We have two positions available for undergraduate interns for the summer of 2011 supported by National Science Foundation, Research Experience for Undergraduate (contingent on funding)
Title: Learning by Teaching a Synthetic Student -- A study of the effect of tutor learning using SimStudent as a teachable agent
Project Description: The primary purpose of the current SimStudent project (www.SimStudent.org) is to study cognitive and social theories on the effect of tutor learning -- a well-known effect that students learn when they teach their peers. To study how and when the effect of tutor learning happens, we are building an on-line game-like learning environment where students learn how to solve algebra equations by teaching a live computer agent, i.e., SimStudent.
The SimStudent architecture and the proposed learning environment provide a rich study environment where we can conduct a various controlled studies to explore the cognitive and social factors on the effect of tutor learning. There would also be opportunities to explore issues in machine learning such that improving SimStudent’s learning mechanism, or issues in human-computer interaction such like interactions between student’s and SimStudent. For potential summer intern projects, we will provide each individual intern an independent research project based on his/her interest and experience. There are a number of potential projects that would be suitable for a summer intern projects as listed below (not exclusive).
(1) Educational Data-mining Study – How do students learn by teaching? We already have data collected from the classroom study conducted in Spring 2010 (the baseline evaluation study where we compared the effectiveness of learning by teaching SimStudent and learning with commercially available Cognitive Tutor) as well as the Winter 2010 study (the self-explanation study mentioned above). These data sets contain fine-grained students’ activity log as well as their test scores. Using these data, a primary goal of a potential REU project would be to explore cognitive and social factors that mediate the tutor learning. The knowledge and experience in advanced statistical analysis and/or a data-mining technique would be required.
(2) Usability Study – What makes the Learning-by-Teaching environment user-friendlier and hence facilitate the tutor learning more? From the human-computer interaction point of view, the improvement of the systems’ usability is an essential key for the success in accomplishing our research agenda. In this line of research project, the REU student intern will apply various HCI methods to evaluate the system’s usability and explore the key HCI factors to maximize the tutor learning. The knowledge and experience in HCI methods would be required.
(3) Prior Knowledge Study – How does the “individual” differences of SimStudent (i.e., the tutee) affect the student’s (i.e., the tutor’s) learning? By manipulating the background knowledge of SimStudent, we can control the speed and accuracy of SimStudent’s learning. For example, SimStudent may start with a certain amount of knowledge for equation solving, or SimStudent might have immature or even irrelevant background knowledge that slows down learning rate and causes more errors. The goal of an REU project would then to study how such differences affect the tutor learning.
(4) Pedagogical Agent Study – How would the appearance of SimStudent and its functionality affect the tutor learning? What if SimStudent has emotion and expresses its affective status? Can SimStudent share its affects with the student and if so how such a sympathetic pedagogical agent would influence the tutor learning?
(5) Emotional Pedagogical Agent Study – How could we improve interaction between SimStudent and the students? So far, SimStudent only learns from the steps demonstrated. It would be more natural and (perhaps) pedagogically more appropriate if the student (the tutor) could give a hint with his/her own everyday language (e.g., “you can subtract the same number from both sides”). Such a natural language input could be used as a heuristic to navigate the search for induction. The goal of the REU project here is to study a rich tutoring dialogue by implementing and testing an augmented dialogue facility in the learning-by-teaching environment.
(6) Machine-Learning Study – Can we improve the SimStudent’s learning algorithm? So far, we used inductive logic programming that is basically implemented as a brute forth search. We also use FOIL (Quinlan, 1990), which learns Horn Clauses from relations provided in examples. There are pros and cons for the current implementation (mostly the issues for domain generality and knowledge representation). The REU on this project would study alternative technologies to enhance the generality and efficiency of SimStudent’s learning.
Duration: 10 weeks in any time from June 1 to August 31
Eligibility: The applicants must be undergraduate students and U.S. citizens (or U.S. permanent resident).
Contact: Noboru Matsuda <Noboru.Matsuda@cs.cmu.edu>
Human Computer Interaction Institute
Carnegie Mellon University
5000 Forbes Ave. Pittsburgh, PA 15213
Voice: 412-268-2357 Fax: 412-268-9433