The Increasing Role of Technology in Teaching and Learning Activities in Higher Education
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
We are pleased to publish the second regular issue (Volume 13, Issue 2) of <em>Higher Learning Research Communications (HLRC)</em> for 2023. If there is a common theme that emerged from the COVID-19 pandemic, it is the increased role that technology did and will continue to play in teaching and learning activities in tertiary education. The range of articles reflects the interest in digital teaching and learning and includes the use of scaffolded simulations, the influence of immersive virtual reality in the classroom, and gamification. In addition, guidelines around instant messaging are proposed that should continue the conversation around the ethical use of technology in teaching and learning. As is typical in the HLRC, the authors reflect diverse countries, including Canada, India, Malaysia, Mexico, South Africa, and the United States. We look forward to 2024, when we expect to publish a special issue on English language influence in higher education teaching, learning, and research.
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.
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 | 0.005 | 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 | 0.001 |
| 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 it