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Record W2143974165 · doi:10.5539/ies.v6n6p161

Direct Measurement and Evaluation for Mechanical Engineering Programme Outcomes: Impact on Continuous Improvement

2013· article· en· W2143974165 on OpenAlexvenueno aff
Mohd Faizal Mat Tahir, Nor Kamaliana Khamis, Zaliha Wahid, Ahmad Kamal Ariffin, Jaharah Ab Ghani, Mohd Anas Mohd Sabri, Zainuddin Sajuri, Shahrum Abdullah, Abu Bakar Sulong

Bibliographic record

VenueInternational Education Studies · 2013
Typearticle
Languageen
FieldEngineering
TopicEngineering Education and Curriculum Development
Canadian institutionsnot available
Fundersnot available
KeywordsAccreditationAuditSession (web analytics)Engineering educationMedical educationData collectionMicrosoft excelProcess (computing)Program evaluationEngineeringEngineering managementComputer scienceMathematicsMedicineAccountingBusiness

Abstract

fetched live from OpenAlex

Universiti Kebangsaan Malaysia (UKM) is a research university that continuously undergoes an audit and accreditation process for the management of its courses. The Faculty of Engineering and the Built Environment (FKAB) is subjected to such processes, one of them is the auditing conducted by the Engineering Accreditation Council (EAC), which gives recognition to engineering programmes in Malaysia. The criteria that have been set by the EAC requires the faculty to measure and evaluate graduates based directly on the course outcomes (CO) and programme outcomes (POs) to ensure that they are able to achieve the programme and course objectives. This paper discusses a method developed for the measurement and evaluation of POs which is a direct measurement for assessing the courses offered in the mechanical engineering programme. Assessment templates are developed using a Microsoft Excel based on the data presented on the grade coordination meetings conducted at the end of each semester. The data used for this study were semester 2 2010/2011 session, and semester 1 session 2011/2012. Based on the results obtained, the majority of the courses achieves more than 80% for course level monitoring for their individual PO achievement except for five subjects. For programme level monitoring, from the average POs marks, all POs were scored more than 80%, which indicates that the Mechanical Programs offered by the department are satisfied with the department standard.

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)0.000
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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.808
Threshold uncertainty score0.614

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.052
GPT teacher head0.347
Teacher spread0.295 · 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 designOther design
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

Citations2
Published2013
Admission routes1
Has abstractyes

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