Links among student club projects, senior design projects, and international competition projects, a case study
Bibliographic record
Abstract
Abstract Links among student club projects, senior design projects, and international competition projects, a case study Abstract: xxxx University is a teaching orientated university without Engineering Ph.D. programs. How to engage undergraduate students in research projects, especially extra-curriculum research projects is challenging from multiple aspects, including financial support, faculty advising support, students' motivation, and resources. This paper presents our successful experience so far with a series of student projects from different entities in three years period from 2018 to 2021, such as IEEE student club and regional competition projects, senior design projects solving local community and industrial problems, and international intelligent ground vehicle competition projects, etc. These projects originated from different opportunities and evolved in variable ways. Yet they link among each other in terms of scope, content, and engineering knowledge. They all bare the commonly important threads of Engineering education, namely student engagement, hands-on experience, real world design and application, as well as teamwork, time management skills, and project management skills. Detailed information of each sample project, the evolution from one project to another, the common thread linking all projects together, factors that contribute to the progress of the projects and students experience, involvement of community and industry, internal and external grant, as well as the relationship to engineering curricula will be presented. This paper will also discuss lessons learned for duplicating the experience, on-going projects, a new technical elective course "intelligent vehicle essentials", and our roadmap for the next few years to sustain two parallel platforms for education and research.
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.
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 | 0.008 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.012 | 0.004 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".