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162,392 result(s) for "undergraduate"
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The ethics of educational healthcare placements in low and middle income countries : first do no harm?
This book is open access under a CC BY 4.0 license. This book examines the current state of elective placements of medical undergraduate students in developing countries and their impact on health care education at home. Drawing from a recent case study of volunteer deployment in Uganda, the authors provide an in-depth evaluation of the impacts on the students themselves and the learning outcomes associated with placements in low resource settings, as well as the impacts that these forms of student mobility have on the host settings. In addition to reviewing the existing literature on elective placements, the authors outline a potential model for the future development of ethical elective placements. As the book concurs with an increasing international demand for elective placements, it will be of immediate interest to universities, intermediary organizations, students as consumers, and hosting organisations in low-resource settings.
Integrating ChatGPT in Orthopedic Education for Medical Undergraduates: Randomized Controlled Trial
ChatGPT is a natural language processing model developed by OpenAI, which can be iteratively updated and optimized to accommodate the changing and complex requirements of human verbal communication. The study aimed to evaluate ChatGPT's accuracy in answering orthopedics-related multiple-choice questions (MCQs) and assess its short-term effects as a learning aid through a randomized controlled trial. In addition, long-term effects on student performance in other subjects were measured using final examination results. We first evaluated ChatGPT's accuracy in answering MCQs pertaining to orthopedics across various question formats. Then, 129 undergraduate medical students participated in a randomized controlled study in which the ChatGPT group used ChatGPT as a learning tool, while the control group was prohibited from using artificial intelligence software to support learning. Following a 2-week intervention, the 2 groups' understanding of orthopedics was assessed by an orthopedics test, and variations in the 2 groups' performance in other disciplines were noted through a follow-up at the end of the semester. ChatGPT-4.0 answered 1051 orthopedics-related MCQs with a 70.60% (742/1051) accuracy rate, including 71.8% (237/330) accuracy for A1 MCQs, 73.7% (330/448) accuracy for A2 MCQs, 70.2% (92/131) accuracy for A3/4 MCQs, and 58.5% (83/142) accuracy for case analysis MCQs. As of April 7, 2023, a total of 129 individuals participated in the experiment. However, 19 individuals withdrew from the experiment at various phases; thus, as of July 1, 2023, a total of 110 individuals accomplished the trial and completed all follow-up work. After we intervened in the learning style of the students in the short term, the ChatGPT group answered more questions correctly than the control group (ChatGPT group: mean 141.20, SD 26.68; control group: mean 130.80, SD 25.56; P=.04) in the orthopedics test, particularly on A1 (ChatGPT group: mean 46.57, SD 8.52; control group: mean 42.18, SD 9.43; P=.01), A2 (ChatGPT group: mean 60.59, SD 10.58; control group: mean 56.66, SD 9.91; P=.047), and A3/4 MCQs (ChatGPT group: mean 19.57, SD 5.48; control group: mean 16.46, SD 4.58; P=.002). At the end of the semester, we found that the ChatGPT group performed better on final examinations in surgery (ChatGPT group: mean 76.54, SD 9.79; control group: mean 72.54, SD 8.11; P=.02) and obstetrics and gynecology (ChatGPT group: mean 75.98, SD 8.94; control group: mean 72.54, SD 8.66; P=.04) than the control group. ChatGPT answers orthopedics-related MCQs accurately, and students using it excel in both short-term and long-term assessments. Our findings strongly support ChatGPT's integration into medical education, enhancing contemporary instructional methods. Chinese Clinical Trial Registry Chictr2300071774; https://www.chictr.org.cn/hvshowproject.html ?id=225740&v=1.0.
