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Record W2472987806 · doi:10.18260/p.26344

A Liberal Education Certified: A Panel on Integrating Liberal Education in a Large, Research-based Institution

2016· article· en· W2472987806 on OpenAlexaffabout
Lydia Wilkinson, Alan Chong, Deborah Tihanyi, Penny Kinnear, Robert Irish, Ken Tallman

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicBiomedical and Engineering Education
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsCurriculumLiberal educationEngineering educationHigher educationExperiential learningCertificationInstitutionMultidisciplinary approachLiberal arts educationCreativitySociologyEngineering ethicsPolitical scienceMedical educationEngineeringPedagogyEngineering managementMedicineSocial science

Abstract

fetched live from OpenAlex

Abstract A Liberal Education Certified: A panel on integrating liberal education in a large, research-based institution Engineering programs that provide opportunities for interdisciplinary collaboration, hands-on learning, and creativity are seen to help develop professionals more aware of their world and invested in its improvement. This liberal education can be achieved in multiple ways, through project-based learning, design-focused curricula, and exposure to non-technical disciplines, including the humanities and social sciences (HSS). Programs that successfully incorporate these approaches are often found within smaller, teaching-focused colleges, which can focus resources on creating these opportunities. Notably, Rose-Hulman, Harvey Mudd and Olin College, ranked top three for undergraduate engineering education in the 2015 US News and World’s university rankings, have mission statements articulating a student-focused experiential approach to engineering learning, while boasting enrollments of at most 2,200, and a single college focus: engineering and technology. Achieving this type of holistic education is more challenging for larger multidisciplinary research institutions. The University of Toronto (Uoft) for example, has a student population of over 84,000 spread across three campuses and seventeen different degree granting Faculties (the equivalent of Colleges within the American system). Its Faculty of Applied Science and Engineering (FASE) has an enrollment of close to 5500 undergraduate and 2100 graduate students spread across a further eight departments. The size and complexity of UofT’s administrative model makes a centralized change in teaching philosophy challenging to implement across programs, and without embedded and integrated HSS offerings, students often look to outside Faculties for their complementary studies requirements. In this situation, students face multiple challenges: administratively, they compete with their HSS colleagues for spots in popular courses; culturally, they must adapt to new pedagogical approaches and classroom norms; and practically, they are forced to juggle the hefty demands of an engineering workload with the expectations of an HSS classroom. This panel discusses the small-scale approach developed at UofT to circumvent many of these challenges while ensuring that our students are provided with meaningful opportunities in the liberal arts. Seven years ago UofT’s Engineering Communication Program (ECP) introduced a suite of HSS electives to provide students with an alternative path to a liberal education. Led by faculty members from ECP in their area of specialization, these courses expose students to a new discipline using familiar approaches and content. Today, we offer six such electives--Representing Science on Stage, Science and Technology in the Popular Media, Language and Power, Engineering and Science in the Arts, Language and Meaning, and The Power of Story--as well as the opportunity to earn a Certificate in Communication. Awarded to students who complete three of these courses, the Certificate reflects the FASE’s success in promoting and rewarding student engagement in educational opportunities outside the core curriculum. In this panel of the Associate Professors, Teaching Stream, and Lecturers who teach these courses, we explain our context at a top-flight research university, before discussing our courses and assessing their success in providing a liberal education for our students. A discussion period will allow us to share insights into how our approach could be adapted to programs that share characteristics of our institution. *Note that this abstract is for a panel, and as per LEES guidelines identifying information has not been redacted.

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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.815
Threshold uncertainty score0.447

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.040
GPT teacher head0.307
Teacher spread0.267 · 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 designOther design
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

Citations1
Published2016
Admission routes2
Has abstractyes

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