MétaCan
Menu
Back to cohort
Record W4212914669 · doi:10.37074/jalt.2022.5.s1.4

Social learning theory and academic writing in graduate studies

2022· article· en· W4212914669 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueJournal of Applied Learning & Teaching · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicHigher Education Practises and Engagement
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsPsychologySocializationPersuasionSocial learning theoryPedagogyMathematics educationSocial psychology

Abstract

fetched live from OpenAlex

Over the past 20 years, the Organization for Economic Co-operation and Development has reported a median of 50% for dropout rates in doctoral programs, all disciplines combined (OECD, 2019). Among reasons for not graduating, PhD students identify a lack of experience and competencies with academic writing, impeding on their progression as students, but also as novice scholars (Litalien & Guay, 2015). Indeed, graduate students are required to undergo professional socialization, by engaging with other scholars, to learn the norms and practices of their respective research fields (Skakni, 2011). This paper aims at communicating preliminary results from a doctoral research to provide a greater understanding of peer learning in academic writing groups organized by Master’s and PhD students. The social learning theory developed by Bandura (1971) is used as a foundation to our study, with its self-efficacy concept at the forefront of our theoretical framework. In that regard, PhD students can develop confidence in their abilities to successfully complete writing projects based on four sources of influence: mastery experiences; vicarious experiences; social persuasion; and physiological and emotional states (Bandura, 2019). While studying a learning community composed of 4,000 graduate students, as an instrumental case study (Stake, 1995), we conducted semi-structured interviews with 25 PhD students, followed by a content analysis of transcripts using a qualitative data analysis software (NVivo12). Participants representing 12 Canadian universities and 14 scholarly disciplines shared significant learning experiences related to all four self-efficacy sources of influence. Of particular interest, findings revealed that PhD students gathering in public places (cafes, libraries, coworking spaces, museums, parks) increased their self-efficacy through peer learning (exchanging, observing, modelling). These results are presented with a view of recommending valuable strategies to develop academic writing competencies through social actions led by graduate students, in conjunction with institutional support in the context of higher education.

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)0.022
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.181
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0220.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0040.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.005
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 head0.109
GPT teacher head0.429
Teacher spread0.319 · 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