Walker A Peer Tutoring Addition
Collaborative Extensions to the Cognitive Tutor Algebra: A Peer Tutoring Addition
Erin Walker, Bruce M. McLaren, Nikol Rummel, and Ken Koedinger
Summary Tables
| PIs | Bruce McLaren, Nikol Rummel |
| Other Contributers |
|
Pre Study 1
| Study Start Date | 05/06 |
| Study End Date | 06/06 |
| LearnLab Site | CWCTC |
| LearnLab Course | Algebra |
| Number of Students | N = 14 |
| Average # of hours per participant | 3 hrs. |
Pre Study 2
| Study Start Date | 11/06 |
| Study End Date | 11/06 |
| LearnLab Site | CWCTC |
| LearnLab Course | Algebra |
| Number of Students | N = 20 |
| Average # of hours per participant | 3 hrs. |
Full Study
| Study Start Date | 04/07 |
| Study End Date | 04/07 |
| LearnLab Site | CWCTC |
| LearnLab Course | Algebra |
| Number of Students | N = 70 |
| Average # of hours per participant | 3 hrs. |
Abstract
In this project, the Algebra I Cognitive Tutor is extended to a collaborative learning environment: Instead of the computer tutoring a student, students tutor each other, and the cognitive tutor provides collaborative support. As research has shown, collaborative problem solving and learning has the potential to increase elaboration on the learning content. However, students are not always able to effectively meet the challenges of a collaborative setting. To ensure that students capitalize on collaborative problem solving with the Tutor, a peer tutoring collaboration script was developed that guides their interaction and prompts fruitful collaboration.
In the baseline version of the script (without cognitive tutor support), students in the same class are seated at different computers and take turs tutoring each other. First, they prepare to tutor by solving problems using the regular cognitive tutor. Then, they tutor each other by marking each other right and wrong, monitoring their partner's skills, and give each other hints and feedback. After preparing and tutoring, they reflect on the problems and their interaction, engaging in metacognitive activities. We have expanded the script to include intelligent cognitive support of the peer tutoring, and hope to ultimately expand it to include intelligent collaborative support.
To assess the effectiveness of the script on robust learning, we are conducting a series of in vivo experiments in the Algebra LearnLab. In an initial, small scale study (pre study) that served to establish basic effects and to test the procedure in a classroom setting, we compared peer tutoring with reflection elements to peer tutoring without reflection elements. In a second study that served to explore the effects of cognitive tutoring of peer tutoring, we compared peer tutoring plus cognitive tutoring to peer tutoring. In the full study, we will compare these collaborative conditions to an individual condition to assess the effect of the collaborative Tutor extension to regular Tutor use.
Background and Significance
In our project, we combined two different instructional methods both of which have been shown to improve students’ learning in mathematics: Learning with intelligent tutoring systems (Koedinger, Anderson, Hadley, & Mark, 1997) and collaborative problem solving (Berg, 1993). The Cognitive Tutor Algebra that was used in our study is a tutor for mathematics instruction at the high school level. Students learn with the Tutor during part of the regular classroom sessions. The Tutor's main features are immediate error feedback, the possibility to ask for a hint when encountering impasses, and knowledge tracing, i.e. the Tutor creates and updates a model of the student’s knowledge and selects new problems tailored to the student’s knowledge level. Although several studies have proven its effectiveness, students do not always benefit from learning with the Tutor. First, because the Tutor places emphasis on learning procedural problem solving skills, yet a deep understanding of underlying mathematical concepts is not necessarily achieved (Anderson, Corbett, Koedinger, & Pelletier, 1995). Second, students do not always make good use of the learning opportunities provided by the Cognitive Tutor (e.g. help abuse, see Aleven, McLaren, Roll, & Koedinger, 2004; gaming the system, Baker, Corbett, & Koedinger, 2004). So far, the Cognitive Tutor has been used in an individual learning setting only. However, as research on collaborative learning has shown, collaboration can yield elaboration of learning content (Teasley, 1995), thus this could be a promising approach to reduce the Tutor’s shortcomings. On the other hand, students are not always able to effectively meet the challenges of a collaborative setting (Rummel & Spada, 2005). Collaboration scripts have proven effective in helping people meet the challenges encountered when learning or working collaboratively (Kollar, Fischer, & Hesse, in press).
