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Record W2901922900 · doi:10.5539/hes.v8n4p177

Empirically Supported Development of Specialisation Courses for Extra-Occupational Studies within the Discipline of Business Informatics

2018· article· en· W2901922900 on OpenAlex
Michael Städler, Knut Linke, André von Zobeltitz

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

VenueHigher Education Studies · 2018
Typearticle
Languageen
FieldComputer Science
TopicEducational Innovations and Challenges
Canadian institutionsnot available
FundersBundesministerium für Bildung und Forschung
KeywordsCurriculumInformaticsBusiness informaticsMedical educationPedagogyEngineering ethicsPsychologyEngineeringHealth informaticsMedicineNursing

Abstract

fetched live from OpenAlex

This article contains the analytical results of qualitative and descriptive research regarding the definition of specialisation courses in the areas of "Informatics" and "Management" for extra-occupational study offers within the discipline of Business Informatics. The subjects were IT specialists with either foundation or advanced Chamber of Commerce (IHK) IT training, who participated as students in the credit transfer courses developed in the "Open IT" research project, or who were interested in participating. The investigative results reveal clearly in certain parts just what the preferences of working IT students are in terms of the scientific specialisation courses on offer, and how student target groups can be actively and effectively integrated into the design process of degree programme curricula.

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)0.000
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.826
Threshold uncertainty score0.326

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.235
GPT teacher head0.446
Teacher spread0.211 · 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