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Record W2151494265 · doi:10.21432/t2ds3s

Authenticity in the process of learning about Instructional Design

2010· article· en· W2151494265 on OpenAlexaffvenue
Jay Wilson, Richard A. Schwier

Bibliographic record

VenueCanadian Journal of Learning and Technology · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicProblem and Project Based Learning
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsInstructional designPedagogyInterpersonal communicationExperiential learningPsychologyCooperative learningTeaching methodSocial psychology

Abstract

fetched live from OpenAlex

Authentic learning is touted as a powerful learning approach, particularly in the context of problem-based learning (Savery, 2006). Teaching and learning in the area of instructional design appears to offer a strong fit between the tenets of authentic learning and the practice of instructional design. This paper details the efforts to broaden and deepen the understanding of instructional design through a service learning approach to teaching, emphasizing authentic learning and assessment. Students are teamed and assigned to an actual contract with an external client under the supervision of the instructor who acts as project manager for the group. Contracts are negotiated to deliberately offer instructional design services to clients who would not otherwise be able to afford them, such as community-based non-profit groups. The reasons are two fold: first, we want to avoid competing for contracts that would interfere with the business of commercial instructional design groups and contractors; second, we want to impress on our students the idea that instructional design has social importance beyond the profit/loss and cost/effectiveness orientation of many instructional design businesses. In this way, we promote the idea that instructional designers are agents of social change, and their influence crosses interpersonal, professional, institutional and societal dimensions of change (Schwier, Campbell and Kenny, 2007). Résumé : L’apprentissage authentique est présenté comme une approche efficace en apprentissage, en particulier dans le contexte de l’apprentissage par problèmes (Savery, 2006). Enseigner et apprendre la conception pédagogique semble offrir une correspondance étroite entre les principes de l’apprentissage authentique et la pratique de la conception pédagogique. Cet article présente de manière détaillée les efforts visant à élargir et à approfondir la compréhension qu’ont les étudiants de la conception pédagogique par l’utilisation d’une approche de la formation à l’enseignement basée sur l’apprentissage du service qui met l’accent sur l’apprentissage authentique et l’évaluation. Les étudiants sont regroupés en équipes et se voient attribuer à un véritable mandat auprès d’un client externe sous la supervision de l’instructeur qui agit à titre de gestionnaire de projet pour le groupe. Les mandats sont délibérément négociés de manière à offrir des services de conception de matériel pédagogique à des clients qui autrement ne seraient pas en mesure de s’offrir ces services, comme les groupes communautaires sans but lucratif. Les raisons pour ce faire sont de deux ordres : d’une part, lors de l’obtention de mandats, nous voulons éviter d’entrer en concurrence et d’interférer avec les activités de groupes commerciaux et d’entrepreneurs en conception pédagogique; d’autre part, nous voulons transmettre à nos étudiants l’idée que la conception pédagogique revêt une importance sociale qui s’étend bien au-delà des orientations axées sur les couples profits/pertes et coûts/efficacité que de nombreuses entreprises de conception pédagogique adoptent. Ainsi, nous véhiculons l’idée que les concepteurs de matériel pédagogique sont des agents de changement social et que leur influence touche aux facettes interpersonnelle, professionnelle, institutionnelle et sociétale du changement.

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)0.068
metaresearch head score (Gemma)0.105
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.068
Threshold uncertainty score0.361

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0680.105
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0070.047
Scholarly communication0.0160.019
Open science0.0030.014
Research integrity0.0060.010
Insufficient payload (model declined to judge)0.0080.003

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 head0.012
GPT teacher head0.278
Teacher spread0.265 · 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".

Quick stats

Citations29
Published2010
Admission routes2
Has abstractyes

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