Combining collaborative activities with intelligent tutoring might combine the benefits of both approaches. Collaborative interaction could augment the effects of an existing ITS by adding deeper interaction, and intelligent tutoring support could improve the quality of student collaboration by providing guidance to students as they attempt to follow a collaboration script. One way to incorporate collaboration into an ITS is to place the intelligent tutoring system in the role of one of the collaborators and have a student interact with this agent. For example, Biswas, Schwartz, Leelawong, Vye, and the TAG-V (2005) have the student collaborate with an agent (“Betty”) in a peer tutoring scenario. The student teaches Betty about ecosystems with the help of a second mentoring agent (“Mr. Davis”), and it has been shown that a student who takes the role of a teacher in this system benefits more than a student who takes the role of a learner in a parallel traditional tutoring system. However, this system does not yet support natural language interaction between the agents involved, and therefore does not take full advantage of important collaborative interaction mechanisms that can increase learning. Another way to combine collaboration and tutoring is to use the ITS to structure and tutor the student collaboration, by connecting collaborative tools with ITS components (see Harrer, McLaren, Walker, Bollen, & Sewall, 2006), and developing a model of good and ineffective collaboration in order to provide on-line hints and feedback (see Soller, 2001). Most research into computer tutoring of the collaboration between two students is still in a preliminary stage.
We integrate collaborative learning with an ITS using a peer tutoring framework. Similar to Biswas et al. (2005), we put the student in the role of the tutor, and intend to have the cognitive elements of the tutoring supported by another agent. However, unlike Biswas et al., (2005), the teachable agent is a real student. Therefore, we have intelligent tutoring components monitoring and providing feedback on student collaboration in addition to student cognition, like Harrer et al. (2006). Our ultimate goal is to allow students to tutor each other through the interface of an ITS, supported by both cognitive and collaborative tutoring.
Glossary
Research question
Do instructional activities that involve three agents (a student, a peer tutor, and a computer tutor) increase robust learning compared to instructional activities that involve two agents (student and peer tutor, student and computer tutor)?
Independent variables
We vary the agents involved in the interaction. The condition where a student interacts with a peer tutor and computer tutor is considered the “peer + cognitive tutoring” condition. The condition where a student interacts only with a peer tutor is considered the “peer tutoring” condition. The condition where a student interacts only with a computer tutor is considered the “cognitive tutoring” condition.
Hypothesis
When students attempt to solve a problem with the help of both a peer tutor and cognitive tutor, they should show more robust learning than when they problem solve with the help of only one of the tutors. A student/cognitive tutor collaboration should produce similar levels of robust learning as a student/peer tutor collaboration, as long as the peer tutor is sufficiently prepared.
Dependent variables
- Near transfer, immediate: During training, student progress on training problems will be analyzed.
- Near transfer, retention: Students will be given a posttest immediately after the study on similar problems
- Acceleration of future learning: Student learning on future equation solving units will be measured.
Explanation
This study is part of the Interactive Communication cluster, and its hypothesis is a specialization of the IC cluster’s central hypothesis. We assume that the instruction is in or above the student’s ZPD. Here is what we expect to happen in the three conditions:
- In the peer tutoring condition, the peer tutor’s help should increase learning compared to a student learning with the cognitive tutor. However, the student may make too many errors and/or require too much communication with the second agent. The peer tutor may not be able to provide the student with the help he/she needs. Learning will not be optimized.
- In the cognitive+peer tutoring condition, the peer tutor’s help should provide the additional benefits of interactive communication, and the cognitive tutor’s help should ensure that both the student and the peer tutor get the problem solving assistance they need. The support of the cognitive tutor and interaction with the student will also increase the peer tutor’s learning.
The target path will have the students learning-by-doing and learning-by-teaching, with the help of the computer agent so students do not make too many errors or require too much communication.
Findings
A previous study involving only peer tutoring suggested that cognitive tutoring is indeed necessary so that problems are in the ZPD of the student and peer tutor. The current study will be completed in the fall.
Annotated bibliography
Walker, E., Rummel, N., McLaren, B. M. & Koedinger, K. R. (submitted). The Student Becomes the Master: Integrating Peer Tutoring with Cognitive Tutoring. Submitted to the conference on Computer Supported Collaborative Learning (CSCL-07). Rutgers University, July 16-21, 2007.
Walker, E., Koedinger, K., McLaren, B. M., & Rummel, N. (2006). Cognitive tutors as research platforms: Extending an established tutoring system for collaborative and metacognitive experimentation. Lecture Notes in Computer Science, Volume 4053/2006. Proceedings of the 8th International Conference on Intelligent Tutoring Systems (pp. 207-216). Berlin: Springer
Walker, E. (2005). Mutual peer tutoring: A collaborative addition to the Algebra-1 Cognitive Tutor. Paper presented at the 12th International Conference on Artificial Intelligence and Education (AIED-05, Young Researchers Track), July, 2005, Amsterdam, the Netherlands.
References
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Carmien, S., Kollar, I., Fischer, G. & Fischer, F. (2006). The interplay of internal and external scripts. In F. Fischer, I. Kollar, H. Mandl &, J. Haake, Scripting computer-supported communication of knowledge. Cognitive, computational, and educational perspectives (pp. 289-311). New York: Springer.
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Harrer, A., McLaren, B. M., Walker, E., Bollen, L., and Sewall, J. (2006). Creating Cognitive Tutors for Collaborative Learning: Steps Toward Realization. User Modeling and User-Adapted Interaction: The Journal of Personalization Research (UMUAI) (2006) 16: 175-209.
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