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Record W4401172661 · doi:10.55016/ojs/ajer.v70i2.77325

Collaborative Concept Mapping: Investigating the Nature of Discourse Patterns and Features of a Concept Map

2024· article· en· W4401172661 on OpenAlexvenueno aff
Hlologelo Climant Khoza, Bob Maseko

Bibliographic record

VenueAlberta Journal of Educational Research · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicWikis in Education and Collaboration
Canadian institutionsnot available
FundersUniversity of PretoriaUniversity of Leeds
KeywordsConcept mapSocial connectednessConstruct (python library)Concept learningCoding (social sciences)Joint (building)Mind mapScience educationGeneralizationPsychologyMathematics educationSociologyEpistemologyComputer scienceSocial psychologySocial science

Abstract

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Research in science education has established the significance of collaborative concept mapping as a powerful strategy in fostering conceptual learning. During such collaboration, students talk about concept map features (i.e., concepts to include, linking words, and cross-links) in constructing a joint map. The quality of the concept map produced depends on the nature of discourses that happen in these collaborative interactions. We explored the nature of discourses between pairs of biology students collaborating on concept mapping and how these discourses contribute to the enhancement of different features of the concept maps. Six students individually constructed weekly individual maps on different topics and then came together in pairs to construct a joint concept map. Their discussions during collaboration were audio-recorded. Both the individual and joint concept maps were analyzed for knowledge of breadth, knowledge of depth, and knowledge of connectedness. To analyze the discussions and understand the nature of the discourses, both deductive and inductive coding approaches were used. The coded episodes were then categorised into the nine discourse patterns identified by Fu et al. (2016). We then matched the episodes with the concept map features that were discussed. Findings indicate that the biology students’ collaboration exhibited mostly knowledge-sharing discourses when deliberating on the three features of a concept map. In turn, the number of valid concepts and propositions improved from individual to joint maps. Although the students’ discussions of cross-links were characterized by knowledge-sharing discourses, most of the joint maps did not show improvement in terms of the number cross-links. We discuss these findings and provide implications regarding the value of understanding the intricacies of discourse patterns in collaborative concept mapping. La recherche dans le domaine de l'enseignement des sciences a établi l'importance de la cartographie conceptuelle collaborative en tant que stratégie puissante pour favoriser l'apprentissage conceptuel. Au cours de cette collaboration, les élèves discutent des caractéristiques de la carte conceptuelle (c'est-à-dire des concepts à inclure, des mots de liaison et des liens croisés) pour construire une carte commune. La qualité de la carte conceptuelle produite dépend de la nature des discours tenus lors de ces interactions collaboratives. Nous avons exploré la nature des discours entre des paires d'étudiants en biologie collaborant sur la cartographie conceptuelle et la façon dont ces discours contribuent à l'amélioration des différentes caractéristiques des cartes conceptuelles. Six étudiants ont construit individuellement des cartes hebdomadaires sur différents sujets et se sont ensuite réunis par paires pour construire une carte conceptuelle commune. Leurs discussions pendant la collaboration ont été enregistrées. Les cartes conceptuelles individuelles et communes ont été analysées du point de vue de la connaissance de l'étendue, de la connaissance de la profondeur et de la connaissance de la connexité. Pour analyser les discussions et comprendre la nature des discours, des approches de codage à la fois déductives et inductives ont été utilisées. Les épisodes codés ont ensuite été classés dans les neuf modèles de discours identifiés par Fu et al. (2016). Nous avons ensuite mis en correspondance les épisodes avec les caractéristiques de la carte conceptuelle qui ont été discutées. Les résultats indiquent que la collaboration des étudiants en biologie présentait principalement des discours de partage des connaissances lorsqu'ils délibéraient sur les trois caractéristiques d'une carte conceptuelle. Par ailleurs, le nombre de concepts et de propositions valides s'est amélioré entre les cartes individuelles et les cartes communes. Bien que les discussions des étudiants sur les liens croisés aient été caractérisées par des discours de partage des connaissances, la plupart des cartes conjointes n'ont pas montré d'amélioration en termes de nombre de liens croisés. Nous discutons de ces résultats et fournissons des implications concernant la valeur de la compréhension des subtilités des modèles de discours dans la cartographie conceptuelle collaborative.

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)0.002
metaresearch head score (Gemma)0.011
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.646
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.043
GPT teacher head0.441
Teacher spread0.398 · 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 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".

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Citations0
Published2024
Admission routes1
Has abstractyes

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