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Record W4238424826 · doi:10.24908/pceea.v0i0.5756

Ipsative learning: a personal approach to a student's experience of PBL within an integrated engineering design cornerstone module

2015· article· en· W4238424826 on OpenAlexvenueno aff
Emanuela Tilley, John Mitchell

Bibliographic record

VenueProceedings of the Canadian Engineering Education Association (CEEA) · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicReflective Practices in Education
Canadian institutionsnot available
Fundersnot available
KeywordsFormative assessmentCornerstoneExperiential learningCurriculumProject-based learningEngineering educationPsychologyEngineering design processProcess (computing)Problem-based learningMathematics educationPedagogyMedical educationEngineeringComputer scienceEngineering managementMedicineMechanical engineering

Abstract

fetched live from OpenAlex

The Faculty of Engineering Science atUniversity College London (UCL) has recently undergonea reform of the undergraduate curriculum, which resultedin the creation of a distinctive programme that connectedcurriculums from across seven engineering disciplines.The Integrated Engineering Programme is extensive,taking in nearly 700 students in its inaugural year at thestart of the autumn 2014 term. Its most significantcontributions are the experiential and authentic learningopportunities it provides students allowing them to applytheir technical knowledge and develop their professionalskills in engineering design modules year on year. Thefirst opportunity for students to do this is within thecornerstone Integrated Engineering Design module inyear I. This paper seeks to investigate the impact of anipsative learning approach (feedback and assessment thatis based on learner’s progress) within this multidisciplinaryproblem/project-based learning environment(PBL/PjBL), which focuses learning outcomes on thestudent’s ability to engage with the process of engineeringdesign. The methods of conducting the research includethe analysis of reflective writings by each studentthroughout the first of two 5-week ‘Challenge’ projects. Aset of reflections written by each student was associatedwith two formative assessment meetings, referred to asDesign Review Meetings, held with their academic leader.This data is also supplemented with verbal feedbackprovided by students and academics, which has beenprovided during follow up interviews and focus groups.Student self reflections written after each of the twomeetings support common theses of increasedunderstanding of the project aims and depth of studentresearch efforts. Surprisingly, however is the evidence,which implies that an ipsative PBL environmentempowers students to make critical personal andengineering decisions for effective progression within anengineering design project.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.010
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.001
Science and technology studies0.0070.008
Scholarly communication0.0080.005
Open science0.0030.010
Research integrity0.0020.006
Insufficient payload (model declined to judge)0.0040.001

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 head0.318
Teacher spread0.278 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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".

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Citations2
Published2015
Admission routes1
Has abstractyes

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