Planning Continuing Medical Education Activities

A review of program development literature in adult education and continuing medical education (CME) indicates the pervasive influence of a single approach to designing instructional activities. An examination of the assumptions of this model indicates several weaknesses. An alternative model is proposed that recognizes the importance and impact of the planners'' interaction with representatives of the learner group, institutional colleagues and persons in outside agencies. Results of previous research, experience in planning, observations of the planning processes of others and discussions with expert continuing medical educators show that planning is a dynamic process of suggesting and selecting from many alternatives those instructional activities with the greatest potential for effecting the desired changes in learners. Through a series of deliberations, needs are specified, instructional activities are designed, goals and objectives are stated, and evaluation techniques are selected. CME planners direct the process and constantly focus on the immediate impact on the learners and ultimately on the learners'' practice behavior.     

Visual immersion for cultural understanding and multimodal literacy

ABSTRACT

When considering inclusive art curriculum that accommodates all learners, including English language learners, two distinct yet inseparable issues come to mind. The first is that English language learner students can use visual language and visual literacy skills inherent in visual arts curriculum to scaffold learning in and through the arts. Second, in facilitating a sense of belonging for students whose home language and cultural aesthetic may be different from those of the dominant school culture, an authentically developed multicultural art curriculum can guide self-efficacy and inclusiveness. Both aspects of teaching art for English language learners can have the added benefits of facilitating collaborative learning opportunities and increasing worldviews for all students.     

The Gender Gap in Second Language Acquisition: Gender Differences in the Acquisition of Dutch among Immigrants from 88 Countries with 49 Mother Tongues

Gender differences were analyzed across countries of origin and continents, and across mother tongues and language families, using a large-scale database, containing information on 27,119 adult learners of Dutch as a second language. Female learners consistently outperformed male learners in speaking and writing proficiency in Dutch as a second language. This gender gap remained remarkably robust and constant when other learner characteristics were taken into account, such as education, age of arrival, length of residence and hours studying Dutch. For reading and listening skills in Dutch, no gender gap was found. In addition, we found a general gender by education effect for all four language skills in Dutch for speaking, writing, reading, and listening. Female language learners turned out to profit more from higher educational training than male learners do in adult second language acquisition. These findings do not seem to match nurture-oriented explanatory frameworks based for instance on a human capital approach or gender-specific acculturation processes. Rather, they seem to corroborate a nature-based, gene-environment correlational framework in which language proficiency being a genetically-influenced ability interacting with environmental factors such as motivation, orientation, education, and learner strategies that still mediate between endowment and acquiring language proficiency at an adult stage.     

Two success-biased social learning strategies

I compare the evolutionary dynamics of two success-biased social learning strategies, which, by definition, use the success of others to inform one’s social learning decisions. The first, “Compare Means”, causes a learner to adopt cultural variants with highest mean payoff in her sample. The second, “Imitate the Best”, causes a learner to imitate the single most successful individual in her sample. I summarize conditions under which each strategy performs well or poorly, and investigate their evolution via a gene-culture coevolutionary model. Despite the adaptive appeal of these strategies, both encounter conditions under which they systematically perform worse than simply imitating at random. Compare Means performs worst when the optimal cultural variant is usually at high frequency, while Imitate the Best performs worst when suboptimal variants sometimes produce high payoffs. The extent to which it is optimal to use success-biased social learning depends strongly on the payoff distributions and environmental conditions that human social learners face.     

ROGERS' PARADOX RECAST AND RESOLVED: POPULATION STRUCTURE AND THE EVOLUTION OF SOCIAL LEARNING STRATEGIES

We explore the evolution of reliance on social and asocial learning using a spatially explicit stochastic model. Our analysis considers the relative merits of four evolved strategies, two pure strategies (asocial and social learning) and two conditional strategies (the "critical social learner," which learns asocially only when copying fails, and the "conditional social learner," which copies only when asocial learning fails). We find that spatial structure generates outcomes that do not always conform to the finding of earlier theoretical analyses that social learning does not enhance average individual fitness at equilibrium (Rogers' paradox). Although we describe circumstances under which the strategy of pure social learning increases the average fitness of individuals, we find that spatial structure introduces a new paradox, which is that social learning can spread even when it decreases the average fitness of individuals below that of asocial learners. We also show that the critical social learner and conditional social learner both provide solutions to the aforementioned paradoxes, although we find some conditions in which pure (random) social learning out-competes both conditional strategies. Finally, we consider the relative merits of critical and conditional social learning under various conditions.     

