An Infographics-based Tool for Monitoring Dropout Risk on Distance Learning in Higher Education

Brito, Maria; Medeiros, Francisco; Bezerra, Ed Porto

doi:10.1109/ithet46829.2019.8937361

Cited by 10 publications

(17 citation statements)

References 12 publications

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“…About LA, Brito et al (2019) state that it has attracted the attention of the scientific community that works with educational technologies, as it provides a more effective way for teachers to track student performance and involvement in educational platforms. However, for the application, accurate data must be provided for processing and analysis since erroneous data can easily lead to misinterpretation and inaccuracy of the obtained results (Tomasevic et al, 2020).…”

Section: Edm and La In Distance Educationmentioning

confidence: 99%

“…The results indicated that the Naive Bayes algorithm had the best performance, with an accuracy of 66.26% in pre-university data (demographic and previous experiences) and 84.56% in academic data (first two written evaluations and presence), favoring the development of personalized learning strategies, increasing retention rates and improving the quality of education. Brito et al (2019) present the Dropout Risk Report tool developed to detect students' dropout risks through Moodle data, such as cognitive, social, and behavioral. According to the authors, the results made it easier for teachers, tutors, and educational directors to obtain more accurate information and indicators of access, performance, and interactions, to rescue students who had never accessed or abandoned the teaching platform, and to intervene immediately in cases identified with the risk of dropout.…”

Section: Rq1: Has Dropout In Distance Education Been An Object Of Study?mentioning

confidence: 99%

“…The highlight for the tool Waikato Environment for Knowledge Analysis (Weka), developed by the University of Waikato, et al (2018) in New Zealand, used in 8 works for this purpose, an essential ally in combating dropout in distance education. An article can use more than one tool, as in Macedo et al (2019) and Brito et al (2019).…”

Section: Rq3 What Were Computational Tools Used To Address Dropout In Distance Education?mentioning

confidence: 99%

“…The tool presented in Cobos and Olmos (2019), EdX-MAS+, was tested in 7 MOOC's and used 3 different techniques to analyze the data contained in the distance learning platforms: classification, prediction, and clustering. Brito et al (2019) presented the Dropout Risk Report tool capable of demonstrating a list of students at risk of dropout through graphical reports. Chen and Zhang (2017), Whitehill et al (2017), Dos Queiroga et al (2017) presented the results obtained by the tools developed, however, they did not disclose the names of their innovative systems.…”

Section: Rq3 What Were Computational Tools Used To Address Dropout In Distance Education?mentioning

confidence: 99%

“…Kostopoulos et al (2018a), for example, used 12 algorithms in order to predict student performance in final exams. , Macedo et al (2019), Chen and Zhang (2017), Whitehill et al (2017), Niu et al (2018) and Santos et al (2015) used only 1 algorithm, and Brito et al (2019) and Imran et al (2019) did not mention the algorithms used. For innovation, new algorithms were developed by some authors of the primary articles studied in an attempt to contribute to the identification and mitigation of dropout in distance education.…”

Section: Rq4 What Were the Algorithms Used To Deal With Dropout In Distance Education?mentioning

confidence: 99%

See 4 more Smart Citations

Active Methodology, Educational Data Mining and Learning Analytics: A Systematic Mapping Study

Andrade¹,

Rigo²,

Barbosa³

2021

Informatics in Education

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Distance Learning has enabled educational practices based on digital platforms, generating massive amounts of data. Several initiatives use this data to identify dropout contexts, mainly providing teacher support about student behavior. Approaches such as Active Methodologies are known as having good potential to involve and motivate students. This article presents a systematic mapping aiming to identify current Educational Data Mining and Learning Analytics methods. Besides, we identify Active Methodologies' application to mitigate dropout in Distance Learning. We evaluated 668 papers published from January 2015 to March 2020. The results indicate a growing application of Educational Data Mining and Learning Analytics to identify and mitigate students' abandonment in Distance Learning. However, studies with Active Methodologies to minimize dropout and enhance student permanence are scarce. Some works suggest Active Methods as a possible complement of Learning Analytics in dropout.

