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Record W2466063683 · doi:10.1111/dsji.12103

A Soft OR Approach to Fostering Systems Thinking: SODA Maps Plus Joint Analytical Process

2016· article· en· W2466063683 on OpenAlexaff
Shouhong Wang, Hai Wang

Bibliographic record

VenueDecision Sciences Journal of Innovative Education · 2016
Typearticle
Languageen
FieldDecision Sciences
TopicComplex Systems and Decision Making
Canadian institutionsSaint Mary's University
Fundersnot available
KeywordsSystems thinkingHigher-order thinkingProcess (computing)Computer scienceCritical thinkingCritical systems thinkingSoft systems methodologyOrder (exchange)Joint (building)Analytical skillThinking processesKnowledge managementMathematics educationManagement scienceTeaching methodPsychologyInformation systemCognitively Guided InstructionArtificial intelligenceStatistical thinkingManagement information systemsEngineeringBusiness

Abstract

fetched live from OpenAlex

ABSTRACT Higher order thinking skills are important for managers. Systems thinking is an important type of higher order thinking in business education. This article investigates a soft Operations Research approach to teaching and learning systems thinking. It outlines the integrative use of Strategic Options Development and Analysis maps for visualizing and assessing systems thinking and the joint analytical process for systems thinking development. This approach has been applied in an MBA course, and has demonstrated its usefulness for students in developing systems thinking skills.

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)0.021
metaresearch head score (Gemma)0.031
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.712
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0210.031
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.011
Science and technology studies0.0010.000
Scholarly communication0.0020.002
Open science0.0030.001
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 head0.344
GPT teacher head0.475
Teacher spread0.131 · 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.

Study designTheoretical or conceptual
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

Citations9
Published2016
Admission routes1
Has abstractyes

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