scholarly journals An Educational Data Mining Approach to Concept Map Construction for Web based Learning

2017 ◽  
Vol 21 (4/2017) ◽  
pp. 41-58 ◽  
Author(s):  
Anal ACHARYA ◽  
Devadatta SINHA
2015 ◽  
Vol 6 (2) ◽  
pp. 18-30 ◽  
Author(s):  
Marijana Zekić-Sušac ◽  
Adela Has

Abstract Background: Previous research has shown success of data mining methods in marketing. However, their integration in a knowledge management system is still not investigated enough. Objectives: The purpose of this paper is to suggest an integration of two data mining techniques: neural networks and association rules in marketing modeling that could serve as an input to knowledge management and produce better marketing decisions. Methods/Approach: Association rules and artificial neural networks are combined in a data mining component to discover patterns and customers’ profiles in frequent item purchases. The results of data mining are used in a web-based knowledge management component to trigger ideas for new marketing strategies. The model is tested by an experimental research. Results: The results show that the suggested model could be efficiently used to recognize patterns in shopping behaviour and generate new marketing strategies. Conclusions: The scientific contribution lies in proposing an integrative data mining approach that could present support to knowledge management. The research could be useful to marketing and retail managers in improving the process of their decision making, as well as to researchers in the area of marketing modelling. Future studies should include more samples and other data mining techniques in order to test the model generalization ability.


2018 ◽  
Vol 24 (3) ◽  
pp. 1872-1875 ◽  
Author(s):  
Mustafa Man ◽  
Wan Aezwani Wan Abu Bakar ◽  
Ily Amalina Ahmad Sabri

Data mining is the concept for extracting the appropriate data from the large set of database. In today’s world it is widely used for many applications where learning applications is one of the major part. The e-Learning is the booming technology where anyone can learn everything from any part of the world. It is the digital way of learning the concepts and does not require the help of other persons to do so. It also requires the large space for data storage such as user information, course records and course details and so on. There are lot of learning applications available on the internet among which some might be subjected to frauds. So the security is the demanding thing every users looking for to protect their details. The users also seek for flexibility of using the applications. In perspective of distributed world, the complexity and interoperability of the data brings challenges in e-learning domain.Depends upon learner’s choice, the web based learning modules were developed for the students. Thus, a holistic approach is required for achieving the personalized content since the student groups are heterogeneous in nature. In addition to, the personalized content has to be protected in order to maintain the data integrity and privacy of the users. In this work, we survey about the present scenario of the web-based e-learning systems. Initially, we present the services oriented architecture of the e-learning systems and also clearly explain the different elearning layers.Then, we portray the existing studies processed in web based e-learning systems. Finally, we discuss about the challenges still persists in web-based learning systems. This paper will guide the upcoming researchers in e-learning fields.


Author(s):  
Sabyasachi Pattnaik ◽  
Jui Pattnayak ◽  
Priyaranjan Dash

Data Mining and Data Warehousing are two most important techniques for pattern discovery and centralized data management in today’s technology. ELearning is one of the most significant applications of data mining. The main objective is to provide a proposal for a functional model and service architecture. The standards and system architecture are analyzed here. This paper gives importance to the integration of Web Services on the e-Learning application domain, because Web Service is the most advanced choice for distance education now. The process of e-Learning can be possible more effectively with the help of Web usage mining. More advanced tools are developed for online customer’s behaviour to increase sales, and profit, but no such tools are developed to understand learner’s behaviour in e-Learning. In this paper, some data mining techniques are discussed that could be used to enhance web-based learning environments.


2018 ◽  
Vol 27 (3S) ◽  
pp. 513-525 ◽  
Author(s):  
Bruno Elias Penteado ◽  
Paula Maria Pereira Paiva ◽  
Marina Morettin-Zupelari ◽  
Seiji Isotani ◽  
Deborah Viviane Ferrari

Purpose This article introduces concepts and a general taxonomy used by the educational data mining (EDM) community, as well as examples of their applications, with the aims of providing audiology educators with a referential basis for developing this area. Method A narrative review was carried out to present an overview of EDM and its main methods. Some of these methods were exemplified with analysis of real data from an Internet-based specialization course on pediatric auditory rehabilitation. Results The review introduced EDM main concepts and applications and described methods from its area. Real data examples illustrated EDM use to predict interpersonal help-seeking, model interpersonal interaction, analyze students' trajectories within a course's module, and understand how students approached group assignments. Some of the insights provided by EDM to support teaching and learning processes were also described. Conclusions EDM methods offer new tools to discover knowledge from digital traces (i.e., logs) and support key stakeholders (students, instructors, or course administrators) to raise awareness about course dynamics. This approach has the potential to foster a better understanding and management of educational processes in audiology distance education.


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