Artificial Intelligence (AI)-Based simulators versus simulated patients in undergraduate programs: A protocol for a randomized controlled trial
Background Healthcare simulation is critical for medical education, with traditional methods using simulated patients (SPs). Recent advances in artificial intelligence (AI) offer new possibilities with AI-based simulators, introducing limitless opportunities for simulation-based training. This study compares AI-based simulators and SPs in undergraduate medical education, particularly in history-taking skills development. Methods A randomized controlled trial will be conducted to identify the effectiveness of delivering a simulation session around history-taking skills to 67 fifth-year medical students in their clinical years of study. Students will be assigned randomly to either an AI-simulator group (intervention) or a simulated patient group (control), both will undergo a history-taking simulation scenario. An Objective Structured Clinical Examination (OSCE) will measure the primary outcomes. In contrast, secondary outcomes including student satisfaction and engagement, will be evaluated following the validated Simulation Effectiveness Tool-Modified (SET-M). The statistical approach engaged in this study will include independent t-tests for group performance comparison and multiple imputations to handle missing data. Discussion This study’s findings will provide valuable insights into the comparative advantages of artificial intelligence-based simulators and simulated patients. Results will guide decisions regarding integrating AI-based simulators into healthcare education and training programs. Hybrid models might be considered by institutions in the light of this study, providing diverse and effective simulation experiences to optimize learning outcomes. Furthermore, this work can prepare the ground for future research that addresses the readiness of AI-based simulators to become a core part of healthcare education.
Does online learning work better than offline learning in undergraduate medical education? A systematic review and meta-analysis
With the increasing use of technology in education, online learning has become a common teaching method. How effective online learning is for undergraduate medical education remains unknown. This article's aim is to evaluate whether online learning when compared to offline learning can improve learning outcomes of undergraduate medical students. Five databases and four key journals of medical education were searched using 10 terms and their Boolean combinations during 2000-2017. The extracted articles on undergraduates' knowledge and skill outcomes were synthesized using a random effects model for the meta-analysis.16 out of 3,700 published articles were identified. The meta-analyses affirmed a statistically significant difference between online and offline learning for knowledge and skill outcomes based on post-test scores (SMD = 0.81; 95% CI: 0.43, 1.20; p < 0.0001; n = 15). The only comparison result based on retention test scores was also statistically significant (SMD = 4.64; 95% CI: 3.19, 6.09; p < 0.00001). The meta-analyses discovered no significant difference when using pre- and post-test score gains (SMD = 3.03; 95% CI: −0.13, 4.13; p = 0.07; n = 3). There is no evidence that offline learning works better. And compared to offline learning, online learning has advantages to enhance undergraduates' knowledge and skills, therefore, can be considered as a potential method in undergraduate medical teaching.
Empowering ChatGPT with guidance mechanism in blended learning: effect of self-regulated learning, higher-order thinking skills, and knowledge construction
In the evolving landscape of higher education, challenges such as the COVID-19 pandemic have underscored the necessity for innovative teaching methodologies. These challenges have catalyzed the integration of technology into education, particularly in blended learning environments, to bolster self-regulated learning (SRL) and higher-order thinking skills (HOTS). However, increased autonomy in blended learning can lead to learning disruptions if issues are not promptly addressed. In this context, OpenAI's ChatGPT, known for its extensive knowledge base and immediate feedback capability, emerges as a significant educational resource. Nonetheless, there are concerns that students might become excessively dependent on such tools, potentially hindering their development of HOTS. To address these concerns, this study introduces the Guidance-based ChatGPT-assisted Learning Aid (GCLA). This approach modifies the use of ChatGPT in educational settings by encouraging students to attempt problem-solving independently before seeking ChatGPT assistance. When engaged, the GCLA provides guidance through hints rather than direct answers, fostering an environment conducive to the development of SRL and HOTS. A randomized controlled trial (RCT) was employed to examine the impact of the GCLA compared to traditional ChatGPT use in a foundational chemistry course within a blended learning setting. This study involved 61 undergraduate students from a university in Taiwan. The findings reveal that the GCLA enhances SRL, HOTS, and knowledge construction compared to traditional ChatGPT use. These results directly align with the research objective to improve learning outcomes through providing guidance rather than answers by ChatGPT. In conclusion, the introduction of the GCLA has not only facilitated more effective learning experiences in blended learning environments but also ensured that students engage more actively in their educational journey. The implications of this study highlight the potential of ChatGPT-based tools in enhancing the quality of higher education, particularly in fostering essential skills such as self-regulation and HOTS. Furthermore, this research offers insights regarding the more effective use of ChatGPT in education.
