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Record W4388976976 · doi:10.5539/ies.v16n6p101

ESL Teachers’ Perceptions of the Individual Plan Measurement System (IPMS) and Its Impact on Professional Development

2023· article· en· W4388976976 on OpenAlexvenueno aff
P.M. Binu, Jayaron Jose

Bibliographic record

VenueInternational Education Studies · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicTechnology-Enhanced Education Studies
Canadian institutionsnot available
Fundersnot available
KeywordsProfessional developmentPlan (archaeology)PerceptionFaculty developmentPerformance appraisalPsychologyTask (project management)Medical educationDevelopment planPedagogyMathematics educationManagementEngineeringMedicine

Abstract

fetched live from OpenAlex

This research paper extrapolates the perceptions of English Language teachers about the effectiveness of the newly introduced Individual Plan Measurement System (IPMS) in terms of task performance at the University of Technology and Applied Sciences, Al Musannah (UTASA), Oman, and how this new performance appraisal system has contributed to teachers’ professional development. For the current study, the researchers employed a mixed methods approach by administering a survey questionnaire among the ESL teachers (N=31) of UTASA, conducting a semi-structured interview with selected staff members (N=7), and analyzing the data related to professional development activities conducted before and after the implementation of the new appraisal system. The study shows that most UTAS-A ELC staff perceive that IPMS has helped them plan and execute their professional goals effectively. Furthermore, the findings of the study highlight that a timebound individual plan guided and monitored by institutional agencies has a positive effect on employees’ intrinsic motivation and professional development, and it can make their task performance more efficient and systematic.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.532
Threshold uncertainty score0.624

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.181
GPT teacher head0.465
Teacher spread0.284 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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
Published2023
Admission routes1
Has abstractyes

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