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Record W2687077863 · doi:10.7213/1981-416x.17.052.ds02

A course design workshop as a possible path from a content-centered to a learning-centered teaching

2017· article· en· W2687077863 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

VenueRevista Diálogo Educacional · 2017
Typearticle
Languageen
FieldComputer Science
TopicE-Learning and Knowledge Management
Canadian institutionsMcGill University
Fundersnot available
KeywordsSyllabusContext (archaeology)Plan (archaeology)Process (computing)InstitutionTask (project management)Mathematics educationComputer scienceActive learning (machine learning)PsychologyPedagogyEngineeringSociologyArtificial intelligence

Abstract

fetched live from OpenAlex

In order to meet the needs of a constantly changing Society, the Universities need to constantly improve their processes of teaching and learning. To do so, it is essential that professors are fully committed and well prepared to teach aiming at students learning, instead of content delivery. Faculty development programs might be helpful to support the institution and the professors in this way. Since designing these programs is a challenging task, we intend to contribute with faculty developers by reporting our experience here. We have adapted a course design workshop developed at McGill University to our context at PUCPR, in Curitiba, South of Brazil. During the workshop, the participants had to write a new syllabus of their course, elaborate a concept map, both of them with only the essential aspects for learning. They had to define the learning outcomes and only afterwards to choose active methods to help students achieve them. Throughout the whole process, participants gave feedback to each other. The activities of the workshop, along with the fruitful discussions among professors of different backgrounds helped professors to view the content as something that supports the development of learning outcomes. Therefore, we conclude that this workshop has opened the way to methodological innovations that develop learning of higher cognitive dimensions, since the professor has established more challenging expectations for the students when writing the new teaching plan.

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 categoriesMeta-epidemiology (narrow), Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.664
Threshold uncertainty score1.000

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 studies0.0010.000
Scholarly communication0.0020.001
Open science0.0030.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.001

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 head0.079
GPT teacher head0.322
Teacher spread0.243 · 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