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Record W4395016148 · doi:10.1039/d4rp00084f

Widening university participation in learning using students’ contextualised storytelling in general chemistry

2024· article· en· W4395016148 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueChemistry Education Research and Practice · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicScience Education and Pedagogy
Canadian institutionsUniversity of CalgaryMount Royal University
FundersMount Royal University
KeywordsStorytellingChemistryContext (archaeology)Experiential learningRelevance (law)Mathematics educationPsychologyClass (philosophy)Chemistry educationNarrativeCreativityPedagogyComputer scienceLiterature

Abstract

fetched live from OpenAlex

Many students find introductory general chemistry courses difficult because they feel alienated by traditional approaches to teaching and learning. This can become particularly problematic in laboratory sessions where students simply follow processes and procedures that students can view as being mundane and lacking creativity. Contextualised storytelling offers a novel pedagogical approach to help students connect and make sense of chemistry ideas in the context of their own life experiences. The current study implemented the CLEAR (chemistry learning via experiential academic reflection) approach to contextualised storytelling as a sequence of four assignments across a laboratory course for first-year students. The research explored students’ experiences writing contextualised stories to make sense of and learn chemistry. Using hermeneutics as a methodology, the data collected included participants’ written contextualised stories, semi-structured interview recordings, and field notes. While the CLEAR approach differs from other approaches to storytelling in chemistry education, the current study suggests that CLEAR can make positive contributions to student learning. The findings showed that, although many students initially resisted or felt confused by the new approach, CLEAR helped students see the connection and relevance of chemistry concepts to their lives. Students also recognized the importance of self-directed learning while writing their CLEAR stories, which suggests that CLEAR engaged students in learning that was active and organic. Furthermore, writing CLEAR stories supported students in talking to people about scientific concepts they learned in class, which suggests that writing the CLEAR stories: (a) helped students find the relevancy of the ideas to the degree that they felt they could share the ideas in their own words outside of class and (b) increased students’ interest in the course and what they were learning to the degree that they wanted to share it. Implementing CLEAR as multiple assignments across the course appears important and valuable because students refined their thinking and writing skills through iteration within and across CLEAR stories.

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)0.005
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.324
Threshold uncertainty score0.682

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
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 head0.209
GPT teacher head0.557
Teacher spread0.348 · 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