Bibliographic record
Abstract
Abstract NOTE: The first page of text has been automatically extracted and included below in lieu of an abstract Main Menu Session 2058 A Building-Block Approach to Dynamics Marilyn J. Smith School of Aerospace Engineering Georgia Institute of Technology Atlanta, GA 30332-0150 Abstract The transition from memorization of formulae to the independent thinking required in engineering courses is accomplished via courses typically entitled “Statics” and/or “Dynamics”. These courses, in particular Dynamics, pose a major hurdle for some students who wish to become engineers. They are known at many universities as “gate” or “weed-out” courses. Since competency in the principles of these courses is necessary for success in the higher-level courses, teaching practices that improve a student's learning and motivation in the course are desired. This paper discusses a practice that has proven successful for a dynamics course that included students in different years and majors, as well as a class of sophomores of one major. Introduction The transition from memorization of formulae, a process that can succeed in high school and collegiate Physics courses, to the independent thinking required in engineering courses is accomplished via courses typically entitled “Statics” and/or “Dynamics”. These courses, in particular Dynamics, pose a major hurdle for some students who wish to become engineers. Not only must the student recall the principles learned in calculus and physics, but the student must also utilize basic geometric and trigonometric concepts that have may been buried since middle and early high school. Competency in Dynamics can be viewed as successfully building a bridge between science and engineering. The pre-requisite mathematics and physics are crucial to developing a stable foundation. Each new concept - the kinematics and kinetics of translating and rotating bodies - is a block necessary to building this bridge. The lack of one of these concepts will cause an instability in the learning structure since concepts introduced as the course progresses require that all previous material be thoroughly understood. The traditional collegiate method of lecturing and testing in these classes may cause some promising students to falter in these courses. Traditionally, three to four tests are given during the course, each accounting for 15% to 25% of the final grade. Because testing is infrequent, each test requires the utilization of concepts in multiple problems. Recognition by the student and professor that a concept is not well understood comes too late to help the student's grade and self-esteem. Subsequently, some students may drop the course, change majors, or give up on succeeding in the course and/or engineering. Proceedings of the 2002 American Society for Engineering Education Annual Conference & Exposition Copyright ã2002, American Society for Engineering Education Main Menu
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".