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Record W2767233829 · doi:10.5430/ijhe.v6n6p1

Scrum Methodology in Higher Education: Innovation in Teaching, Learning and Assessment

2017· article· en· W2767233829 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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueInternational Journal of Higher Education · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicReflective Practices in Education
Canadian institutionsnot available
Fundersnot available
KeywordsAutonomyEmpathyFeelingScrumProcess (computing)PortfolioCritical thinkingPsychologyQuality (philosophy)Knowledge managementPedagogyMathematics educationComputer sciencePolitical scienceBusiness

Abstract

fetched live from OpenAlex

The present paper aims to detail the experience developed in a classroom of English Studies from the Spanish University of Málaga, where an alternative project-based learning methodology has been implemented. Such methodology is inspired by scrum sessions widely extended in technological companies where staff members work in teams and are assigned tasks within long-termed projects. Students were initially reluctant and afraid to work in teams but, as the experience advanced, their point of view was changing. Thus they positively stated that this methodology encouraged themselves to participate and to change ideas, with a deeper feeling of empathy, self-organisation and self-knowledge. At the end, most of the students declared they would participate again in a similar activity. Hence, considering the opinions from the students (and also from the teachers), and after observing the whole experience and analyzing the documents generated in an electronic portfolio, we think this method can be considered as a good proposal to accomplish a teaching-learning process of high quality at universities for three main reasons: first, it improves the capacity of using the knowledge in a disciplined, critical and creative way; second, it promotes the coexistence in heterogeneous human groups; and third, it develops the capacity of thinking, living and acting with complete autonomy.

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)0.004
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.332
Threshold uncertainty score0.561

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.002
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.175
GPT teacher head0.581
Teacher spread0.406 · 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