Network analysis characterizing classroom dynamics and syntactic structure - Roxas, Ranzivelle Marianne L. (Quezon City College of Science, University of the Philippines, 2007)
A teaching framework patterned from Eric Mazur's Peer Instruction Method is developed to probe the transmission of information in a classroom composed of interacting students [1,2]. Based on actual experimentation, we demonstrate that a two layer neural network (NN) is capable of accurately characterizing the performance of interacting students in a class based on their seating location. The resulting complex adaptive dynamics suggests that the spreading of correct information can be optimized by imposing a strategic seating arrangement based on the perceived intelligence (1) level of each student. For instance, when students with high 1 are situated at the outer four corners of a classroom, the collective performance of the class after student interaction opportunities (SIO), fares better than in random, inner four or centered arrangements. The trained NN also predicts homogeneous-sectioned classes achieve better performance than heterogeneous-sectioned class during SIO. The results are expected to provide impetus on new instructional structures/formats that inherently incorporate student interactions during lectures.
Thesis (M.S. Physics)--University of the Philippines Diliman
Keywords: Communication -- Network analysis; Classroom management