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MEDER 2013 : The Workshop on Mining Educational Data for effective Educational Resources (MEDER-2013) | |||||||||||||||
Link: http://amcs.co/daeng2013/page/special-session/meder-2013.php | |||||||||||||||
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Call For Papers | |||||||||||||||
The Workshop on Mining Educational Data for effective Educational Resources (MEDER-2013)
Description and Aim The rapid expansion of the web has had a big impact on different fields and particularly in education. Online learning is being common practice in different educational institutions. This way of learning is involved with two kinds of data sets: Educational Resources (ER) : data that students “consume” when interacting with the online environments Educational Data (ED): “traces” that students leave as they interact with the online learning environments. Confident that ED can teach us about learners’ behaviors and help us enhancing learning experience and particularly the process of the development, the design and the recommendation of ER, there has been a growing interest in the automatic analysis of such data. The main idea behind this is “Learning from students to build for students”. In this context, the workshop aims to provide a venue for scientific discourse to exchange opinions and ideas on how: Can the analysis of ED help for a better use of educational resources? How can we help authors better design educational resources based on the analysis of ED? Can we help instructors to develop their resources more effectively and efficiently? How can educational data mining help to detect anomalies in resources designed by instructors? Which types of analysis can be conducted on ED to impact on the development process of ER? Which concepts, approaches and algorithms are appropriate to benefit ER from ED? The workshop will bring together researchers and practitioners proposing innovative use of Educational Data to discuss, exchange and disseminate their work. Topics: List of topics includes but not limited to: Learning Analytics to enhance learning process Learning design recommendation systems Methods and approaches for Educational data analysis Characteristics of educational data Impact of educational data on the development of learning resources Data mining for predicting user interests Resources recommendation based on user behavior Important Dates Submission Deadline: July 30, 2013 Review Notification: August 30, 2013 Submission of Camera Ready Paper and Copyright: September 10, 2013 Authors Registration: September 10, 2013 Special Session/Conference: December 16-18, 2013 Paper Guidelines and Submission Submissions should be with respect to DaEng-2013 paper submission instruction HERE. All papers will be peer reviewed by at least two independent referees. Papers must be submitted electronically in PDF format via the EasyChair online submission page https://www.easychair.org/conferences/?conf=meder2013. Proceeding All accepted and registered papers of the workshop will be published in the special section of DaEng-2013 conference proceeding in the renowned Lecture Notes in Electrical Engineering of Springer Verlag (Approved). Workshop chairs Henda Chorfi, King Saud University, Saudi Arabia Hend Al-Khalifa, King Saud University, Saudi Arabia Muna Al-Razgan, King Saud University, Saudi Arabia The contact email address for the chairs: iwan@ksu.edu.sa Program Committee Member Demetrios Sampson, University of Piraeus & CERTH, Greece Mohamed Jemni, Research Laboratory LaTICE, University of Tunis Leila Jemni Ben Ayed, Laboratory LaTICE, University of Tunis Maha Al-Yahya, King Saud University, Saudi Arabia Muna Al-Razgan, King Saud University, Saudi Arabia Auhood Al-Faris, King Saud University, Saudi Arabia Shurug Al-Khalifa, King Saud University, Saudi Arabia Entisar Al-Mosallem, King Saud University, Saudi Arabia Ameera Al-Masoud, King Saud University, Saudi Arabia Reem Al-Qifary, King Saud University, Saudi Arabia Asma Al-Sumait, Kuwait university, Kuwait Nora Al-Rajebah, Southampton University, UK Ghada Ak-Hudhud, King Saud University, Saudi Arabia Amany Al-Shawi, King Abduliaziz City for science and technology (KACST), Saudi Arabia Sofien Gannouni, King Saud University, Saudi Arabia Belgacem Ben Youssef, King Saud University, Saudi Arabia |
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