MEDER 2013 - The Workshop on Mining Educational Data for effective Educational Resources (MEDER-2013)
Date2013-12-16 - 2013-12-18
Deadline2013-06-25
VenueKUALA LUMPUR , Malaysia
Keywords
Websitehttps://amcs.co/daeng2013
Topics/Call fo Papers
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
:
June 25, 2013
Review Notification
:
July 25, 2013
Submission of Camera Ready Paper and Copyright
:
August 10, 2013
Authors Registration
:
August 10, 2013
Special Session/Conference
:
December 16-18, 2013
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
:
June 25, 2013
Review Notification
:
July 25, 2013
Submission of Camera Ready Paper and Copyright
:
August 10, 2013
Authors Registration
:
August 10, 2013
Special Session/Conference
:
December 16-18, 2013
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Last modified: 2013-05-14 22:17:06