Research Insights from a Decade of Campus-Wide Implementation of Web-Supported Academic Instruction at Tel Aviv University
Bibliographic record
Abstract
This paper describes the scope and outcomes of Virtual TAU, a campus-wide project that aims to integrate information and communication technologies into the academic instruction at Tel Aviv University (TAU). It provides data, insights, and conclusions drawn from various research and evaluation studies that were conducted at the university during the last decade. The paper presents its material on three main levels: (a) the institutional level, in which we describe the scope and pace of the process of diffusing the Web as an innovation into the university’s instruction, and how this diffusion compares to classical diffusion models; (b) the pedagogical level, in which we present some of the innovative pedagogical practices developed and implemented as well as the current state of Web usage among both the university’s teachers and students; and (c) the costs and benefits of the integration of Web-supported academic instruction, where we apply a newly-developed cost-effectiveness model to Virtual TAU courses.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.015 | 0.040 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.008 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".