Implications For Problem Solving Research Articles

Cognition-emotion interactions: patterns of change and implications for math problem solving.

Surprisingly little is known about whether relationships between cognitive and emotional states remain stable or change over time, or how different patterns of stability and/or change in the relationships affect problem solving abilities. Nevertheless, cross-sectional studies show that anxiety/worry may reduce working memory (WM) resources, and the ability to minimize the effects anxiety/worry is higher in individuals with greater WM capacity. To investigate the patterns of stability and/or change in cognition-emotion relations over time and their implications for problem solving, 126 14-year-olds’ algebraic WM and worry levels were assessed twice in a single day before completing an algebraic math problem solving test. We used latent transition analysis to identify stability/change in cognition-emotion relations, which yielded a six subgroup solution. Subgroups varied in WM capacity, worry, and stability/change relationships. Among the subgroups, we identified a high WM/low worry subgroup that remained stable over time and a high WM/high worry, and a moderate WM/low worry subgroup that changed to low WM subgroups over time. Patterns of stability/change in subgroup membership predicted algebraic test results. The stable high WM/low worry subgroup performed best and the low WM capacity-high worry “unstable across time” subgroup performed worst. The findings highlight the importance of assessing variations in cognition-emotion relationships over time (rather than assessing cognition or emotion states alone) to account for differences in problem solving abilities.

Huffman coding as metaphor

Purpose – David Huffman, as a graduate student, earned his immortality by solving a problem that had stumped Claude Shannon, the creator of the field of information theory. How he saw the problem differently and the nature of his discovery have implications for how we get stuck, how we get unstuck, and how the internal models limit the ability to see patterns in the world. The paper aims to discuss these issues. Design/methodology/approach – This paper describes how Huffman discovered his elegant algorithm, why it had not been discovered previously, how the algorithm may relate to the attempt to find meaning in decision making, and generalises implications for problem solving and daily lives. Findings – Huffman was only able to see the problem anew in the cathartic moment of abandoning it. The algorithm he discovered suggests that the concept of “meaning” was an obstacle in his process. Practical implications – Huffman coding is one of the underpinnings of computer science. While it should be widely understood for that alone, the process of its discovery and its fundamental methodology are deeply instructional. Originality/value – Alexander Pope said “As the twig is bent, so grows the tree”, a classic statement about conscious purpose and man's controlling nature. Huffman's algorithm suggests the real world works the other way around: “As the leaves are lit, so grows the tree”.

The Questionable Effect of Retinal Variables on Information Displays: Implications for Problem Solving and Learning

This study challenged the long-held assumption that the “retinal variable,” such as color or shape, used to represent data on an information display influences how well it is interpreted and understood. Forty-eight undergraduates solved problem scenarios by consulting a multivariate display using either color, value, or shape to represent age groups of Indian tourists. The type of retinal variables employed affected neither the accuracy nor latency of question responses, regardless of whether or not the display was in view during testing. However, problem-solving tasks were rated significantly easier to perform when display information was depicted through variation in color versus value.

Predictors of well‐structured and ill‐structured problem solving in an astronomy simulation

AbstractThis study compared the problem‐solving skills required for solving well‐structured problems and ill‐structured problems in the context of an open‐ended, multimedia problem‐solving environment in astronomy. Two sets of open‐ended questions assessed students' abilities for solving well‐structured and ill‐structured problems. Generalized, rubric scoring systems were developed for assessing problem‐solving skills. Instruments were also developed and administered to assess cognitive and affective predictors of problem‐solving performance. By regressing the scores on the cognitive and affective predictors onto students' scores on the well‐structured and ill‐structured problems, we concluded that solving well‐structured and ill‐structured problems require different component skills. Domain knowledge and justification skills were significant predictors of well‐structured problem‐solving scores, whereas ill‐structured problem‐solving scores were significantly predicted by domain knowledge, justification skills, science attitudes, and regulation of cognition. Implications for problem solving in science education are presented. © 2003 Wiley Periodicals, Inc. J Res Sci Teach 40: 6–33, 2003

Justification effects on the judgment of analogy.

Many of us share a strong intuition that justification forces us to better understand the situations we face. And there is substantial evidence indicating that this is often the case. However, there is a growing body of research showing that, under certain circumstances, explanation and justification can impair performance on a variety of cognitive tasks. In the present research, the effects of justification on judgment of the soundness of analogies were examined. Subjects judged the quality of the match between pairs of stories with varying degrees of superficial and analogical similarity. Experimental subjects either provided reasons for their judgments or wrote recollections of the target stimuli. These subjects rated the match between stimulus pairs as more sound than did control subjects. Also, providing reasons led to poorer discrimination between superficially similar aspects of the stimuli and analogous aspects. Explanations of these findings are proposed, and implications for problem solving and confidence judgment are discussed.

