Educational data mining is an emerging research field concerned with developing methods for exploring the unique types of data that come from educational context. These data allow the educational stakeholders to discover new, interesting and valuable knowledge about students. In this paper, we present a new user-friendly decision support tool for…

Web development is an important component in the curriculum of computer science and information systems areas. However, it is generally considered difficult to learn among students. In this study,we examined factors that could influence students' perceptions of accomplishment and enjoyment and their intention to learn in the web development…

Purpose: This paper presents a part of our research work that places an emphasis on Tracking Data Analysis and Visualization (TrAVis) tools, a web-based system, designed to enhance online tutoring and learning activities, supported by computer-mediated communication (CMC) tools. TrAVis is particularly dedicated to assist both tutors and students…

TIMSS measures trends in mathematics and science achievement at the fourth and eighth grades in participating countries around the world, while also monitoring curricular implementation and identifying promising instructional practices. Conducted on a regular 4-year cycle, TIMSS has assessed mathematics and science in 1995, 1999, 2003, 2007, and…

Knowledge discovery is a wide ranged process including data mining, which is used to find out meaningful and useful patterns in large amounts of data. In order to explore the factors having impact on the success of university students, knowledge discovery software, called MUSKUP, has been developed and tested on student data. In this system a…

This study focuses on the impact of wireless, mobile computing tools on student assessment outcomes. In a campus-wide wireless, mobile computing environment at an upper Midwest university, an empirical analysis is applied to understand the relationship between student performance and Tablet PC use. An experimental/control group comparison of…

Community colleges continue to experience growth in online courses. This growth reflects the need to increase the numbers of students who complete certificates or degrees. Retaining online students, not to mention assuring their success, is a challenge that must be addressed through practical institutional responses. By leveraging existing student…

The ability to predict a student's performance could be useful in a great number of different ways associated with university-level learning. In this paper, a grammar guided genetic programming algorithm, G3P-MI, has been applied to predict if the student will fail or pass a certain course and identifies activities to promote learning in a…

Earlier studies have suggested that higher education institutions could harness the predictive power of Learning Management System (LMS) data to develop reporting tools that identify at-risk students and allow for more timely pedagogical interventions. This paper confirms and extends this proposition by providing data from an international…