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Record W2601951093 · doi:10.24908/pceea.v0i0.6515

CONCEPTS ONLY PLEASE! INNOVATING A FIRST YEAR ENGINEERING COURSE

2017· article· en· W2601951093 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) · 2017
Typearticle
Languageen
FieldEngineering
TopicEngineering Education and Curriculum Development
Canadian institutionsUniversity of Waterloo
FundersUniversity of Waterloo
KeywordsDeliverableTeamworkCourse (navigation)Process (computing)RestructuringConstructivePlan (archaeology)Critical thinkingMathematics educationPsychologyComputer scienceEngineeringEngineering managementManagement

Abstract

fetched live from OpenAlex

MSCI 100, a first year course dedicated to Management Engineering, introduces the main concepts of this discipline to students in their first term. The course’s main goals are introducing core principles that students will apply throughout their undergraduate studies and also preparing them for their first co-operative education term. In Fall 2015, this course was pedagogically redesigned based on authentic self-directed learning, accommodating different learners, and providing students with opportunities to develop professional skills (especially teamwork, project planning, time management and critical thinking).The course was designed holistically with emphasis on integrating concepts and communicating the course plan to students. Although engineering design was an inherent part of the course, there were no memory-driven tests and no math. The course’s learning outcomes were instead formulated around students’ understanding of improving effectiveness and efficiency in various facets of business through the development of their professional skills.There were numerous teaching innovations from the perspective of a first year engineering course. The essence of many course deliverables was for students to experience constructive failure-recovery cycles. This allowed them to learn from their mistakes as they completed case study challenges, hands-on activities, unique assessments and a final team project requiring integration of knowledge and skills. These activities were supported by various groups on campus.A panel of educators was formed near the end of the term so students could reflect on their learning process and be provided with the educators' feedback.. Moreover, the results from the course evaluations indicated that the restructuring of MSCI 100 was largely successful. Most students were able to fully grasp fundamental concepts and apply critical thinking skills. In this paper, we share reasons for redesigning the course, our experience in delivery and assessment, the impact of different teaching and learning methods and finally feedback on switching to in-depth, student-centered learning.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.204
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 science0.0010.000
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 head0.005
GPT teacher head0.213
Teacher spread0.208 · 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