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Record W1563916424 · doi:10.19173/irrodl.v8i1.261

Online Distance Teaching of Undergraduate Finance: A case for Musashi University and Konan University, Japan

2007· article· en· W1563916424 on OpenAlexvenueno aff
Keiichi Kubota, Kiyoshi Fujikawa

Bibliographic record

VenueThe International Review of Research in Open and Distributed Learning · 2007
Typearticle
Languageen
FieldSocial Sciences
TopicInnovations in Educational Methods
Canadian institutionsnot available
Fundersnot available
KeywordsObstacleDistance educationClass (philosophy)The InternetComputer scienceCourse (navigation)Mathematics educationStatistical analysisOnline courseTeaching methodCourse evaluationMultimediaHigher educationPsychologyWorld Wide WebMathematicsArtificial intelligenceEngineeringStatistics

Abstract

fetched live from OpenAlex

We implemented a synchronous distance course entitled: Introductory Finance designed for undergraduate students. This course was held between two Japanese universities. Stable Internet connections allowing minimum delay and minimum interruptions of the audio-video streaming signals were used. Students were equipped with their own PCs with pre-loaded learning materials and Microsoft Excel exercises. These accompanying course and exercise materials helped students comprehend the mathematical equations and statistical numerical exercises that are indispensable to learning Introductory Finance effectively. The general tendency for students, not to raise questions during the class hours in Japan, however, was found to be a big obstacle. As such, motivational devices are needed and should ideally be combined to promote interaction between the e-classrooms.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.025
Threshold uncertainty score0.050

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0090.002
Scholarly communication0.0030.003
Open science0.0010.003
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0080.001

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 head0.123
GPT teacher head0.509
Teacher spread0.386 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designCase report
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

Citations2
Published2007
Admission routes1
Has abstractyes

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