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Record W1921847714 · doi:10.5430/ijhe.v4n3p129

Real World Projects with Companies Supporting Competence Development in Higher Education

2015· article· en· W1921847714 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueInternational Journal of Higher Education · 2015
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicManagement and Marketing Education
Canadian institutionsnot available
Fundersnot available
KeywordsCompetence (human resources)Good practiceBusinessEngineering managementKnowledge managementEngineering ethicsEngineeringManagementComputer scienceEconomics

Abstract

fetched live from OpenAlex

The department of business administration of Münster University of Applied Sciences (MUAS) in Germany has a long tradition in realising practice-oriented research projects in cooperation with industry. The objective of these cooperative projects is to offer students real-life experiences and to make the theoretical know-how of university lectures more tangible by using it in an actual business case setting. Students are given responsibility for project deliveries fitting the expectations of real companies in their real business. Through the projects students are encouraged to develop individual learning and problem solving competencies. In this paper, four good practice examples for university-industry cooperation integrated in the education of students in the field of marketing, specifically market analysis, will be presented. The project descriptions will highlight the different methodological approaches, focusing on their specific innovative features. The paper will evaluate the competencies students gain during their involvement in those kind of projects. To follow a valid scientific approach, the competence matrix of Erpenbeck & Heyse will be presented and used to highlight the specific competences gained by the students working on those projects.

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.

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)0.000
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 score0.301
Threshold uncertainty score0.543

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.002
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 head0.043
GPT teacher head0.312
Teacher spread0.269 · 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