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Record W2791851775 · doi:10.5539/hes.v8n2p9

Knowledge Growth, Academic Beliefs and Motivation of Students in Business and Economics - A longitudinal German Case Study

2018· article· en· W2791851775 on OpenAlexvenueno aff
Martin Biewen, Roland Happ, Susanne Schmidt, Olga Zlatkin‐Troitschanskaia

Bibliographic record

VenueHigher Education Studies · 2018
Typearticle
Languageen
FieldPsychology
TopicEducational Strategies and Epistemologies
Canadian institutionsnot available
Fundersnot available
KeywordsSkepticismGermanEconomics educationObjectivity (philosophy)PsychologyIntrinsic motivationMathematics educationSocial psychologyEpistemology

Abstract

fetched live from OpenAlex

In this study we examine the determinants of and the relationship among economic knowledge, epistemological beliefs, and extrinsic and intrinsic motivation over the course of undergraduate studies in a sample of students of business and economics at a university in Germany. We found economic knowledge increased over the course of studies, extrinsic and intrinsic motivation declined, and students became more skeptical in their epistemological beliefs about the objectivity of economic content being taught in their courses. The students’ level of economic knowledge was related to intrinsic motivation but unrelated to extrinsic motivation and epistemological beliefs. Furthermore, the students’ tendency to become more skeptical over the course of their studies was mitigated by high levels of extrinsic motivation. The use of internationally established assessments such as the Test of Economic Literacy, developed by the Council of Economics Education, enables implications for higher education business and economics programs at the international level to be drawn from our findings.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.041
Threshold uncertainty score0.513

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.140
GPT teacher head0.466
Teacher spread0.326 · 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

Citations6
Published2018
Admission routes1
Has abstractyes

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