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Record W4293251376 · doi:10.3389/feduc.2022.891534

Academic Writing Challenges and Supports: Perspectives of International Doctoral Students and Their Supervisors

2022· article· en· W4293251376 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.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueFrontiers in Education · 2022
Typearticle
Languageen
FieldHealth Professions
TopicDoctoral Education Challenges and Solutions
Canadian institutionsUniversité de MontréalQueen's University
FundersQueen's University
KeywordsFocus groupAcademic writingMedical educationQualitative propertyGraduate studentsQualitative researchMathematics educationPsychologyComputer sciencePedagogySociologyMedicine

Abstract

fetched live from OpenAlex

Introduction Academic writing is a core element of a successful graduate program, especially at the doctoral level. Graduate students are expected to write in a scholarly manner for their thesis and scholarly publications. However, in some cases, limited or no specific training on academic writing is provided to them to do this effectively. As a result, many graduate students, especially those having English as an Additional Language (EAL), face significant challenges in scholarly writing. Further, faculty supervisors often feel burdened by reviewing and editing multiple drafts and find it difficult to help and support EAL students in the process of scientific writing. In this study, we explored academic writing challenges faced by EAL doctoral students and faculty supervisors at a research intensive post-secondary university in Canada. Methods and Analysis We conducted a sequential explanatory mixed-method study using an online survey and subsequent focus group discussions with EAL doctoral students (n = 114) and faculty supervisors (n = 31). A cross-sectional online survey was designed and disseminated to the potential study participants using internal communications systems of the university. The survey was designed using a digital software called Qualtrics™. Following the survey, four focus group discussions (FGDs) were held, two each with two groups of our participants with an aim to achieve data saturation. The FGD guide was informed by the preliminary findings of the survey data. Quantitative data was analyzed using Statistical Package of Social Sciences (SPSS) and qualitative data was managed and analyzed using NVivo. Discussion The study findings suggest that academic writing should be integrated into the formal training of doctoral graduate students from the beginning of the program. Both students and faculty members shared that discipline-specific training is required to ensure success in academic writing, which can be provided in the form of a formal course specifically designed for doctoral students wherein discipline-specific support is provided from faculty supervisors and editing support is provided from English language experts. Ethics and Dissemination The general research ethics board of the university approved the study (#6024751). The findings are disseminated with relevant stakeholders at the university and beyond using scientific presentations and publications.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.355
Threshold uncertainty score0.400

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 integrity0.0000.001
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 head0.476
Teacher spread0.367 · 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