Enhancing educational data mining techniques on online educational resources with a semi-supervised learning approach

Tam, Vincent; Lam, Edmund Y.; Fung, Sheldon; Fok, Wwt; Yuen, Andrea

doi:10.1109/tale.2015.7386044

Cited by 6 publications

(7 citation statements)

References 6 publications

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“…This application is directly related to the student's participation in the educational process such as in terms of the analysis of learning styles or learning strategies, the analysis and improvement of student skills, and the motivation trends of students, among others. A second application area of LA [4,7,[22][23][24]32,35,38,44,45,47,57,62,63,66,69,72,76] Institutional database 15 [2,5,5,13,14,16,[39][40][41]48,52,53,67,68,79] Specific databases 13 [1,15,18,19,43,44,50,54,61,68,72,74,80] Not specified 7 [3,12,17,…”

Section: Areas Of Application Of La and Edm Results In Engineering mentioning

confidence: 99%

The use of tools of data mining to decision making in engineering education—A systematic mapping study

Buenaño-Fernández

Villegas-Ch

Luján‐Mora³

2019

Comp Applic In Engineering

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In recent years, there has been an increasing amount of theoretical and applied research that has focused on educational data mining. The learning analytics is a discipline that uses techniques, methods, and algorithms that allow the user to discover and extract patterns in stored educational data, with the purpose of improving the teaching‐learning process. However, there are many requirements related to the use of new technologies in teaching‐learning processes that are practically unaddressed from the learning analytics. In an analysis of the literature, the existence of a systematic revision of the application of learning analytics in the field of engineering education is not evident. The study described in this article provides researchers with an overview of the progress made to date and identifies areas in which research is missing. To this end, a systematic mapping study has been carried out, oriented toward the classification of publications that focus on the type of research and the type of contribution. The results show a trend toward case study research that is mainly directed at software and computer science engineering. Furthermore, trends in the application of learning analytics are highlighted in the topics, such as student retention or dropout prediction, analysis of academic student data, student learning assessment and student behavior analysis. Although this systematic mapping study has focused on the application of learning analytics in engineering education, some of the results can also be applied to other educational areas.

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Section: Areas Of Application Of La and Edm Results In Engineering mentioning

confidence: 99%

The use of tools of data mining to decision making in engineering education—A systematic mapping study

Buenaño-Fernández

Villegas-Ch

Luján‐Mora³

2019

Comp Applic In Engineering

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“…Ambient intelligence has been developed as a new discipline that is targeted to facilitate the daily activities of all human beings, including a diversity of assessment schemes, interaction styles, pedagogical methods, supporting environments and tools, etc. of the involved learning activities and platforms [4,18,66,67].…”

Section: Ambient Intelligence For E-learningmentioning

confidence: 99%

“…The innovative interaction mechanisms and pedagogical methods between learners and their supporting e-learning platforms create ample opportunities for AmI techniques to carefully analyse and categorize the learners' characteristics and learning needs together with the supporting environments, tools and other customizable system features to come up with a more effective or personalized e-learning platform. In this direction, there are many active research works on learning analytics [67], intelligent tutoring systems [66], collaborative learning platforms [30], etc.…”

Section: Ambient Intelligence For E-learningmentioning

confidence: 99%

“…Also, [66] explores the possible uses of intelligent image-processing techniques such as statistical learning approaches or machine-learning methods [14] with feature extraction and filtering mechanisms to analyse the learners' responses to educational videos or other online materials. The analysis is based on snapshots of the learners' facial expressions captured on the webcams of mobile devices such as tablet and laptop PCs.…”

Section: Ambient Intelligence For E-learningmentioning

confidence: 99%

“…Besides facial analytics (FA), there are many AmIassisted or intelligent tutoring systems [66] that employ AmI methods, including classification algorithms Fig. 7.…”

Section: Ambient Intelligence For E-learningmentioning

confidence: 99%

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Artificial intelligence and ambient intelligence

Gams

Härmä

et al. 2019

AIS

Self Cite

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Ambient intelligence (AmI) is intrinsically and thoroughly connected with artificial intelligence (AI). Some even say that it is, in essence, AI in the environment. AI, on the other hand, owes its success to the phenomenal development of the information and communication technologies (ICTs), based on principles such as Moore's law. In this paper we give an overview of the progress in AI and AmI interconnected with ICT through information-society laws, superintelligence, and several related disciplines, such as multi-agent systems and the Semantic Web, ambient assisted living and e-healthcare, AmI for assisting medical diagnosis, ambient intelligence for e-learning and ambient intelligence for smart cities. Besides a short history and a description of the current state, the frontiers and the future of AmI and AI are also considered in the paper.

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Analytical Review on Various Aspects of Educational Data Mining and Learning Analytics

Patil¹,

Gupta

2019

2019 International Conference on Innovative Trends and Advances in Engineering and Technology (ICITAET)

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Enhancing educational data mining techniques on online educational resources with a semi-supervised learning approach

Cited by 6 publications

References 6 publications

The use of tools of data mining to decision making in engineering education—A systematic mapping study

The use of tools of data mining to decision making in engineering education—A systematic mapping study

Artificial intelligence and ambient intelligence

Analytical Review on Various Aspects of Educational Data Mining and Learning Analytics

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