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Record W3184194162 · doi:10.1007/s10758-021-09535-0

Promoting Students’ Collective Cognitive Responsibility through Concurrent, Embedded and Transformative Assessment in Blended Higher Education Courses

2021· article· en· W3184194162 on OpenAlexaff
Stefano Cacciamani, Vittore Perrucci, Nobuko Fujita

Bibliographic record

VenueTechnology Knowledge and Learning · 2021
Typearticle
Languageen
FieldPsychology
TopicInnovative Teaching and Learning Methods
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsTransformative learningPortfolioMathematics educationPsychologyCommunity of inquiryCognitionOnline communityFace (sociological concept)PedagogyComputer scienceSociology

Abstract

fetched live from OpenAlex

This study investigates different instructional designs to promote students’ collective cognitive responsibility for Knowledge Building in blended university courses. Using an iterative, design-based research methodology with reference to the conjecture mapping technique, the blended learning design of an undergraduate educational psychology course was refined over three years in three design iterations. The iterations differed substantially in the embodiment of the Concurrent Embedded and Transformative Assessment Knowledge Building principle that engaged students in knowledge assessments and strategy assessments of their community’s work. The design of the knowledge assessment involved face-to-face small group and whole class discussions in all three iterations. In the first and second iterations, students also worked online by writing individual reflections and contributing to a community portfolio. The design of the strategy assessment changed in each iteration. In the first iteration, the students’ strategy assessment took place in face-to-face discussions; in the second iteration, students contributed to an online community portfolio; and in the third iteration, the strategy assessment took place in an online community portfolio and face-to-face discussions before beginning the course and in the online community portfolio in the middle of the course. Collective cognitive responsibility was analyzed in terms of productive and informative participation, interdependence between participants, self-regulation skills. The results show that the second iteration’s design was most effective for fostering the students' collective cognitive responsibility, showing an increase in productive participation and self-regulation skills in the first part of the course and also an increase in the interdependence of participants during the course. Some implications concerning the relationship between the implementation of the CETA principle and Knowledge Building are identified for future directions of inquiry and for blended learning environments design.

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)0.007
metaresearch head score (Gemma)0.016
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.016
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.044
GPT teacher head0.454
Teacher spread0.410 · 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 designObservational
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

Citations24
Published2021
Admission routes1
Has abstractyes

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