"The effectiveness of intelligent tutoring systems at increasing learning might be improved if the systems were combined with collaborative activities that encouraged conceptual elaboration. We extended the Cognitive Tutor Algebra, an intelligent tutoring system for high-school mathematics, with a peer tutoring activity that was designed to encourage interaction, reflection, and accountability. Two types of domain support were provided: adaptive support, which used the intelligent tutor domain models to provide feedback to the peer tutor, and fixed support, which simply consisted of answers to the problems. We compared the two peer tutoring conditions (adaptive or fixed support) to individual use of the cognitive tutor (without peer-tutoring activities). Even though students in the individual condition solved more problems during instruction, we did not find significant differences between the individual and collaborative conditions on learning. However, we found a correlation between tutee impasses and tutor learning."
Walker E., Rummel N., Koedinger K.R. (2008) To Tutor the Tutor: Adaptive Domain Support for Peer Tutoring. In: Woolf B.P., Aïmeur E., Nkambou R., Lajoie S. (eds) Intelligent Tutoring Systems. ITS 2008. Lecture Notes in Computer Science, vol 5091. Springer, Berlin, Heidelberg
1. SUMMARY
The paper discusses the need for adaptive meta-tutor in a peer-tutoring process. The raised problems involve fixed one-size-fit-all scripts that are too restrictive in some scenarios; adaptive feedback based on machine learning techniques that may be disruptive to dyadic interactions; and finally, human-taught intelligent agents that cannot communicate with students naturally.
The paper proposed a new approach - students tutoring each other with the helps of a meta-tutor - and measure its performance against other methods of (1) adaptive collaboration/tutor scripting and (2) individual use of CTA software. The results show equal great performance among the paper proposed method and individual use of CTA. However, the paper believes the meta-tutor still has a great potential since the method was able to achieve the same results with lesser problems solved.
2. STRENGTHS
The paper’s approach is very interesting - improving conceptual elaboration through aided tutoring, with helps from an adaptive meta-tutor. The results also suggested interesting directions for future research regarding impasses, correlations between post-test results and long-term retention of knowledge, impacts of human interactions on learning, etc.
3. WEAKNESSES
The paper could have explained in more details as of why the pool of 64 students was enough for the experiment.
