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Record W2150233247 · doi:10.5539/ies.v2n4p117

Evaluation from Students—A Case Study in Construction Engineering Technology of YAU

2009· article· en· W2150233247 on OpenAlexvenueno aff
Liping Chen

Bibliographic record

VenueInternational Education Studies · 2009
Typearticle
Languageen
FieldSocial Sciences
TopicReflective Practices in Education
Canadian institutionsnot available
Fundersnot available
KeywordsMathematics educationProcess (computing)Teaching methodPsychologyEngineering educationWork (physics)PedagogyComputer scienceEngineeringEngineering management

Abstract

fetched live from OpenAlex

This paper not only aims to present the feedback received from the students, but also evaluate the feedback by review the teaching practice. It analyses the teacher should be aware of the importance that feedback, both to and from the students, has upon the teaching and learning process. Through a case study about the feedback from the students in Construction Engineering Technology of YAU, the author gives some suggestions on the teaching that the teacher’s reflective evaluation can refine the teaching and help them to be better teachers. The teacher may incorporate feedback into practice, which teachers, like students, can benefits from assessment and evaluation of their own work or practice.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.019
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.008
Threshold uncertainty score0.043

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.019
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0060.003
Scholarly communication0.0030.001
Open science0.0010.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0020.001

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 head0.087
GPT teacher head0.551
Teacher spread0.464 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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
Published2009
Admission routes1
Has abstractyes

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