease of use (PEOU), as well as usage of the library portal. This included significant positive changes in perceived ease of use and information quality in the short-term (from pre-instruction to post-instruction). The results were mixed for perceived usefulness and system quality. Though there was mixed long-term impact on usage, the course does not appear to have had a long-term effect on PU and PEOU. The interview participants were asked questions to explore why and how they used the library portal, and revealed that both high- and low-use students used the library portal for similar reasons: to find information for research papers or projects, to search the library catalogue for books, and in response to a mandate or encouragement from instructors. Conclusion – The study supports the theory that an information literacy course could change student perception and use of the library portal in the short-term. Replicating this design in other settings could provide a systematic approach for assessing whether information literacy courses address learning outcomes over time. A longitudinal approach could be useful for comparing proficiency and information behaviors of those who take information literacy courses with those who do not.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.014
metaresearch head score (Gemma)0.029
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.023
Threshold uncertainty score0.077

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.029
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.003
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0030.001
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0230.002

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.

Opus teacher head0.007
GPT teacher head0.246
Teacher spread0.238 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations1
Published2016
Admission routes1
Has abstractyes

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