Jim Slotta, Ontario Institute for Studies in Education, University of Toronto
After an undergraduate, and some graduate training in physics, I moved to graduate studies in cognitive psychology at The University of Massachusetts, Amherst, where I did a research thesis on robotics and movement control. That prompted me to leave graduate school and I became a computer programmer at IBM Corp in 1989. That prompted me to go back to graduate school, which I did in 1990, to obtain a PhD with Professor Micki Chi at the University of Pittsburgh. I was motivated by Chi's earlier work in the study of physics misconceptions, and quickly took up the empirical effort to provide support for her (at that time) current theoretical efforts.
The topic of my doctoral research was concerned with the "persistent" nature of physics misconceptions: why are they so resistant to instruction. McClosky (1983), Driver and Erickson (1983) and many others had been remarking at the incredibly durable state of students' "alternative conceptualizations" of topics such as force, light, heat, and electric current. We began with a major review of all the literature relating to students conceptualizations of these topics (Reiner, Slotta, Chi and Resnick, 2000), and articulated something that was more or less clear, but perhaps had never been stated explicitly before: That physics novices appear to form a strong bias toward "matrerialistic" or "substance-based" conceptualizations of such topics. Perhaps this is because of biases in the language with which they first encounter the ideas as children (ie, "shut the door, you're letting all the heat out;" "throw some more light on it;" etc.).
Building on psychological notions of the categorical nature of concepts (e.g., Rosch, Murphy and Medin, Smith), and in particular on the notion that children form their conceptual categories based on "ontological attributions" Keil (1981, 1987, 1989), Chi made an important observation: that scientific conceptualizations. Ontological attributes are those of the most fundamental kind. When a child or a science novice encounters an unfamiliar term like "omentum" (the linning of the stomach), he or she looks for clues to try to understand it, and (following the concepts-as-categories literature) makes a categorization decision in order to "inherit" a bunch of helpful attributes. If the language treat omentum as a substance or a process or an attribute, the learner will commit to that ontology. Chi (1992; 2005) observed that, in the scientific theory, topics like heat and electric current are actually of the ontology "constraint-based interactions" or "emergent processes." BUt they are often talked about and reasoned about as direct processes, or even as substances themselves. This leads physics novices to make an ontological attribution error, committing to a substance-based ontology for these topics, and then having great difficulties with any subsequent instruction that tries to convey the emergent process view.
Note - most complex systems in science will include concepts of the emergent process ontology. So - this essay is potentially quite relevant to any learning of complex systems.
Part of the problem is that science novices simply do not HAVE the ontological category of emergent processes. There are no prior exemplars, and no way for the novice to abstract that category or ontology. SO its not possible for them to identify new concepts as having that ontology, because they don't even possess the ontological category. Slotta and Chi (1996; 2006) demonstrated empirical evidence for this hypothesis (my dissertation). We first demonstrated that physics novices do not speak about electric current as an emergent process (the statistical migration of electric charge alone a conducting medium in the presence of an electric field). We did this by "trapping" them into characteristic patterns of misconceptions in qualitative problems, as well as asking them to explain their choices of answers to those problems (always in the "substance-based language). Then, we provided them with a strong dose of "ontology training" - hitting them over the head with intensive treatment where they learned all about what a constraint-based interaction was (boring...!) - with animated examples of predatory-prey relations, the ideal gas law, and various other unrelated topics. A control group got a balanced task with no treatment of the relevant ontology. THEN we gave both groups some physics training in the topic of electric current. Low and behold, we found that the experimental group - who had been dosed up with the target ontology - was now able to make that attribution. They were able to learn that ontological aspect of electric current. And their choices to the qualitative physics problems changed. And their way of talking about those problems changed.
That work was done in 1993-5, published in proceedings of Cognitive Science (Slotta and Chi, 1996), and not appearing as a journal article until 2006, in Cognition and Instruction (Slotta and Chi, 2006 - sorry - long story!). Since 1996, the ontological attribution hypothesis has been researched by CHi and her colleagues, with several empirical and theoretical papers (see Chi, 2005 - major paper in Journal of the Learning Sciences). In 2005, I was invited to be part of an engineering education grant proposal to NSF, led by Prof. Ron Miller at Colorado School of Mines. They had read drafts-in-preparation of the Slotta and Chi paper, and were convinced that it was for EXACTLY such reasons that their undergraduates were having difficulties learning tropics of thermodynamics and fluid mechanics (because of they had made "classical commitments" to those topics. We began, essentially, a replication of my dissertation, with an ontology training for engineering undergraduates, and then some science instruction, with the aim of seeing if there was any improvement in their understanding of thermal transfer and microfluidics. This seems to be working - see the attached paper for a 2010 conference of the American Society for Engineering Education.
