Optimizing Lectures From a Cognitive Load Perspective

Lectures are a common instructional method in medical education. Understanding the cognitive processes and theories involved in learning is essential for lecturers to be effective. Cognitive load theory is one theory that is becoming increasingly recognized in medical education and addresses the appropriate use of one’s working memory. Memory is essential to knowledge acquisition. Two types of memory can be considered, working memory (processing of information) and long‐term memory (storage of information). Working memory has a limited capacity. Cognitive load refers to the amount of information processing activity imposed on working memory and can be divided into three domains: intrinsic, extraneous, and germane. By attending to cognitive load, educators can promote learning. This paper highlights various ways of improving cognitive load for learners during lecture‐based instruction by minimizing extraneous load, optimizing intrinsic load, and promoting germane load.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/156199/2/aet210389.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/156199/1/aet210389_am.pd

Keeping Up With the Kids: Diffusion of Innovation in Pediatric Emergency Medicine Among Emergency Physicians

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/137273/1/acem13185.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/137273/2/acem13185_am.pd

No time, no room: On‐shift teaching for any shift

It can be difficult to carve out dedicated time to teach in the busy environment of the Emergency Department. With some intention, you can find educational opportunities in every shift. Here we highlight some of those opportunities, with careful attention to those without special equipment or preparation required. These can be used to teach less traditional practice points such as interprofessional communication as well as clinical pearls. Select the moments that make the most sense for you, your trainees, and your shift.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/171150/1/aet210701.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/171150/2/aet210701_am.pd

Increasing Education Research Productivity: A Network Analysis

Introduction: Forming effective networks is important for personal productivity and career development. Although critical for success, these networks are not well understood. The objective of this study was to usze a social network analysis tool to demonstrate the growth of institutional publication networks for education researchers and show how a single institution has expanded its publication network over time.Methods: Publications from a single institution’s medical education research group (MERG) were pulled since its inception in 2010 to 2019 using Web of Science to collect publication information. Using VOSViewer software, we formed and plotted a network sociogram comparing the first five years to the most recent 4.25 years to compare the institutions of authors from peer reviewed manuscripts published by this group.Results: We found 104 peer-reviewed research articles, editorials, abstracts, and reviews for the MERG authors between 2010 and 2019 involving 134 unique institutions. During 2010-2014, there were 26 publications involving 56 institutions. From 2015- 2019, there were 78 publications involving 116 unique institutions.Conclusion: This brief report correlates successful research productivity in medical education with the presence of increased inter-institutional collaborations as demonstrated by network sociograms.  Programs to intentionally expand collaborative networks may prove to be an important element of facilitating successful careers in medical education scholarship

Increasing Education Research Productivity: A Network Analysis

Introduction: Forming effective networks is important for personal productivity and career development. Although critical for success, these networks are not well understood. The objective of this study was to usze a social network analysis tool to demonstrate the growth of institutional publication networks for education researchers and show how a single institution has expanded its publication network over time.Methods: Publications from a single institution’s medical education research group (MERG) were pulled since its inception in 2010 to 2019 using Web of Science to collect publication information. Using VOSViewer software, we formed and plotted a network sociogram comparing the first five years to the most recent 4.25 years to compare the institutions of authors from peer reviewed manuscripts published by this group.Results: We found 104 peer-reviewed research articles, editorials, abstracts, and reviews for the MERG authors between 2010 and 2019 involving 134 unique institutions. During 2010-2014, there were 26 publications involving 56 institutions. From 2015- 2019, there were 78 publications involving 116 unique institutions.Conclusion: This brief report correlates successful research productivity in medical education with the presence of increased inter-institutional collaborations as demonstrated by network sociograms.  Programs to intentionally expand collaborative networks may prove to be an important element of facilitating successful careers in medical education scholarship

Development of a lecture evaluation tool rooted in cognitive load theory: A modified Delphi study.

