Collaborating For Success: Team Teaching The Engineering Technical Thesis
Bibliographic record
Abstract
This paper will examine the collaborative teaching process undertaken at College of the North Atlantic- Qatar (CNA-Q) by Engineering and the Communication faculties to improve the overall quality of engineering students’ capstone projects known as the Technical Thesis. The Technical Thesis is divided into two separate components: a proposal stage (Tech Thesis 1- investigative) and a technical/presentation stage (Tech Thesis 2 - final written and oral communicative report). It involves a complex blending of experimentation, technical information and data with competent formal technical report writing skills. In an EFL (English as a Foreign Language) environment, this challenge is formidable for students as it involves high technical as well as linguistic competencies. In an effort to gain accreditation from the Canadian Technology Accreditation Board (CTAB), a standing committee of The Canadian Council of Technicians and Technologists (CCTT) which provides national accreditation for over 240 post-secondary engineering technology and applied technology programs in Canada, the School of Engineering realized student results on the Technical Thesis at CNA-Q needed marked improvement. A pilot project, started during the 2008- 2009 academic year, brought engineering faculty from various fields (Chemical Processing, Electrical, Mechanical, Process Automation and Telecommunications) together with writing faculty from the Communications Department to take on the task of improving final Tech Thesis results through co-delivery. Specifically, this paper will examine: the process of developing the collaborative teaching approach at CNA-Q; its perceived value by the stakeholders (faculty and students); the ongoing challenges associated with its delivery; and the overall level of improvement in student performance on the Technical Thesis as a result of the collaboration.
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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 | 0.023 | 0.048 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.014 | 0.010 |
| Scholarly communication | 0.023 | 0.011 |
| Open science | 0.003 | 0.019 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.008 | 0.004 |
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".