Analyzing Implicit Science and Math Outcomes in Engineering and Technology Programs

Abstract

One of the key steps when developing pathways between baccalaureate and diploma programs is comparing learning goals between the programs. This paper presents application of a sevendimensional framework (cognitive process, transferability, depth of analysis, interdependence, question novelty, scaffolding and communication) to analyze the implicit learning outcomes in 11 of Ontario's post-secondary programs in engineering and engineering technology. We collected 319 calculus questions (179 from six technology programs and 140 from five engineering programs) and 205 physics questions (122 from two technology programs and 83 from four engineering programs). Content specialists assessed each question in the first four of these dimensions, and instructors from the participating institutions scored random questions from their own disclosed questions on the remaining dimensions. Analysis of scaffolding in physics questions showed that engineering questions mostly required the students to choose from or synthetize a range of approaches while technology questions often required the students to use a specific approach. The study found that technology programs focused more on discipline-specific physics concepts and their applications than physics courses in engineering. Calculus questions from both sectors mostly required application of mathematical concepts in non-contextualized scenarios or a general engineering context, with no significant difference in question novelty, scaffolding and level of communication. From a credits perspective, these results suggest that direct credit for bidirectional transfers may be warranted, and that small bridging learning modules targeting missing outcomes may be able to support efficient transfer pathways.

Professional Training of Emerging Fuel and Energy Industry Professionals Based on Factor Analysis

“…Simulation or situational modeling programs based on real experience are the most often used specialized programs designed for engineering training and mathematical modeling. Such programs can relate to both the sphere of economics and mathematical forecasting of economic phenomena, as well as modeling production activities or the operation of complex technical devices [3], [10]. In comparison to our developed training program scientists propose approaches to encourage students to develop modeling programs in order to ensure a deeper understanding of both the economic or technical processes being studied and the mathematical methods for their modeling [12].…”

“…The mathematics education of fuel and energy industry professionals plays an important role in preventing the most complex technological violations [1]; it should form the basis for the ability to quickly and properly address real issues related to the operation of complex technical equipment and predict its behavior [2], [3].…”