No to mandatory continuing medical education,Yes to mandatory practice auditing and professional educational development

The issue of mandatory continuing medical education (CME) is controversial. Traditional measures mandate only attendance, not learning, and have no measurable performance end points. There is no evidence that current approaches to CME, mandatory or voluntary, produce sustainable changes in physician practices or application of current knowledge. Ongoing educational development is an important value in a professional, and there is an ethical obligation to keep up to date. Mandating self-audit of the effect of individual learning on physician''s practices and evaluation by the licensing authority are effective ways of ensuring the public are protected. The author recommends the use of a personal portfolio to document sources of learning, the effect of learning and the auditing of their applications on practice patterns and patient outcomes. A series of principles are proposed to govern its application.     

Simulation in health care education

During the past 15 years there has been widespread adoption of simulation in health care education as a method to train and assess learners. Multiple factors have contributed to this movement, including reduced patient availability, limited faculty teaching time, technological advances in diagnosis and treatment that require a new skills set, greater attention to patient safety with the need to reduce medical errors, and a focus on outcomes-based education. In this discussion, simulation refers broadly to any device or set of conditions that attempts to present the patient authentically. While simulation offers many advantages over traditional methods of teaching, there are several challenges that must be addressed to ensure its effective use. This article presents the range of available simulation technologies, explores the challenges that health care educators face when using this method, provides an example of a successful program that has integrated simulation into the culture of learning at its institution, and discusses an approach to maximizing the effectiveness of simulation as a means to learning and practicing skills in a safe, interactive environment.     

From the science of learning (and development) to learning engineering

ABSTRACT

In this issue, Cantor and colleagues synthesize a broad representation of the literature on the science of learning, and how learning changes over the course of development. Their perspective highlights three important factors about the emerging field of science of learning and development: (1) that it draws insights from increasingly diverse fields of research inquiry, from neuroscience and social science to computer science and adversity science; (2) that it provides a means to understand principles that generalize across learners, and yet also allow individual differences in learning to emerge and inform; and (3) that it recognizes that learning occurs in context, and is thus a shared responsibility between the learner, the instructor, and the environment. Here I discuss how this complex systems dynamical perspective can be integrated with the emerging framework of ‘learning engineering’ to provide a blueprint for significant innovations in education.     

以问题为中心的学习方法在高职社区问诊技能教学中的应用

目的:探讨以问题为中心的教学方法(problem-based learning,PBL)在高职社区问诊教学中的效果,寻求更有效的现代医学教育方法。方法:在高职社区问诊技能学习中开展以问题为中心的教学方法(PBL),分析问诊中存在的问题,以提高知识应用与沟通能力。结果:通过对62名高职医学生进行问诊技能和见习报告评分显示,成绩优良比率为89%,满意度调查显示83.87%的高职医学生对PBL教学方法满意。PBL教学可以让高职医学生灵活的利用自已的时间,进行比较主动的学习,可以更好的发现高职医学生在问诊见习中存在的问题,有利于提高高职医学生的问诊技能及医患沟通能力,但实施中所需时间较长,占用课时多。结论:PBL教学对高职医学生的主动学习能力、问诊技能及医患沟通能力的提高有利,医学生对PBL教学方法满意度高。在医学教育中可以将PBL教学和传统教学方法结合起来,以在有效的时间里达到更好的教学效果。     

Evolution of social learning: a mathematical analysis

Social learning is an important ability seen in a wide range of animals including humans. It has been argued that individual learning, social learning, and innate determination of behavior are favored by natural selection when environmental changes occur at short, intermediate, and long intervals, respectively. Only recently, however, has the hypothesis been examined by means of mathematical models. In this paper, we construct a simple model in which each organism uses one of three genetically determined strategies--it is an individual learner, a social learner or an "innate"--and the three types of organisms are in direct competition with each other. A reduced model, involving only the individual learners and innates, is effectively linear, and we show that by solving the eigenvalue problem of this reduced system we arrive at a good approximation to the global dynamics of the full model. We also study the effect of stochastic environmental changes and reversible mutations among the three strategies. Our results are consistent with the predictions of previous studies. In addition, we identify a critical level of environmental constancy below which only individual and social learners are present.     

The impact and effectiveness of faculty development program in fostering the faculty’s knowledge,skills, and professional competence: A systematic review and meta-analysis

BackgroundFaculty vitality is the main ingredient to enhance professional education and competence. Enriching the faculty vitality in key domains of teaching, assessing, research, professionalism, and administration is perceived to improve educational environment significantly and enhances the academic performance of learners. Faculty development program (FDP) has been considered as a stand-alone educational pedagogy in fostering knowledge and professional skills of faculty. However, few studies have provided objective reports about the impact of such programs in a healthcare system.MethodsThis research was conducted by selecting data sources of PubMed-Medline, Wiley online library, Cochrane library, Taylor & Francis Online, CINAHL, Springer link, Proquest, ISI Web of knowledge, ScienceDirect, EJS, EBSCO, Blackwell, Emerald and ABI Inform. This search followed a step-wise approach defined by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). A total of 37 studies that explored the impact of FDPs on medical and allied health faculty’s professional development were selected.ResultsThis meta-analysis reported a mean effect size of 0.73 that reflects a significant and positive impact of FDPs in enhancing faculty’s knowledge and professional competence (z-statistics of 4.46 significant at p-value < 0.05) using the random effects model and forest plot.ConclusionThis article reiterates the incorporation of FDPs in all healthcare institutions for improving the academic performance of faculty with resultant enrichment of learners’ knowledge and skills.     

