The use of anti-patterns in human computer interaction: wise or III-advised?
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
In this paper the tenability of anti-patterns in Human-Computer Interaction is explored. Patterns have been accepted as being useful in software development and more recently also in Human-Computer Interaction. A concerted effort is being made in Software Engineering to identify and document anti-patterns. Patterns and anti-patterns are essentially about transferring captured expert knowledge, therefore compatibility between the nature of anti-patterns and the nature of the learner's internal knowledge representation and processing is crucial. This paper addresses the differences and similarities between patterns and anti-patterns and how this impacts on the mental models and cognitive processing of patterns and anti-patterns. We present evidence from theories of mental modelling and reasoning that highlight possible significant dangers in the use of anti-patterns to teach novices human-computer interaction principles. If the notion that the current representation of anti-patterns is not supporting cognitive processing is correct, a new approach to structuring anti-patterns is needed. Recommendations are made towards a new specification technique for HCI antipatterns.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.002 |
| 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 it