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Record W3001856150 · doi:10.24908/pceea.vi0.13823

ACTIVE LEARNING IN A SECOND YEAR SURVEYING COURSE

2019· article· en· W3001856150 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.
venuePublished in a venue whose home country is Canada.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueProceedings of the Canadian Engineering Education Association (CEEA) · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicInnovative Teaching Methods
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsGeomaticsConstructiveActive learning (machine learning)Psychomotor learningMathematics educationClass (philosophy)Process (computing)Computer scienceCognitionPsychologyArtificial intelligenceGeographyCartography

Abstract

fetched live from OpenAlex

As a course that develops both cognitive and psychomotor skills of geomatics engineering students, the second-year surveying course at the University of Calgary has been re-designed to include more active, constructive and interactive learning experiences. Classroom activities have been designed around the idea that a balance between the four levels of learning in the ICAP (interactive-constructive-active-passive) framework should be achieved. Passive learning is acceptable because it provides students with time to accumulate knowledge and overcome their initial uncertainty in the surveying classroom. Eventually, their learning undergoes transformation most notably during the interactive team-based field labs. 
 An observation protocol has been designed, which, in addition to mapping student learning, assesses the teaching and learning environment and specifically its student cognitive and behavioural engagement aspects. The provisional results in winter 2019 confirmed that the geomatics engineering students were more engaged in the learning process as the time spent practicing active and constructive learning accounted for 78% of the class time in three observed lectures.

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)0.003
metaresearch head score (Gemma)0.004
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 score0.049
Threshold uncertainty score0.973

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.010
GPT teacher head0.281
Teacher spread0.271 · 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