Mccraymeyer9231

We discuss psychological principles and "best practices" underlying effective psychosocial interventions that could guide the development of interventions to increase instructors' motivation to attend TPD. We encourage new interdisciplinary research collaborations to explore the potential of these interventions, which could be a new approach to mitigating at least one barrier to undergraduate education reform.Cognitive scientists have recommended the use of test-enhanced learning in science classrooms. Test-enhanced learning includes the testing effect, in which learners' recall of information encountered in testing exceeds that of information not tested. The influence of incentives (e.g., points received) on learners who experience the testing effect in classrooms is less understood. The objective of our study was to examine the effects of incentives in a postsecondary biology course. We administered exams in the course using a quasi-experimental design with low and high point incentives and measured student learning. Although exposure to exams predicted better learning, incentive level did not moderate this effect, an outcome that contradicted recent laboratory findings that higher incentives decreased student recall. We discuss possible explanations of the disparate outcomes as well as the implications for further research on the testing effect in postsecondary biology classrooms.The creation and analysis of models is integral to all scientific disciplines, and modeling is considered a core competency in undergraduate biology education. There remains a gap in understanding how modeling activities may support changes in students' neural representations. The aim of this study was to evaluate the effects of simulating a model on undergraduates' behavioral accuracy and neural response patterns when reasoning about biological systems. During brief tutorials, students (n = 30) either simulated a computer model or read expert analysis of a gene regulatory system. Subsequently, students underwent functional magnetic resonance imaging while responding to system-specific questions and system-general questions about modeling concepts. Although groups showed similar behavioral accuracy, the Simulate group showed higher levels of activation than the Read group in right cuneal and postcentral regions during the system-specific task and in the posterior insula and cingulate gyrus during the system-general task. Students' behavioral accuracy during the system-specific task correlated with lateral prefrontal brain activity independent of instruction group. Bexotegrast supplier Findings highlight the sensitivity of neuroimaging methods for identifying changes in representations that may not be evident at the behavioral level. This work provides a foundation for research on how distinct pedagogical approaches may affect the neural networks students engage when reasoning about biological phenomena.The Current Insights feature is designed to introduce life science educators and researchers to current articles of interest in other social science and education journals. In this installment, I highlight three studies drawing on psychology and learning sciences to understand how to increase student motivation to engage in scientific writing, how drawing can enhance learning, and whether spacing, or distributed practice, matters in actual classes.Research in science, technology, engineering, and mathematics education supports a shift from traditional lecturing to evidence-based instruction in college courses, yet it is unknown whether particular evidence-based pedagogies are more effective than others for learning outcomes like problem solving. Research supports three distinct pedagogies worked examples plus practice, productive failure, and guided inquiry. These approaches vary in the nature and timing of guidance, all while engaging the learner in problem solving. Educational psychologists debate their relative effectiveness, but the approaches have not been directly compared. In this study, we investigated the impact of worked examples plus practice, productive failure, and two forms of guided inquiry (unscaffolded and scaffolded guidance) on student learning of a foundational concept in biochemistry. We compared all four pedagogies for basic knowledge performance and near-transfer problem solving, and productive failure and scaffolded guidance for far-transfer problem solving. We showed that 1) the four pedagogies did not differentially impact basic knowledge performance; 2) worked examples plus practice, productive failure, and scaffolded guidance led to greater near-transfer performance compared with unscaffolded guidance; and 3) productive failure and scaffolded guidance did not differentially impact far-transfer performance. These findings offer insights for researchers and college instructors.We previously reported that students' concept-building approaches, identified a priori using a cognitive psychology laboratory task, extend to learning complex science, technology, engineering, and mathematics topics. This prior study examined student performance in both general and organic chemistry at a select research institution, after accounting for preparation. We found that abstraction learners (defined cognitively as learning the theory underlying related examples) performed higher on course exams than exemplar learners (defined cognitively as learning by memorizing examples). In the present paper, we further examined this initial finding by studying a general chemistry course using a different pedagogical approach (process-oriented guided-inquiry learning) at an institution focused on health science majors, and then extended our studies via think-aloud interviews to probe the effect concept-building approaches have on problem-solving behaviors of average exam performance students. From interviews with students in the average-achieving group, using problems at three transfer levels, we found that 1) abstraction learners outperformed exemplar learners at all problem levels; 2) abstraction learners relied on understanding and exemplar learners dominantly relied on an algorithm without understanding at all problem levels; and 3) both concept-building-approach students had weaknesses in their metacognitive monitoring accuracy skills, specifically their postperformance confidence level in their solution accuracy.