BACKGROUND: Didactics play a key role in medical education. There is no standardized didactic evaluation tool to assess quality and provide feedback to instructors. Cognitive load theory provides a framework for lecture evaluations. We sought to develop an evaluation tool, rooted in cognitive load theory, to assess quality of didactic lectures. METHODS: We used a modified Delphi method to achieve expert consensus for items in a lecture evaluation tool. Nine emergency medicine educators with expertise in cognitive load participated in three modified Delphi rounds. In the first two rounds, experts rated the importance of including each item in the evaluation rubric on a 1 to 9 Likert scale with 1 labeled as not at all important and 9 labeled as extremely important. In the third round, experts were asked to make a binary choice of whether the item should be included in the final evaluation tool. In each round, the experts were invited to provide written comments, edits, and suggested additional items. Modifications were made between rounds based on item scores and expert feedback. We calculated descriptive statistics for item scores. RESULTS: We completed three Delphi rounds, each with 100% response rate. After Round 1, we removed one item, made major changes to two items, made minor wording changes to nine items, and modified the scale of one item. Following Round 2, we eliminated three items, made major wording changes to one item, and made minor wording changes to one item. After the third round, we made minor wording changes to two items. We also reordered and categorized items for ease of use. The final evaluation tool consisted of nine items. CONCLUSIONS: We developed a lecture assessment tool rooted in cognitive load theory specific to medical education. This tool can be applied to assess quality of instruction and provide important feedback to speakers

Emergency Medicine Virtual Conference Participants’ Engagement with Competing Activities

Introduction: Residency didactic conferences transitioned to a virtual format during the COVID-19 pandemic. This format creates questions about effective educational practices, which depend on learner engagement. In this study we sought to characterize the competitive demands for learner attention during virtual didactics and to pilot methodology for future studies. Methods: This was a prospective, observational, cohort study of attendees at virtual didactics from a single emergency medicine residency, which employed a self-report strategy informed by validated classroom assessments of student engagement. We deployed an online, two-question survey  polling across six conference days using random signaled sampling. Participants reported all activities during the preceding five minutes. Results: There were 1303 responses over 40 survey deployments across six nonadjacent days. Respondents were residents (63.4%); faculty (27.5%); fellows (2.3%); students (2%); and others (4.8%). Across all responses, about 85% indicated engagement in the virtual conference within the last five minutes of the polls. The average number of activities engaged in was 2.0 (standard deviation = 1.1). Additional activities included education-related (34.2%), work-related (21.1%), social (18.8%), personal (14.6%), self-care (13.4%), and entertainment (4.4%).  Conclusion: Learners engage in a variety of activities during virtual didactics. Engagement appears to fluctuate temporally, which may inform teaching strategies. This information may also provide unique instructor feedback. This pilot study demonstrates methodology for future studies of conference engagement and learning outcomes

Development of entrustable professional activities for emergency medicine medical education fellowships: A modified Delphi study.

BACKGROUND: It is essential that medical education (MedEd) fellows achieve desired outcomes prior to graduation. Despite the increase in postgraduate MedEd fellowships in emergency medicine (EM), there is no consistently applied competency framework. We sought to develop entrustable professional activities (EPAs) for EM MedEd fellows. METHODS: From 2021 to 2022, we used a modified Delphi method to achieve consensus for EPAs. EM education experts generated an initial list of 173 EPAs after literature review. In each Delphi round, panelists were asked to make a binary choice of whether to include the EPA. We determined an inclusion threshold of 70% agreement a priori. After the first round, given the large number of EPAs meeting inclusion threshold, panelists were instructed to vote whether each EPA should be included in the 20 most important EPAs for a MedEd fellowship. Modifications were made between rounds based on expert feedback. We calculated descriptive statistics. RESULTS: Seventeen experts completed four Delphi rounds each with 100% response. After Round 1, 87 EPAs were eliminated and two were combined. Following Round 2, 46 EPAs were eliminated, seven were combined, and three were included in the final list. After the third round, one EPA was eliminated and 13 were included. After the fourth round, 11 EPAs were eliminated. The final list consisted of 16 EPAs in domains of career development, education theory and methods, research and scholarship, and educational program administration. CONCLUSIONS: We developed a list of 16 EPAs for EM MedEd fellowships, the first step in implementing competency-based MedEd