(Page 3 of 7) - A Taxonomy of Generative Activity Design Supported by Next-Generation Classroom Networks authored by Stroup, Walter., Ares, Nancy. and Hurford, Andrew.

Using a pathways-and-endpoints representation, the form of generative activity shown in Figure 2 is barely, or

nominally, generative because the structure of the activity has an agreed upon endpoint and a single pathway to this
endpoint. An example would be asking students to simplify the expression 2x + 3x. The endpoint would be 5x and
the path to getting to this endpoint would be the application of a specific rule for simplifying.

One pathway:
apply rule for
simplifying

2x + 3x

endpoint
5x

Nominally Generative

Figure 2. Nominally generative activities have one pathway to get to a single endpoint.

The “space” created by nominally generative activity in a classroom is a discussion of “right” and “wrong” answers
and of how to correctly apply the given rule or procedure. Nominally generative activity accounts for much of
traditional, or pre-reform-based, classroom practice. As a design approach it is relatively ineffective in putting
students’ ideas at the center of classroom discourse and learning.

In our work with teachers we have sometimes talked about nominally generative activity as deriving from

approaches associated with one-on-one tutoring. Whatever the efficacy of asking questions like “What is 2x + 3x?”
is in the context of tutoring individuals, tutoring-type questions tend to “break” as they are pushed to scale beyond
one-on-one situations. In a classroom if we are asking one student the 2x + 3x question, other students are left with
little to do or to contribute and this kind of questioning makes nearly no use of the group itself. As the number
students moves from a few to a whole class, the limitations of tutoring-type questions becomes more profound; at
any given moment most of the students, of necessity, are not included in the core activity. Rather than critiquing the
usefulness of nominally generative questions group contexts, too often teachers simply use the technology of the
copy machine to compensate for and artificially scale to the group “tutor type” of questions. Individual copies of
nominally generative questions are handed to each student (or, similarly, written on the overhead projector or
chalkboard), and each student can now “participate” individually in answering the questions, but the group itself has
no constructive role. Moreover the teacher is still confronted with the task of figuring out what, if anything, to do
with all these worksheet responses.

Computer-assisted instruction (CAI) environments, supported by traditional forms of networking, have

attempted to address the issues related to teacher load but they do so in ways that preserve the limited focus on right
and wrong answers. In addition, network-supported CAI systems make no use of the group itself as a community of
inquiry and insight. “Individualized instruction” is somehow understood to mean the learning must take place
“alone” and the responses must be evaluated in terms of right and wrong. More recent “cognitive” tutoring
environments, while representing significant improvements over traditional CAI, still retain this very limited sense
of what individualized means and what it might represent as a purported ideal of instruction (cf., Carnegie Learning,
2003). Generative design, as supported by group-supportive networking, moves in a very different direction.
Individualization is associated with seeing the unique-ness and diversity of each student’s participation as making an
essential contribution to the emergent sense-making taking place in the classroom. Space-creating play (Stroup,
Ares, et. al, 2002; Stroup, Ares & Hurford, in press), not item-response convergence, is a central feature of
generative instructional designs.

4.2 Multiple Path, Agreed upon Endpoint