Sustainability within Technical Engineering Curriculum – A Hydraulic Fracturing Module in Fluid Mechanics
Bibliographic record
Abstract
A transferable module is presented that brings sustainability topics into a core chemical engineering fluid dynamics course. A topic was chosen based on technical applicability to the course and currentdebate on the topic. In this case, hydraulic fracturing (‘fracking’) was chosen for the connection tocourse content (e.g. pumps, porous media flows) and its widespread debate in the United States. Onthe day of the activity, a guest instructor first surveyed the students with questions on theirunderstanding of and opinion on topics within fracking. The students were then shown two short videoson the topic, one from a science-focused group and one from an industrial proponent of the frackingtechnology. After the videos, students were sorted into five theme areas: science/technology,economics, policy, society, and the environment. These areas were chosen to highlight the breadth oftopics that must be engaged in order to approach such complex problems. Further, it is a move towardinterdisciplinary learning within engineering curricula where students consider broader societal themesas part of an engineering solution4. Students brought a research device for this day, and all students hadaccess to laptops or various smart phone devices. During the in-class activity, the students in theirgroups engaged in their own research on the topic using a variety of web-based sources. As they foundinformation relevant to their theme area, they took notes and then brought that into a groupaccumulation of relevant information. With this data compiled, one representative from each areasummarized salient points to the entire class. A course-wide (n ~ 40) discussion ensued with facilitationfrom the guest instructor. Beyond that day of integration, the course instructor aimed to show theimportance of such topics via three practices. First, the course objective ‘Students will analyzeengineering problems in the context of economics, technology, society, and the environment’ wasadded to the course syllabus along with ten other objectives focused on more traditional technicalcontent. Second, after the activity, a homework assignment was given on material balances and pumpsizing requirements associated with a typical hydraulic fracturing site to directly connect the technicalcourse content to the broader focus of the fracking activity. Lastly, a bonus problem on the final examasked students “If you were a landowner, would you allow hydraulic fracturing (fracking) on your land?Briefly explain your answer.” Select survey results from Fall 2017 are chosen to highlight students’ selfreportedunderstand of and support for fracking (pre-post responses), if the class-format was effectivein their learning, and open ended comments relating to changes in their opinion and the course format.The transferability of this module is discussed, along with ways to translate the concept to othercourses, such as into a heat transfer course via a nuclear power module.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".