Engineering with Electricity and Magnetism: A Guided-Inquiry Exercise for High-School Students to Enhance Understanding of Faraday’s and Lenz’s Laws
Bibliographic record
Abstract
Abstract Engineering with Electricity and Magnetism: A Guided-Inquiry Exercise for High-School Students to Enhance Understanding of Faraday’s and Lenz’s LawsMany high-school students and teachers find the concepts of Faraday’s and Lenz’s laws to bedifficult to comprehend and often cannot see their relevance to our everyday lives. In manycases, these topics are omitted from the high-school curriculum or given a cursory coverage dueto the teachers’ lack of comfort with this material. However, these two laws are a criticalfoundation for many of the key technological innovations which have taken place over the past100 years, particularly in the area of electricity generation. As such, it is important that all high-school students develop a basic comprehension of these laws and how they can be used in anengineering context.As part of our high-school outreach effort we have developed a guided-inquiry exercise which isdesigned to enhance the understanding of these two fundamental laws. This hands-on exerciseenables high-school students to discover through their own efforts the essential ideas behindthese laws. At the same time, the students gain a greater appreciation for the role of engineers insociety by working through the steps to solve a simple design problem. This problem is basedaround the generation, storage, and use of renewable energy. For this exercise the students aregiven a kit which includes a flashlight that contains a coil and a magnet assembly. Thisassembly allows energy to be generated by shaking the flashlight, through the process ofelectromagnetic induction. The basic design problem which the students uncover through thesteps of the exercise is how to make use of this energy which is generated in this highly transientmanner.In order to share this exercise with as many students and teachers as possible we have begun topresent this as a workshop to high-school teachers at regional conferences of science teachers.The primary purpose of this paper is to fully describe this hands-on exercise and how the guided-inquiry method was implemented to highlight the most important concepts behind Faraday’s andLenz’s laws. We will also discuss the supplementary material that was prepared for the teachers,so that they would have the tools to highlight the engineering developments which have resultedfrom these laws. In addition, we will present some preliminary survey data that we havegathered from these conferences.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.004 | 0.008 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.015 | 0.006 |
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".