A review of the trend of microlearning

PurposeMicrolearning has been considered as a promising topic in work-based learning. This paper aims to review the trends of microlearning in terms of related publications and Internet searches. Hopefully, the findings can serve as a reference for the education sector, government, business and academia to promote, design and use microlearning.Design/methodology/approachIn this study, two sets of analysis were conducted. Firstly, the authors analysed the publication trend of microlearning. Second, the authors analysed the trend of Internet searches related to microlearning. More specifically, the authors analysed real-world data of 14 years obtained from Scopus and Google Trends for the purpose. These data include the first relevant publication found in the database.FindingsIn total, 476 relevant publications have been identified during 2006–2019. According to the findings from the analysis of the identified publications, microlearning is a relevantly new and emerging global topic involving authors, affiliations and funding sponsors from different countries. Moreover, many microlearning-related publications were conducted from perspectives of e-learning or mobile learning. Furthermore, the authors notice higher education was the most frequently mentioned education level in the identified publications. On the other hand, language learning (i.e. second language, vocabulary learning, etc.) had been mentioned more times in the titles and abstracts than other subject areas. Overall, the increasing trend of publications on “microlearning” (as a knowledge supply) is in line with the established increasing Internet searches of “microlearning” (as a practical demand) in recent years.Practical implicationsFrom the work-based learning perspective, microlearning has been considered as one of the key topics in talent development topics. Policymakers, educators, researchers and participators have the responsibility to explore how to promote, design and use microlearning to help people to learn in the right direction through valid knowledge with ethical consideration.Originality/valueAlthough many works had been done on microlearning, there is a lack of comprehensive studies reviewing the trends of microlearning in terms of related publications and Internet searches. This study aims to fill this gap by analysing real-world data obtained from Scopus and Google Trends – these data include the first relevant publication found in the database. The authors believe this is the first time that a study has been conducted to comprehensively review the development trends of microlearning. Hopefully, this study can shed some light on related research.

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Assessing the conformity to clinical guidelines in oncology

Management Decision ◽

10.1108/md-09-2017-0906 ◽

2018 ◽

Vol 56 (10) ◽

pp. 2172-2186 ◽

Cited By ~ 3

Author(s):

Jacopo Lenkowicz ◽

Roberto Gatta ◽

Carlotta Masciocchi ◽

Calogero Casà ◽

Francesco Cellini ◽

...

Keyword(s):

Real World ◽

Clinical Pathway ◽

Clinical Guidelines ◽

Process Mining ◽

State Transitions ◽

Real World Data ◽

Electronic Health Record Data ◽

Conformance Checking ◽

Content Type ◽

World Data

Purpose The purpose of this paper is to describe a methodology to deal with conformance checking through the implementation of computer-interpretable-clinical guidelines (CIGs), and present an application of the methodology to real-world data and a clinical pathway for radiotherapy-related oncological treatment. Design/methodology/approach This methodology is implemented by a software able to use the hospital electronic health record data to assess the adherence of the actual executed clinical processes to a clinical pathway, monitoring at the same time management-related efficiency and performance parameters, and ideally, suggesting ways to improve them. Findings Three use cases are presented, in which the results of conformance checking are used to compare different branches of the executed guidelines with respect to the adherence to ideal process, temporal distribution of state-to-state transitions, and overall treatment efficacy, in order to extract data-driven evidence that could be of interest for the hospital management. Originality/value This approach has the result of applying management-oriented data mining technique on sequential data, typical of process mining, to the result of a conformity check between the preliminary knowledge defined by clinicians and the real-world data, typical of CIGs.

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Consensus Development of a Modern Ontology of Emergency Department Presenting Problems – the HierArchical Presenting Problem ontologY (HaPPy)

10.1101/126870 ◽

2017 ◽

Author(s):

Steven Horng ◽

Nathaniel R. Greenbaum ◽

Larry A. Nathanson ◽

James C McClay ◽

Foster R. Goss ◽

...

Keyword(s):

Emergency Department ◽

Real World ◽

Emergency Department Patient ◽

Validation Dataset ◽

Snomed Ct ◽

Presenting Problems ◽

Real World Data ◽

World Data ◽

Academic Level ◽

The Right

ABSTRACTObjectiveNumerous attempts have been made to create a standardized ‘presenting problem’ or ‘chief complaint’ list to characterize the nature of an Emergency Department visit. Previous attempts have failed to gain widespread adoption as none were freely sharable and contained the right level of specificity, structure, and clinical relevance to gain acceptance by the larger emergency medicine community. Using real-world data, we constructed a presenting problem list that addresses these challenges.Materials and MethodsWe prospectively captured the presenting problems for 180,424 consecutive emergency department patient visits at an urban, academic, Level I trauma center in the Boston metro area. No patients were excluded. We used a consensus process to iteratively derive our system using real-world data. We used the first 70% of consecutive visits to derive our ontology; followed by a 6 month washout period, and the remaining 30% for validation. All concepts were mapped to SNOMED-CT.ResultsOur system consists of a polyhierarchical ontology containing 692 unique concepts, 2,118 synonyms, and 30,613 non-visible descriptions to correct misspellings and non-standard terminology. Our ontology successfully captured structured data for 95.9% of visits in our validation dataset.Discussion and ConclusionWe present the HierArchical Presenting Problem ontologY (HaPPy). This ontology was empirically derived then iteratively validated by an expert consensus panel. HaPPy contains 692 presenting problem concepts, each concept being mapped to SNOMED-CT. This freely sharable ontology can help to facilitate presenting problem based quality metrics, research, and patient care.

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