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Continuous Improvement Philosophy in Higher Education

2019· book-chapter· en· W2969872528 on OpenAlexaff
Parminder Singh Kang, Rajbir Singh Bhatti, Gurinder Singh

Bibliographic record

VenueAdvances in higher education and professional development book series · 2019
Typebook-chapter
Languageen
FieldBusiness, Management and Accounting
TopicQuality and Supply Management
Canadian institutionsMount Royal UniversityUniversity of Saskatchewan
Fundersnot available
KeywordsWorkflowLean manufacturingContext (archaeology)Process (computing)Toyota Production SystemEngineeringWork (physics)Process managementManagement philosophyProduction (economics)Lean constructionValue stream mappingKnowledge managementManufacturing engineeringEngineering managementComputer scienceManagementMechanical engineeringConstruction engineering

Abstract

fetched live from OpenAlex

This chapter explores the unspoken roles of Toyota production system in the context of program/course delivery process. These rules are; how people work, how people connect, how the workflow is organized, how to improve and who does the improvements. These four unspoken rules of Toyota production system are strict guidelines from the shop floor to the top-level management. Toyota production system emphasizes learner's philosophy to improve the value-added activities by understanding the root cause of a given problem. Under these four rules, further, this chapter will look into the different tools that could be applied for the continuous improvement in course/program delivery process. This paper will define the lean principles and waste in the context of the delivery process.

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)0.002
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.005
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.006
Scholarly communication0.0040.003
Open science0.0010.001
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0050.001

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 head0.026
GPT teacher head0.276
Teacher spread0.250 · 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 designTheoretical or conceptual
Domainnot available
GenreOther

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".

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Citations0
Published2019
Admission routes1
Has abstractyes

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