Biomechanics - Review of approaches for performance training in spinal manipulation

Motor skills development is an inherent part of clinical training in health disciplines. The conscious use of educational theory to ground learning is receiving increasing attention across health care education. There are three distinct, yet overlapping, stages of motor skill learning; the cognitive, the integrative or associative, and the autonomous; in which a contextual framework for learning content may be structured. The learning is associated with a mapping of changes within the central nervous system by the interactive mechanisms of adaptation, use-dependent plasticity and operant reinforcement. Successful skill learning requires a sufficient amount of practice and the implementation of relevant feedback strategies in the form of knowledge of performance (KP) or knowledge of results (KR). There is a natural maturation of skills that may be accelerated by feedback. Several factors contribute to stronger skills development. "Mixture-of-experts" models systematically sequence tasks into logical blocks of theory, practice and student reflection on performance. Feedback should involve both KP and KR that compares performance to a tangible standard. Rehearsals should balance use of simulators and volunteer simulated patients to provide the full range of safe and effective learning opportunities prior to students accepting a role as care givers to the public in any clinical setting.     

Using a high-fidelity patient simulator with first-year medical students to facilitate learning of cardiovascular function curves

Students are relying on technology for learning more than ever, and educators need to adapt to facilitate student learning. High-fidelity patient simulators (HFPS) are usually reserved for the clinical years of medical education and are geared to improve clinical decision skills, teamwork, and patient safety. Finding ways to incorporate HFPS into preclinical medical education represents more of a challenge, and there is limited literature regarding its implementation. The main objective of this study was to implement a HFPS activity into a problem-based curriculum to enhance the learning of basic sciences. More specifically, the focus was to aid in student learning of cardiovascular function curves and help students develop heart failure treatment strategies based on basic cardiovascular physiology concepts. Pretests and posttests, along with student surveys, were used to determine student knowledge and perception of learning in two first-year medical school classes. There was an increase of 21% and 22% in the percentage of students achieving correct answers on a posttest compared with their pretest score. The median number of correct questions increased from pretest scores of 2 and 2.5 to posttest scores of 4 and 5 of a possible total of 6 in each respective year. Student survey data showed agreement that the activity aided in learning. This study suggests that a HFPS activity can be implemented during the preclinical years of medical education to address basic science concepts. Additionally, it suggests that student learning of cardiovascular function curves and heart failure strategies are facilitated.     

Perspectives on facilitating dynamic ecology courses online using active learning

As education methodology has grown to incorporate online learning, disciplines with a field component, like ecology, may find themselves sidelined in this transition. In response to challenges posed by moving classes online, previous studies have assessed whether an online environment can be effective for student learning. This work has found that active learning structures, which maximize information processing and require critical thinking, best support student learning. All too commonly, online and active learning are perceived as mutually exclusive. We argue the success of online learning requires facilitating active learning in online spaces. To highlight this intersection in practice, we use a case study of an online, active, and synchronous ecology and conservation biology course from the College of Natural Sciences at Minerva Schools at KGI. We use our perspectives as curriculum designers, instructors, and students of this course to offer recommendations for creating active online ecology courses. Key components to effective course design and implementation are as follows: facilitating critical “thinking like a scientist”, integrating open‐ended assignments into class discussion, and creating active in‐class dialogues by minimizing lecturing. Based on our experience, we suggest that by employing active learning strategies, the future of ecology in higher education is not inhibited, but in fact supported, by opportunities for learning online.     

