Using “big data” to guide implementation of a web and mobile adaptive learning platform for medical students

Menon, Ashwin; Gaglani, Shiv; Haynes, Meagan Campol; Tackett, Sean

doi:10.1080/0142159x.2017.1324949

Cited by 25 publications

(40 citation statements)

References 30 publications

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“…Experts such as Menon, Gaglani, Haynes and Tackett [68] show that the treatment that teachers give Big Data does not reach efficiency due to the lack of training in data analytics. In the same vein, Álvarez and Gisbert [69] specify that teachers have a shortfall of competence in the management, evaluation and transformation of data in information.…”

Section: Digital Learning and Massive Data Generationmentioning

confidence: 99%

Analytical Competences of Teachers in Big Data in the Era of Digitalized Learning

et al. 2019

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The progress of technology in the field of education has led to the development of new professional skills in the teaching community, such as digital competence. Likewise, it has propagated the appearance of new learning environments mediated by technological resources that favor the generation of a large volume of data, known as Big Data, derived from the interactions of educational agents in virtual environments. This study aims to determine the level of digital competence in the informational area of teachers and to determine the projection of Big Data in them. For this study, a descriptive and correlational quantitative method was followed. The study sample consists of 832 Spanish teachers, with data collected through a questionnaire. The results reveal that the teaching staff have a medium level of digital competence in the informational area. The teachers obtained better valuations in the dimensions concerning storage and recovery, postulating themselves as connoisseurs of the Big Data concept to a large extent. In some instances, the teachers affirmed that sometimes they access and interpret the data generated by the digital interactions, transforming it into useful information to improve their teaching processes. Finally, our research shows that the level of digital competence in the informational area influences the degree of knowledge about Big Data.

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Section: Digital Learning and Massive Data Generationmentioning

confidence: 99%

Analytical Competences of Teachers in Big Data in the Era of Digitalized Learning

et al. 2019

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“…Other concepts related to Big Data are data learning mining or learning analytics. Data learning mining is all those techniques and procedures used to extract useful and relevant information from the large amount of data reported from educational platforms (Menon et al 2017). On the other hand, learning analytics is a construct that is derived from data mining and alludes to the management, processing, and analysis of students' educational data, which are studied with the purpose of improving and optimizing the learning process (Liang et al 2016).…”

Section: Introductionmentioning

confidence: 99%

“…However, experts such as Menon et al (2017) consider that data mining techniques in the field of education-to this day-are not completely successful, so not all meaningful and valuable information is extracted. This is due to the fact that the handling and treatment of Big Data requires the collaboration of teachers with specialists, with the objective of being able to obtain the relevant information from the data reported by the use of tools and digital resources of an educational nature (Huda et al 2017).…”

Section: Introductionmentioning

confidence: 99%

Big Data in Education. A Bibliometric Review

et al. 2019

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The handling of a large amount of data to analyze certain behaviors is reaching a great popularity in the decade 2010–2020. This phenomenon has been called Big Data. In the field of education, the analysis of this large amount of data, generated to a greater extent by students, has begun to be introduced in order to improve the teaching–learning process. In this paper, it was proposed as an objective to analyze the scientific production on Big Data in education in the databases Web of Science (WOS), Scopus, ERIC, and PsycINFO. A bibliometric study was carried out on a sample of 1491 scientific documents. Among the results, the increase in publications in 2017 and the configuration of certain journals, countries and authors as references in the subject matter stand out. Finally, potential explanations for the study findings and suggestions for future research are discussed.

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“…All of these movements are influenced by larger forces such as crowdsourcing, social media, and the penetration of technologies in developed (and increasingly developing) countries. As these movements grow, there are calls for consortia of medical schools to pool resources (Le and Prober, 2018) as well as examples of networked communities of health professional students using free videos and adaptive learning platforms to make learning more efficient (Menon et al, 2017;Tackett et al, 2018). We believe these are all positive developments in the longitudinal trajectory of medical Joshi M, Verduzco R, Yogi S, Garcia M, Saxena S, Tackett S, Dexter N, Dempsey A, Whitaker E, Azzam A MedEdPublish https://doi.org/10.15694/mep.2019.000146.1 education.…”

Section: Impact On Medical Educationmentioning

confidence: 99%

Wikipedia Editing Courses at Three US Medical Schools in the 2017-2018 Academic Year

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Verduzco²,

Yogi³

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Using “big data” to guide implementation of a web and mobile adaptive learning platform for medical students

Abstract: Our study of a large sample of U.S. medical students illustrates big data medical education research and provides guidance for improving implementation of ALPs and further investigation.

Cited by 25 publications

References 30 publications

Analytical Competences of Teachers in Big Data in the Era of Digitalized Learning

Analytical Competences of Teachers in Big Data in the Era of Digitalized Learning

Big Data in Education. A Bibliometric Review

Wikipedia Editing Courses at Three US Medical Schools in the 2017-2018 Academic Year

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