Collegiality in Schools: Its Nature and Implications for Problem Solving

Greater collegiality among teachers is frequently suggested in the research literature as one way of improving decision making and problem solving in schools. In this article, we argue that this claim cannot be sustained without more sophisticated theorizing about the attributes of collegiality that promote quality decision making and problem solving. In the first part of our argument, we use a constraint inclusion theory of a problem to argue that the attributes of collegiality most frequently discussed in the literature are as likely to generate poor as high quality problem-solving processes and solutions. In the second part of the article, we illustrate this argument in a case study of collegial problem solving by identifying the precise processes that contributed to the quality of the problem solutions.

The thinking style of the managers of multiple projects: implications for problem solving when managing change

The purpose of this paper is twofold: (a) To draw attention to an important aspect of cognition—thinking style. Theory predicts, and research has clearly shown, that thinking style influences the way in which individuals prefer to use their intelligence, ability, knowledge and skills when making decisions and solving problems. (b) To discuss the results obtained from testing the hypothesis that managers of multiple projects are likely to have a more innovative thinking style than managers in general. The hypothesis is supported and the paper discusses the influence of thinking style on several key aspects of the management of multiple projects.

Geographic information systems: Implications for problem solving

During the 1980s a revolutionary type of computer software called Geographic Information Systems (GIS) was developed for integrating environmental data bases with automated map makers. Educational applications of GIS are presently gaining serious attention, and promise to impact US classrooms of tomorrow. Because technophiles focus initially on hardware and software issues, the expansion of educational technologies tends to outpace the associated knowledge base concerning learning and teaching. The emerging consensus is that systematic investigations of how technological innovations can support learning should precede the adoption of new educational practices. This study compared expert/novice-based problem-solving behaviors with a GIS program called ArcView. GIS problem-solving strategies described during reflective think-aloud sessions were evaluated through naturalistic research methods and were analyzed for the occurrence of thematic elements. Three GIS problem-solving typologies were identified. Experts relied on logical formulations to query the data base. Among the novice population, trial-and-error methods and midlevel cognitive strategies that relied on spatial analyses were most prevalent. As novices progressed through the problem set, higher-level cognitive operations were used more frequently. The findings suggest the importance of additional cognitive studies and classroom evaluations of various instructional models prior to the wholesale introduction of GIS technology into high school classrooms. © 1996 John Wiley & Sons, Inc.

Geographic information systems: Implications for problem solving

Geographic information systems: Implications for problem solving

SCALING BEHAVIOR OF PROBLEM SOLVING SYSTEMS

Problem solving is a ubiquitous phenomenon currently being studied in a number of fields. Still at issue is the problem of scaling up to large problems. Distributed systems with a focus on the architecture and communications of the processors are one possible solution. The model presented here differs by focussing on the distribution of search modifying heuristics available to processors that can be used to speed problem solving. This paper characterizes the shape of speed-up with respect to the heuristics and shows some of the implications for problem solving. Theoretical justifications are given and tested using a rule learning program.

Mobility-Fixity Dimension in Witkin's Theory of Field-Dependence/Independence and its Implications for Problem Solving in Science

Various studies have shown the advantage of field independence for problem solving in science courses. The mobility-fixity dimension of Witkin's theory suggests that, although field-independent subjects are successful in science courses, field-independent subjects who ate mobile are expected to be more successful. Mobile subjects are those who have available to them both a developmentally advanced mode of functioning (field independence) and a developmentally earlier mode (field dependence). To test the hypothesis that mobile subjects would obtain a better performance than fixed subjects in freshman chemistry, mathematics, and biology courses, the Group Embedded Figures Test was used along with the Figural Intersection Test to classify subjects as mobile or fixed ( ns = 0–24 per group). As predicted, subjects' performance in chemistry, mathematics, and biology courses showed the advantage of the mobile group. Necessary is a replication with a larger number of subjects, inclusion in content of course tests of items requiring scientific analysis, and use of a psychometrically rigorous Figural Intersection Test.

Hemisphericity Research: An Overview With Some Implications for Problem Solving

Hemisphericity Research: An Overview With Some Implications for Problem Solving