Evidence-Based Practices in Special Education: A Reflection on the Philosophy, Research and Teaching
Bibliographic record
Abstract
Some researchers have taken evidence-based practices (EBPs) as the main solution for enhancing the learning outcomes of students with disabilities. The manner in which the application of EBPs assumes teaching strategies to be aligned with students’ learning problems or disability situations betrays a mechanical approach to dealing with issues of students with disabilities. Post/positivism and scientific methods are underpinning threads supporting these developments. Yet, the complexity of teaching practice tends to be overlooked and scientific methods overextended. In this background, this article reviews the philosophy of science so that a more complete and historical understanding of science is represented, which is helpful in facilitating the discipline to draw attention to the limitations of current discussions about EBPs. Subsequently, we raise three ways to elucidate the research and teaching practices. First, ontological, epistemological and methodological diversities should be practiced to interrogate issues related to EBPs. Second, alternative methodologies should be encouraged to counter the environmental and systematic barriers compromising students’ learning difficulties. Last, a problem-solving approach should be used to compete with a mechanistic approach in responding to students' learning difficulties.
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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 | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 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".