Critical analysis of quantitative-qualitative research models into the effect of instructional and transformational leadership on student achievement
Bibliographic record
Abstract
The purpose of this study is to examine a body of mixed methods (qualitative and quantitative) research on how instructional and transformational leaders' behaviours affect student achievement. Current political demands on the role of the school principal and increased emphasis on accountability place students' academic achievement at the top of school reform agendas and add weight to the role of the school principal (Gentilucci & Muto, 2007; VSB Leadership District Review Team, 2008; Ministry of Education BC Mandate for the School System, 2008, British Columbia Educational Council, 2008). I critically analyze the latest research findings with the purpose of offering practical insights and contributions to policy makers, researchers and educational leaders to model future courses of action in educational administration and accountability. The two research studies considered in this review were conducted by Alig- Mielcarek (2003) and Leithwood, Jantzi, and McElheron-Hopkins (2006). Alig- Mielcarek (2003) in the state of Ohio, United States, carried out a study on instructional leadership and student achievement in 146 schools. Similarly, Leithwood, Jantzi, and McElheron-Hopkins (2006) conducted a study in Ontario, Canada, over five years, on transformational leadership and student achievement in 100 schools. Two layers of analysis are used in this review. The first layer of analysis conceptualizes the leadership role according to De Maeyer et al.' s (2007) theoretical framework: instructional and transformational leadership models. The objective of this layer of analysis is to see to what extent the conceptual role of the principal matches the variables considered in the methodology of each study. The second layer of analysis examines the conceptual methodologies used by the researchers according to Hallinger and Heck's (1988) theoretical perspective on administrative leadership. I interpret the multilevel nature of the path analyses utilized by the researchers and the variables they linked directly or indirectly to student achievement. The objective of the second layer of analysis is to examine the extent of the multilevel approach employed in their path analysis and the validity of the findings. This study concludes that both Alig-Mielcarek's (2003) study and Leithwodd et al.'s (2006) study contribute to a better understanding of the path models that can be used to study educational leadership and student achievement. However, there are some threats to the validity of both studies; careful attention must be paid to the numbers of variables at each level and to gathering the most accurate data available. Neither study's leadership frameworks appears sufficient for effective school leadership. A combination of diverse frameworks is recommended to meet current educational demands.
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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 | 0.383 | 0.477 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.013 | 0.009 |
| Science and technology studies | 0.009 | 0.020 |
| Scholarly communication | 0.013 | 0.013 |
| Open science | 0.004 | 0.009 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".