Author Bios:
Amy Ogan - Amy is a Postdoctoral Fellow at Carnegie Mellon University in the Human-Computer Interaction Institute.
Samantha Finkelstein - Samantha is a Doctoral Student in the Articulab in the Human-Computer Interaction Institute at Carnegie Mellon University.
Elijah Mayfield - Elijah is a Ph.D. student at Carnegie Mellon University at the Language Technologies Institute in the School of Computer Science.
Claudia D’Adamo - Claudia is a Psychology and Computer Science double major with an interest in Human Computer Interaction at Wheaton College and a research Assistant at Carnegie Mellon University.
Noboru Matsuda - Noboru is a professor at Carnegie Mellon University
Justine Cassell - Justine is the Charles M. Geschke Director of the Human-Computer Interaction Institute, in the School of Computer Science at Carnegie Mellon University.
Summary
The main focus of the paper was to gain insight on how peer teaching affects a child's learning of a subject. The researchers focused mainly on correlations between increased cognitive or meta-cognitive reflection moves, inside-system versus outside-system language, and increased social moves with the learning of children. This was tested using a system called SimStudent. SimStudent is basically designed to test a "think-aloud technique" of tutoring.
Stacy is a simulated student who was based on a Nintendo Wii character.
The study featured two sessions that were split between two days. 12 (2 girls and 10 boys) students between the 7th and 10th grade were studied for these sessions. Before beginning the first session, Stacy was programmed to know only basic operations. On the first day, they were asked to take a pre-test in algebra, then given study instructions, and finally tutored Stacy. These study instructions simply told the students to teach Stacy how to simplify linear equations. On the second day, the same students tutored Stacy immediately until she could pass 4 quizzes or until their time of 45 minutes expired. Finally, the students too apost-test in algebra and
were interviewed.
The inside-system versus outside-system language refers to using pronouns like "you" versus using pronouns such as "she". Researchers thought that participants would learn more when inside-system language was used. The inside system language insinuates that the participants have formed some sort of a bond with the system.
Related Work
Biswas, G., Bransford, J., Brophy, S., Katzlberger, T., Schwartz, D. (1999) Teachable agents: Combining insights from learning theory and computer science
Blair, K., Schwartz, D. (2007) Pedagogical agents for learning by teaching: Teachable agents
were interviewed.
The inside-system versus outside-system language refers to using pronouns like "you" versus using pronouns such as "she". Researchers thought that participants would learn more when inside-system language was used. The inside system language insinuates that the participants have formed some sort of a bond with the system.
Related Work
Biswas, G., Bransford, J., Brophy, S., Katzlberger, T., Schwartz, D. (1999) Teachable agents: Combining insights from learning theory and computer science
Blair, K., Schwartz, D. (2007) Pedagogical agents for learning by teaching: Teachable agents
Biswas, G., Bransford, J., Katzlberger, T., Schwartz, D. (2001) Extending Intelligent Learning Environments
with Teachable Agents to Enhance Learning
Biswas, G., Davis, J., Leelawong, K., Vye, N. (2002) The effects of feedback in supporting learning by teaching in a teachable agent environment
Chou, C., Chan, T., Lin, C. (2003) Redefining the learning companion: the past, present, and future of educational agents
Chase, C., Cheng, B., Chin, D., Dohmen, I., Oppezze, M., Schwartz, D. (2010) Preparing students for future learning with Teachable Agents
Pareto, L., Schwartz, D., Svensson, L. (2009) Learning by Guiding a Teachable Agent to
Play an Educational Game
Belynne, K., Biswas, G., Bodenheimer, B., Bransford, J., Davis, J., Leelawong, K., Vye, N. (2003) Intelligent user interface design for teachable agent systems
Biswas, G., Blair, K., Leelawoong, K., Schwartz, D. (2007) Animations of thought: Interactivity in the teachable agent paradigm
Biswas, G., Leelawang, K. (2008) Designing Learning by Teaching Agents: The Betty's Brain System
This is obviously not the most novel of concepts, but the approach to the study was a new one.
Evaluation
The evaluations completed on this system were both qualitative and quantitative. The scores on both the pre-tests and post-tests were recorded as well as the students interview answers and all of their remarks during tutoring sessions. The participants remarks were categorized and given numeric values based on these categories. These categories were as follows:
1. social: positive - hope, encouragement, excitement, or negative - threats, frustration
2. tutoring: examples, elaboration
3. alignment: based on pronoun use - inside-system - you, we, outside-system - she, it
4. cognitive: simple - "she understands", elaborated - "she doesn't understand distribution"
5. correctness: evaluating Stacy's knowledge as either correct or incorrect
These numeric values were used to create the following chart:
Discussion1. social: positive - hope, encouragement, excitement, or negative - threats, frustration
2. tutoring: examples, elaboration
3. alignment: based on pronoun use - inside-system - you, we, outside-system - she, it
4. cognitive: simple - "she understands", elaborated - "she doesn't understand distribution"
5. correctness: evaluating Stacy's knowledge as either correct or incorrect
These numeric values were used to create the following chart:
I found this to be an extremely interesting topic, because children and their learning at young ages is so often overlooked. Any new strides made in this area is welcomed. It is something that even I should keep in mind as I approach my studies from here.
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