The potential for big data to enhance the higher education sector in Oman

Riffai, M.M.M.A.; Duncan, Peter; Edgar, David; Al-Bulushi, Ahmed Hassan

doi:10.1109/icbdsc.2016.7460346

Cited by 13 publications

(7 citation statements)

References 10 publications

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“…Besides the three major themes above, key-terms cluster analysis also reveals that big data has a strong impact on every sector, from medical healthcare [24,25,[63][64][65], finance and business [26,[66][67][68], energy [69,70], government [71][72][73][74], education [75][76][77] to transportation [78][79][80]. The main source of big data comes from daily life and activities, for example, social media and networks.…”

Section: Big Data Applications and Servicesmentioning

confidence: 99%

Theme Mapping and Bibliometrics Analysis of One Decade of Big Data Research in the Scopus Database

Parlina

Ramli²,

Murfi³

2020

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Recently, the popularity of big data as a research field has shown continuous and wide-scale growth. This study aims to capture the scientific structure and topic evolution of big data research using bibliometrics and text mining-based analysis methods. Bibliographic data of journal articles regarding big data published between 2009 to 2018 were collected from the Scopus database and analyzed. The results show a significant growth of publications since 2014. Furthermore, the findings of this study highlight the core journals, most cited articles, top productive authors, countries, and institutions. Secondly, a unique approach to identifying and analyzing major research themes in big data publications was proposed. Keywords were clustered, and each cluster was labeled as a theme. Moreover, the papers were divided into four sub-periods to observe the thematic evolution. The theme mapping reveals that research on big data is dominated by big data analytics, which covers methods, tools, supporting infrastructure, and applications. Other critical aspects of big data research are security and privacy. Social networks and the Internet of things are significant sources of big data, and the resources and services offered by cloud computing strongly support the management and processing of big data.

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Section: Big Data Applications and Servicesmentioning

confidence: 99%

Theme Mapping and Bibliometrics Analysis of One Decade of Big Data Research in the Scopus Database

Parlina

Ramli²,

Murfi³

2020

Information

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“…According to Lenz et al [60] information about people can be collected through a variety of devices, including smartphones, wearables or even other types of sensors, and therefore reflect the distinctive behavior and personality of those people. In parallel, according to [61], current HEIs receive data from various sources, namely LMS, social networks, digital libraries, student surveys and Internet logs [62].…”

Section: Rationalmentioning

confidence: 99%

“…This information can be useful, through its analysis, using methods in the context of Big Data, for the personalization of curricula, for student performance, among other issues. The Big Data methods, according to [60], are determined by two basic requirements: "(i) the ability of a multilayer information system to bring together all these different heterogeneous data and provide methods for a combined analysis of collected information. (ii) The ability of devices to collect userspecific data such as movements, gestures, eye movements and so on."…”

Section: Rationalmentioning

confidence: 99%

“…Professors. Teachers will be able, according to [60] to observe the behavior of the students during the classes, as well as throughout the training time, with the help of IoT. For example, authors highlight the use of speech recording devices, reading progress recording tablets or wearables to record heart rate, student eye movement, among others, which will enable the teacher to obtain a more complete view of the students' behavior.…”

Section: Conceptual Approachmentioning

confidence: 99%

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Higher Education Disruption Through IoT and Big Data: A Conceptual Approach

Moreira

Ferreira

Cardoso

2017

Lecture Notes in Computer Science

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The emergence of new technologies such as IoT and Big Data, the change in the behavior of society in general and the younger generation in particular, require higher education institutions to "look" for teaching differently. This statement is complemented by the prediction of the futurist Thomas Frey, who postulates that "in 14 years it will be a big deal when students learn from robot teachers over the internet". Thus, it is necessary to urgently begin a disruption of current teaching models, to be able to include in these processes the new technologies and the daily habits of the new generations. The early usage of mobile devices and the constant connection to the Internet (social networks, among others) mean that the current generation of young people, who are reaching higher education, has the most technological literacy ever. In this new context, this article presents a disruptive conceptual approach to higher education, using information gathered by IoT and based on Big Data & Cloud Computing and Learning Analytics analysis tools. This approach will, for example, allow individualized solutions taking into account the characteristics of the students, to help them customize their curriculum and overcome their limitations and difficulties, throughout the learning process .

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“…So we have seen various "waves" of attention and "hype" on technologies and solutions related to Technology Enhanced Learning, but many of these hypes have revealed to be simply another buzzword and have not been consolidated. Today's buzzword that has been sweeping the world for a few years but has only just started appearing more commonly in eLearning is Big Data [10].…”

Section: Introductionmentioning

confidence: 99%

Is e-learning ready for big data? And how big data would be useful to e-learning ?

Maresca

Molinari

2016

International Conferences on Distributed Multimedia Systems

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The paper presents an overview of possible application fields of big data to the Technology-Enhanced Learning (TEL), with the many different facets this could imply. Many are the benefits for e-learning when approaching the collection of data, especially when elearning is delivered in a life-long learning perspective. All these benefits could impact the future of eLearning, by revolutionizing the way we analyze and assess the eLearning experience. On one side, we present our experience in enriching the persistence layer of an LMS with a deeper log system on users' actions, in the perspective of collecting volumes of data compatible with big data tools and technologies, while highlighting some related issues. On the other hand we will deal with the first applications of cognitive systems that are responsible for catalysing the big data in analytics aimed at e-learning activities.

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The potential for big data to enhance the higher education sector in Oman

Cited by 13 publications

References 10 publications

Theme Mapping and Bibliometrics Analysis of One Decade of Big Data Research in the Scopus Database

Theme Mapping and Bibliometrics Analysis of One Decade of Big Data Research in the Scopus Database

Higher Education Disruption Through IoT and Big Data: A Conceptual Approach

Is e-learning ready for big data? And how big data would be useful to e-learning ?

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