Bibliographic record
Abstract
In my 2020 paper ‘Teaching, telling and technology’, I explored the essentially second-personal, I-thou, relation between teacher and student—a relation I take to be essential to teaching at its most effective and inspiring. I concluded that essay with a critique of web-based instruction in universities, arguing that there are features of online courses that undermine dimensions of the teacher–student relation that are profoundly valuable. ‘Teaching, telling and technology’ appeared just as the COVID-19 pandemic disrupted the completion of the 2019–2020 academic year and forced many schools and colleges around the world to teach part or all of the 2020–2021 academic year online. In this article, I consider how the experience of teaching remotely during the pandemic illuminates the position I took in my earlier paper. I find that while we all have reason to be grateful that remote communication platforms made it possible for formal education to continue during the pandemic, there remain reasons for caution about online courses, particularly when taught asynchronously. This, I argue, is particularly, though not exclusively, true of teaching in the humanities. More concerning still is that many problematic features of web-based instruction are symptoms of deleterious trends in higher education in general. Nevertheless, the last year has vividly revealed that online platforms create exciting possibilities for collaborative teaching and research and that there is reason to hope that further innovations in technology can ameliorate existing shortcomings in online education, so long as we do not lose sight of certain core educational values. Drawing on such diverse thinkers as Oakeshott, Ilyenkov and Kant, I argue that, if we are to initiate pupils into the conversation of humanity and enable them to think for themselves, then educational encounters must foster and exhibit the creative movement of thought in conditions of uncertainty, and that our model—our ideal—for achieving this should be real-time, in-person intellectual engagement between embodied beings in shared physical space.
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 | 0.002 | 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 | 0.000 | 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 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".