This study examined whether experience with different computer-based complex problem situations would improve complex problem solving competence in an unknown problem situation. Therefore, university students took part in a control group study. They were trained in five different complex problem situations for up to 7 hr, and their performance was tested in a sixth complex problem situation. The data analyses revealed that the training influenced the CPS process of knowledge acquisition. However, the CPS process of knowledge application was not impacted (...) by experience with other problem situations. Implications for the concept of CPS as a trainable competence as well as the training of CPS in general are discussed. (shrink)

The purpose of the two studies reported here was to develop an integrated model of the scientific reasoning process. Subjects were placed in a simulated scientific discovery context by first teaching them how to use an electronic device and then asking them to discover how a hitherto unencountered function worked. To do this task, subjects had to formulate hypotheses based on their prior knowledge, conduct experiments, and evaluate the results of their experiments. In the first study, using 20 adult subjects, (...) we identified two main strategies that subjects used to generate new hypotheses. One strategy was to search memory and the other was to generalize from the results of previous experiments. We described the former group as searching an hypothesis space, and the latter as searching an experiment space. In a second study, with 10 adults, we investigated how subjects search the hypothesis space by instructing them to state all the hypotheses that they could think of prior to conducting any experiments. Following this phase, subjects were then allowed to conduct experiments. Subjects who could not think of the correct rule in the hypothesis generation phase discovered the correct rule only by generalizing from the results of experiments in the experimental phase.Both studies provide support for the view that scientific reasoning can be characterized as search in two problem spaces. By extending Simon and Lea's (1974) Generalized Rule Inducer, we present a general model of Scientific Discovery as Dual Search (SDDS) that shows how search in two problem spaces (an hypothesis space and an experiment space) shapes hypothesis generation, experimental design, and the evaluation of hypotheses. The model also shows how these processes interact with each other. Finally, we interpret earlier findings about the psychology of scientific reasoning in terms of the SDDS model. (shrink)

In dynamic system control, cognitive mechanisms and abilities underlying performance may vary depending on the nature of the task. We therefore investigated the effects of system structure and its interaction with cognitive abilities on system control performance. A sample of 127 university students completed a series of different system control tasks that were manipulated in terms of system size and recurrent feedback, either with or without a cognitive load manipulation. Cognitive abilities assessed included reasoning ability, working memory capacity, and cognitive (...) reflection. System size and recurrent feedback affected overall performance as expected. Overall, the results support that cognitive ability is a good predictor of performance in dynamic system control tasks but predictiveness is reduced when the system structure contains recurrent feedback. We discuss this finding from a cognitive processing perspective as well as its implications for individual differences research in dynamic systems. (shrink)

The current study had three goals: to investigate strategies, tactics, and errors as predictors of success and failure under uncertainty following the dynamic decision making and complex problem solving framework; to use observation and to examine its reliability and potential as a data collection method when using microworlds; and to investigate the applicability and validity of a microworld developed in the West, to an Asian sample. One hundred three participants in the Philippines took the role of fire chief in the (...) microworld WINFIRE. Their strategies, tactics, and errors were observed and coded by experimenters as they worked individually on the simulation twice. Results showed that DDM strategies, tactics, and errors predicted success and failure in WINFIRE, and strategies and tactics that led to success increased while errors decreased over time; strategies, tactics, and errors can be validly assessed through observation by experimenters, specifically that two types of decision makers were identified: the active, flexible, and big picture planners and the slow or cautious, and singlefocused decision makers; these findings together with participants’ survey ratings speak for the applicability of the microworld in an East Asian sample and for its validity. Findings are potentially relevant for experts and for training programs, highlighting the benefits of virtual environments during DDM. (shrink)

This paper presents a learning theory pertinent to dynamic decision making (DDM) called instancebased learning theory (IBLT). IBLT proposes five learning mechanisms in the context of a decision‐making process: instance‐based knowledge, recognition‐based retrieval, adaptive strategies, necessity‐based choice, and feedback updates. IBLT suggests in DDM people learn with the accumulation and refinement of instances, containing the decision‐making situation, action, and utility of decisions. As decision makers interact with a dynamic task, they recognize a situation according to its similarity to past instances, (...) adapt their judgment strategies from heuristic‐based to instance‐based, and refine the accumulated knowledge according to feedback on the result of their actions. The IBLT's learning mechanisms have been implemented in an ACT‐R cognitive model. Through a series of experiments, this paper shows how the IBLT's learning mechanisms closely approximate the relative trend magnitude and performance of human data. Although the cognitive model is bounded within the context of a dynamic task, the IBLT is a general theory of decision making applicable to other dynamic environments. (shrink)

With the advent of computers in the experimental labs, dynamic systems have become a new tool for research on problem solving and decision making. A short review of this research is given and the main features of these systems (connectivity and dynamics) are illustrated. To allow systematic approaches to the influential variables in this area, two formal frameworks (linear structural equations and finite state automata) are presented. Besides the formal background, the article sets out how the task demands of system (...) identification and system control can be realised in these environments, and how psychometrically acceptable dependent variables can be derived. (shrink)