Use of Learning Media by Undergraduate Medical Students in Pharmacology: A Prospective Cohort Study

The ubiquity of the internet and computer-based technologies has an increasing impact on higher education and the way students access information for learning. Moreover, there is a paucity of information about the quantitative and qualitative use of learning media by the current student generation. In this study we systematically analyzed the use of digital and non-digital learning resources by undergraduate medical students. Daily online surveys and semi-structured interviews were conducted with a cohort of 338 third year medical students enrolled in a general pharmacology course. Our data demonstrate a predominant use of digital over non-digital learning resources (69 ± 7% vs. 31 ± 7%; p < 0.01) by students. Most used media for learning were lecture slides (26.8 ± 3.0%), apps (22.0 ± 3.7%) and personal notes (15.5 ± 2.7%), followed by textbooks (> 300 pages) (10.6 ± 3.3%), internet search (7.9 ± 1.6%) and e-learning cases (7.6 ± 3.0%). When comparing learning media use of teaching vs. pre-exam self-study periods, textbooks were used significantly less during self-study (-55%; p < 0.01), while exam questions (+334%; p < 0.01) and e-learning cases (+176%; p < 0.01) were utilized more. Taken together, our study revealed a high prevalence and acceptance of digital learning resources by undergraduate medical students, in particular mobile applications.     

Toward meaningful learning in undergraduate medical education using concept maps in a PBL pathophysiology course

Problem-based learning (PBL) is now an established method in undergraduate medical education that aims to develop reasoning skills based on clinical problems. More recently, the use of concept mapping in medical education aims to improve meaningful learning. At the New University of Lisbon, we have been using PBL as a major educational method in a pathophysiology course. In 2003-2004, we started to use Inspiration, a computer-based concept mapping tool, with a single tutorial PBL group. A total of 36 maps were constructed related to short cases, already used in the PBL course, in which a certain number of key nodes were hidden to allow the students to fill in the gaps. The results obtained appear to indicate that the use of concept maps stimulated meaningful learning within a PBL course.     

A meta-learning approach for B-cell conformational epitope prediction

Background

One of the major challenges in the field of vaccine design is identifying B-cell epitopes in continuously evolving viruses. Various tools have been developed to predict linear or conformational epitopes, each relying on different physicochemical properties and adopting distinct search strategies. We propose a meta-learning approach for epitope prediction based on stacked and cascade generalizations. Through meta learning, we expect a meta learner to be able integrate multiple prediction models, and outperform the single best-performing model. The objective of this study is twofold: (1) to analyze the complementary predictive strengths in different prediction tools, and (2) to introduce a generic computational model to exploit the synergy among various prediction tools. Our primary goal is not to develop any particular classifier for B-cell epitope prediction, but to advocate the feasibility of meta learning to epitope prediction. With the flexibility of meta learning, the researcher can construct various meta classification hierarchies that are applicable to epitope prediction in different protein domains.

Results

We developed the hierarchical meta-learning architectures based on stacked and cascade generalizations. The bottom level of the hierarchy consisted of four conformational and four linear epitope prediction tools that served as the base learners. To perform consistent and unbiased comparisons, we tested the meta-learning method on an independent set of antigen proteins that were not used previously to train the base epitope prediction tools. In addition, we conducted correlation and ablation studies of the base learners in the meta-learning model. Low correlation among the predictions of the base learners suggested that the eight base learners had complementary predictive capabilities. The ablation analysis indicated that the eight base learners differentially interacted and contributed to the final meta model. The results of the independent test demonstrated that the meta-learning approach markedly outperformed the single best-performing epitope predictor.

Conclusions

Computational B-cell epitope prediction tools exhibit several differences that affect their performances when predicting epitopic regions in protein antigens. The proposed meta-learning approach for epitope prediction combines multiple prediction tools by integrating their complementary predictive strengths. Our experimental results demonstrate the superior performance of the combined approach in comparison with single epitope predictors.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-014-0378-y) contains supplementary material, which is available to authorized users.     

Adaptive learning style prediction in e-learning environment using levy flight distribution based CNN model

A learning style that focuses on individual learning is one of the most important aspects of any learning environment. Each learner has a unique manner of understanding, retaining, processing, and interpreting new information based on their learning styles. The ability of an e-learning system to automatically determine a student's learning style has become more essential. For learning events, the evolution of e-learning platforms provides students with higher opportunities online. In this paper, we proposed a Convolutional Neural Network-based Levy Flight Distribution (CNN-LFD) algorithm for learning style prediction. An adaptive e-learning system is divided into two sections: automatic learning style prediction and classification based on the number of learning styles included. Initially, the student logs in with their user ID, and the data is saved in the database. The features such as questionnaire score, login credentials (session ID, learner ID, and course ID), and login time (location, session ID) are extracted along with the sequence of the user's learning behavior. After that, the CNN-LFD algorithm predicts the learning styles of the learners namely Active/reflective, Sensing/intuitive, visual/verbal, sequential/global based on the extracted features. The dataset information are gathered from a Massive Open Online Course (MOOC), and the proposed model is built in JAVA software. The experimental results demonstrate higher classification accuracy during learning style prediction. The proposed CNN-LFD algorithm accomplishes 97.09% accuracy, 94.76% specificity, 92.12% sensitivity, and 97.56%, precision values than other methods.