THE SELF-REPORTED CONFIDENCE AND PROFICIENCY LEVELS OF UNDERGRADUATE ENGINEERING STUDENTS IN AN ENGINEERING TECHNICAL COMMUNICATION COURSE
Bibliographic record
Abstract
We have conducted surveys at thebeginning and the end of semesters in an EngineeringTechnical Communication course, surveys that aredesigned to determine how confident our students feelabout “Communication Skills” and personal skillsdevelopment, or “Lifelong Learning” (defined here asthe ability to devise ways to develop broader knowledgeand to identify personal strengths and weaknesses). Ourobjective is to see whether students’ confidence levelsincrease and then compare these levels with wherestudents believe they should be once they graduate. Inthis paper, we report on the data obtained from thesetwo surveys conducted from Winter 2013 until Winter2015. Normally, one section of the class completed thesurveys, although two sections (A01 and A02) completedthe surveys in both the Winter 2013 semester and in theWinter 2015 semester, for a total of 9 classes thatparticipated.. So far, we have found that students doindeed feel more confident in all the surveyed areas atthe end of the semester.Yet, regardless of their growing confidence,many students also feel they have not yet achieved thelevel of proficiency expected of them once they graduate.For example, for “personal skills” (such as applyingcritical inquiry and analysis to engineering problemsand doing the communications that support theengineering work), 5 represents an ability to lead orinnovate in a particular area, and 3 indicates an abilityto understand and explain. In our surveys the aggregatewas 3.4 for the initial survey (n=450 students) and 3.5for the end-of-term survey (n=378). Most telling,however, is the level students feel they must achieve bythe time they graduate (4.5). In other words, byacknowledging that lifelong learning is an importantattribute, one that they will have to continue to developif they are ever to achieve the level expected of them,students demonstrate a remarkable level of selfawareness.
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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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".