Data Mining - Concepts and Techniques.

A wide variety of media can be used in learning, including distance learning, such as print, lectures, conference sections, tutors, pictures, video, sound, and computers. Any one instance of distance learning will make choices among these media, perhaps using several.

Multimedia in Learning

The Origins of Intelligence in Children

research work deals with efficient data mining procedure for predicting the diabetes from medical records of patients. Diabetes is a very common disease these days in all populations and in all age groups. Diabetes contributes to heart disease, increases the risks of developing kidney disease, nerve damage, blood vessel damage and blindness. So mining the diabetes data in efficient manner is a critical issue. The Pima Indians Diabetes Data Set is used in this paper; which collects the information of patients with and without having diabetes. The modified J48 classifier is used to increase the accuracy rate of the data mining procedure. The data mining tool WEKA has been used as an API of MATLAB for generating the J-48 classifiers. Experimental results showed a significant improvement over the existing J-48 algorithm. KeywordsDecision Tree, MATLAB, Data Mining, Diabetes, WEKA.

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Improved J48 Classification Algorithm for the Prediction of Diabetes

Mobile marketing, also known as wireless marketing, promises vast opportunities. Still in an experimental phase, businesses have little experience using this new marketing tool. Mobile services offer companies powerful marketing potential via direct communication with consumers, anytime and anywhere, but little research on this subject exists. This paper discusses Short Message Services (SMS), which belong to the first and most successful forms of mobile data transmission. Based on a literature review and exploratory qualitative research, this paper defines mobile marketing, describes its most popular application, text messaging, introduces a conceptual model of success factors for implementing mobile marketing, and proposes future research avenues.

An Investigation and Conceptual Models of SMS Marketing

This paper validates effects of online self-assessment tests as a formative assessment strategy in one of the first year undergraduate courses. Achieved students' results such as test scores and pass rates are compared for three different generations for the same course but also judged against the exam results of other courses taught in the same semester. The analysis points out that there is a statistically significant difference between the groups for half-semester tests and exam pass rates after online self-assessment tests were introduced. Positive effects on students' success are approximated for the overall institution using a simulation model. Results point out that a small increase in pass rates could significantly impact the overall success i.e. decrease of dropout rates. Students' results from three different generations were compared.Inspecting effects of online self-assessment tests on students' success.Simulation model of course pass rates in higher education institution.

Online self-assessment and students' success in higher education institutions

Introduction In the context of the inclusive knowledge society, the role of system interfaces that are more closely tailored to the way people naturally work, live and acquire knowledge is unquestionably recognized as important. In addition, the need for active and accessible learning promotes only the e-learning that engages the users effectively. Nevertheless, despite so much publicity and activity, the progress in the field of e-learning has been relatively slow until recently, when problems were often associated with poor designed e-learning applications cf. (SIGCHI, 2001; Granic, 2008). It seems that too much of the research has been driven by technical possibilities, while paying inadequate attention to the area of application. This issue has been ignored for some time, in the hope that new technologies will somehow resolve the lack of real progress. However, to efficiently communicate the contents and improve the learning experience, interaction mechanisms merit particular consideration. Usability studies in the e-learning field are not very frequent despite the important role that usability plays in the success of every e-learning system. If the interface is not transparent and easy to use, the learners/students concentrate on interaction aspects and not on acquiring content. In addition, it has been claimed that usability assessment needs further consideration of the learning perspective. Namely, the approaches to e-learning usability range from those adapted to e-learning to those applying heuristics without special adjustment to the educational context. Accordingly, as an established set of heuristics and a joint evaluation methodology for e-learning systems do not exist yet, there is obviously a need for further research and empirical evaluation. The paper reports on a case study of an e-learning platform implemented in the network of fourteen European schools. The contribution of this paper is two-fold. First, it critically examines the usability of a large-scale e-learning system across several countries in Europe. The second contribution of the paper is providing some general findings and lessons learned from the experience. Usability testing, which integrated six empirical methods into a laboratory-based test, was complemented with heuristic inspections. Interface compliance with Nielsen's (1994) traditional principles was enhanced with experts' judgment of the system's "educational evaluation" by means of three sets of criteria: Learning with software heuristics (Squires & Preece, 1999), Educational design heuristics (Quinn, 1996) and Pedagogical dimensions (Reeves, 1994). We expect that this contribution with its general findings and know-how from the experience will facilitate the understanding on how to evaluate and improve the usability of e-learning systems based on users' (learners'/students' and teachers') and experts' feedback. Since there are limited studies in the field, this contribution adds to the body of knowledge. Related Work Research in the human-computer interaction (HCI) field has provided numerous principles and guidelines that can steer designers in making their decisions. Although applying good design guidelines alone is a good start, it is no substitute for system usability evaluation. In general, usability is context-dependent and is shaped by the interaction between users, tasks and system purpose. A variety of usability evaluation methods have been developed over the past few decades and most are grouped into usability test methods, user-based involving end-users, and inspection methods engaging HCI experts. Research studies involving different kinds of applications, different user groups and evaluation techniques have been conducted and the need for combining the methods is well understood in the usability field; see e.g., Sears & Jacko (2008). To analyze usability of interaction mechanisms of e-learning systems, more or less standard assessments and studies have been carried out. …

