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Record W4405214904 · doi:10.3389/feduc.2024.1307903

Lessons on developing animated modules to introduce the sustainable development goals in undergraduate global health pedagogy

2024· article· en· W4405214904 on OpenAlexafffund
Obidimma Ezezika, Kishif Fatima, Mona Jarrah, Umayangga Yogalingam, Suzanne Sicchia

Bibliographic record

VenueFrontiers in Education · 2024
Typearticle
Languageen
FieldMedicine
TopicGlobal Health and Surgery
Canadian institutionsThe Scarborough HospitalUniversity of TorontoWestern University
FundersUniversity of Toronto
KeywordsSustainable developmentComputer scienceEngineering managementKnowledge managementEngineering ethicsMathematics educationEngineeringPsychologyPolitical science

Abstract

fetched live from OpenAlex

Storyline animations can be used as immersive academic tools to engage students’ learning experiences. Based on Kolb’s experiential learning theoretical framework, we produced and pilot-tested a new storyline animation encompassing the Sustainable Development Goals for undergraduate students in a health studies course and utilized student survey responses to gather their feedback. In this paper, we outline the design, implementation, and feedback from students, culminating in five key lessons. First, simplicity should be the goal. Second, segments should be short and accessible. Third, interposed questions, discussion forums, and varying storyline routes improve interactivity. Fourth, relatability, positionality, and empathy enhance learning and immersion. Fifth, supplementary materials can improve learning. Based on these findings, we offer recommendations across the five lessons to help educators overcome challenges and facilitate the implementation of similar pedagogical opportunities in their curricula.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.508
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.017
GPT teacher head0.386
Teacher spread0.369 · 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 designNot applicable
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

Citations0
Published2024
Admission routes2
Has abstractyes

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