"Now what I have in mind is more a breadth of phenomenology than a depth."

Tom cited this quote as somewhat reductionist in nature, and voiced the opinion that diSessa's actual treatment of the material seems to contradict the statement. The very dense reading gave Tom the impression that it was extremely detailed, and very deeply structured. This led us into a discussion about Andy diSessa's motives as a cognitive scientist and technological educator.

Mark stated the diSessa, being a cognitive scientist first and foremost, is concerned with the way learning happens. He would like to understand the long-term and far-ranging processes involved with a learner's cognition, rather than collecting painstakingly detailed data about the small aspects that make up these larger processes. But, Mark points out, one should not read diSessa and mistake the very focused nature of his writing for a great depth of detail. diSessa researches by long-term observation, and draws inferences about the process; he doesn't claim that this mode of observations yields much quantifiable data about discrete phenomena.

Mark illustrated diSessa's ideas by discussing the Dyna-Turtle, (left) the original micro-world that diSessa created in Logo. A microworld is a world in which you remove all extraneous factors in order to look at a specific process. With the Dyna-Turtle, they sought to create a world uninhibited by the factors of the natural world (gravity, friction) that could illustrate some laws of Newtonian physics. The goal was to get the triangle Turtle, in a constant forward motion (path 1) into a box that was stationed perpendicular to the path of the turtle. What diSessa found was that those tested -- even physics graduate students -- often fell back on Aristotelian notions of physics to predict path that the turtle would take. The subjects incorrectly assumed that if they kicked the turtle when it was directly across from the box, that it would follow path 2. Of course, the forward momentum dictated that the turtle would actually follow a path diagonal to the box (path 3.) From data like this, diSessa draws large-scale inferences about such things as internalization of knowledge, rather than claiming specific knowledge about a particular phenomenon.