Student response systems (SRS) continue to evolve as bring-your-own-device (BYOD) systems allow more question and answer types to be utilized. While users were once limited to a button press on a clicker selecting from a list of predetermined responses, students can now generate text and numerical responses on their personal devices. Question and response types are now limited only by software, and new features can be added without requiring an overhaul of the existing system. Using two successive course offerings of a biomedical lab techniques class, the effect of question type was evaluated, using a crossover experimental design, and applied to novel discipline-specific calculations. Students used the Top Hat student response system (tophat.com) to answer either multiple choice questions (MCQ) or numerical response questions (NRQ) in class. Student responses were tracked for elapsed time to completion, performance, and subsequent test performance. Additionally, students were surveyed about their question-type preference. Analysis shows that on formative assessments, students take less time on multiple choice questions, are successful more often, and show a clear preference for this type. When students used those calculations on summative exams, they performed similarly regardless of whether they initially used MCQ or NRQ. Students also expressed clear preference for MCQ. The use of NRQ is still recommended to be used strategically as it increases question difficulty and diversity. The findings from this study may assist STEM instructors looking to formulate their own evidence-based best practices when incorporating SRSs intotheir pedagogy.

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Spatiotemporal reasoning is a fundamental contributor to effective problem solving. In an effort to design better problem-solving agents, we examined and evaluated the strategies that humans use to solve Tower Defense puzzles, a complex and popular class of real-time strategy games. A consistent and unexpected finding was that humans frequently treated time and space as equivalent. Players stated temporal goals but solved spatial problems. An analysis of human data and computer simulations showed that re-representing temporal problems as spatial problems was beneficial, but treating the two separately can lead to higher scores. The work presented here holds several possibilities for level designers and others who design and analyze maps and spatial arrangements for domains requiring strategic reasoning.

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