scholarly journals Instructional design and instructional effectiveness in virtual classrooms: Research trends and challenges

2021 ◽  
pp. 156-174
Author(s):  
Baris Cukurbasi ◽  
Mubin Kiyici
Keyword(s):  
Data Mining ◽  
Instructional Design ◽  
Literature Review ◽  
Curriculum Development ◽  
Subject Matter ◽  
Virtual Classroom ◽  
Instructional Effectiveness ◽  
Research Trends ◽  
Virtual Classrooms ◽  
The Status

This literature review aimed to examine the status, trends and tendencies in publications about virtual classrooms, instructional design in the virtual classroom and instructional effectiveness in the virtual classroom, as indexed in the ERIC database. For this review, we examined 2680 publications indexed in ERIC between 1994 and 2018. We collected data with data mining and utilised several Python libraries as resources for developing the analysis plan. The results of the analysis are presented in visual form. For each of the three subject matter areas examined in this study, we present the themes in the publications by years, titles, abstracts and ERIC descriptors. We report in detail the trends and challenges that emerged from the analysis. The results show that the words “learning”, “online”, and “environment” were prominent in each of the three subject matter areas. The primary topics addressed were literacy and curriculum development, and researchers examined the roles of instructors, learners and managers. Implications for practice or policy: This review will be a useful resource for scientists, researchers and policymakers who conduct studies on the virtual classroom. Instruction should be planned according to differences in instructor, learner and manager roles, as revealed by the studies. Practitioners who want to teach in virtual classrooms can also use it as a guide.

What’s in a name

2014 ◽  
Vol 3 (3) ◽  
pp. 259-286 ◽  
Author(s):  
Olga Gladkova ◽  
Chrysanne DiMarco ◽  
Randy Allen Harris
Keyword(s):  
Complex System ◽  
Literature Review ◽  
Empirical Research ◽  
Research Trends ◽  
Linguistic Features ◽  
Scholarly Research ◽  
Environmental Scan ◽  
Binary Oppositions ◽  
The Status ◽  
Professional Research

We survey the disciplinary status and the research trends of argumentation studies. Our investigation combines the methods of a literature review and environmental scan. The latter consists in analysis of the linguistic features of journal titles, which we approach as a type of metacommunication. The results of our environmental scan suggest that the authors contributing to argumentation research envision it as a well-integrated field with a complex system of relations among the communities, agendas, methods, and venues involved in it. Yet we also found that the field is often seen as divided along the lines of binary oppositions between theory and its applications, as well as between theoretical and empirical research. We found that the field is increasingly turning to empirical, applied, and professional research, while the status of scholarly research is declining. Our analysis suggests that argumentation studies is developing a more sophisticated and tractable theory and methodology

scholarly journals Daya Saing Tujuan Wisata: Kajian Pustaka Sistematis

2020 ◽  
Vol 1 (2) ◽  
pp. 103-117
Author(s):  
Khaeril Khaeril ◽  
Mahlia Muis ◽  
Jusni Jusni ◽  
Madris Madris
Keyword(s):  
Data Mining ◽  
Data Analysis ◽  
Literature Review ◽  
Research Trends ◽  
Tourism Destination ◽  
Research Gaps ◽  
Publish Or Perish ◽  
Destination Competitiveness ◽  
Research Findings

This article aims to discuss the current research trends on the tourism destination competitiveness. This research is sistemic literature review by using Publish or Perish software for data mining and VOSviewer for data analysis and visualization. The results indicate 4 research cluster themes on tourism destination competitiveness and 5 research clusters related to tourism destination competitiveness. The main cited articles on tourism destination competitiveness for period of 2005-2020 are Larry Dwyer, Chulwo Kim, Tanja Mihalic, Tanja Amenski, Vanja Dragineva, and Ugljesa Stankov. Based on the research findings, we state that the research gaps in the tourism destination competitiveness are still wide open, particularly in Indonesia.

Virtual classroom project

2017 ◽  
Author(s):  
Nicholas Gmeiner
Keyword(s):  
Virtual Reality ◽  
Students With Disabilities ◽  
Learning Experience ◽  
Virtual Classroom ◽  
Traditional Classroom ◽  
Video Capture ◽  
Interactive Learning Environment ◽  
Virtual Reality Technology ◽  
Virtual Classrooms ◽  
Classroom Project

This project aims to provide students with disabilities the same in class learning experience through virtual reality technology, 360-degree video capture, and the use of Arduino units. These technologies will be combined to facilitate communication between teachers in physical classrooms with students in virtual classrooms. The goal is to provide a person who is affected by a disability (which makes it hard to be in a traditional classroom) the same benefits of a safe and interactive learning environment.

Psychological Research Literature Review Canvas

2020 ◽  
Author(s):  
Quang Ngoc Nguyen
Keyword(s):  
Literature Review ◽  
Research Process ◽  
Psychological Research ◽  
Research Literature ◽  
Status Quo ◽  
Chaotic Process ◽  
Psychological Construct ◽  
The Status ◽  
Guiding Questions

Without a guideline or structure, conducting a literature review on a psychological construct might become a chaotic process . This canvas was built based on the author's experience in order to help psychological researchers classify, organize, and summarize the information relating to the psychological construct of interest into several essential aspects including definition, classification, measurement, sample, predictors and outcomes, mediators and moderators, interventions, and theories. For each aspect, there are some guiding questions which are expected to help researcher decice which information should be focused while examining scientific documents. The completely filled canvas should depict the status quo of the research on the psychological construct of interest, facilitating the research process.

