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Record W7082150504 · doi:10.11575/prism/50254

Beyond the Surface: Navigating Students’ Identities through the ABC’s Model

2025· other· en· W7082150504 on OpenAlexaboutno aff

Bibliographic record

VenueOpen MIND · 2025
Typeother
Languageen
FieldComputer Science
TopicGeochemistry and Geologic Mapping
Canadian institutionsnot available
Fundersnot available
KeywordsMulticulturalismNarrativeAffordanceIdentity (music)Cultural diversityAction researchDiversity (politics)Immigration

Abstract

fetched live from OpenAlex

In our contemporary multicultural society, Canadian schools face the complexities presented by a diverse immigrant demographic. Traditional ways of teaching often made multilingual students, either newcomers or second-generation immigrants, feel left out, which made it hard for them to grow academically and develop their sense of self. To address this, educators are increasingly turning to culturally responsive pedagogies that celebrate and affirm diverse cultural backgrounds. This research introduced an intervention designed for sixth-grade students, with the objective of fostering self-awareness, celebrating diversity, and promoting identity exploration through narrative and multimodal approaches. While the project was conducted in a regular classroom setting with the involvement of all students, the primary emphasis was on students from diverse backgrounds, including newcomers to the country categorized as English Language Learners (ELLs) and second-generation immigrants. The study was guided by Ruggiano Schmidt's ABC’s model of cultural understanding and communication (1998), which stands for autobiography (A), biography (B), and cross-cultural comparison (C), to evaluate its influence on the development of personal identity. The aim was to cultivate a classroom environment that welcomes diversity and nurtures a sense of belonging. This study explored two research questions: (a) How does the ABC’s model support Grade 6 students from diverse backgrounds, including newcomers or children of immigrant families, in navigating students’ personal identities? (b) What are the affordances of a multimodal approach to exploring students’ personal identities? Employing an action research approach, I collaborated with a sixth-grade teacher to co-design a multimodal ABC’s project for implementation in the classroom. After the implementation phase concluded, I analyzed and reflected upon my observations and students’ final products. The findings were discussed based on the theoretical framework that guided the study: critical literacy and sociocultural perspectives. These theories emphasize that learning happens through conversation in a social setting and that literacy is deeply connected to culture, an understanding that was evident throughout the project. Students reflected on personal experiences such as language, names, special places, childhood stories, and important people in their lives. This reflection enabled them to value their personal identities and recognize the significance of their cultural and linguistic backgrounds. Through collaborative dialogue and peer interactions, students found meaningful connections across differences. They came to understand that they do not need to conform to the dominant culture to feel a sense of belonging; rather, their true selves are appreciated and valued. The ABC’s model offered students a framework for understanding both themselves and others, contributing to stronger interpersonal connections and a more inclusive classroom culture. Ultimately, this project demonstrated how culturally responsive, multimodal pedagogies can empower students, promote mutual respect, and foster lasting bonds among classmates.

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)0.002
metaresearch head score (Gemma)0.004
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: Other · Consensus signal: Other
Teacher disagreement score0.063
Threshold uncertainty score0.124

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.011
Scholarly communication0.0090.006
Open science0.0020.005
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0070.001

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 head0.033
GPT teacher head0.324
Teacher spread0.290 · 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
GenreOther

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

Citations0
Published2025
Admission routes1
Has abstractyes

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