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Record W7054745699

Assessing Understanding of Complex Causal Networks Using an Interactive Game

2013· article· en· W7054745699 on OpenAlex

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

VenueSound Ideas (University of Puget Sound) · 2013
Typearticle
Languageen
FieldEngineering
TopicLaser Design and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsReductionismProcess (computing)Causal modelKey (lock)CognitionComponent (thermodynamics)Causal structureA priori and a posterioriVariety (cybernetics)
DOInot available

Abstract

fetched live from OpenAlex

Assessing people’s understanding of the causal relationships found in large-scale complex systems may be necessary for addressing many critical social concerns, such as environmental sustainability. Existing methods for assessing systems thinking and causal understanding frequently use the technique of cognitive causal mapping. However, the logistics of this methodology may miss valuable and informative indicators of reductionist and linear thinking, both of which conflict with systems understanding.\nThis dissertation explores how interactive computer systems can aid in the assessment of causal understanding, allowing educators to perform more in-depth analysis of how subjects engage with the process of causal mapping. In addition, it considers how computer games as a particular form of interactive system may be able to support assessment. Games are framed as effectively supporting learning and education and although assessment is a key component of education, the use of video games for performing assessment is under-explored.\nTo address these topics, I present a prototype interactive game system based on Plate’s (2006) framework for assessing causal understanding through cognitive causal mapping. I tested this prototype in a user study with both student and non-student subjects. Through this study, I found that evaluating the structural forms of causal maps created in an interactive system can suggest the presence of reductionist thinking, while the sequence of causal map construction can indicate the presence of linear thinking. Furthermore, I found that although games as interactive systems can be effective in enabling learning, they may be less readily effective in supporting stand-alone\nassessments due to requiring an a priori understanding of the complex game system used in assessment, as well as traditional educational assessment contexts not supporting the forms of feedback critical to game-based learning.\nThese results indicate how the linear narratives prominently found in both education and games may interfere with effective systems thinking. This dissertation thus suggests that educators in both formal and informal education contexts should consider alternative, non-narrative curricula and games for teaching and assessing causal understanding of complex systems.

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)0.000
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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.454
Threshold uncertainty score0.684

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 communication0.0000.001
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 head0.084
GPT teacher head0.268
Teacher spread0.184 · 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