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Record W4390224962 · doi:10.59668/279.12261

Rethinking and recasting the textbook: Reframing learning design with open educational practices

2023· book-chapter· en· W4390224962 on OpenAlexaff
Michelle Harrison, Irwin DeVries, Michael Paskevicius, Tannis Morgan

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldComputer Science
TopicOpen Education and E-Learning
Canadian institutionsVancouver Community CollegeUniversity of VictoriaThompson Rivers University
Fundersnot available
KeywordsCognitive reframingOpen educational resourcesAffordanceContext (archaeology)Open learningEquity (law)NarrativeResource (disambiguation)PedagogyComputer scienceOpen educationEngineering ethicsKnowledge managementSociologyEngineeringTeaching methodPolitical sciencePsychologyCooperative learningHuman–computer interaction

Abstract

fetched live from OpenAlex

Many notable developments have taken place in the evolution of open educational practices (OEP). Among these, we focus on two in particular. First is the proliferation of the use of open textbooks, which have become a major component within OEP. Second, there are ongoing efforts at rethinking learning design in the context of open education. The purpose of this chapter is to discuss how we challenged ourselves to rethink learning designs that can result from a rethinking of open textbooks as educational artefact. We position this in the context of centering equity and social justice in learning design through both challenging single narratives and taking advantage of the affordances of an open textbook. As part of this discussion and challenge, we outline a design-based research project where we are developing a prototype for a community-generated, non-hierarchical teaching and learning resource (“untextbook”) model that is open to ongoing extension and reframing. As we engage in the development of an organic, fluid resource, we invite learners to participate in ongoing cycles of extending and reframing the existing content to open new learning pathways prompted by considerations of relevant issues, lenses, roles and settings in a WordPress-based authoring tool. These cycles include a research project that is in the process of obtaining feedback and reflections from graduate students involved in courses where the prototype is being implemented.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.746
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0030.001
Open science0.0020.001
Research integrity0.0000.001
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 head0.137
GPT teacher head0.333
Teacher spread0.196 · 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.

Study designTheoretical or conceptual
Domainnot available
GenreOther

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

Citations1
Published2023
Admission routes1
Has abstractyes

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