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Record W2116889900 · doi:10.3138/jelis.56.3.213

Studying Online: Student Motivations and Experiences in ALA-Accredited LIS Programs

2015· article· en· W2116889900 on OpenAlex
Fatih Oguz, Clara M. Chu, Anthony W. Chow

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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of Education for Library and Information Science · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicOnline and Blended Learning
Canadian institutionsnot available
Fundersnot available
KeywordsAccreditationHigher educationMedical educationLibrary sciencePsychologyPedagogySociologyComputer sciencePolitical scienceMedicine

Abstract

fetched live from OpenAlex

This paper presents a large scale study of online MLIS students (n = 910), who completed at least one online course and were enrolled in 36 of the 58 ALA-accredited MLIS programs in Canada and the United States. The results indicate that the typical student is female, White, lives in an urban setting, and is in her mid-30s. Online students were found to be quite diverse, with statistically significant differences in their preferences and satisfaction across five demographic variables: age (generational cohort), employment status, urban status, commute distance, and program modality. Three motivations emerged: accommodation, predisposition, and selectivity, which influenced the respondents to choose online learning. The prevalent issues online MLIS students experienced were a sense of isolation from peers and instructors, and a lack of professional development and networking opportunities with peers. The findings have implications for enhancing MLIS online education including marketing, course offerings, and student support services.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.366
Threshold uncertainty score0.985

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.029
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 head0.052
GPT teacher head0.373
Teacher spread0.321 · 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