ED-MEDIA 1999 Proceedings Book - Association for the ...

Toward a framework for instruction with technology
Marcia C. Linn, University of California at Berkeley
Based on over a decade of research in the Computer as Learning Partner project, The Scaffolded
Knowledge Integration (SKI) framework guides the design of effective, technology rich learning environments
(Linn, 1995; Linn & Hsi, in press). My research targets scientific understanding, with particular focus on preparing
students to become lifelong science learners in a complex, changing world. In this panel, I describe how the
Scaffolded Knowledge Integration framework can guide decisions made by instructional designers. This process has
succeeded in our Computer as Learning Partner Project and Knowledge Integration Environment Project (Bell,
Davis and Linn (in press), and is currently guiding our work in two new projects: The Web-based Integrated Science
Environment (WISE) and Science Controversies On-line: Partnerships in Education (SCOPE).
An effective framework for instructional design should respond to a wide range of questions: How can we
help students gain lifelong learning skills What kinds of guidance do students need in order to best succeed in the
activities we design How do we capitalize on the social aspects of classrooms too often ignored by instruction An
instructional framework should integrate the findings from abstract theories and detailed experiments into principles
that can effectively guide the design of learning technologies and curriculum.
I define knowledge integration as the dynamic process of connecting, distinguishing, organizing, and
structuring models of a particular scientific phenomenon. I use the term "model" loosely to refer to patterns,
templates, views, ideas, theories, and visualizations. In general, learners bring multiple models of the phenomenon
to any intellectual situation and regularly revise and reconnect their ideas. For example, if one wishes to instruct
students in the area of heat and temperature, a quick review of the vocabulary around these concepts suggest a broad
range of models available to students. Students may believe that heat and temperature are interchangeable, based on
verbal formulations such as "turn up the heat" and "turn up the temperature." Or they may distinguish heat from
temperature, for example, remarking that temperature refers to all of the possible degrees on the thermometer
whereas heat refers to the degrees near the top of the thermometer.
In general, students bring a multitude of models to any situation and engage in a dynamic process of
selecting among them to deal with particular problems or social interactions. Rather than viewing multiple models as
a problem, we see this as an opportunity for students to gain a rich understanding of the learning process and of the
distinction between scientific and everyday problem solving. The Scaffolded Knowledge Integration framework
helps designers create materials that invite students to develop a deeper, more connected understanding of scientific
phenomena. This view of students as “seeking connections” and instruction as “fostering knowledge integration”
stands in contrast to the conventional model of learners as receiving information and of instruction as providing
information. To design for knowledge integration, we articulate four major tenets of our framework:
Making Science Accessible: To enable students to connect new ideas to their existing knowledge, we must
assess their baseline understanding and design materials that connect to this knowledge. Effective instruction
provides opportunities for students to evaluate scientific evidence according to their own understanding, to articulate
their own theories and explanations, and participate actively in principled design. This might involve using models
of phenomena that are more accessible to students than the normative scientific models (Linn & Songer, 1991).
Making Thinking Visible: To model the process of knowledge integration teachers and software can
illustrate the wrong paths and confusions typical of scientific reasoning. To design instruction, we also need to help
students make their own thinking visible (e.g., Collins, Brown and Holum, 1991; Linn and Songer, 1991; Slotta and
Linn, in press).
Promoting Lifelong Science Learning: To prepare students for autonomous, lifelong science learning we
start with small but independent student activities that require sustained reasoning. To make such projects authentic,
we draw on students existing knowledge and incorporate scientific evidence that students find personally relevant.
In our Computer as Learning Partner project, we found that electronic coaches could helps students use such
evidence productively. Electronic coaches, carefully designed, can be just as effective and more efficient than some
forms of human coaching.
Providing Social Supports for Learning: Science learning is rarely performed in isolation from ones peers;
rather, peer exchange is often vital to learning. (e.g., Brown and Campione, 1990; Vygotsky, 1987). Science projects
should be designed to foster collaborative work, both because this will be an important skill for students throughout
their lives, and also because it is an efficient means of learning how others connect ideas. Designing an effective
social context for learning involves guiding the process of social interaction. Hearing ideas in the words of peers,
validating each others' ideas, and asking questions of peers can all foster links and connections among ideas when
carefully designed.