Teaching Strategies and Adaptations of Teachers in Multiculturally Diverse Classrooms in Seventh-day Adventist K-8 Schools in North America
Bibliographic record
Abstract
Problem. The rapid growth of diverse populations is affecting the educational system, and teachers often have not received training in multicultural education. The goal of this study is to document the multicultural teaching experiences of elementary Seventh-day Adventist (SDA) teachers in the United States and Canada. Method. Survey questionnaires were sent to elementary school teachers to ascertain training, goals, paradigms, and challenges in teaching students from diverse cultures. Through a purposive sampling process, three teachers were chosen for in-depth interviews and observation. Results. Seventy percent of the 1,780 questionnaires sent out were returned. Many teachers reported receiving training in their formal education or during in-service training while 40% reported never having any training. Five multicultural paradigms describe the strategies used by the teachers. The self-concept development paradigm and the ethnic additive paradigm were used by the majority of the teachers. The least used paradigm was the language awareness paradigm. Observations and interviews corroborated the data from the survey. The various paradigms (Banks, 1994) were not closely related to goals (Nel, 1993). The greatest challenges experienced by teachers were language related. Other challenges included teachers’ sensitivity to students’ needs, difficulty in dealing with parents, and several learning barriers. Learning barriers included students’ low self-esteem; lack of academic preparation or motivation; fear of failure, lack of role models; race rivalry and prejudices. Conclusions. The teachers in this study tend to primarily utilize the human relations approach in their multicultural classrooms rather than the social reconstructionist approach.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".