The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
A Data Mining Service to Assist Instructors Involved in Virtual Education
|
|
Author(s): Marta E. Zorrilla (University of Cantabria, Spain)and Diego García (University of Cantabria, Spain)
Copyright: 2012
Pages: 22
Source title:
Business Intelligence Applications and the Web: Models, Systems and Technologies
Source Author(s)/Editor(s): Marta E. Zorrilla (University of Cantabria, Spain), Jose-Norberto Mazón (University of Alicante, Spain), Óscar Ferrández (University of Alicante, Spain), Irene Garrigós (University of Alicante, Spain), Florian Daniel (University of Trento, Italy)and Juan Trujillo (University of Alicante, Spain)
DOI: 10.4018/978-1-61350-038-5.ch010
Purchase
|
Abstract
In this chapter we present a BI application delivered as a service on-demand. In particular, it is a data mining service that aims to help instructors involved in distance education to discover their students’ behavior profiles and models about how they navigate and work in their virtual courses offered in Learning Content Management Systems such as Blackboard or Moodle. The main characteristic is that the users do not require data mining knowledge to use the service; they only have to send a data file according to one of the templates provided by the system and request the results. The service carries out the KDD process itself. Furthermore, the service provides an interface based on Web services, which can be called by external software. In short, the chapter talks about the necessity of a service with these characteristics and includes the description of its architecture and its method of operation as well as a discussion about some of the patterns it offers and how these provide instructors valuable knowledge to make decisions.
Related Content
|
Dina Darwish.
© 2024.
48 pages.
|
|
Dina Darwish.
© 2024.
51 pages.
|
|
Smrity Prasad, Kashvi Prawal.
© 2024.
19 pages.
|
|
Jignesh Patil, Sharmila Rathod.
© 2024.
17 pages.
|
|
Ganesh B. Regulwar, Ashish Mahalle, Raju Pawar, Swati K. Shamkuwar, Priti Roshan Kakde, Swati Tiwari.
© 2024.
23 pages.
|
|
Pranali Dhawas, Abhishek Dhore, Dhananjay Bhagat, Ritu Dorlikar Pawar, Ashwini Kukade, Kamlesh Kalbande.
© 2024.
24 pages.
|
|
Pranali Dhawas, Minakshi Ashok Ramteke, Aarti Thakur, Poonam Vijay Polshetwar, Ramadevi Vitthal Salunkhe, Dhananjay Bhagat.
© 2024.
26 pages.
|
|
|