Though statistics on penetration and effectiveness are scarce, electronic learning/training (e-learning), and remote learning are entering mainstream engineering instruction and are competing with in-person training. Which is more appropriate for which students and for what subject matter?
R. D. Garrick, Ph.D., P.E., associate professor of manufacturing and mechanical engineering at the Rochester Institute of Technology, Rochester, NY, believes that desired learning outcomes, and not subject matter (for example, thermodynamics, fluid mechanics) determines the suitability of e-learning and in-person instruction.
Garrick, whose institution provides both traditional classroom and remote instruction, sees the benefit in reversing the traditional classroom lecture/offsite homework model to a model in which students experience lectures or other instructional material remotely or electronically, but solve problems in a classroom setting. This paradigm allows students to consume educational materials as quickly or slowly as they wish, while working through problems in large but well-monitored groups.
“If the instructional objective is to build intellectual bridges between instructors and students through analogies, metaphors, images, or simulations, this can be accommodated through e-learning,” Garrick says. “But learning outcomes that involve problem-solving or understanding points of view are best conveyed in person, where the instruction can be personalized.”
Online training is cost-effective for students in remote locations or who are employed at traditional jobs. The downside is a lack of interaction. For example, there is a lack of focus on student body language or facial reactions to instructional elements. And some students or trainees feel more comfortable asking questions in a live environment than online.
Attempts to classify knowledge and delivery methods systematically produces interesting ideas. Byron Newberry, Ph.D., P.E., associate professor of mechanical engineering at Baylor University, Waco, TX, refers to Bloom’s Taxonomy, a model for learning objectives that suggests a hierarchy of learning levels. These are, from lowest to highest: knowledge, comprehension, application, analysis, synthesis, and evaluation. “At the lower levels, people simply know facts and comprehend ideas,” Newberry says. Facts and ideas combine and rearrange uniquely at the higher levels, which is where complex decisions are synthesized.
“Impersonal, electronic education works better at the lower levels, where electronic media easily communicate basic information.” Engineers already familiar with design codes readily learn code amendments through an electronic medium because they are already familiar with the concepts. A design code novice likely will need in-person training because application of design is far from straightforward. “Engineers must judge when a code applies and when it doesn’t, how to resolve code conflicts, and how to select one design over another when both meet code requirements.”
These judgments, Newberry observes, depend not only on the codes but on the unique context of the problem. Experiential knowledge at the higher levels of Bloom’s Taxonomy, he argues, is not condensed easily into generic principles that fit onto a DVD. “Having interaction with an experienced person is crucial to the learning process.”
Yet significant exceptions exist. Raman Unnikrishnan, dean of the College of Engineering and Computer Science, California State University, Fullerton, CA, notes that top hardware and software companies already provide online troubleshooting, for example, which involves judgment and evaluation that fall under higher-level activities.
Fullerton soon will introduce an online M.S. program in environmental engineering that follows the success of an online software engineering course. Yet he disagrees with the application of taxonomic rules to decide on the mode of instruction.
Unnikrishnan points out that remote learning and collaboration have become crucial elements – some would say competencies – for software developers. “Software developed in Los Angeles gets handed over to programmers in Ireland for the next shift, and on to Bangalore before returning to California the next day.”
E-training for hands-on coursework would not be as successful, he says. “We have a large machine shop here. You can teach the basics through electronic media, but learning to operate the equipment, rendering complex shapes, and understanding safety and compliance has to be done on site.”
E-learning works best, Unnikrishnan says, with self-motivated individuals and materials that build on the student’s previous knowledge. Thus, classroom interaction may be critical for 101-level courses, but not for graduate work where students are already familiar with the basics. Although, he admits, “There isn’t a very strong research base for what I’m claiming.”
by Angelo DePalma, ASME.org