American Educational Research Journal · 1994 · 109 citations · 41 references
EducationMathematics EducationTeachingClassroom AssessmentInstructional DesignMathematics InstructionFeedback GenerationPeer InteractionPeer LearningTeacher-student InteractionInteractional StyleStudent Explanations
The study examined how prior training and experience in peer tutoring affect student interaction patterns. Sixteen classrooms were randomly assigned to receive peer tutoring with or without prior training; teachers delivered a structured verbal rehearsal routine with step‑by‑step feedback on a math operations curriculum twice weekly for 10 weeks, pairing an average‑achieving student as tutor with a low‑achieving student as tutee, and sessions were videotaped and analyzed at micro, global, and transcript levels. Experienced dyads produced more interactional, principle‑based explanations, yet in both conditions explanations remained largely algorithmic rather than conceptual.
This study examined the effects of previous training and experience in peer tutoring on the nature of student interactions. Sixteen classrooms were assigned randomly to two treatments: with and without previous training and experience in peer tutoring. Peer-tutoring teachers taught students a structured, interactional, explanatory verbal rehearsal routine that incorporated step-by-step feedback. Peer tutoring was implemented on a mathematics operations curriculum twice weekly for 10 weeks. Each teacher had identified an average achiever and a low achiever to serve, respectively, as the tutor and the tutee during peer-tutoring generalization sessions. Videotapes were analyzed at three levels: microlevel quantifications, global ratings, and transcripts of representative dyads. Across levels of analysis and across operations and applications content, experienced dyads provided explanations in a more interactional style that incorporated sounder instructional principles. As revealed in the transcripts, however, the nature of student explanations in both conditions was primarily algorithmic rather than conceptual.
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