Redesigning for Student Success: Cultivating Communities of Practice in a Higher Education Classroom
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In this paper, I discuss the process of redesigning and teaching a mandatory, academic skill building course for students on academic probation at Mount Saint Vincent University (MSVU) in Atlantic Canada. The rationale for redesigning the course was to offer an alternative, holistic instructional approach for instructors who were teaching a modular-based curriculum. The original course was designed to focus on improving students’ individual self-efficacy and motivation for academic success; however, the social and relational nature of learning was not articulated as an underpinning theory in the curriculum. In the new curriculum, I draw on both Etienne Wenger’s (1998) notions of communities of practice as sites for learning and Howe and Strauss’ (2000; 2007) work on generational analysis as theoretical frameworks. Furthermore, I incorporate Wenger, McDermott, and Snyder’s (2002) principles for cultivating communities of practice as a way of putting theory into practice. Initial data collection led to the main inquiry question: How could a curriculum, centered on building community in the classroom, help students to cultivate meaningful learning experiences that take learning beyond a “fake it ‘til you make it” mentality? This question guided the curricular design process and also my experiences teaching the course at MSVU during the Fall semester of 2012
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 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 it