Scaffolding Problem-Solving and Inquiry: From Instructional Design to a “Bridge Model”

Scaffolding Problem-Solving and Inquiry: From Instructional Design to a “Bridge Model”

Zvia Fund
DOI: 10.4018/978-1-60566-120-9.ch014
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Abstract

The study examines cognitive support for science learning in a computerized environment. The research was carried out with junior high school students, who used a problem-solving computerized environment in science. For this purpose, four support components were identified - structural, reflection, subjectmatter, and enrichment components. These components were used to construct four computerized cognitive support models based on human teaching. The effects of these support models on achievement, on cognitive and meta-cognitive skills, and on reflective behavior are compared to one another and to a control group. The results led to the construction of a theoretical-functional “Bridge Model”. The model elucidates the functions of the structural, reflective and subject-matter components upon the cognitive system, and offers an explanation of the research findings. The study and its main results are presented, as well as a theoretical description of the Bridge Model.
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Design Approaches

A number of scaffolding studies have adopted a strategies-oriented support approach (Hmelo-Silver et al., 2007; Zhang et al., 2004). Some of these, support learners in accomplishing specific tasks--such as generating hypotheses--in simulation-based discovery learning (Njoo & de Jong, 1993), or developing causal or evidence-based explanations (Hmelo-Silver et al., 2007); others focus on the impact of specific support strategies (de Jong, 2006; de Jong & van Joolingen, 1998). Quintana et al. (2004) organize their scaffolding design framework around three constituent processes of inquiry: sense making (the basic operations of testing hypotheses and interpreting data); process management (the strategic decisions involved in controlling the inquiry process); and articulation and reflection (the process of constructing, evaluating, and articulating what has been learned). De Jong (2006) reviews scaffolding of inquiry learning, organized around each of the learning processes involved – orientation, hypothesis generation, experimentation, drawing conclusions and making evaluations. Although in the study we used a teacher oriented approach for scaffolding (see the following), we included some detailed categorization of computerized science problem-solving skills (Fund, 2003; Method, the COSPROS Scheme, experiment B, and Table 2).

Key Terms in this Chapter

Structural Support: Providing a general framework that guides the student with the cognitive skills necessary to effect cognitive and work patterns.

Subject-Matter Support Component: Clarifying ideas and concepts relevant to each problem, and addressing general domain-specific guidance, as well as providing short guiding questions for the solving process.

Cognitive / Meta-Cognitive Scaffolding: Support and guidance addressing cognitive/meta-cognitive skills and work pattern.

Cognitive / Meta-Cognitive Skills: Construction of the ‘computerized science problem solving’ (COSPROS) scheme, based on three major steps involved in effective science problem solving: initial problem analysis; tentative construction of a solution; and self-monitoring of the solution allowing for appropriate revision--as necessary ( Reif, 1995 ). This scheme consists of eleven main skills (categories). Eight of these involve cognitive skills while three incorporate meta-cognitive skills during the self-monitoring of the solution.

Science Problem Solving: Solving problems in the scientific domain.

Reflection: the process of constructing, evaluating, and articulating what has been learned; meta-cognitive skills such as monitoring and control, self-assessment and self-regulation.

Computerized Problem Solving: Problem solving performed in a computerized learning environment.

The Bridge Model: A theoretical-functional model constructed, based on the research findings, to elucidate the functions of the structural, reflective and subject-matter support components upon the cognitive system, and to offer explanations of the research findings.

Computerized Learning Environment: Computerized environment designed mainly for open-ended learning tasks.

Reflection Support: Providing a general framework to stimulate and activate meta-cognitive skills.

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