Understanding the determinants of problem-solving behavior in a complex environment

NASA Technical Reports Server (NTRS)

Casner, Stephen A.

1994-01-01

It is often argued that problem-solving behavior in a complex environment is determined as much by the features of the environment as by the goals of the problem solver. This article explores a technique to determine the extent to which measured features of a complex environment influence problem-solving behavior observed within that environment. In this study, the technique is used to determine how complex flight deck and air traffic control environment influences the strategies used by airline pilots when controlling the flight path of a modern jetliner. Data collected aboard 16 commercial flights are used to measure selected features of the task environment. A record of the pilots' problem-solving behavior is analyzed to determine to what extent behavior is adapted to the environmental features that were measured. The results suggest that the measured features of the environment account for as much as half of the variability in the pilots' problem-solving behavior and provide estimates on the probable effects of each environmental feature.

How Can We Improve Problem Solving in Undergraduate Biology? Applying Lessons from 30 Years of Physics Education Research

PubMed Central

Hoskinson, A.-M.; Caballero, M. D.; Knight, J. K.

2013-01-01

If students are to successfully grapple with authentic, complex biological problems as scientists and citizens, they need practice solving such problems during their undergraduate years. Physics education researchers have investigated student problem solving for the past three decades. Although physics and biology problems differ in structure and content, the instructional purposes align closely: explaining patterns and processes in the natural world and making predictions about physical and biological systems. In this paper, we discuss how research-supported approaches developed by physics education researchers can be adopted by biologists to enhance student problem-solving skills. First, we compare the problems that biology students are typically asked to solve with authentic, complex problems. We then describe the development of research-validated physics curricula emphasizing process skills in problem solving. We show that solving authentic, complex biology problems requires many of the same skills that practicing physicists and biologists use in representing problems, seeking relationships, making predictions, and verifying or checking solutions. We assert that acquiring these skills can help biology students become competent problem solvers. Finally, we propose how biology scholars can apply lessons from physics education in their classrooms and inspire new studies in biology education research. PMID:23737623

What Does (and Doesn't) Make Analogical Problem Solving Easy? A Complexity-Theoretic Perspective

ERIC Educational Resources Information Center

Wareham, Todd; Evans, Patricia; van Rooij, Iris

2011-01-01

Solving new problems can be made easier if one can build on experiences with other problems one has already successfully solved. The ability to exploit earlier problem-solving experiences in solving new problems seems to require several cognitive sub-abilities. Minimally, one needs to be able to retrieve relevant knowledge of earlier solved…

Teaching Problem Solving; the Effect of Algorithmic and Heuristic Problem Solving Training in Relation to Task Complexity and Relevant Aptitudes.

ERIC Educational Resources Information Center

de Leeuw, L.

Sixty-four fifth and sixth-grade pupils were taught number series extrapolation by either an algorithm, fully prescribed problem-solving method or a heuristic, less prescribed method. The trained problems were within categories of two degrees of complexity. There were 16 subjects in each cell of the 2 by 2 design used. Aptitude Treatment…

The Association between Motivation, Affect, and Self-regulated Learning When Solving Problems

PubMed Central

Baars, Martine; Wijnia, Lisette; Paas, Fred

2017-01-01

Self-regulated learning (SRL) skills are essential for learning during school years, particularly in complex problem-solving domains, such as biology and math. Although a lot of studies have focused on the cognitive resources that are needed for learning to solve problems in a self-regulated way, affective and motivational resources have received much less research attention. The current study investigated the relation between affect (i.e., Positive Affect and Negative Affect Scale), motivation (i.e., autonomous and controlled motivation), mental effort, SRL skills, and problem-solving performance when learning to solve biology problems in a self-regulated online learning environment. In the learning phase, secondary education students studied video-modeling examples of how to solve hereditary problems, solved hereditary problems which they chose themselves from a set of problems with different complexity levels (i.e., five levels). In the posttest, students solved hereditary problems, self-assessed their performance, and chose a next problem from the set of problems but did not solve these problems. The results from this study showed that negative affect, inaccurate self-assessments during the posttest, and higher perceptions of mental effort during the posttest were negatively associated with problem-solving performance after learning in a self-regulated way. PMID:28848467

Cognitive and Motivational Impacts of Learning Game Design on Middle School Children

