Ateneo Laboratory for the Learning Sciences Summer School
Ateneo Laboratory for the Learning Sciences Summer School
26-30 May 2014, 8:30 to 4:30Room CTC 112
Hosted by
Ateneo Laboratory for the Learning Sciences
Department of Information Systems and Computer Science
Ateneo de Manila University, Loyola Heights, Quezon City
In cooperation with
The Educational Data Mining Laboratory
Teachers College, Columbia University
New York, New York
Resource Speakers
Teachers College, Columbia University
Ma. Mercedes T. Rodrigo, Ph.D.
Ateneo de Manila University
The Ateneo Laboratory for the Learning Sciences (ALLS) is a research office that lies at the intersection of computer science and education. The Educational Data Mining Laboratory of Teachers College, Columbia University is headed by Dr. Ryan Baker, President of the International Educational Data Mining Society and Associate Editor of the Journal of Educational Data Mining. Both laboratories make use of statistical and data mining techniques to investigate behavioral and affective phenomena that mediate learning. These include in depth examinations of learning outcomes, prediction of STEM career choice, student help-seeking, carelessness, and conscientiousness as well as patterns of student confusion, frustration, and boredom.
The goal of the ALLS Summer School is to assist participants explore the quantitative analysis of student interactions with computer-based learning environments to derive insights about how students learn best. The Summer School will begin with a poster presentation in which participants will discuss their current work. The Summer School continues with an intensive five-day workshop that will familiarize participants with the data collection and analysis techniques that ALLS uses to conduct its research. Ample time will be provided for hands-on work. Each participant will be expected to produce a data analysis. The workshop ends with poster presentation in which resource people will critique student work and recommend ways in which the work may be extended.
The Summer School is open to current or prospective graduate students who wish to learn more about the learning sciences and its associated methods. The tentative schedule of activities is as follows:
|
Date |
Activities |
|
26 May, 2014 |
Introduction of participants |
|
27 May, 2014 |
Low-fidelity text replays annotation |
|
28 May, 2014 |
Educational data mining |
|
29 May, 2014 |
Educational data mining |
|
30 May, 2014 |
Poster preparation |
To apply, prospective participants must email a 2-3 PDF document (12-point Times New Roman
Font, 1 inch margins on all sides, double spaced) with the following information to Ma.
Mercedes T. Rodrigo (
This email address is being protected from spambots. You need JavaScript enabled to view it.
) by 31 March 2014:
1. Full name
2. Email address
3. Institution
4. Position
5. Highest degree earned or ongoing studies
6. Describe background in statistics and data mining. What statistics or data mining packages have you used? What techniques are already familiar to you?
7. If you are not currently enrolled in a graduate degree program, are you planning to enrol in graduate school? What is your time line? What specialization do you intend to pursue?
8. Why are you interested in attending the ALLS Summer School? How is it relevant to your current or future work? How do you see yourself applying what you learned? (The response to this question must be 500 to 600 words long.)
Successful applicants will be allowed to attend the Summer School free of charge. They will, however, be responsible for their own transportation, meals, and lodging. Current graduate students also have the option of officially registering for this course and taking it for credit as CS 214 User Modeling and User Profiling for Adaptive Systems.
Slots are limited, so please apply soon!
