A novel electronic assessment strategy to support applied Drosophila genetics training on university courses
Research output: Contribution to journal › Article
Abstract
The advent of “omic” technologies has revolutionized genetics and created a demand to focus 3 ; 2 ; 1 classical genetics on its present-day applications (Redfield, 2012, PLoS Biol 10: e1001356). This demand can 5 ; 4 be met by training students in Drosophila mating scheme design, which is an important problem-solving 6 skill routinely applied in many modern research laboratories. It requires a thorough understanding and application of classical genetics rules while also an introduction to transgenic technologies and the use 7 of model organisms. As we show here, such training can be implemented as a flexible and concise module (~1-day home study, ~8-hour course time) on university courses by using our previously published training package designed for fly researchers (Roote and Prokop, 2013, G3 (Bethesda) 3: 3532358). However, assessing this training to make it an accredited course element is difficult, especially in large courses. Here, we present a powerful assessment strategy based on a novel hybrid concept in which students solve crossing tasks initially on paper and then answer automatically marked questions on the computer (1.5 hours total). This procedure can be used to examine student performance on more complex tasks than conventional e-assessments and is more versatile, time-saving, and fairer than standard paper-based assignments. Our evaluation shows that the hybrid assessment is effective and reliably detects varying degrees of understanding among students. It also may be applicable in other disciplines requiring complex problem solving, such as mathematics, chemistry, physics, or informatics. Here, we describe our strategies in detail and provide all resources needed for their implementation.
Bibliographical metadata
Original language | English |
---|---|
Pages (from-to) | 689-698 |
Number of pages | 10 |
Journal | G3: Genes, Genomes, Genetics |
Volume | 5 |
Issue number | 5 |
DOIs | |
Publication status | Published - 18 Feb 2015 |