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Record W1507541396 · doi:10.24908/pceea.v0i0.3740

SPATIAL THINKING AND COMMUNICATIONG: A COURSE FOR FIRST-YEAR UNIVERSITY STUDENTS

2011· article· en· W1507541396 on OpenAlexaffvenue
Halil Erhan, Belgacem Ben Youssef, Michael Sjoerdsma, John R. Dill, Barbara Berry, Janet McCracken

Bibliographic record

VenueProceedings of the Canadian Engineering Education Association (CEEA) · 2011
Typearticle
Languageen
FieldEngineering
TopicDesign Education and Practice
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsMechatronicsCourse (navigation)Computer scienceMathematics educationThe artsMultimediaEngineeringPsychologyArtificial intelligence

Abstract

fetched live from OpenAlex

This paper describes a course on spatial thinking and communicating designed by an interdisciplinary team and offered to first-year university students. An important goal was to introduce spatial thinking while accommodating the needs of the students from diverse backgrounds, educational goals and career pathways. Students in a first-year interdisciplinary cohort of 340 represented Mechatronics Systems Engineering, Business, Interactive Arts, Communications, and Computing Science. A major feature of the course design was an integrated laboratory, which served to amplify lecture content via practicing exercises aimed at developing their abilities to think and work spatially in 2D and 3D using tools including pencil and paper, digital and physical Lego, and a computer-aided design system. We describe our course design and team-teaching processes, realities that constrained our choices, the tools we use to assist our decision making during course design and delivery, and the structure and function of the teaching team. We also present selected student artifacts to demonstrate how students learned to think spatially. We then identify lessons-learned and revision plans.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.102
Threshold uncertainty score0.460

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 communication0.0000.000
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 head0.012
GPT teacher head0.209
Teacher spread0.197 · 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.

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

Citations4
Published2011
Admission routes2
Has abstractyes

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