Usability Testing and Expert Inspections Complemented by Educational Evaluation: A Case Study of an e-Learning Platform

One of the indicators of potential problems in the higher education system may be a large number of student dropouts in the junior years. An analysis of the existing transaction data provides the information on students that will allow the definition of the key processes that have to be adapted in order to enhance the efficiency of studying. To understand better the problem of dropouts, the data are processed by the application of data mining methods: logistic regression, decision trees and neural networks. The models are built according to the SEMMA methodology and then compared to select the one which best predicts the student dropout. This paper concentrates primarily to the application of the data mining method in area of higher education, in which such methods have not been applied yet. In addition, a model, useful for strategic planning of additional mechanisms to improve the efficiency of studying, is also suggested.

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Student Dropout Analysis with Application of Data Mining Methods

The concept of personas that represent the key audience segments of a service, product, site, or a brand has been widely used in marketing. As of lately, personas are often used in digital services design and development. However, there are some frequent errors and issues that designers and developers come across in the process of developing realistic personas. Namely, personas are sometimes developed based on irrelevant data (e.g. statistically insignificant dataset), or have been developed based on assumptions, inadequate analyses or, most often — intuitively. Another issue is that once created, personas cannot be easily updated. There is great potential in using big data technologies to tackle these issues since it enables analyses of large amounts of data to gain insights into real user behavior patterns that lead to better business decisions. This paper explores the possibilities for developing data-driven web personas based on real user-data with the aim to save time in comparison with current data collection methods and also to enable easier updates. The preliminary study is presented using a dataset from an e-business site. The research results highlight the great potential of developing data-driven web personas based entirely on interactions between real users and a webshop, but also a number of identified issues in the process.

The potential and issues in data-driven development of web personas

The paper elaborates on the design of an empirically tested pedagogical framework for e-Learning, covering pedagogies which underpin the subject matter in everyday learning environment as well as the ways in which learning material is delivered and assessed. Designed framework presents an essential part of UNITE e-Learning system conceptualization and development. Five-component pedagogical framework which, by means of its constituents, drives and guides the creation of e-Learning scenarios is presented. An insight to the framework implementation is offered as well.

Maja Ćukušić

Papers

Online self-assessment and students' success in higher education institutions

Usability Testing and Expert Inspections Complemented by Educational Evaluation: A Case Study of an e-Learning Platform

Student Dropout Analysis with Application of Data Mining Methods

The potential and issues in data-driven development of web personas

An Approach to the Design of Pedagogical Framework for e-Learning