Effective Teaching & Teaching Evaluation Practices: Canadian University Geography Departments
Bibliographic record
Abstract
In this thesis teaching evaluation practices in Canadian university geography departments are examined. The objective of this research is to identify good practices for teaching evaluation that can be applied within geography departments at Canadian universities and may be applicable to other departments and within other countries. In order to meet this goal a number of research questions were identified. These include: What is effective teaching in higher education?; What is effective teaching within the discipline of geography in higher education?; How and why is teaching evaluated in higher education?; What is the breadth of teaching evaluation practices currently used in geography departments within Canada?; How are the results of teaching evaluations used to enhance teaching quality within the discipline of geography in higher education?; How are the results of teaching evaluations used to reward teaching excellence within the discipline of geography in higher education?; and, What are ‘good’ teaching evaluation practices within the discipline of geography in higher education? \nA thorough review of the literature resulted in the development of a conceptual framework for effective teaching and for effective teaching evaluation. Both of these frameworks were tested using empirical data. The empirical data were collected from a national-level survey of geography departments across Canada (n=10), oral interviews with chairs of Canadian geography departments (n=23) and oral interviews with individuals suggested by chairs of Canadian geography departments (n-11).\nThe research provided validation of the conceptual framework of good teaching. This framework identified eight parameters of good teaching: discipline knowledge, course organization, delivery of instruction, student/instructor interaction, assessment tasks, administration, professional development and skill development. The results from the research suggested that the original conceptual framework of effective teaching evaluation was too simplistic. It also demonstrated that effective teaching evaluation occurs within the demographics and culture of place which results in the creation of an environment of evaluation. In this environment of evaluation seven parameters of an effective teaching evaluation system are identified including: defining good teaching, operationalizing good teaching, defining purpose of teaching evaluation, using a multiplicity of tools, employing an iterative teaching evaluation cycle, including a system of awards and including a mechanism for teaching enhancement.\nIn the future these conceptual frameworks can be tested in a variety of other disciplines and within different countries. The primary stakeholder in this research was chairs of geography departments. There are a number of other stakeholders described in this research and the frameworks could be tested from their perspectives.
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 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 | 0.009 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.011 | 0.000 |
| Scholarly communication | 0.000 | 0.006 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".