Preliminary Investigation of Validating Chain Computer Adaptive Testing Based on the Force Concept Inventory
This pilot study explores the feasibility of using Chain FCI-CAT—a formative assessment system combining the Force Concept Inventory (FCI) with a sequential Computerized Adaptive Testing (CAT) algorithm utilizing collateral information—to track conceptual change in Newtonian mechanics. Three undergraduate students participated in five sessions of Chain FCI-CAT and subsequent think-aloud interviews. Interview transcripts were analyzed using two scoring methods (Count and Judge) and compared with CAT-derived proficiency estimates. The primary aim of this pilot study is to examine appropriate methods for conducting and analyzing student interviews, prior to validating the assessment system in a larger-scale main study. The results revealed that Chain FCI-CAT effectively captures changes in student understanding and provided insights for improving the validation method.
What We Say is Not What We Do: Effective Evaluation of Faculty Professional Development Programs
Professional development (PD) workshops designed to help faculty move from teacher- to learner-centered science courses for undergraduates are typically evaluated with self-reported surveys that address faculty's satisfaction with a workshop, what they learned, and what they applied in the classroom. Professional development outcomes are seldom evaluated through analysis of observed teaching practices. We analyzed videotapes of biology faculty teaching following PD to address three questions: (1) How learner centered was their teaching? (2) Did self-reported data about faculty teaching differ from the data from independent observers? (3) What variables predict teaching practices by faculty? Following PD, 89% of the respondents stated that they made changes in their courses that included active, learner-centered instruction. In contrast, observational data showed that participation in PD did not result in learner-centered teaching. The majority of faculty (75%) used lecture-based, teacher-centered pedagogy, showing a clear disconnect between faculty's perceptions of their teaching and their actual practices.
Cost-effectiveness of peer role play and standardized patients in undergraduate communication training
Background The few studies directly comparing the methodological approach of peer role play (RP) and standardized patients (SP) for the delivery of communication skills all suggest that both methods are effective. In this study we calculated the costs of both methods (given comparable outcomes) and are the first to generate a differential cost-effectiveness analysis of both methods. Methods Medical students in their prefinal year were randomly assigned to one of two groups receiving communication training in Pediatrics either with RP ( N  = 34) or 19 individually trained SP ( N  = 35). In an OSCE with standardized patients using the Calgary-Cambridge Referenced Observation Guide both groups achieved comparable high scores (results published). In this study, corresponding costs were assessed as man-hours resulting from hours of work of SP and tutors. A cost-effectiveness analysis was performed. Results Cost-effectiveness analysis revealed a major advantage for RP as compared to SP (112 vs. 172 man hours; cost effectiveness ratio .74 vs. .45) at comparable performance levels after training with both methods. Conclusions While both peer role play and training with standardized patients have their value in medical curricula, RP has a major advantage in terms of cost-effectiveness. This could be taken into account in future decisions.
The impact of COVID-19 on the undergraduate medical curriculum
The coronavirus pandemic has impacted medical education globally. As universities seek to deliver medical education through new methods of modalities, this continuing of education ensures the learning of the future workforce of the NHS. Novel ways of online teaching should be considered in new medical curricula development, as well as methods of delivering practical skills for medical students online.
Classroom undergraduate research experiences are a “CURE” that increases engagement by students and teachers
ABSTRACT It is widely acknowledged that having experience conducting research is invaluable for undergraduate science students. Most undergraduate research is undertaken by students in a mentor's laboratory, but this limits the number of opportunities for students, as each laboratory can only take on a certain number of undergraduate researchers each semester. Additionally, it is also widely acknowledged that it is difficult for teachers to meet research goals while providing the best possible coursework for undergraduate students. Both of these bottlenecks can be circumvented via Classroom Undergraduate Research Experiences (CUREs), which integrate research into the curricula of structured undergraduate classes. Students enrolled in classes that include CUREs conduct research to address open-ended questions as part of their coursework. In this commentary, I describe the many ways in which CUREs are helpful for students and teachers, as well as considerations for designing successful CUREs. I provide several examples of CUREs from Microbial Physiology laboratory classes and Genomics classes that I have taught. Results from these CUREs have been successfully integrated into many peer-reviewed publications in which the students are co-authors, which has been a boon both to students’ post-baccalaureate opportunities, as well as my research agenda. Classroom undergraduate research experiences can promote engagement of students via ownership of course materials, and of teachers by providing a mechanism to link their teaching responsibilities to their research goals.