ERIC Educational Resources Information Center

Akcaoglu, Mete

2013-01-01

In today`s complex and fast-evolving world, problem solving is an important skill to possess. For young children to be successful at their future careers, they need to have the "skill" and the "will" to solve complex problems that are beyond the well-defined problems that they learn to solve at schools. One promising approach…

Using Educational Data Mining Methods to Assess Field-Dependent and Field-Independent Learners' Complex Problem Solving

ERIC Educational Resources Information Center

Angeli, Charoula; Valanides, Nicos

2013-01-01

The present study investigated the problem-solving performance of 101 university students and their interactions with a computer modeling tool in order to solve a complex problem. Based on their performance on the hidden figures test, students were assigned to three groups of field-dependent (FD), field-mixed (FM), and field-independent (FI)…

Solving the Problem of Linear Viscoelasticity for Piecewise-Homogeneous Anisotropic Plates

NASA Astrophysics Data System (ADS)

Kaloerov, S. A.; Koshkin, A. A.

2017-11-01

An approximate method for solving the problem of linear viscoelasticity for thin anisotropic plates subject to transverse bending is proposed. The method of small parameter is used to reduce the problem to a sequence of boundary problems of applied theory of bending of plates solved using complex potentials. The general form of complex potentials in approximations and the boundary conditions for determining them are obtained. Problems for a plate with elliptic elastic inclusions are solved as an example. The numerical results for a plate with one, two elliptical (circular), and linear inclusions are analyzed.

How Students Circumvent Problem-Solving Strategies that Require Greater Cognitive Complexity.

ERIC Educational Resources Information Center

Niaz, Mansoor

1996-01-01

Analyzes the great diversity in problem-solving strategies used by students in solving a chemistry problem and discusses the relationship between these variables and different cognitive variables. Concludes that students try to circumvent certain problem-solving strategies by adapting flexible and stylistic innovations that render the cognitive…

Complex Problem Solving in a Workplace Setting.

ERIC Educational Resources Information Center

Middleton, Howard

2002-01-01

Studied complex problem solving in the hospitality industry through interviews with six office staff members and managers. Findings show it is possible to construct a taxonomy of problem types and that the most common approach can be termed "trial and error." (SLD)

Assessing Student Written Problem Solutions: A Problem-Solving Rubric with Application to Introductory Physics

ERIC Educational Resources Information Center

Docktor, Jennifer L.; Dornfeld, Jay; Frodermann, Evan; Heller, Kenneth; Hsu, Leonardo; Jackson, Koblar Alan; Mason, Andrew; Ryan, Qing X.; Yang, Jie

2016-01-01

Problem solving is a complex process valuable in everyday life and crucial for learning in the STEM fields. To support the development of problem-solving skills it is important for researchers and curriculum developers to have practical tools that can measure the difference between novice and expert problem-solving performance in authentic…

Internet Computer Coaches for Introductory Physics Problem Solving

ERIC Educational Resources Information Center

Xu Ryan, Qing

2013-01-01

The ability to solve problems in a variety of contexts is becoming increasingly important in our rapidly changing technological society. Problem-solving is a complex process that is important for everyday life and crucial for learning physics. Although there is a great deal of effort to improve student problem solving skills throughout the…

Prompting in Web-Based Environments: Supporting Self-Monitoring and Problem Solving Skills in College Students

ERIC Educational Resources Information Center

Kauffman, Douglas F.; Ge, Xun; Xie, Kui; Chen, Ching-Huei

2008-01-01

This study explored Metacognition and how automated instructional support in the form of problem-solving and self-reflection prompts influenced students' capacity to solve complex problems in a Web-based learning environment. Specifically, we examined the independent and interactive effects of problem-solving prompts and reflection prompts on…

Solving the Inverse-Square Problem with Complex Variables

ERIC Educational Resources Information Center

Gauthier, N.

2005-01-01

The equation of motion for a mass that moves under the influence of a central, inverse-square force is formulated and solved as a problem in complex variables. To find the solution, the constancy of angular momentum is first established using complex variables. Next, the complex position coordinate and complex velocity of the particle are assumed…

Clinical Problem Analysis (CPA): A Systematic Approach To Teaching Complex Medical Problem Solving.

ERIC Educational Resources Information Center

Custers, Eugene J. F. M.; Robbe, Peter F. De Vries; Stuyt, Paul M. J.

