Search arXiv⌕ Search

arXiv · physics/0612117

Science and Engineering Education: Who is the Customer?

Abstract

As education systems move toward business models of operation, there is a strong tendency to misidentify the student as the customer. Misidentifying the student as the customer leads to interpretation of the course credit or degree as the product. The true product is the additional knowledge, skill, and ability that course credit and degree should represent. Consequences are potentially disastrous, because the notion that "the customer is always right" can lead to the perceived product (course credit or degree) meeting the desires of the misidentified "customer" (student) rather than the real product (value added to student) meeting the standards of the properly identified customers (future employers and taxpayers).

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Michael Courtney, Amy Courtney. 2012-08-25. Science and Engineering Education: Who is the Customer?. https://arxiv.org/abs/physics/0612117

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

Active Learning with Generative AI in Introductory Physics: A Multi-Institutional Study of the P-A.I.R. Framework

Generative AI tools have become part of how students study physics, yet unstructured use may reduce students' opportunities to work through problems independently. The Physics AI-Replication (P-A.I.R.) framework structures AI use as a four-step cycle: students identify a challenging problem, obtain an AI-generated explanation and solution, request similar practice problems, and solve them independently before reviewing the AI's solutions. We evaluated P-A.I.R. in 11 algebra- and calculus-based introductory physics sections at four U.S. institutions using a common end-of-semester survey. Most students reported improved conceptual understanding (90.9\%) and found the replicated practice problems helpful (97.7\%), and these two ratings were strongly associated ($r_s = 0.58$). Perceptions of both components, as well as post-engagement confidence ($μ= 7.18$ on a 1-10 scale), were consistent across institutions. Post-engagement confidence was associated with perceived improvement in conceptual understanding ($r_s = 0.37$) and the helpfulness of replicated practice ($r_s = 0.35$), but not with how often students used AI ($r_s = 0.02$) or with self-reported GPA ($r_s = 0.13$). Thematic analysis of open-ended responses showed that students valued AI primarily for conceptual clarification and structured problem solving (63.0\%), while their main concerns were AI accuracy (34.2\%) and the need for explanations that guide rather than simply provide answers (29.7\%). These findings suggest that how students engage with AI matters more than how often they use it, and that frameworks sequencing AI assistance with independent problem solving offer a practical, transferable approach for physics instruction.

physics.ed-ph↗

Balancing broomsticks to a t!

A classic question from rotational mechanics asks, "Is it easier to balance a broomstick heavy side up or heavy side down?" Measuring the time a student can balance an asymmetrically weighted meter stick in two orientations is a straightforward exercise that can be used to introduce or review the t' framework, which guides lab students in comparisons of results and iterative improvement of their measurements. As a two-year college physics program, many of our students attend from other institutions, so while t' is taught in the introductory mechanics labs, there is no guarantee that a student in a following lab course will be familiar with the material. To address this, the t' concepts are reviewed in the first session of subsequent lab courses. The broomstick experiment is a quick and fun implementation.

physics.ed-ph↗

Getting the picture - Subtractive color mixing with an inkjet printer

When teaching colors, physics teachers ask their students to ignore what is taught in art classes and embrace a primary color system of red, green, and blue. This scheme is additive and all colors can be generated by combining light of these three colors with varying intensities. There have been a number of demonstrations and tools to help students understand additive color mixing, using LEDs, color monitors, or similar technologies. However, the subtractive primaries of cyan, magenta, and yellow have received far less attention, if students have previous knowledge it is from printer ink cartridges. This gap may exist because as pigments it can be harder to vary their intensities in real time. Fortunately, our colleagues in the art department are well-versed in subtractive color mixing, and have taught this topic for many years through the lens of color printing. We steal a page from their book and describe how to create a color image using cyan, magenta, yellow, and black layers (CMYK). Black is used as an additional layer due to mixing issues concerning the imperfections of the CMY pigments. With imaging software, an inkjet printer, and some transparencies, physics instructors are just a few keystrokes away from being able to demonstrate subtractive color mixing.

physics.ed-ph↗