Editorial: Teaching and learning human–computer interaction (HCI): current and emerging practices
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
Human-Computer Interaction (HCI) is the academic discipline dedicated to understanding how 14 humans interact with technology. Since technologies play such a prominent role in our daily lives, 15 ensuring they are designed to reflect the full spectrum of human abilities, skills, and experiences is 16 more important than ever. Sturdee explored pedagogical approaches to teach sketching to computer science and HCI students, 71 many of whom were uncomfortable with the technique and needed to be convinced of its value as an 72 ideation and exploration method. 73The authors declare that the research was conducted in the absence of any commercial or financial 75 relationships that could be construed as a potential conflict of interest. 76Author Contributions 77 CMM drafted the editorial. KS, AK, AJ, and OSC contributed to the draft. All authors approved the 78 submitted version. 79
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 | 0.006 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.007 |
| 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