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Getting Radical: Using Design thinking to Tackle Collaboration Issues

2020· article· en· W3209080730 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenuePapers on postsecondary learning and teaching. · 2020
Typearticle
Languageen
FieldEngineering
TopicDesign Education and Practice
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsComputer scienceDesign thinkingManagement scienceProcess managementKnowledge managementEngineering managementHuman–computer interactionEngineering

Abstract

fetched live from OpenAlex

Design Thinking (DT) has recently been adopted in some higher education disciplines as an effective pedagogical approach to enable students to acquire the skills needed for solving real world problems. As a human-centered, iterative process, design thinking is characterized by working with others to understand, define and solve problems using empathy, creativity, and radical collaboration. Many university courses also stress collaboration as a learning approach. However, not all students function well in collaborative environments. Based on their work in the Design-based Thinking course at the Werklund School of Education, University of Calgary, the authors asked, “could the design thinking process be used to foster collaboration among students and encourage radical collaboration”? In this paper the authors present a brief overview of the literature in this area and propose some parallels between the design thinking and collaborative team building processes.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.868
Threshold uncertainty score0.796

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 integrity0.0000.001
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 head0.020
GPT teacher head0.287
Teacher spread0.266 · 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