Reimagining home-based learning through comparisons of alternative schooling methods
Bibliographic record
Abstract
Moving forward into a post-pandemic world, we can reimagine institutional education systems by reflecting on the lived experiences of emergency home-based learning and exploring the alternative narratives of traditional homeschooling. Having worked in the educational sector of Ontario during the pandemic, I observed families transitioning their homes into blended learning spaces for emergency home-based learning and the challenges that came with this change. Parents found themselves trying to explain teaching materials with no previous training while teachers tried to enforce traditional classroom expectations in households where many children had no remote learning structures in place (Fontenelle-Tereshchuk, 2020; Orelien-Hernandez et al., 2021). In contrast, the growing homeschooling alternative, a blend of home and educational space, had established relational systems to support this kind of community-based pedagogy. This alleviated many of the challenges of multimodal learning and had shown promise in increasing student academic scores, creating alternatives to socioeconomic barriers found in institutional education, and fostering racial protectionism (Mazama & Lundy, 2012; Statistics Canada, 2021a; Van Pelt, 2015). My paper introduces the preliminary questions and discussion of my proposed study for my master’s thesis using place-based pedagogy (Corbett, 2009; Ellsworth, 2005; Gruenewald, 2003; Illich, 1971) to open a conversation around homeschooling as a resource for post-pandemic pedagogical design and development.
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 | 0.014 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".