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Record W2970232980 · doi:10.35199/epde2019.15

ASSESSMENT OF COLLABORATIVE DESIGN: A SOCIOCULTURAL APPROACH

2019· article· en· W2970232980 on OpenAlexaff
Virginie Tessier

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicInnovative Education and Learning Practices
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsSociocultural evolutionSocial constructivismCollaborative learningKnowledge managementActivity theoryProcess (computing)Learning theoryComputer scienceSocial learningManagement scienceProcess managementEngineeringSociologyPedagogy

Abstract

fetched live from OpenAlex

This article adopts a sociocultural perspective, based on a Designerly version of Activity Theory, to propose a coherent framework in response to the challenges of assessing collaborative design. In reaction to the transforming requirements of professional designers, educational establishments need to adapt their pedagogical strategies and offer students collaborative projects during their training as this approach is now a widely-spread practice for innovative companies. Many authors conclude that efforts are needed to ensure its proper integration and successful unfolding for the learners. An important challenge to the comprehensive integration of collaborative design in learning situations resides in its proper, fair and coherent assessment. A number of gaps between the intention and the implantation of collaboration are identified. First of all, a gap is noted between the conditions of social learning and those of individual assessment. This raises interrogations about the conflicting paradigms guiding traditional assessment practices and contemporary socio-constructivist learning strategies. Secondly, another gap is found when assessing the value of a final team product over the complexity of the collaborative design process. While design is a social process (Bucciarelli, 1988), the assessment of a single final stage is puzzling. Referring to the authors’ previous studies, Activity Theory (AT) propose unexplored avenues towards the coherent assessment of collaborative design. The theory brings to light the operative components of an activity and the tensions persisting amongst its components (Engeström, 1999). In harmony with collaborative dynamics, AT seeks the active participation of actors in reaching systemic comprehension of sociocultural and organizational issues to propose coherent solutions. The sociocultural perspective is based on the concept of mediation according to which an interaction is never direct, but always mediated by a third component of the model. In a team assessment context, mediation allows the ‘re-socialisation’ of the object being assessed (Morissette, 2009), encouraging the emergence of a discussion space between the assessor and the team. AT recognize the benefits of such formative interventions through the concept of “knotworking”, defined as a form of collaboration emerging from a shared object: from unorganized collaborative efforts toward an expanded object – in our case assessment (Sannino & Ellis, 2014; Engeström, 2015). Formative interventions allow to revise incomplete or invalid knowledge and enhance learning by motivating reflective and critical thinking within the educational activity. Adopting a sociocultural perspective, this article will seek to investigate the following questions: What should be the object of assessment emerging from the re-socialisation process of a collaborative project? And, how should it be assessed? The introduction of the new Designerly interpretation of Activity Theory (d.AT), will allow to frame an assessment strategy on its strong theoretical foundations. In brief, the strategy aims at actively involving teams of learners to assess collaborative design in a coherent manner according to the emerging distinctiveness of these complex learning situations. The assessment strategy evolved around the 13 components of the d.AT model. The article will propose clear definitions of each of the components in order to propose ways to implement those within the design project-based learning pedagogy.

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)0.033
metaresearch head score (Gemma)0.043
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.033
Threshold uncertainty score0.173

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0330.043
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0130.004
Science and technology studies0.0060.022
Scholarly communication0.0170.014
Open science0.0040.015
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0030.001

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 head0.098
GPT teacher head0.454
Teacher spread0.356 · 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 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".

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Citations5
Published2019
Admission routes1
Has abstractyes

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