Since leaving Pittsburgh in 1995, I have moved into the field of education, although I maintain a perspective of cognitive psychology. I spent 10 years working in the University of California, Berkeley school of education, leading research projects in the use of technology for learning and instruction. This gave me a wealth of understanding about the "real world" of teachers, students, curriculum, etc. It also changed the way that I think about learning and instruction - now much less mechanistically (hmmm... maybe learning itself is an emergent process, and not so mechanistic like: "first establish the correct ontology, then they will learn better..."). One of the important technologies we developed in Berkeley was called WISE - the Web-based Inquiry Science Environment (Slotta and Linn, 2000; Slotta, 2004; and a recent comprehensive book: Slotta and Linn, 2009). This was a Web-based learning environment whose goal was to introduce inquiry science projects to a wired classroom. Using WISE, the teacher is free to walk around the room, interacting deeply with students as they engage with carefully designed inquiry materials. This allows the teacher to learn about what the students are thinking (as opposed to lecture, for example). WISE also allowed us to conduct a substantive research program concerning the design of such activities, particularly in the use of complex visualizations and simulations in science (including complex systems). In 2003, we won a major NSF center, called "Technology Enhanced Learning in Science" (see http://telscenter.org) - which sought to develop a wealth of new curriculum, assessments, and a new generation of technologies.
In 2006, I moved to the University of Toronto, where I now hold the Canada Research Chair in Education and Technology. One of my goals was to move beyond the WISE framework, where students are engaged primary with "curriculum in the window" - and to bring the technology out of the box, and into the classroom itself. I began a research program in the area of smart classrooms, with an emphasis on pedagogical models. I also wanted to explore a knowledge community model of learning, where students in a classroom are considered as a whole, and not as individual learning solos. This was partly motivated by the socially oriented software of "Web 2.0." One of the papers I attach is a book chapter about the first run of a "Knowledge Community and Inquiry (KCI) curriculum, written with one of my PhD students (Peters and Slotta, 2010). We are just beginning this process, but it is very exciting. The current KCI curriculum, which I will present briefly at the workshop, is concerned with helping high school students develop a deep understanding of the science of global climate change.
References
Chi, M. T. H. (1992). Conceptual change within and across ontological categories: Examples from learning and discovery in science. In R. Giere (Ed.), Cognitive Models of Science: Minnesota Studies in the Philosophy of Science, (pp. 129-186). University of Minnesota Press: Minneapolis, MN.
Chi, M.T.H. (2005). Common sense conceptions of emergent processes: Why some misconceptions are robust. Journal of the Learning Sciences, 14: 161-199.
Driver, R. & Erickson, G. (1983). Theories-in-action: Some theoretical and empirical issues in the study of students' conceptual frameworks in science. Studies in Science Education, 10, 37-60.
Keil, F. C. (1981). Constraints on knowledge and cognitive development. Psychological Review, 88, 197-227.
Keil, F. C. (1987). Conceptual development and category structure. In U. Neisser (Ed.), Concepts and conceptual development. Cambridge, MA: Cambridge University Press.
Keil, F. C. (1989). Concepts, kinds, and cognitive development. Cambridge, MA: MIT Press.
McCloskey. M. (1983). Intuitive physics. Scientific American, 48: 122-130.
Reiner, M. Slotta, J. D., Chi, M. T. H. & Resnick, L. B. (2000). Naive physics reasoning: A commitment to substance-based conceptions. Cognition and Instruction, 18(1), 1-35.
Slotta, J. D. & Linn, M. C. (2009). WISE Science: Inquiry and the Internet in the Science Classroom. Teachers College Press.
Slotta, J. D. & Chi, M. T. H. (2006). The impact of ontology training on conceptual change: Helping students understand the challenging topics in science. Cognition and Instruction 24(2). 261-289. Lawrence Erlbaum Associates.
Slotta, J.D (2004). The Web-based Inquiry Science Environment (WISE): Scaffolding Knowledge Integration in the Science Classroom. In M.C. Linn, P. Bell and E. Davis (Eds). Internet Environments for Science Education. 203-232. LEA.
Slotta, J. D. & Linn, M. C. (2000). The Knowledge Integration Environment: Helping students use the Internet Effectively. In Jacobson, M. J. & Kozma, R. (Ed.), Learning the Sciences of the 21st Century. 193-226. Hilldale, NJ: Lawrence Erlbaum & Associates.
Slotta, J. D., & Chi, M. T. H. (1996). Understanding constraint-based processes: A precursor to conceptual change in physics. In G. W. Cottrell (Ed.), Proceedings of the Eighteenth Annual Conference of the Cognitive Science Society. 306-307.