2000-01-01

Discusses clinical problem analysis (CPA) in medical education, an approach to solving complex clinical problems. Outlines the five step CPA model and examines the value of CPA's content-independent (methodical) approach. Argues that teaching students to use CPA will enable them to avoid common diagnostic reasoning errors and pitfalls. Compares…

Teaching Problem-Solving Skills to Nuclear Engineering Students

ERIC Educational Resources Information Center

Waller, E.; Kaye, M. H.

2012-01-01

Problem solving is an essential skill for nuclear engineering graduates entering the workforce. Training in qualitative and quantitative aspects of problem solving allows students to conceptualise and execute solutions to complex problems. Solutions to problems in high consequence fields of study such as nuclear engineering require rapid and…

Dynamic Modeling as a Cognitive Regulation Scaffold for Developing Complex Problem-Solving Skills in an Educational Massively Multiplayer Online Game Environment

ERIC Educational Resources Information Center

Eseryel, Deniz; Ge, Xun; Ifenthaler, Dirk; Law, Victor

2011-01-01

Following a design-based research framework, this article reports two empirical studies with an educational MMOG, called "McLarin's Adventures," on facilitating 9th-grade students' complex problem-solving skill acquisition in interdisciplinary STEM education. The article discusses the nature of complex and ill-structured problem solving…

Are Middle School Mathematics Teachers Able to Solve Word Problems without Using Variable?

ERIC Educational Resources Information Center

Gökkurt Özdemir, Burçin; Erdem, Emrullah; Örnek, Tugba; Soylu, Yasin

2018-01-01

Many people consider problem solving as a complex process in which variables such as "x," "y" are used. Problems may not be solved by only using "variable." Problem solving can be rationalized and made easier using practical strategies. When especially the development of children at younger ages is considered, it is…

From problem solving to problem definition: scrutinizing the complex nature of clinical practice.

PubMed

Cristancho, Sayra; Lingard, Lorelei; Regehr, Glenn

2017-02-01

In medical education, we have tended to present problems as being singular, stable, and solvable. Problem solving has, therefore, drawn much of medical education researchers' attention. This focus has been important but it is limited in terms of preparing clinicians to deal with the complexity of the 21st century healthcare system in which they will provide team-based care for patients with complex medical illness. In this paper, we use the Soft Systems Engineering principles to introduce the idea that in complex, team-based situations, problems usually involve divergent views and evolve with multiple solution iterations. As such we need to shift the conversation from (1) problem solving to problem definition, and (2) from a problem definition derived exclusively at the level of the individual to a definition derived at the level of the situation in which the problem is manifested. Embracing such a focus on problem definition will enable us to advocate for novel educational practices that will equip trainees to effectively manage the problems they will encounter in complex, team-based healthcare.

Solving Problems.

ERIC Educational Resources Information Center

Hale, Norman; Lindelow, John

Chapter 12 in a volume on school leadership, this chapter cites the work of several authorities concerning problem-solving or decision-making techniques based on the belief that group problem-solving effort is preferable to individual effort. The first technique, force-field analysis, is described as a means of dissecting complex problems into…

Assessing problem-solving skills in construction education with the virtual construction simulator

NASA Astrophysics Data System (ADS)

