IN COLLISIONS AND COOPERATION THEY LEARNT: FINDING A BALANCE BETWEEN ONLINE AND IN PERSON TEACHING TOOLS
Bibliographic record
Abstract
As our courses implement more online learning tools, we are facing both the opportunities and the challenges that such tools present. On the one hand, students can watch and re-watch streamable and downloadable lectures, in their own time and at their own pace, to get more benefit out of course material than they might in a single, in-person exposure. Moreover, by providing not only captured scheduled lectures, but also additional custom created lectures, we are able to expand our teaching opportunities in order to go into greater detail on topics relevant to students with particular interests or needs. At the same time as we have been moving toward online teaching tools, we have been developing more creative personal teaching methods. In our first year course, we introduced seminars, unusual for engineering education at the undergraduate level. The seminars get students used to learning through independent reading and small group discussion, facilitated by an expert. In a second year design course, instead of attending tutorials of 30 students, teams meet for half an hour a week with a Project Manager who is also their Communication Instructor. These deeply personal meetings both monitor the progress of their design and allow for individualized instruction on design documents. The question we are exploring here is whether we can use Marshall McLuhan’s concept of extending into technology to understand how in-person, interactive teaching modes balance the effects of on-line and remote methods. The idea of the in-person, physical dimension of learning is reflected in the title of this paper, which quotes The History of the World by J.M. Roberts. He suggests that what generated "civilization" out of roughly organized communities, was a combination of a critical mass – a certain, unstated number of settled humans –and movement, the addition of different humans from different places. It was both physical presence and interaction that created the basis for the kinds of astounding developments that led to writing, art, complex government and justice systems. Once certain numbers were achieved, civilization was enabled "by throwing together peoples of different tradition. In collision and cooperation they learnt from one another and so increased the potential of their society." (62) We have been intuitively moving forward on these two fronts: implementing new technological teaching tools, and developing innovative ways to balance these impersonal methods by “throwing together” students from all over the world and instructors at every level, from Teaching Assistants to Professors. We are now seeking a clearer understanding of how these forces balance, enable and/or augment one another
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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 | 0.001 | 0.003 |
| 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 | 0.000 |
| 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".