Trends and Opportunities in Health Analytics as a Service and Implications for Use in Low Resource Settings: A Literature Review Abstract (Preprint)

2019 ◽  
Author(s):  
Meghana Bastwadkar ◽  
Carolyn McGregor ◽  
S Balaji
Keyword(s):  
Data Mining ◽  
Cloud Computing ◽  
Big Data ◽  
Intensive Care ◽  
Literature Review ◽  
Health Monitoring ◽  
Data Analytics ◽  
Neonatal Intensive Care ◽  
Big Data Analytics ◽  
Healthcare Facilities

BACKGROUND This paper presents a systematic literature review of existing remote health monitoring systems with special reference to neonatal intensive care (NICU). Articles on NICU clinical decision support systems (CDSSs) which used cloud computing and big data analytics were surveyed. OBJECTIVE The aim of this study is to review technologies used to provide NICU CDSS. The literature review highlights the gaps within frameworks providing HAaaS paradigm for big data analytics METHODS Literature searches were performed in Google Scholar, IEEE Digital Library, JMIR Medical Informatics, JMIR Human Factors and JMIR mHealth and only English articles published on and after 2015 were included. The overall search strategy was to retrieve articles that included terms that were related to “health analytics” and “as a service” or “internet of things” / ”IoT” and “neonatal intensive care unit” / ”NICU”. Title and abstracts were reviewed to assess relevance. RESULTS In total, 17 full papers met all criteria and were selected for full review. Results showed that in most cases bedside medical devices like pulse oximeters have been used as the sensor device. Results revealed a great diversity in data acquisition techniques used however in most cases the same physiological data (heart rate, respiratory rate, blood pressure, blood oxygen saturation) was acquired. Results obtained have shown that in most cases data analytics involved data mining classification techniques, fuzzy logic-NICU decision support systems (DSS) etc where as big data analytics involving Artemis cloud data analysis have used CRISP-TDM and STDM temporal data mining technique to support clinical research studies. In most scenarios both real-time and retrospective analytics have been performed. Results reveal that most of the research study has been performed within small and medium sized urban hospitals so there is wide scope for research within rural and remote hospitals with NICU set ups. Results have shown creating a HAaaS approach where data acquisition and data analytics are not tightly coupled remains an open research area. Reviewed articles have described architecture and base technologies for neonatal health monitoring with an IoT approach. CONCLUSIONS The current work supports implementation of the expanded Artemis cloud as a commercial offering to healthcare facilities in Canada and worldwide to provide cloud computing services to critical care. However, no work till date has been completed for low resource setting environment within healthcare facilities in India which results in scope for research. It is observed that all the big data analytics frameworks which have been reviewed in this study have tight coupling of components within the framework, so there is a need for a framework with functional decoupling of components.

Data Mining-based Financial Statement Fraud Detection: Systematic Literature Review and Meta-analysis to Estimate Data Sample Mapping of Fraudulent Companies Against Non-fraudulent Companies

2021 ◽  
pp. 097215092098485
Author(s):  
Sonika Gupta ◽  
Sushil Kumar Mehta
Keyword(s):  
Machine Learning ◽  
Data Mining ◽  
Literature Review ◽  
Systematic Literature Review ◽  
Classification Accuracy ◽  
Meta Analysis ◽  
Financial Statement ◽  
Research Articles ◽  
Financial Statement Fraud ◽  
Data Mining Techniques

Data mining techniques have proven quite effective not only in detecting financial statement frauds but also in discovering other financial crimes, such as credit card frauds, loan and security frauds, corporate frauds, bank and insurance frauds, etc. Classification of data mining techniques, in recent years, has been accepted as one of the most credible methodologies for the detection of symptoms of financial statement frauds through scanning the published financial statements of companies. The retrieved literature that has used data mining classification techniques can be broadly categorized on the basis of the type of technique applied, as statistical techniques and machine learning techniques. The biggest challenge in executing the classification process using data mining techniques lies in collecting the data sample of fraudulent companies and mapping the sample of fraudulent companies against non-fraudulent companies. In this article, a systematic literature review (SLR) of studies from the area of financial statement fraud detection has been conducted. The review has considered research articles published between 1995 and 2020. Further, a meta-analysis has been performed to establish the effect of data sample mapping of fraudulent companies against non-fraudulent companies on the classification methods through comparing the overall classification accuracy reported in the literature. The retrieved literature indicates that a fraudulent sample can either be equally paired with non-fraudulent sample (1:1 data mapping) or be unequally mapped using 1:many ratio to increase the sample size proportionally. Based on the meta-analysis of the research articles, it can be concluded that machine learning approaches, in comparison to statistical approaches, can achieve better classification accuracy, particularly when the availability of sample data is low. High classification accuracy can be obtained with even a 1:1 mapping data set using machine learning classification approaches.

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