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Record W1951887237 · doi:10.24908/pceea.v0i0.5929

OFFERING INTERDISCPLINARY COURSES: THE WHY, THE HOW AND THE WHAT

2015· article· en· W1951887237 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.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueProceedings of the Canadian Engineering Education Association (CEEA) · 2015
Typearticle
Languageen
FieldPsychology
TopicLearning Styles and Cognitive Differences
Canadian institutionsUniversity of AlbertaYork University
FundersCanada School of Energy and Environment
KeywordsLearning stylesMathematics educationPeer learningPsychologyFace (sociological concept)PedagogyEngineeringMedical educationSociologyMedicineSocial science

Abstract

fetched live from OpenAlex

Students in their future workplace will likely face multifacetedchallenges; as such, solutions require integrationand collaboration across disciplines. An interdisciplinaryinstruction benefits students’ learning by exposing themto fundamental topics and perspectives that they wouldnot have been able to obtain easily within their programs.Peer learning and interactions by students from differentbackgrounds provides further learning opportunities. Thepaper is a reflection of the experience of the fourinstructors involved in teaching an interdisciplinarycourse in the area of energy who were from four distinctFaculties over the period of 2010-2012. Planning well inadvance is important to allow instructors from differentbackgrounds with varied traditions in teaching to developa working rapport. Throughout the planning stagesdedicated administrative support must be provided tofacilitate attending to logistics of setting up the coursewithin the university system. The right incentivise for theinstructors should also be provided due to higher thannormal time commitment. What was learnt that there is aneed to provide both foundation material and moreadvanced perspectives simultaneously given the diversebackground of students and topics in an interdisciplinarycourse. Also, it was found that instructors benefitted fromteaching such a course by learning from traditions andmethods in another discipline, and went on to improveother courses in their discipline both in content andteaching style. It was also found that lack of integrationwith “regular” programs, or “official” endorsing candissuade some students from participating. Other lessonsinclude issues around instructor team’s chemistry, coursecontent design, e.g. the need for group projects tointernalize the material, and the use of technology.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.411
Threshold uncertainty score0.761

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.243
Teacher spread0.231 · 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