Visual Analytics for Systematic Reviews According to PRISMA

Sina, Lennart B.; Nazemi, Kawa

doi:10.1109/iv56949.2022.00059

Cited by 4 publications

(5 citation statements)

References 19 publications

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“…Figure 2 shows an exemplary application of a forecast visualization that shows the temporal development of a technology with forecast results using an integrated hybrid approach in a visual analytics system [22,24,25]. The future prediction is displayed through lower saturation measured by the standard deviation values of the prediction algorithm.…”

Section: Application Of Hybrid Forecasting Approaches In Visual Analy...mentioning

confidence: 99%

“…The more precise predictions could be used to predict the future influence of individuals, which could also support the decision-making process [44]. Exemplary application of an integrated hybrid approach in a visual analytics system [22,24,25]. The future prediction is illustrated through lower saturation measured by the standard deviation values of the prediction algorithm.…”

Section: Application Of Hybrid Forecasting Approaches In Visual Analy...mentioning

confidence: 99%

“…This fact leads us to analyze in this systematic review reports on hybrid forecasting methods that have measured the quality of the individual statistical models and the neural networks, as well as that of their hybrid approach. To identify the relevant literature in this area, we use the established methodology according to PRISMA for this review, which has emerged in the BMC research but is also increasingly applied in computer science [25] and other domains to analyze literature in a structured and systematic way.…”

Section: Introductionmentioning

confidence: 99%

“…Figure 2. Exemplary application of an integrated hybrid approach in a visual analytics system[22,24,25]. The future prediction is illustrated through lower saturation measured by the standard deviation values of the prediction algorithm.…”

mentioning

confidence: 99%

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Hybrid Forecasting Methods—A Systematic Review

et al. 2023

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Time series forecasting has been performed for decades in both science and industry. The forecasting models have evolved steadily over time. Statistical methods have been used for many years and were later complemented by neural network approaches. Currently, hybrid approaches are increasingly presented, aiming to combine both methods’ advantages. These hybrid forecasting methods could lead to more accurate predictions and enhance and improve visual analytics systems for making decisions or for supporting the decision-making process. In this work, we conducted a systematic literature review using the PRISMA methodology and investigated various hybrid forecasting approaches in detail. The exact procedure for searching and filtering and the databases in which we performed the search were documented and supplemented by a PRISMA flow chart. From a total of 1435 results, we included 21 works in this review through various filtering steps and exclusion criteria. We examined these works in detail and collected the quality of the prediction results. We summarized the error values in a table to investigate whether hybrid forecasting approaches deliver better results. We concluded that all investigated hybrid forecasting methods perform better than individual ones. Based on the results of the PRISMA study, the possible applications of hybrid prediction approaches in visual analytics systems for decision making are discussed and illustrated using an exemplary visualization.

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Section: Application Of Hybrid Forecasting Approaches In Visual Analy...mentioning

confidence: 99%

Section: Application Of Hybrid Forecasting Approaches In Visual Analy...mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

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Hybrid Forecasting Methods—A Systematic Review

et al. 2023

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“…Farhat et al (2022) identified Ovid, Covidence, and Rayyan as the most accurate electronic tools for identifying and removing duplicate references.Moreover, researchers can gain advantages from the integration of a Visual Analytics system that combines interactive visualizations and artificial intelligence. This integration facilitates the implementation of complex protocols and analysis during the review process (Sina & Nazemi, 2022;Sobieraj & Baker, 2021). Practitioners must use critical appraisal methods and carefully consider the quality of the systematic review before applying the evidence (Boaye & Zhao, 2022).…”

Section: Introductionmentioning

confidence: 99%

A scientometrics analysis and systematic review of STEAM education with gamification

Jantakoon,

Jantakun,

Jantakun

2024

EDU

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This scientometric analysis and systematic review methodologies examine the integration of gamification into steam education from 2017 to 2023. We collected data from the Scopus database. The study employed content analysis to evaluate 34 articles published during the past 7 years. The aggregate magnitude and trajectory of publications. The study examined trends in terms of annual accounts, number of articles, distribution of articles by sources, most productive sources, keywords, top collaboration groups, theme evolutions, contributions, practical consequences, and conceptual framework. The findings revealed the publication of 34 papers across 30 sources between 2017 and 2023, offering significant insights into the data and document formats. The research on steam with gamification revealed fluctuations, alternating between deceleration and positive acceleration. The articles experienced their highest growth rate in 2022. "CEUR workshop proceedings" is the primary source for the most frequently published articles. We request the keyword Plus growth rate for phrases such as "computer-aided instruction," "e-learning," and "embedded systems." The analysis’s findings on thematic evolution unveiled three significant advancements: (1) Studies in science and technology have shifted their focus towards steam education. (2) Research on learning environments has expanded to include further investigation into stem education and the integration of science and technology. (3) School students’ research has evolved and merged with the study of the learning process. The outcomes, contributions, and real-world significance of incorporating gamification into steam education. The conceptual framework ultimately fosters the development of creativity, problem-solving skills, and innovative abilities.

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