Pan-Diversity Integration as an Equity Trap: Lessons From Preservice Teachers’ Preparation for Teaching English Language Learners in a Predominantly White Institution in the United States
Bibliographic record
Abstract
Background: Nationally, there is an overwhelming body of research that has revealed a systemwide underpreparedness of both pre- and in-service teachers who are predominantly White and monolingual for teaching English language learners (ELLs) throughout the United States. Despite various responses to address preservice teachers’ underpreparedness to teach ELLs, there has been a lack of transformative change in White mainstream preservice teachers’ preparation to teach ELLs, due to teacher education programs’ indiscriminate, pan-diversity approach to diversity as inclusive of all forms of difference, without explicitly attending to any form of difference such as those confronted by ELLs. This pan-diversity approach endorses generic fairness as sameness practices that may lead to equity traps that shape preservice teachers’ patterns of thinking and behavior that hinder the possibilities for creating equitable schools for children of color, including ELLs. Purpose: The widespread underpreparedness of teachers for ELLs suggests an urgent need to reexamine how teacher education programs are providing opportunities for learning about ELL-related knowledge and practice. The goal of this study is to understand 433 preservice teachers’ experiences of learning to teach ELLs in a predominantly White teacher education program under a pan-diversity framework. Research Design: A mixed-methods design that includes surveys and interviews was used to address two central research questions: What are preservice teachers’ perceptions of learning to teach ELLs in a predominantly White teacher education program that utilizes a pan-diversity framework? How do their opportunities to learn ELL-related content differ across subprogram groups? Quantitative and qualitative data analysis methods were used to analyze the data generated from the survey and interviews. Findings: Triangulation of our quantitative and qualitative data revealed systemic neglect of ELLs in both coursework and field practice in the teacher education curriculum, resulting in underpreparedness among the preservice teachers across the subprograms. The results indicate that the current pan-diversity integration approach has served as an “equity trap” that will preclude the preservice teachers from becoming successful with their future ELLs. Conclusion: This study demonstrates the critical need to eliminate the pan-diversity equity trap to systemically incorporate ELL issues within teacher education to not only transform preservice teachers’ deficit thinking about ELLs but also fill their knowledge and skill gaps for working with ELLs. The study has significant implications for teacher education programs to transform ELLs’ status from invisibility to rightful prominence in the program.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".