Computational models of learning and the theories they represent are often validated by calibrating them to human data on decision outcomes. However, only a few models explain the process by which these decision outcomes are reached. We argue that models of learning should be able to reflect the process through which the decision outcomes are reached, and validating a model on the process is likely to help simultaneously explain both the process as well as the decision outcome. To demonstrate the (...) proposed validation, we use a large dataset from the Technion Prediction Tournament and an existing Instance-based Learning model. We present two ways of calibrating the model’s parameters to human data: on an outcome measure and on a process measure. In agreement with our expectations, we find that calibrating the model on the process measure helps to explain both the process and outcome measures compared to calibrating the model on the outcome measure. These results hold when the model is generalized to a different dataset. We discuss implications for explaining the process and the decision outcomes in computational models of learning. (shrink)

The question 'What is intelligence?' may seem simple to answer, but the study and measurement of human intelligence is one of the most controversial subjects in psychology. For much of its history, the focus has been on differences between people, on what it means for one person to be more intelligent than another, and how such differences might have arisen, obscuring efforts to understand the general nature of intelligence. These are obviously fundamental questions, still widely debated and misunderstood. New definitions (...) of intelligence and new factors affecting intelligence are frequently being described, while psychometric testing is applied in most large industries.IQ and Human Intelligence provides a clear, authoritative overview of the main issues surrounding this fascinating area, including the development of IQ tests, the heritability of intelligence, theories of intelligence, environmental effects on IQ, factor analysis, relationship of cognitive psychology to measuring IQ, and intelligence in the social context. The clear, accessible style and numerous explanatory boxes make this the ideal text for advanced undergraduate and graduate students in psychology. Online Resource CentreThe Online Resource Centre to accompany IQ and Human Intelligence features the following resources:For registered adopters of the text:- Figures from the book, available to downloadFor students:- Hyperlinks to primary literature articles cited in the and 'Further Reading' sections of the book. (shrink)

Wisdom is an ancient concept with close conceptual relations to human goals, means and problem solving. However, in the recent scientific discourse there has been some confusion about the meaning of "wisdom". In this paper the most prominent definitions are contrasted with each other and a new reading is proposed: Based on an extensive literature review it is proposed that "wisdom" is explanatory knowledge of the fundamental truths in the domain of living well – an orienting knowledge about what is (...) good and right. It is demonstrated that deviations of modern philosophic definitions from this view can be traced back to slight misconceptions of traditional views. Further, in this paper the content of wisdom is specified in more detail as a set of propositions that were claimed by wise men from different cultures and bolstered by empirical psychological research. (shrink)

The assessment of highly domain-general problem solving skills is increasingly important as problem solving is increasingly demanded by modern workplaces and increasingly present in international large-scale assessments such as the Programme for International Student Assessment. This thesis is about the computer-based assessment of problem solving skills based on Multiple Complex Systems : The main idea of the MCS approach is to present multiple computer-simulations of “minimally complex” problems in order to reliably assess certain problem solving skills. In each simulation, the (...) problem solver has to interact with a problem in order to find out how to adequately represent the problem, and how to solve the problem. Up to now, two instances of the MCS approach have been proposed: the MicroDYN approach and – more recently, in the second paper of this thesis – the MicroFIN approach. In the current thesis I will elaborate on three research questions regarding the validity of the MCS approach: its content validity with regard to the concept of complex problem solving; the convergent validity of different instances of the MCS approach; the discriminant validity of the interactive problems of the MCS approach with regard to traditional static measures of reasoning and analytic problem solving skills. Each research question will be addressed in one corresponding paper: In a first paper complex problem solving is defined as the goal-oriented control of systems that contain multiple highly interrelated elements. After reviewing some of the major strands of research on complex problem solving a theoretical framework outlining the most important cognitive processes involved in solving complex problems is derived. The theoretical framework highlights both interactive knowledge acquisition and interactive knowledge application as the two major phases in the process of complex problem solving. Both phases are represented in all current instances of the MCS approach. In a second paper the convergent validity of MicroDYN and MicroFIN is investigated in order to demonstrate that both instances address the same kind of problem solving skills. Based on a multitrait-multimethod analysis of a sample of university students it is demonstrated that – in addition to method-specific skills – both instances assess a common set of skills related to representing and solving different kinds of interactive problems. In a regression of science grades on reasoning and the skills assessed by the instances of the MCS approach it is demonstrated that only the method-general representation trait and reasoning have substantial unique contributions. Thus, MicroDYN and MicroFIN seem to address a common set of skills and this set of skills is relevant for explaining school grades in science classes even beyond reasoning. In a third paper the discriminant validity of the interactive MicroDYN test is investigated by relating it to reasoning and traditional static measures of Analytic Problem Solving skills as they were applied in PISA 2003. Besides a common core of problem solving skills addressed by both kinds of tasks Fischer et al. expected to find evidence for additional skills that were related to interactive problems only. Results indicate that MicroDYN shares a lot of variance with APS even after controlling for reasoning in a sample of high-school students and the university student sample. With regard to the explanation of school grades MicroDYN had an incremental value compared to reasoning and APS in the high-school student sample but not significantly so in the university student sample. Basically these findings highlight both potential and limitations of the MicroDYN approach in its current form. Current instances of the MCS approach address a small set of problem solving skills reliably, but it takes more than these skills to competently solve complex problems. Implications for future research on the assessment of problem solving skills are discussed. (shrink)