Castronovo, Fadi

The ability to solve complex problems is an essential skill that a construction and project manager must possess when entering the architectural, engineering, and construction industry. Such ability requires a mixture of problem-solving skills, ranging from lower to higher order thinking skills, composed of cognitive and metacognitive processes. These skills include the ability to develop and evaluate construction plans and manage the execution of such plans. However, in a typical construction program, introducing students to such complex problems can be a challenge, and most commonly the learner is presented with only part of a complex problem. To support this challenge, the traditional methodology of delivering design, engineering, and construction instruction has been going through a technological revolution, due to the rise of computer-based technology. For example, in construction classrooms, and other disciplines, simulations and educational games are being utilized to support the development of problem-solving skills. Previous engineering education research has illustrated the high potential that simulations and educational games have in engaging in lower and higher order thinking skills. Such research illustrated their capacity to support the development of problem-solving skills. This research presents evidence supporting the theory that educational simulation games can help with the learning and retention of transferable problem-solving skills, which are necessary to solve complex construction problems. The educational simulation game employed in this study is the Virtual Construction Simulator (VCS). The VCS is a game developed to provide students in an engaging learning activity that simulates the planning and managing phases of a construction project. Assessment of the third iteration of the VCS(3) game has shown pedagogical value in promoting students' motivation and a basic understanding of construction concepts. To further evaluate the benefits on problem-solving skills, a new version of the VCS(4) was developed, with new building modules and assessment framework. The design and development of the VCS4 leveraged research in educational psychology, multimedia learning, human-computer interaction, and Building Information Modeling. In this dissertation the researcher aimed to evaluate the pedagogical value of the VCS4 in fostering problem-solving skills. To answer the research questions, a crossover repeated measures quasi-experiment was designed to assess the educational gains that the VCS can provide to construction education. A group of 34 students, attending a fourth-year construction course at a university in the United States was chosen to participate in the experiment. The three learning modules of the VCS were used, which challenged the students to plan and manage the construction process of a wooden pavilion, the steel erection of a dormitory, and the concrete placement of the same dormitory. Based on the results the researcher was able to provide evidence supporting the hypothesis that the chosen sample of construction students were able to gain and retain problem-solving skills necessary to solve complex construction simulation problems, no matter what the sequence with which these modules were played. In conclusion, the presented results provide evidence supporting the theory that educational simulation games can help the learning and retention of transferable problem-solving skills, which are necessary to solve complex construction problems.

Schizophrenia, narrative, and neurocognition: The utility of life-stories in understanding social problem-solving skills.

PubMed

Moe, Aubrey M; Breitborde, Nicholas J K; Bourassa, Kyle J; Gallagher, Colin J; Shakeel, Mohammed K; Docherty, Nancy M

2018-06-01

Schizophrenia researchers have focused on phenomenological aspects of the disorder to better understand its underlying nature. In particular, development of personal narratives-that is, the complexity with which people form, organize, and articulate their "life stories"-has recently been investigated in individuals with schizophrenia. However, less is known about how aspects of narrative relate to indicators of neurocognitive and social functioning. The objective of the present study was to investigate the association of linguistic complexity of life-story narratives to measures of cognitive and social problem-solving abilities among people with schizophrenia. Thirty-two individuals with a diagnosis of schizophrenia completed a research battery consisting of clinical interviews, a life-story narrative, neurocognitive testing, and a measure assessing multiple aspects of social problem solving. Narrative interviews were assessed for linguistic complexity using computerized technology. The results indicate differential relationships of linguistic complexity and neurocognition to domains of social problem-solving skills. More specifically, although neurocognition predicted how well one could both describe and enact a solution to a social problem, linguistic complexity alone was associated with accurately recognizing that a social problem had occurred. In addition, linguistic complexity appears to be a cognitive factor that is discernible from other broader measures of neurocognition. Linguistic complexity may be more relevant in understanding earlier steps of the social problem-solving process than more traditional, broad measures of cognition, and thus is relevant in conceptualizing treatment targets. These findings also support the relevance of developing narrative-focused psychotherapies. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Problem solving using soft systems methodology.

PubMed

Land, L

This article outlines a method of problem solving which considers holistic solutions to complex problems. Soft systems methodology allows people involved in the problem situation to have control over the decision-making process.

Thresholds of Knowledge Development in Complex Problem Solving: A Multiple-Case Study of Advanced Learners' Cognitive Processes

ERIC Educational Resources Information Center

Bogard, Treavor; Liu, Min; Chiang, Yueh-hui Vanessa

2013-01-01

This multiple-case study examined how advanced learners solved a complex problem, focusing on how their frequency and application of cognitive processes contributed to differences in performance outcomes, and developing a mental model of a problem. Fifteen graduate students with backgrounds related to the problem context participated in the study.…

Can Television Enhance Children's Mathematical Problem Solving?

ERIC Educational Resources Information Center

Fisch, Shalom M.; And Others

1994-01-01

A summative evaluation of "Square One TV," an educational mathematics series produced by the Children's Television Workshop, shows that children who regularly viewed the program showed significant improvement in solving unfamiliar, complex mathematical problems, and viewers showed improvement in their mathematical problem-solving ability…

The Complex Route to Success: Complex Problem-Solving Skills in the Prediction of University Success

ERIC Educational Resources Information Center

Stadler, Matthias J.; Becker, Nicolas; