(^) Comparisons could then be made between different students, teachers, or instructional
strategies by using variables related to the types of statements.
It is important to note that this type of analysis is appealing because of its
quantitative nature. It allows for a factor analysis (ANOVA) of classroom behavior on
the part of the students and teachers. This method, however, is self-limiting. In a
summary of research on classroom observations, Delamont and Hamilton (1984, pp. 8-
10), gives seven reasons why the teacher-student interaction coding schemes are
inherently limiting. These warnings are appropriate to student-student schemes as well.
- The aim of coding schemes using prespecinormative data. ...the data produced tell the reader about 'average' or 'typical' classrooms, fied categories is to produce numerical and
teachers, and pupils. 2. Systematic observation schemes typically ignore the temporal and spatial context in
which the data are collected. Divorced from context in this way, the data collected may gloss over aspects relevant to their their social and temporal (or historical)
interpretation. 3. Prespecified coding system are usually concerned only with overt, observable
behaviour. They do not take directly into behind such behaviour. ...by concentrating on account the differing intentions that may lie surface features, interaction analysis runs
the risk of neglecting added] underlying but possibly more meaningful features. [emphasis - Prespecified coding systemmeasured. They may, however, obscure, dists are expressly concerned with what can be categorized or ort or ignore the qualitative features which
they claim to investigate by using crude boundaries between categories. measurement techniques or having ill-defined - Prespecified coding systems focus on smaglobal concepts. ll bits of action or behaviour rather than
- [These] category systems may assume the tr7. ...by placing arbitrary (and little understood) boundaries on continuous phenomena uth of what they claim to be explaining.
category systems may create an initial bias from which it is extremely difficult to escape.
Brown and Palinscar (1989) continually point out the necessity of the "fine-
grained" analysis to understand the process of cooperative learning. "Unfortunately, the
written reports, on the outcomes of Jigsaw [a specific cooperative learning method] leave
us somewhat in the dark about the learning process... A further look at Jigsaw and other