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Record W4414577958 · doi:10.1177/19367244251372595

Exploring Student Experiences with Work-Integrated Learning in Undergraduate Sociology Courses

2025· article· en· W4414577958 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

VenueJournal of Applied Social Science · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicHigher Education and Employability
Canadian institutionsMacEwan University
Fundersnot available
KeywordsTeamworkIdeal (ethics)Sociology of EducationHigher educationBridge (graph theory)Space (punctuation)Student engagementSociological research

Abstract

fetched live from OpenAlex

Work-integrated learning (WIL) facilitates student opportunities to bridge classroom learning with practice and is becoming increasingly popular in higher education internationally. Sociology courses provide an ideal learning space to engage in WIL, allowing for the application of sociological skills and knowledge to a practical setting. Yet, research on WIL opportunities in undergraduate and sociology courses is limited. A survey was deployed to 240 students enrolled in seven different undergraduate sociology courses that incorporated WIL during the 2021/2022 and 2022/2023 school years to further understand student experiences with WIL opportunities and the perceived impacts. Findings from 26 respondents revealed that students found the experience to be relevant, valuable, and an effective learning opportunity. Students experienced challenges with teamwork and communication. The study adds to the literature examining student successes and challenges related to their WIL experiences and allows for student voices to be heard in discourses of WIL.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.091
Threshold uncertainty score0.971

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.003
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.064
GPT teacher head0.386
Teacher spread0.322 · 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