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Record W2120114698 · doi:10.1057/palgrave.ivs.9500130

The Concept Plot: A Concept Mapping Visualization Tool for Asynchronous Web-Based Brainstorming Sessions

2006· article· en· W2120114698 on OpenAlexaff
Alex Ivanov, Dianne Cyr

Bibliographic record

VenueInformation Visualization · 2006
Typearticle
Languageen
FieldPsychology
TopicTeam Dynamics and Performance
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsBrainstormingComputer scienceUploadVisualizationAsynchronous communicationHuman–computer interactionPlot (graphics)Task (project management)Process (computing)Interface (matter)Web applicationFace (sociological concept)World Wide WebArtificial intelligence

Abstract

fetched live from OpenAlex

Electronic brainstorming systems have been shown to lead to more ideas, yet unsupported face-to-face brainstorming is still widely preferred. This paper proposes a graphical user interface for a web-based system for design problem-solving or other intellective tasks involving convergent and divergent thinking. Referring to the literature on group support systems and information and knowledge visualization, the study extends features of concept mapping and synthesizes these into a prototype called the Concept Plot (CP). Based on an advertising design task, the paper shows how the CP can be collaboratively constructed in two directions, as text and pictures are uploaded onto nodes, and these nodes scaled up or down as users click to evaluate ideas. The expectation is that this integrated visualization would diminish information overload, while enhancing the social dynamics of the process. Also presented is the pilot deployment of a Flash prototype. The results were inconclusive, yet promising that a study with more participants might demonstrate the functional and affective benefits of the CP.

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)0.003
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.026
Threshold uncertainty score0.088

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.001
Science and technology studies0.0000.000
Scholarly communication0.0020.003
Open science0.0020.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0260.003

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 head0.014
GPT teacher head0.311
Teacher spread0.298 · 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 designBench or experimental
Domainnot available
GenreMethods

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

Citations18
Published2006
Admission routes1
Has abstractyes

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