MétaCan
Menu
Back to cohort
Record W4406408711 · doi:10.5539/elt.v18n2p11

Teaching Practicums at the Postgraduate Level: Problems, Solutions, and Recommendations

2025· article· en· W4406408711 on OpenAlexvenueno aff
Listyani Listyani

Bibliographic record

VenueEnglish Language Teaching · 2025
Typearticle
Languageen
FieldHealth Professions
TopicDoctoral Education Challenges and Solutions
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyMathematics educationPedagogy

Abstract

fetched live from OpenAlex

In any educational study program, teaching practicums are necessary to be implemented. It often serves as an apprenticeship to give pre-service teachers practical experience regarding the real world of teaching. It is commonly implemented at the undergraduate level. At the postgraduate level, however, this implementation remains controversial. This study was conducted to reveal postgraduate students’ problems and solutions during their teaching practicums. Besides that, this study also aimed to examine and give critical insights into the implementation of teaching practicums at the postgraduate level for educational study program students. Data was retrieved from open-ended questionnaires to 8 postgraduate students about their problems and solutions in doing their teaching practicums. Data was also taken from 7 other respondents. They were practitioners like lecturers, teachers, and alumni from educational departments. The findings revealed that in doing their teaching practicums, the master’s degree students dealt with various problems similar to those faced by their undergraduate counterparts. Another finding disclosed the practitioners’ opinions that for the postgraduate level, the focus of teaching practicums can be altered and implemented in a form other than teaching. It can be research, curriculum development, language teaching technology development, and material development. At the postgraduate level, students are expected to focus on research, not just the practice of teaching.

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.

How this classification was reachedexpand

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)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.524
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0060.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
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 head0.151
GPT teacher head0.497
Teacher spread0.347 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designQualitative
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueEnglish Language TeachingSame topicDoctoral Education Challenges and SolutionsFrench-language works237,207