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Record W4404858902 · doi:10.55982/openpraxis.16.4.702

Understanding Innovation Vectors in the Use of Open Educational Resources

2024· article· en· W4404858902 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
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

VenueOpen Praxis · 2024
Typearticle
Languageen
FieldComputer Science
TopicOpen Education and E-Learning
Canadian institutionsnot available
FundersErasmus+
KeywordsOpen educational resourcesOpen educationKnowledge managementEducational resourcesDistance educationEducational technologyComputer scienceMathematics educationEngineering ethicsSociologyPedagogyPsychologyEngineering

Abstract

fetched live from OpenAlex

Open educational resources (OER) are teaching and learning materials that are either in the public domain or published on an open licence which permits various forms of redistribution, reuse and repurposing. Many organisations and higher education institutions around the world are using such resources, and anecdotally many believe this is supporting innovations in practice. However, there is scant research into how such innovations should be understood or evaluated conceptually. In this paper, we present a conceptual framework that can describe and evaluate innovative practice as well as results from a study of 44 cases using this framework in the context of the ENCORE+ (European Network for Catalysing Open Resources in Education) project (2021–2023). This conceptual framework provides a rich qualitative description for instances of innovation which use OER. Our examples cover many countries, including Argentina, Australia, Canada, China, Colombia, UK, Germany, Greece, Hungary, India, Ireland, Kenya, the Netherlands, Norway, Scotland, Slovenia, South Africa, Spain, Taiwan, USA, and Zanzibar. The sample includes organisations of all sizes and maturities of implementation. This allowed us to differentiate OER value propositions for a range of stakeholders at different levels of maturity of OER use. We explore whether variables such as the size and maturity of an organisation influences innovation strategies and the perception of stakeholder relationships. Our data indicates four elements to the development of OER value propositions as innovation vectors. Firstly, OER value propositions tend to be transformative, and focused on modifying or redefining pedagogical activity. Secondly, they are practical, targeting users/providers and influencing behaviour in direct and achievable ways. Thirdly, OER users and advocates emphasise observability, simplicity and compatibility as key aspects for communicating OER value propositions. Fourthly, OER innovation is aspirational in that greater maturity of organisations using OER sees the OER value proposition widened to include more stakeholder types.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.910
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0030.003
Open science0.0020.001
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 head0.277
GPT teacher head0.383
Teacher spread0.106 · 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