TravelTales: Reflecting on Meaningful Travel through Digital Scrapbooking and Journaling
Bibliographic record
Abstract
Travel experiences represent enjoyable periods in one's life, but also offer opportunities for thoughtful reflection and personal growth. To facilitate these insights and enhance self-understanding, we developed TravelTales, a smartphone app designed to support storytelling through scrapbooking and reflection through guided journal questions. The development of the app followed a human-centred design approach, starting from design space formulation to initial formative interviews (n = 23) that further explored the concept of meaningful travel. Our initial findings frame travel as a fleeting life experience that challenges one's usual position in space and time, accelerating personal growth. To understand how people narrate their travels to derive such growth, we deployed TravelTales in a probing field study with travellers (n = 8), finding that TravelTales fosters promising outcomes related to personal reflection, remembrance, and self-learning. Finally, we discuss the implications of our work in designing to support reflection and enhance travel experiences.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".