the complex classroom

seating arrangement, student homogeneity and student interaction affect how students learn

Classroom dynamics is not as simple as it may seem. The transfer of knowledge from teacher to students is intimately connected with the students' individual learning capabilities and prevailing classroom conditions. Effective educators know how to adjust the teaching strategies to account for these factors.

It has been shown that peer instruction can enhance learning rates for students in a class. Interaction between students provides a venue for healthy exchange of ideas without the imposing presence of the teacher. Dr. Eric Mazur, a Physics Professor at Harvard University realized this as he developed (in 1990) the Peer Instruction method of teaching, now adopted by successful educators around the world. The method is even more effective for handling large classes [1].

In the Philippine setting, classrooms are usually filled to the roof, especially in rural communities where there is shortage of teachers and teaching facilities. Moreover, students are usually grouped into sections based on their performance in the previous year: the brightest students are usually placed on a premier “star” section (section 1) and the rest are placed in sections of increasing numbers yet decreasing mean rating, and correspondingly, decreasing level of attention and concentration in terms of teaching and resources. These factors contribute to the continuing problem of primary and secondary education in the country. Peer instruction may prove to be a solution to these woes, but how effective really is it in the context of the real classroom, where students are grouped based on rank and seating is random?

The goal of the study conducted by Dr. C. Monterola, R. M. Roxas and S.L. Carreon-Monterola is to answer that question. In their paper published in the journal Complexity titled “Characterizing the Effect of Seating Arrangement on Classroom Learning Using Neural Networks,” they present results of actual classroom experiments coupled with neural network predictions [2].

Optimal seating arrangement

The perceived status of each student can be evaluated by the teacher either by grades in a previous course or by a pre-test, a short examination after a lecture and prior to student interactions. The scores of these tests may reveal who among the students remembered and understood the topics as discussed by the teacher. Of course, those who fared better are expected to play important roles in the peer instruction to follow – they will be the source of correct information to teach their other classmates.

The researchers tried to check if the spatial distribution of these students in class (i.e., where these brightest students are located in the classroom) will have a significant effect on the effectiveness of the peer instruction procedure. They measured the average increase in scores between the pre- and post-student interaction quizzes for different seating schemes: the brightest students are placed (1) randomly; (2) in the four corners; (3) in middle of the room; and (4) in an inner four corners.

Comparing the results for the following arrangements, they realized that marked improvement in class score is achieved when students are arranged such that the highest scorers are placed toward the outer four corners of the classroom. It is in this configuration that most low aptitude students get to interact with the high aptitude ones. In contrast, the paper describes that the “S[eating] A[rrangement] with high P[erceived] A[ptitude] L[evel] students concentrated at the center (less interaction opportunity for low PAL) has the lowest average” score gain. Neural network predictions generally agree with these experimental results.

The paper thus adds an important result to the Peer Instruction method of Mazur: the method will be more effective when applied to an optimal student arrangement that maximizes efficient transfer of information.

Groupings

There seems to be a basis for grouping students into sections of the same capabilities.

As for students with high aptitude levels, the paper straightforwardly says that “S[tudent] I[nteraction] O[pportunities] is deemed ineffective,” in the sense that bright students do not benefit that much. Whether it is because they already have high grades in the first place – or they are just stubborn – the paper doesn’t say.

On the other hand, students with low aptitude levels benefit more upon interaction with other students of comparable aptitude levels, the paper discusses. A significant increase in score gain is obtained after peer interaction between students of comparably lower aptitudes.

With this, it can be seen that the existing structure found in Philippine high schools can be considered to be optimized and thus may be utilized to further instruction and learning. That is, students from “lower” sections can be made to be competitive, by inclusion of peer instruction and student interaction in their curriculum.

Education research

Two of the authors form the education research subgroup of the Complex Systems Group, and their co-author is an educator herself from the College of Education in the same University.

Before being an Instructor in UP Diliman, R.M. Roxas served as a teacher in a university in her home province of Mindoro. Coming from a family of educators, this research is especially close to her heart.

C.P. Monterola and S.C. Monterola are a husband and wife team, both of whom are professors of the University. The former teaches Physics at the NIP and heads the Complex Systems Group, while the latter is considered to be one of the finest professors in the UP Integrated School, where she has handled the high school physics courses.■

1. E. Mazur. Peer Instruction: A User's Manual (Prentice Hall, 1997).
2. C. Monterola, R. Roxas, and S.L. Carreon-Monterola (2008). Characterizing the Effect of Seating Arrangement on Classroom Learning Using Neural Networks, Complexity (In press, doi:10.1002/cplx.20237).