Reform initiatives call for increased use of computers in K-12 science classrooms. It therefore becomes increasingly important to understand how particular types of computer software and pedagogical structures can support interactions that lead to meaningful learning by students. The role that the computer plays in students' learning in a collaborative environment depends not only on the ways that students use the computer and software but also on how they interact with each other as they use the computer. In this paper, we present some research results of studies that were conducted in collaborative guided-inquiry physical science courses for prospective elementary teachers. In these courses, each group of three students had access to its own computer. We first describe how the computer can be used as a representational tool to support meaning-making conversations in small student groups. Second, we discuss how special computer simulators make it easier for groups of students to construct robust conceptual models. It does so by providing the opportunity for students to make model-like observations that can help them bridge the phenomenological and conceptual domains. Finally, we discuss the design of this pedagogy, how the computer is embedded within classroom activities, and how these activities are based on prior research in science learning. Introduction Contemporary researchers in physics education have determined that innovative pedagogical strategies that make use of inquiry and collaborative techniques can be very ∗ The work described in this paper was supported in part by the National Science Foundation grant #ESI-9454341. ‡ Present address is Center for Excellence in Math and Science Education, Black Hills State University. successful (Hake, 1998). They have done this by computing learning gains from measurements of pre and post-test scores using commonly available assessment instruments and comparing these gains to learning gains computed for traditional lecture style classrooms. In depth studies on student learning in collaborative environments can generally look at what students learn and/or how students learn. To understand more about what students have learned we can take an individual cognition perspective focusing on students' ideas and changes in those ideas. We can also examine students' inquiry skills and beliefs, and changes in those skills and beliefs. However, if we wish to look at how students have learned, many other factors become relevant. For example, the learning environment in a collaborative guided inquiry physical science classroom often consists of small groups of students, laboratory apparatus, and pedagogical materials. Computers can also play a role. We consider the small group, computer, laboratory apparatus, and pedagogical materials to be a cognitive system. We seek to understand learning in this complex system by looking for things that transform, or change the nature of interactions within, this system. We therefore look not only at how ideas evolve within a group, but also at the roles that various components of the system play in mediating discussion and sense-making activity and how members of a group share in the group's construction of ideas. Our research has revealed that the computer, as it is used in a specific collaborative guided inquiry classroom, can play a significant role in the learning that takes place in this environment and can have positive effects on knowledge construction. Some of our research conclusions are described in this paper. In Part I we describe our theoretical background, the research setting, and methodology for our research. In Part II, we focus on how students use computer documents as shared spaces for representation and how this facilitates collaboration and the articulation of ideas. In Part III, we discuss how students use simulator results as a special type of evidence and how this seems to assist in the formulation and development of explanatory models. Finally, in Part IV, we describe how physics education research is incorporated into the development of the pedagogy and design of the computer software, and illustrate how the computer simulators are embedded in the pedagogical structure. Part I: Theoretical and Experimental Background Theoretical Perspective Learning often involves gradual development of ideas including making new connections, comparing with what is already known, and creating and trying out new ways of talking (Lemke, 1990). To understand these social and cultural processes, we follow a social constructivist perspective established by Vygotsky (1986) and developed by others (Cole, 1996; Cobb & Bowers, 1999). In his work, Vygotsky focused on learning in interactions between an authoritative superior such as a teacher, and a student. We believe, however, that social interactions between peers such as those in a collaborative group can also result in gradual construction of knowledge. Such gradual peer-based learning relies on the social and cultural milieu of the setting, in this case, the guided inquiry classroom. We also follow a systems cognition perspective where the student, the student in interaction with other students, and the student in interaction with others and with tools (such as the computer, activities, and the pedagogy) are considered a cognitive system (Hutchins, 1995). This perspective focuses on influences of environmental structures on students' sense-making processes. Environmental features such as classroom layout and how the computer is used in the pedagogy contribute to the ways that people organize their cognitive activity. In other words, learners may often solve problems by "piggybacking" on reliable environmental features. According to Hutchins, the 'opportunistic' use of, and interaction with, these sorts of features is a fundamental aspect of cognition that is often overlooked. To elucidate this notion, we provide an analogy given by cognitive scientist Andy Clark in his book Being There: Putting The Brain, Body, and World Together Again. The simple sponge, which feeds by filtering water, exploits the structure of its natural physical environment to reduce the amount of actual pumping it must perform: it orients itself so as to make use of ambient currents to aid its feeding. The trick is an obvious one, yet not until quite recently did biologists recognize it. The reason for this is revealing: Biologists have tended to focus solely on the individual organism as the locus of adaptive structure. They have treated the organism as if it could be understood independent of its physical world. In this respect, biologists have resembled those cognitive scientists who have sought only inner-cause explanations of cognitive phenomena (Clark, 1996). In the same way, we believe that humans use physical, social, and cultural features of their environment to their advantage. The process of cognition, like the analogous process of feeding, becomes a system consisting of interactions between individuals and their surroundings. Like the biologists in the analogy above, if we look only at the individual student's minds, we may miss some crucial aspects of the cognitive process. As researchers of learning, we feel that we must seek explanations for cognitive phenomena that include structures that are external, as well as internal, to individuals. Our research in the science classroom suggests that two particular classroom features, computer documents and computer simulators, are relevant factors of the cognitive system and, therefore, in students' learning. In the pages that follow, we provide descriptions and examples of the special roles that the computer can play in the learning process. Setting and Research Methodology This article draws on research conducted in a physical science course for prospective elementary teachers at San Diego State University. The course is taught using a collaborative inquiry pedagogy that focuses on the building of conceptual models and makes heavy use of computers in the classroom. (Goldberg, 1997). The course design was part of a five-year NSF funded project entitled Constructing Physics Understanding in a Computer Supported Learning Environment (CPU Project). In a CPU course, students are in control of inventing science ideas. Through carefully guided For more information about the CPU Project and software distribution please see http://cpuproject.sdsu.edu/CPU/. and sequenced activities, students are expected to construct physics ideas that are very closely aligned with the main ideas found in physics textbooks. For example, in the CPU classroom students are expected to establish for themselves that force is proportional to acceleration and ultimately to establish the relation between force, acceleration, and mass (or Newton's Second Law). There is no textbook for the course, instead, students construct their own "textbook" from print-outs of the computer activities they engage in a majority of class time. The main role of the CPU instructor is to guide whole class discussions that either bring out students' initial ideas or lead to a class consensus on a small set of powerful ideas that can explain a majority of the experimental observations students have made. The instructor provides very little direct information involving the content of physics but sometimes asks questions that lead to rich discussions in the whole class or in small groups. Most of the students who enrolled in this course are college juniors and seniors who plan to become elementary school teachers. These students have little science background and many of them express fear and anxiety about science when they first enter the classroom. They come from a mix of socioeconomic and ethnic backgrounds within the range of lower to upper middle class. Typically about 90% of the students are women, and approximately one third are Hispanic. Possibly because of their junior and senior class standing, some
[1]
Luciano Meira,et al.
The Microevolution of Mathematical Representations in Children's Activity
,
1995
.
[2]
D. Kuhn.
Children and adults as intuitive scientists.
,
1989,
Psychological review.
[3]
Fred M. Goldberg,et al.
An investigation of student understanding of the real image formed by a converging lens or concave mirror
,
1987
.
[4]
Fred Goldberg,et al.
Making the invisible visible: A teaching/learning environment that builds on a new view of the physics learner
,
1995
.
[5]
G. J. Kelly,et al.
Student's interaction with computer representations: Analysis of discourse in laboratory groups
,
1996
.
[6]
E. Hutchins.
Cognition in the wild
,
1995
.
[7]
Fred M. Goldberg,et al.
Prospective elementary teachers' prior knowledge about light
,
1993
.
[8]
J. Lemke.
Talking Science: Language, Learning, and Values
,
1990
.
[9]
Fred M. Goldberg,et al.
The effects of prior knowledge and instruction on understanding image formation
,
1993
.
[10]
David Hammer,et al.
Epistemological Beliefs in Introductory Physics
,
1994
.
[11]
Fred M. Goldberg,et al.
Student difficulties in understanding image formation by a plane mirror
,
1986
.
[12]
R. Hake.
Interactive-engagement vs Traditional Methods in Mechanics Instruction*
,
1998
.
[13]
P. Cobb,et al.
Cognitive and Situated Learning Perspectives in Theory and Practice
,
1999
.
[14]
A. Clark.
Being There: Putting Brain, Body, and World Together Again
,
1996
.