Assessing Problem Solving in Technology-Rich Environments: What Can We Learn from Online Strategy Indicators?

Assessing Problem Solving in Technology-Rich Environments: What Can We Learn from Online Strategy Indicators?

Jean-Francois Rouet (University of Poitiers, France), Zsofia Vörös (University of Poitiers, France) and Matthias von Davier (Educational Testing Service, USA)
DOI: 10.4018/978-1-4666-9441-5.ch027
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The spread of digital information system has promoted new ways of performing activities, whereby laypersons make use of computer applications in order to achieve their goal through the use of problem solving strategies. These new forms of problem solving rely on a range of skills whose accurate assessment is key to the development of postindustrial economies. In this chapter, we outline a definition of problem solving in technology-rich environment drawn from the OECD PIAAC survey of adult skills. Then we review research studies aimed at defining and using online indicators of PS-TRE proficiency. Finally, we present a case study of one item that was part of the PIAAC PS-TRE assessment.
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Problem Solving In Technology-Rich Environments (Ps-Tre)

People are said to face a problem whenever they cannot routinely fulfill their purposes. Problem solving has been a prominent subject of investigation in cognitive science ever since the advent of the “cognitivist” paradigm (e.g., Newell & Simon, 1972). Problem solving typically involves a series of cognitive steps and operations: One must understand the nature of the problem (i.e., “problem finding”; Getzels, 1979); plan a set of subgoals and actions that can lead to the resolution of the problem (or “problem shaping”); and unfold the plan until a solution is reached, unless an impasse or another obstacle forces them to reconsider their plans. Problem solving plays a central part in a large number of activities—from the simplest everyday issues, to schooling, to post-secondary training, to the most complex professional occupations. Accumulated experience, knowledge, and one’s ability to articulate goals and plans are essential to successful problem solving (Chi, Glaser, & Rees, 1982Funke, 2010; Mayer, 1992; Sweller, 1998).

Problems vary according to a number of dimensions. The openness of the problem space or the amount of information needed to come to a solution (a continuum sometimes construed as the “information-lean” vs. “information-rich” problem dichotomy) are two of the dimensions along which problems may vary. In recent decades, there has been a growing interest in problems that require people to make use of large amounts of information. The phrase “information problem solving” (Eisenberg & Berkowitz, 1990; Moore, 1995) was proposed to denote this category of problems. Brand-Gruwel, Wopereis, and Vermetten (2005) define information problems as “tasks or assignments that require [students] to identify information needs, locate corresponding information sources, extract and organize relevant information from each source, and synthesize information from a variety of sources.” Early studies found that even simple information problems can be challenging for students from grade school (Kobasigawa, 1983; Moore, 1995; Rouet, 1990) to college and beyond (Brand-Gruwel, Wopereis, & Walraven, 2009; Rouet, Favart, Britt & Perfetti, 1997; see also Lazonder & Rouet, 2008).

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