Teacher expectations in the early primary grades: A scoping review
Bibliographic record
Abstract
Abstract Teachers are the single most important in‐school factor affecting student learning outcomes. As a result, researchers and policy makers are particularly interested in the ways that teacher‐level factors influence the learning opportunities that teachers provide in their classrooms. A growing body of research suggests that the expectations a teacher sets for individuals and groups of students can significantly affect the learning opportunities that are provided to them. This is highly problematic, especially since teacher expectations can be inaccurate evaluations of student abilities and teacher expectations differentially affect the learning outcomes of racialised students as well as children living in poverty. Much of the research base regarding teacher expectations has focused on upper elementary and secondary grades with little research focus on the ways that teacher expectations are formed and impact children in the first years of formal schooling. Given the potential impact of sustained teacher expectation effects, an in‐depth review of teacher expectation research in the early primary grades is warranted. This study uses a scoping review methodology (H. Arksey and L. O’Malley, ‘Scoping Studies: Towards a Methodological Framework, International Journal of Social Research Methodology , 2005, 8(1), 19–32) to analyse research on teacher expectations in the early primary grades. Five themes encapsulate the scope of research published from 2000–2021: (1) teacher expectations of school readiness skills, (2) factors that influence the formation of teacher expectations, (3) teacher expectation effects, (4) stability of teacher expectations, and (5) intervention studies. This paper presents the current state of knowledge surrounding expectations in the early primary grades, as well as highlights challenges in need of further research.
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 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 | 0.020 | 0.093 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.015 | 0.015 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".