Understanding Multilingual Learner’s Mathematical Experiences and Meaning Making in a Canadian Educational Setting
Bibliographic record
Abstract
This is an ethnographic study designed to form an in-depth description and understanding of multilingual learners’ mathematical experiences and meaning-making in a plurilingual educational setting. I assumed a sociocultural perspective that draws from Vygotsky’s theory of learning and development. A sociocultural perspective offers a promising epistemological conceptualization of children, their learning, and language development as mediated by social, cultural, and historical contexts. One grade 2/3 classroom with 18 students from Eritrea, Nepal, Somalia, Sudan, and Syria participated in the study. The data included observations, video recordings of students working on mathematics activities, copies of students’ work, and interviews with students. The results of the study revealed the teacher’s pedagogical practices as a significant influence on students’ mathematical meaning-making and learning experiences, which in turn influenced students’ individual identities as mathematics learners in the grade 2/3 classroom. There were also institutional and sociopolitical aspects that influenced the teacher’s practices, and in turn, influenced students’ mathematics experiences. Hence, the influences on students’ learning of mathematics take the form or shape of a reciprocal formation where one influence is connected to and influences the other. The findings of the analysis also show that it was the students’ interactions with one another that were at the heart of their meaning making. Students’ interactions were significant to their meaning making as they were constantly learning from one another. Little meaning making would have happened without these interactions. These interactions encouraged students to develop a collection of resources to share their thinking and ideas through verbal, visual, and written mathematical communications. Hence, utilizing language to make meaning and to negotiate their mathematical understanding. Ultimately, the descriptions of multilingual learners’ mathematics experiences and meaning making may inform research and practices to support other multilingual learners’ experiences in mathematics education. This study also contributes to what is still a very limited body of literature on multilingual students’ mathematical experiences and meaning in a Canadian educational setting.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.023 | 0.006 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".