MétaCan
Menu
Back to cohort
Record W4403199070 · doi:10.3126/fwr.v2i1.70497

Academic Writing Challenges and Encouragements: Perspectives of University Teachers in Far Western University

2024· article· en· W4403199070 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

VenueFar Western Review · 2024
Typearticle
Languageen
FieldComputer Science
TopicEducational Methods and Teacher Development
Canadian institutionsWestern University
Fundersnot available
KeywordsPsychologyPedagogySociologyMathematics educationLibrary scienceComputer science

Abstract

fetched live from OpenAlex

While academic writing skills constitute a central place in master’s level courses at universities, institutional support for students has often been lacking. As a result, students face challenges in producing scholarly writing. In this study, I attempted to explore the academic writing challenges and encouragements to enhancing academic writing of master’s level students from the perspectives of university teachers at Far Western University of Nepal. This is a qualitative study. The data were collected through semi-structured interviews. Five university teachers from three different disciplines were selected as the research participants. The study shows that students’ awareness of academic writing is very low. Additionally, the traditional role of supervisors has negative effects on students’ academic writing. The study, however, reveals that training, workshops, virtual seminars and individual feedback have contributed to improving their academic writing. The study concludes that there is no adequate provision for research, and the university does not seem to have visible policies and plans for developing students’ academic writing.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.894
Threshold uncertainty score0.476

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.074
GPT teacher head0.335
Teacher spread0.261 · 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