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Record W2801668380 · doi:10.5539/ies.v11n5p14

Preparation of a Learning Module for Entrepreneurship Course at Economic Education Study Program of Faculty of Teacher Training and Education Sriwijaya University

2018· article· en· W2801668380 on OpenAlex
Firmansyah Firmansyah, Rusmin Rusmin

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 Education Studies · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicVocational and Entrepreneurial Education
Canadian institutionsnot available
Fundersnot available
KeywordsEntrepreneurshipSyllabusMathematics educationCreativityMindsetSubject (documents)CurriculumSociologyComputer sciencePsychologyPedagogyBusinessArtificial intelligence

Abstract

fetched live from OpenAlex

The objective of this study was to prepare teaching materials in the form of entrepreneurship learning module to be used as a handbook in the classroom learning process. Entrepreneurship lecture of study program at FKIP UNSRI has various material differences delivered in lecturing activity. One of the objectives to be achieved in this study was to obtain a general description of the entrepreneurship learning materials that should be the subject. 14 materials obtained from the results of data processing from questionnaires given to lecturers of entrepreneurship courses were as follows: the scope of entrepreneurship, determination of ideas and entrepreneurial opportunities, business plan, innovation and creativity in entrepreneurship, the concept of management in entrepreneurship, marketing strategy and the concept of Break Event Point (BEP), subject of entrepreneurial ethics, entrepreneurial mindset, competitive strategy, motivation theory in entrepreneurship, risk management of customer behavior and the path to successful entrepreneurship. The materials obtained from this data processing were then used as a guide for the preparation of entrepreneurship learning modules starting from the preliminary study, in the form of needs analysis of the learning module and found out that entrepreneurship learning module needed to be prepared to support the achievement of learning objectives. The next step was to map the module based on the syllabus to obtain the title of the module developed, followed by the preparation of the opaque module and the module writing stages containing the introductory section (introduction, table of contents, list of figures, list of tables, description, module usage guide, glossary), section of learning materials (14 Materials) and references. Finally the entrepreneurship learning module for the students was prepared.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.360
Threshold uncertainty score0.488

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.098
GPT teacher head0.461
Teacher spread0.362 · 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