MétaCan
Menu
Back to cohort
Record W4313569887 · doi:10.29173/istl2725

Information Literacy Instruction in Engineering Graduate Courses: Instructional Design and Reflection

2022· article· en· W4313569887 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueIssues in Science and Technology Librarianship · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicLibrary Science and Information Literacy
Canadian institutionsWestern University
Fundersnot available
KeywordsInformation literacyCurriculumLibrary instructionMathematics educationGraduate studentsReflection (computer programming)Computer scienceWork (physics)Critical thinkingMedical educationPsychologyPedagogyEngineering

Abstract

fetched live from OpenAlex

Prior research on information literacy instruction in engineering graduate programs rarely considers course instructor perspectives, and instead only uses student feedback to evaluate the efficacy of information literacy instruction. This study documents the authors’ efforts to evolve the library curriculum to motivate student learning and meet the course needs. Data collected from the student survey and course instructor questionnaire found that most students reported that the instruction was engaging and satisfying, but evaluations of the usefulness of the instruction were mixed. The course instructor was satisfied with the students’ overall work in information gathering though found their project reports unsatisfactory in terms of report writing and critical thinking. The findings shed light on student needs and faculty expectations of engineering project-based graduate courses.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.542
Threshold uncertainty score0.980

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.005
Science and technology studies0.0010.001
Scholarly communication0.0000.033
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.027
GPT teacher head0.298
Teacher spread0.271 · 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