Enhancing Travel Ease: Designing an Integrated Platform for Camping Trip Planning in Alberta, Canada
Bibliographic record
Abstract
Alberta’s diverse natural landscapes make it an attractive destination for camping, yet young adults often face barriers when organizing short camping trips. Essential information about campsites, activities, transportation, budgeting, and social connection is scattered across multiple platforms, while existing tools address only parts of the process. As a result, planning can feel fragmented, costly, and socially isolating. This thesis responds by proposing Campac, an integrated digital platform designed to simplify camping trip planning for young adults in Alberta. Through a combination of literature review, user surveys, and expert interviews, the research identifies common challenges: fragmented and inconsistent information, limited access to affordable gear and transportation, and difficulties in finding travel companions. These insights informed a user-centered design process that guided the development of the platform. The resulting concept consolidates trip planning into four core sections: Explore for discovering campsites, activities, and budget-friendly options; Profile for personalized experience; Community for discussions and connections; and Feeds for sharing trips and resources. The platform’s visual identity draws on nature-inspired graphic elements and accessible typography to foster usability. Prototyping across both web and mobile ensured consistency, while usability testing confirmed the value of centralizing resources and emphasized the importance of clear navigation and inclusive features. Findings indicate that Campac addresses key gaps in existing camping services by unifying scattered resources, supporting affordability, and fostering community. While the project was limited by a small survey sample and prototype-level testing, it provides a strong foundation for future development, including broader user studies and integration with official park databases. Overall, the research demonstrates how a user-centered digital platform can make outdoor recreation more convenient for young adults by transforming fragmented information into a cohesive and supportive experience. By bridging logistical, social, and financial barriers, Campac demonstrates how design can enhance not only the practicality of camping but also the sense of connection and confidence among young adventurers. In doing so, the project highlights the broader role of visual communication design in shaping meaningful, inclusive experiences in outdoor camping and activities.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 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".