Pattern discovery in UTM library circulation database

Huge databases are being used in organizations to store data. These databases contain hidden patterns which can be discovered and used in the organizations. In this project, we applied data mining techniques to uncover the patterns in the circulation database of UTM library. In order to discover worthwhile patterns we followed knowledge discovery process (KDD) to transform row data to suitable format. Weka machine learning software was applied to do the data mining task. In this project, we studied two association rules mining algorithms, Apriori and FPGrowth. The later was used to discover some patterns among borrowed books. These patterns which are presented in a list can be used to make recommendations to patrons who are searching for a certain topic based on items that previously were borrowed together. In addition, a novel rule matrix was presented to store the found rules for future use. Both the list for recommendation and rule matrix are useful to construct a recommender system for users of UTM library

A naive recommendation model for large databases

It is difficult for users to find items as the number of choices increase and they become overwhelmed with high volume of data. In order to avoid them from bewilderment, a recommender could be applied to find more related items in shorter time. In this paper, we proposed a naive recommender model which uses Association Rules Mining technique to generate two item sets enabling to find all existing rules for a certain item and has the capability to search on demand which decrease the response time dramatically This model mines transactions’ database to discover the existing rules among items and stores them in a sparse matrix. It also searches the matrix by means of a naive algorithm to generate a search list.We have applied and evaluated our model in Universiti Teknologi Malaysia and the results reflect a high level of accuracy

Application of self organizing map for knowledge discovery based in higher education data

This paper focuses on knowledge discovery among attributes of Iran Higher Education Institute using self organizing map (SOM); the key problem with massive volume of data is extracting knowledge and patterns that are hidden in data. Managerial needs to explore this data for the purpose of decision making and strategy making reveals its importance. Furthermore it can be useful for researchers that study and research about higher education. Meanwhile planning for higher education has significant impact on developing of one society, successful planning needs to analysis some huge and historical data that is available in higher education institutes. SOM is a particular type of neural network used in clustering and helps discover patterns and relations without advanced knowledge about them. The steps of this approach can be discussed under five headings, which are (i) Data Preparation (ii) Data Loading, (iii) Initializing, (iv) Map training and (v) Interpretation of the results. The target dataset contains data of five universities located in Tehran, Iran affiliated to Medical Ministry of Iran and the most important attributes are program of study, learning style, study mode and degree. Results show that the number of enrolling students for Tehran medical university has decreased for the past 23 years from 1988 to 2005. This study also finds that Tehran University of Medical Science covers the majority of high degrees like MDdisplay(Doctor of Medicine) and PhD. The findings of this study can be used in improving of higher education decision making systems and the results of this study indicate SOM toolbox utility in similar institutes to knowledge discovery in a visualizing way

A cloud-based teaching framework: an introduction

One of the most significant discussions in education and information technology is cloud computing. Over the past six years, researchers have shown an increased interest in cloud computing for educational contexts. However, these rapid changes in information technology have a serious effect on teaching frameworks. Concerns have been raised about how cloud computing can be integrated with teaching frameworks and if it can improve teaching. In this paper, the Danielson Teaching Framework, which focuses on key aspects of teaching, was used. This framework has divided complex teaching activities into components such as communicating with students, students engagement and others which all might be improved by cloud computing; using cloud computing has capability to enhance performance of teaching. This paper seeks to address the domains of teaching frameworks and introduce an initial version of a cloud–based teaching framework that considers cloud computing can provides insight to future research on teaching frameworks

The impact of ICT on reinforcing citizens' role in government decision making

In this paper, we discuss the role of ICT and social media on democratic activities. Some overview of political systems are presented to show its impact on governments’ decision making. At the end of research we suggest some recommendations to enhance the quality of online democratic activities

Individual characteristics and hacking, piracy, online gambling and pornography use among students: a study in Malaysia

In this study, 441 Universiti Teknologi Malaysia students participated as respondents. Through a questionnaire respondents were asked how frequently they engage in specific behaviors, including hacking, using pirated software, music and movies in addition to use of gambling and pornography sites. The aim was to investigate which individual characteristics including age, gender, religion, citizenship, level of education, ego strength and locus of control are among determinants of these behaviors. The results of these questions were used to report the ratio of frequent users of these materials based on different categories. Logistic regression was used to see what the influential factors in the investigated behaviors are. The results suggest that males are more engaged with almost all of the investigated behaviors. In addition, citizenship, ego strength, age and religion reflected a statistically significant difference among people in certain activities. Level of education and locus of control did not reflect any significance in engaging in aforementioned behaviors

Exploring MOOC from education and information systems perspectives: a short literature review

Massive Open Online Courses (MOOCs) have gained significance as a new paradigm in education. MOOCs are open to any interested person and provide education products for a scalable number of learners who have access to the Internet. In recent years, there has been an increasing interest in MOOCs including their types, theories and challenges. Although this is an important and challenging field for Information Systems researchers, a rich and structural literature review has not yet been conducted in this area. The purpose of this article is to present a short review of recent research into MOOCs. Thirty-two papers were selected for review through four search engines with a search of key terms related to MOOCs. On the basis of this review, a holistic definition on MOOCs is presented and an overview of the relevant theories and issues is provide

A NETNOGRAPHY STUDY OF MOOC COMMUNITY

Massive online open courses (MOOC) are one of the widely used groups of online education and have been thought of as a key factor in future education. In recent years, there has been an increasing interest in MOOC from education and information systems researchers. In this paper, the aim is to observe MOOC in their natural setting to examine a particular community of MOOC by drawing on the concepts of communities of practice as a theoretical lens. One of the most significant current discussions on MOOC is Coursera. Questions have been raised about the structure of an emergent type of community within MOOC. However, far too little attention has been paid to study community of practice in this type of online education. The authors conducted an online ethnographic study on a sample of discussion forums of Coursera. Discussions were qualitatively content analyzed in order to understand the structure of an emergent type of community within MOOC. Our findings suggest that cohesion in a MOOC community is brought about by the domain of doubts, questions, new knowledge, experiences and the community of learners who meet people around the world with similar interests; the practices of documents, information, ideas, stories, experiences and software sharing. The combination of forces for MOOC community are global, free and online education identity of community which provides great materials, top professors, mass participation and certificates from top universities; voting system for warrant; movement of new comers from peripheral to the core of community by contributing more in discussions

A NETNOGRAPHY STUDY OF MOOC COMMUNITY

Abstract Massive online open courses (MOOC