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Record W1977788398 · doi:10.1080/02602930903337612

Student satisfaction with Canadian music programmes: the application of the American Customer Satisfaction Model in higher education

2010· article· en· W1977788398 on OpenAlexaffabout
Alexander Serenko

Bibliographic record

VenueAssessment & Evaluation in Higher Education · 2010
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCustomer Service Quality and Loyalty
Canadian institutionsLakehead University
Fundersnot available
KeywordsLoyaltyCustomer satisfactionPsychologyHigher educationWord of mouthMarketingQuality (philosophy)Minor (academic)Social psychologyAdvertisingBusinessPolitical science

Abstract

fetched live from OpenAlex

The purpose of this project is to empirically investigate several antecedents and consequences of student satisfaction (SS) with Canadian university music programmes as well as to measure students’ level of programme satisfaction. For this, the American Customer Satisfaction Model was tested through a survey of 276 current Canadian music students. The results indicate that customer satisfaction is strongly affected by programme quality, is slightly impacted by its perceived value but is not influenced by prior student expectations. Satisfaction strongly increases programme loyalty and positive word‐of‐mouth, marginally raises tuition change loyalty, and slightly decreases complaining behaviour. Contrary to expectations, tuition‐related constructs play only a minor role in the model. Therefore, money is a marginal factor in the educational environment; this empirically demonstrates the flaws underlying the premises of the students‐as‐customers metaphor. The resulting satisfaction index may facilitate the comparison among institutions. It was also found that the level of SS with Canadian music programmes was somewhat lower than those with services in other industries.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.324
Threshold uncertainty score0.686

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.047
GPT teacher head0.360
Teacher spread0.313 · 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 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

Citations66
Published2010
Admission routes2
Has abstractyes

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