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Record W3187464074 · doi:10.18260/1-2--37118

Examining In-Person and Asynchronous Information-Seeking Behavior Instruction Among First-Year Engineering Students

2024· article· en· W3187464074 on OpenAlexaff
George Lamont, Stephanie Mutch, Chimdindu Ohaegbu, Hamza Butt, Kate Mercer, Kari D. Weaver

Bibliographic record

Venue2021 ASEE Virtual Annual Conference Content Access Proceedings · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicLibrary Science and Information Literacy
Canadian institutionsWestern UniversityUniversity of Waterloo
Fundersnot available
KeywordsAsynchronous communicationComputer scienceInformation behaviorEngineering educationMathematics educationInformation seekingMultimediaHuman–computer interactionPsychologyEngineeringEngineering managementInformation retrievalComputer network

Abstract

fetched live from OpenAlex

This is a complete evidence-based practice paper.The current COVID-19 global pandemic has required educators to pioneer online instruction even as they deliver it.This shift has particularly impacted first-year programs, in which training engineering students to find reliable information is fundamental to their professional development and ABET and CEAB accreditation criteria.Typically, information seeking is taught in person so that instructors and librarians can directly observe and guide student behavior, a practice still evolving but well-established by research.However, the effects of online information-seeking training and the sudden transition on students' learning are very poorly understood.Even less is known about the use of asynchronous instructional methods.This paper significantly enhances existing knowledge by directly examining the efficacy of in-person and asynchronous online instructional modalities.For 60 students in a mandatory engineering-communication course, we deployed an enhanced online baseline-assessment exercise to understand students' existing information-seeking behavior.Librarians then deployed an asynchronous online lesson to teach engineering research practices, critical evaluation, and information literacy.We evaluated the extent to which the online lesson impacted student information-seeking behavior and compared it to existing data from the prior year's classroom version.Our results demonstrate that the asynchronous learning module significantly enhanced the students' critical evaluation of sources and student outcomes were comparable with results in the previous synchronous course.These results have dramatic implications for how we understand students' baseline information-seeking behaviors, pedagogical design to bring about meaningful changes in students' use of sources, and how course design can incorporate effective asynchronous online delivery in diverse models.

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)0.003
metaresearch head score (Gemma)0.010
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 score0.003
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.044
GPT teacher head0.283
Teacher spread0.239 · 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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Citations0
Published2024
Admission routes1
Has abstractyes

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