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A new page has been made for the Learning Sciences and Technologies PhD program. This page below is old.
The Computer Science Department at Worcester Polytechnic Institute is looking to recruit graduate students in the area of Learning Science and Technologies to its PhD and Computer Science programs as well as a newly established graduate program in Learning Science and Technologies. These areas are interdisciplinary in cognitive science, cognitive psychology and psychometrics (the study and measuring of the human potential).
Here is a brochure for the PhD program.
Here is a video.
Here is a brochure .
Contents |
General Overview
Graduate Research Assistantships are available for students interested in working on Intelligent Tutoring Systems Research and examining how they are used in real school settings. If you have a background in Computer Science, Cognitive Psychology or Statistics this position is for YOU!
Research will be done using the ASSISTment System. The research goal of the ASSISTment Project is to provide a way to give web-based intelligent tutoring to middle and high school students in mathematics and science and is a joint collaboration between Worcester Polytechnic Institute (WPI) and Carnegie Mellon University (CMU). The ASSISTment System is currently being used by over 3,000 7th and 8th graders in the Worcester Public Schools system as well as schools near Worcester and Pittsburgh. WPI and CMU provide this service free while conducting interesting research on what makes for effective intelligent tutoring. For more information see http://www.wpi.edu/research/discovery/ and on the left scroll down to Intelligent Tutoring Systems that Teach and Assess.
See also A Day in the Life of a GK12 Fellow and TV News Spot
Types of Research Conducted
The types of research we do includes:
- Cognitive research to determine the most effective ways for tutoring students. For example, Leena Razzaq’s work has shown that we can maximize students’ learning by first recognizing their level of background knowledge; higher performing students learn more from explanations while students with less math background learn more from our intensive tutoring techniques. More detail can be found in her paper: Razzaq, L., Heffernan, N. T., Lindeman, R. W. What level of tutor feedback is best? In Luckin & Koedinger (Eds.) Proceedings of the 13th Conference on Artificial Intelligence in Education. IOS Press. 2007. (pdf)
- Educational data mining: We examine millions of students’ actions for patterns. Educational data mining is to education what bio-informatics is to biology. See EducationalDatamining.org for more information. For sample publications on educational data mining with the ASSISTment System see Zach Pardos’ use of Bayesian networks to see if fine-grained skill models can more accurately predict students’ state test performance. Pardos, Z. A., Heffernan, N. T., Anderson, B., & Heffernan C. Using Fine-Grained Skill Models to Fit Student Performance with Bayesian Networks. Workshop in Educational Data Mining held at the 8th International Conference on Intelligent Tutoring Systems. 2006. (pdf)
- Creating innovative education applications: We are building systems to email parents and track students’ effort levels. See Jason Walonoski’s paper: Walonoski, J., Heffernan, N.T. Detection and Analysis of Off-Task Gaming Behavior in Intelligent Tutoring Systems. In Ikeda, Ashley & Chan (Eds.). Proceedings of the 8th International Conference on Intelligent Tutoring Systems. Springer-Verlag: Berlin. pp. 382-391. 2006. (pdf)
- Creating new types of tutors that are smarter and track students' knowledge of the scientific method. A recent NSF grant and a US Dept of Ed Grant, will allows us to build tutoring system to tutor scientific inquiry. point to Science ASSISTMENT page
- Scaling up intelligent tutoring systems to work for millions of students and teachers.
Affiliated Faculty
Affiliated Faculty at Worcester Polytechnic Institute:
- Neil Heffernan: Intelligent Tutoring Systems (Director of PIMSE)
- Janice Gobert: Cognitive Psychology (Program Committee)
- Joseph Beck: Educational Data Mining
- George Heinemann: Software Engineering
- Ryung Kim: Statistics (Math Department)
- Rob Lindeman: Human Computer Interaction
- Murali Mani: Databases
- Gary Pollice: Software Engineering
- Charles Rich: Intelligent user interfaces
- Carolina Ruiz: Data Mining
- Elke Rundensteiner: Databases
- John Goulet: Mathematics. Directs the | of Mathematics for Educators program
Faculty at Carnegie Mellon University associated with the ASSISTment Project:
- Ken Koedinger (HCII)
- Brian Junker (Stats)
To Apply
- Apply to the computer science department's graduate program and mention in your cover letter and research statement your interest in intelligent tutoring systems. WPI-CS.
- You might also want to apply to the PIMSE project. This National Science Foundation (NSF) GK12 grant funds five Computer Science graduate students for up to five years with stipends of $30,000 per year and a full tuition waiver. For the GK12 Application GK12-Graduate-Student-Application. Unfortunately, it only for US residents.
- If you not applying for the PIMSE program, please inform Prof Heffernan's team of your interest by email gk12@cs.wpi.edu. Send a short description about why this RA is a good match for your background and interests. To make the application process easier, include copies of whatever materials you sent (or will send) to apply for a graduate degree in Computer Science at WPI.
We will use a rolling admission program and accept students as quickly as possible.
Principal Investigator
Neil Heffernan
This page was created by Christina Heffernan
