Product Design Enhancing Environmental Perception and Encouraging Behavioural Change: Eco-Information – the Relationship of Design Styles and User’s Emotions
Bibliographic record
Abstract
This research is to develop the products that can communicate environmental information to the user. The study investigated design styles of eco-information and impact on user’s emotions which can be used as data for product design enhancing environmental perception and encouraging behavioural change. The research aimed to 1) study design styles of eco-information and impact on user’s emotions 2) analyse the relationship of design styles and impact on user’s emotions effective in promoting environmental behaviour change. Ten-second video clips of seven design styles were presented through a computer and a projector and perception evaluation forms were employed. The sample included 60 students from the Faculty of Architecture and Design, Rajamangala University of Technology Phra Nakhon, Bangkok, Thailand. The results showed that the most effective design style could encourage emotions in the aspects of interest, excitement and preference. This study found that using living creatures to encourage emotions was the most effective attribute. Additionally, giving detailed information through the use of texts and graphs could encourage effectiveness in promoting behavioural change towards energy and resource consumption.
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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 | 0.002 | 0.005 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".