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Section: Edm and La In Distance Educationmentioning

confidence: 99%

Section: Rq1: Has Dropout In Distance Education Been An Object Of Study?mentioning

confidence: 99%

Section: Rq3 What Were Computational Tools Used To Address Dropout In Distance Education?mentioning

confidence: 99%

Section: Rq3 What Were Computational Tools Used To Address Dropout In Distance Education?mentioning

confidence: 99%

Section: Rq4 What Were the Algorithms Used To Deal With Dropout In Distance Education?mentioning

confidence: 99%

See 3 more Smart Citations

Active Methodology, Educational Data Mining and Learning Analytics: A Systematic Mapping Study

Andrade¹,

Rigo²,

Barbosa³

2021

Informatics in Education

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Learning analytics in distance education: A systematic review study

Palanci,

Yılmaz,

Turan

2024

Educ Inf Technol

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This study aims to reveal the main trends and findings of the studies examining the use of learning analytics in distance education. For this purpose, journal articles indexed in the SSCI index in the Web of Science database were reviewed, and a total of 400 journal articles were analysed within the scope of this study. The systematic review method was used as the research methodology. The first study on the subject was published in 2011, and the publications continued to increase over the years. It was found that the publications on the subject were primarily found in “Computers and Education” and “Education and Information Technologies” journals. It was observed that China, USA, and Spain were the leading countries where the related studies were conducted. The studies primarily used the quantitative method, and university students were included as the sample. In addition, within the scope of learning analytics, it was observed that the data were mainly analysed with “regression analysis”, “correlation analysis”, “special algorithms-models”, “ANOVA”, and “cluster analysis” methods. It was determined that the most preferred platforms in the studies were learning management systems and MOOCs, learning behaviours were mostly examined, and log data were mainly used in this process. It was observed that the variables tested in the studies mainly consisted of students’ behaviours on the platform, learning performances, communication processes, dropout behaviours and course designs. Furthermore, in the studies examined, the advantages of learning analytics in the context of distance education are mostly related to the possibilities of improving the teaching process, and as disadvantages, it is stated that learning analytics is not suitable for use in some situations, negatively affect students’ performances, have limited interaction with students and are an expensive investment.

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Infographics in Educational Settings: A Literature Review

Bhat,

Alyahya

2024

IEEE Access

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Infographics are visual representations of data that utilize various graphic elements, including pie charts, bar graphs, line graphs, and histograms. Educators and designers can maximize the potential of infographics as powerful educational tools by carefully addressing challenges and capitalizing on emerging technologies. However, current education systems showcase the need for development guidelines and the best practices targeted at designing and developing infographics while exploring the major economic and social impacts of infographics on education. This study examines the concept and role of infographics in education, methodologies, trends, and obstacles. It evaluates potential economic implications and gives insights to design and development experts. The study is based on a scoping literature review methodology, uncovering the conceptual background and the role of infographics. The study emphasizes the unique functions of infographics in data visualization for educational purposes and investigates the current trends and practices in infographics creation. The key challenges associated with the use of infographics are also discussed. Furthermore, the study attempts to identify the cutting-edge frameworks for infographic creation and development while evaluating their economic implications for the role of global education. Finally, the potential recommendations for creating successful infographics while focusing on professional design and development are also covered. The guided literature review will be vital for understanding and using infographics in education.INDEX TERMS Data visualization; design; digital tools and platforms; educational technology; frameworks; infographics; learning outcomes; visual communication.

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An Infographics-based Tool for Monitoring Dropout Risk on Distance Learning in Higher Education

Cited by 10 publications

References 12 publications

Active Methodology, Educational Data Mining and Learning Analytics: A Systematic Mapping Study

Active Methodology, Educational Data Mining and Learning Analytics: A Systematic Mapping Study

Learning analytics in distance education: A systematic review study

Infographics in Educational Settings: A Literature Review

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