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      What Are We Looking for in Computer-Based Learning Interventions in Medical Education? A Systematic Review

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          Computer-based learning (CBL) has been widely used in medical education, and reports regarding its usage and effectiveness have ranged broadly. Most work has been done on the effectiveness of CBL approaches versus traditional methods, and little has been done on the comparative effects of CBL versus CBL methodologies. These findings urged other authors to recommend such studies in hopes of improving knowledge about which CBL methods work best in which settings.


          In this systematic review, we aimed to characterize recent studies of the development of software platforms and interventions in medical education, search for common points among studies, and assess whether recommendations for CBL research are being taken into consideration.


          We conducted a systematic review of the literature published from 2003 through 2013. We included studies written in English, specifically in medical education, regarding either the development of instructional software or interventions using instructional software, during training or practice, that reported learner attitudes, satisfaction, knowledge, skills, or software usage. We conducted 2 latent class analyses to group articles according to platform features and intervention characteristics. In addition, we analyzed references and citations for abstracted articles.


          We analyzed 251 articles. The number of publications rose over time, and they encompassed most medical disciplines, learning settings, and training levels, totaling 25 different platforms specifically for medical education. We uncovered 4 latent classes for educational software, characteristically making use of multimedia (115/251, 45.8%), text (64/251, 25.5%), Web conferencing (54/251, 21.5%), and instructional design principles (18/251, 7.2%). We found 3 classes for intervention outcomes: knowledge and attitudes (175/212, 82.6%), knowledge, attitudes, and skills (11.8%), and online activity (12/212, 5.7%). About a quarter of the articles (58/227, 25.6%) did not hold references or citations in common with other articles. The number of common references and citations increased in articles reporting instructional design principles ( P=.03), articles measuring online activities ( P=.01), and articles citing a review by Cook and colleagues on CBL ( P=.04). There was an association between number of citations and studies comparing CBL versus CBL, independent of publication date ( P=.02).


          Studies in this field vary highly, and a high number of software systems are being developed. It seems that past recommendations regarding CBL interventions are being taken into consideration. A move into a more student-centered model, a focus on implementing reusable software platforms for specific learning contexts, and the analysis of online activity to track and predict outcomes are relevant areas for future research in this field.

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          The NumPy array: a structure for efficient numerical computation

          In the Python world, NumPy arrays are the standard representation for numerical data. Here, we show how these arrays enable efficient implementation of numerical computations in a high-level language. Overall, three techniques are applied to improve performance: vectorizing calculations, avoiding copying data in memory, and minimizing operation counts. We first present the NumPy array structure, then show how to use it for efficient computation, and finally how to share array data with other libraries.
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            “Amplification and direct sequencing of fungal ribosomal RNA genes for phylogenetics,” in

             T. WHITE,  T Bruns,  S Lee (1990)
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              Social media use in medical education: a systematic review.

              The authors conducted a systematic review of the published literature on social media use in medical education to answer two questions: (1) How have interventions using social media tools affected outcomes of satisfaction, knowledge, attitudes, and skills for physicians and physicians-in-training? and (2) What challenges and opportunities specific to social media have educators encountered in implementing these interventions? The authors searched the MEDLINE, CINAHL, ERIC, Embase, PsycINFO, ProQuest, Cochrane Library, Web of Science, and Scopus databases (from the start of each through September 12, 2011) using keywords related to social media and medical education. Two authors independently reviewed the search results to select peer-reviewed, English-language articles discussing social media use in educational interventions at any level of physician training. They assessed study quality using the Medical Education Research Study Quality Instrument. Fourteen studies met inclusion criteria. Interventions using social media tools were associated with improved knowledge (e.g., exam scores), attitudes (e.g., empathy), and skills (e.g., reflective writing). The most commonly reported opportunities related to incorporating social media tools were promoting learner engagement (71% of studies), feedback (57%), and collaboration and professional development (both 36%). The most commonly cited challenges were technical issues (43%), variable learner participation (43%), and privacy/security concerns (29%). Studies were generally of low to moderate quality; there was only one randomized controlled trial. Social media use in medical education is an emerging field of scholarship that merits further investigation. Educators face challenges in adapting new technologies, but they also have opportunities for innovation.

                Author and article information

                J Med Internet Res
                J. Med. Internet Res
                Journal of Medical Internet Research
                JMIR Publications (Toronto, Canada )
                August 2016
                01 August 2016
                : 18
                : 8
                1Department of Medical Education and Simulation Faculty of Medicine University of Porto PortoPortugal
                2Department of Clinical Neurosciences and Mental Health, Medical Psychology Unit Faculty of Medicine University of Porto PortoPortugal
                3Department of Clinical Epidemiology, Predictive Medicine and Public Health Faculty of Medicine University of Porto PortoPortugal
                Author notes
                Corresponding Author: Tiago Taveira-Gomes tiago.taveira@
                ©Tiago Taveira-Gomes, Patrícia Ferreira, Isabel Taveira-Gomes, Milton Severo, Maria Amélia Ferreira. Originally published in the Journal of Medical Internet Research (, 01.08.2016.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on, as well as this copyright and license information must be included.

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