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Record W2743841831 · doi:10.14236/ewic/ndm2009.62

Computer Algebra Systems and Their Effect on Cognitive Load

2009· article· en· W2743841831 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueElectronic workshops in computing · 2009
Typearticle
Languageen
FieldPsychology
TopicVisual and Cognitive Learning Processes
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of Waterloo
KeywordsComputer scienceOriginalityField (mathematics)Process (computing)CognitionValue (mathematics)Cognitive loadHuman–computer interactionMathematics educationPsychologyProgramming languageMathematics

Abstract

fetched live from OpenAlex

Motivation – In this paper we discuss the beginning of a research project into the design of user interfaces for Computer Algebra Systems (CASs). Research approach – Findings/Design – We begin to examine a theoretical framework describing how people learn problem-solving skills. We also briefly discuss a field study we conducted. Research limitations/Implications – The field study, while small and preliminary, allowed us to see some areas where students ran in to difficulty using Maple. The theoretical framework we begin to outline should help us understand the cause of some of those difficulties. Originality/Value – We begin to better understand how people use CASs to learn mathematics. We also begin to combine Cognitive Load Theory and the Skills-Rules-Knowledge framework. Take away message – This is the beginning of a research project that should help us better understand how CASs can be better designed to assist with learning and the problem-solving process.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.978
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.012
GPT teacher head0.308
Teacher spread0.295 · 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