Using Big Data in Collaborative Learning

Author(s):  
Liz Sokolowski ◽  
Samia Oussena

Big data emerged as a dominant trend for predictive analytics in many areas of industry and commerce. The study aimed to explore whether similar trends and benefits have been observed in the area of collaborative learning. The study looked at the domains in which the collaborative learning was undertaken. The results of the review found that the majority of the studies were undertaken in the Computing and Engineering or Social Science domains, primarily at undergraduate level. The results indicate that the data collection focus is on interaction data to describe the process of the collaboration itself, rather than on the end product of the collaboration. The student interaction data came from various sources, but with a notable concentration on data obtained from discussion forums and virtual learning environment logs. The review highlighted some challenges; the noisy nature of this data and the need for manual pre-processing of textual data currently renders much of it unsuitable for automated ‘big data' analytical approaches.

Daedalus ◽  
2021 ◽  
Vol 150 (3) ◽  
pp. 121-142
Author(s):  
Beth Simone Noveck

Abstract To create government that is neither bigger nor smaller but better at solving problems more effectively and legitimately, agencies need to use big data and the associated technologies of machine learning and predictive analytics. Such data-analytical approaches will help agencies understand the problems they are addressing more empirically and devise more responsive policies and services. Such data-processing tools can also be used to make citizen engagement more efficient, helping agencies to make sense of large quantities of information and invite meaningful participation from more diverse audiences who have never participated in our democracy. To take advantage of the power of new technologies for governing, however, the federal government needs, first and foremost, to invest in training public servants to work differently and prepare them for the future of work in a new technological age.


Author(s):  
Rubí Estela Morales-Salas ◽  
Daniel Montes-Ponce

A virtual learning environment is conceived as an interaction space that ease the realization of mediated activities by technology, in this case the internet; besides using multimedia materials, learning objects, social networks, among others; which have changed imminently the traditional education. In this article an instrument is proposed in a checklist format, to evaluate any platform that has interaction spaces such as a Virtual Learning Environment, in this case responding to four spaces or general indicators: information Space, Mediation / Interaction Space, Instructional Design Space and Exhibition Space. Criteria are used according to the interactions and activities carried out by the consultant and virtual student. These, in turn, come up from the analysis and interaction of the advisers achieved in the discussion forums and portfolio activities through collaborative work. It was situated as a qualitative research, with a descriptive nature since it is not limited to data collection only, but also it refers and analyzes the interaction of the advisers achieved in the discussion forums and portfolio activities through the collaborative work of the workshop course "Virtual Learning Environments" developed in a virtual learning environment.


2019 ◽  
Vol 10 (4) ◽  
pp. 106
Author(s):  
Bader A. Alyoubi

Big Data is gaining rapid popularity in e-commerce sector across the globe. There is a general consensus among experts that Saudi organisations are late in adopting new technologies. It is generally believed that the lack of research in latest technologies that are specific to Saudi Arabia that is culturally, socially, and economically different from the West, is one of the key factors for the delay in technology adoption in Saudi Arabia. Hence, to fill this gap to a certain extent and create awareness about Big Data technology, the primary goal of this research was to identify the impact of Big Data on e-commerce organisations in Saudi Arabia. Internet has changed the business environment of Saudi Arabia too. E-commerce is set for achieving new heights due to latest technological advancements. A qualitative research approach was used by conducting interviews with highly experienced professional to gather primary data. Using multiple sources of evidence, this research found out that traditional databases are not capable of handling massive data. Big Data is a promising technology that can be adopted by e-commerce companies in Saudi Arabia. Big Data’s predictive analytics will certainly help e-commerce companies to gain better insight of the consumer behaviour and thus offer customised products and services. The key finding of this research is that Big Data has a significant impact in e-commerce organisations in Saudi Arabia on various verticals like customer retention, inventory management, product customisation, and fraud detection.


Author(s):  
Muhammad Junaid ◽  
Shiraz Ali Wagan ◽  
Nawab Muhammad Faseeh Qureshi ◽  
Choon Sung Nam ◽  
Dong Ryeol Shin

2017 ◽  
Vol 93 (1) ◽  
pp. 79-95 ◽  
Author(s):  
Eric T. Bradlow ◽  
Manish Gangwar ◽  
Praveen Kopalle ◽  
Sudhir Voleti

2016 ◽  
Vol 67 (2) ◽  
pp. 227-236 ◽  
Author(s):  
Alexander T. Janke ◽  
Daniel L. Overbeek ◽  
Keith E. Kocher ◽  
Phillip D. Levy

2002 ◽  
Vol 30 (4) ◽  
pp. 365-377 ◽  
Author(s):  
Susan M. Land ◽  
Michele M. Dornisch

Recent interest in computer-supported collaborative learning (CSCL) has prompted educators to incorporate communication tools into their courses. This article reports findings of students' use of two Web-based discussion forums across two semesters to supplement face-to- face instruction. By tracking the discussions, we discovered that when students initiated reflection and integration of perspectives, they did so through concessions and oppositions to the postings of their peers. Findings point to the importance of explicit scaffolding of conversations to encourage student sharing and evaluation of perspectives.


2020 ◽  
Vol 10 (10) ◽  
pp. 26-29
Author(s):  
J. Festersen

Fast 350 Sprengungen an Geldautomaten gab es im Jahr 2019. Auch wenn die Täter ins Visier geraten, besteht weiterhin ein hohes Gefährdungs- und Schadenspotenzial, da die Angriffe überwiegend durch „reisende Täter“ verübt werden. Für mehr Sicherheit von 60.000 Bargeldautomaten sollen „Big Data & Predictive Analytics“ sorgen.


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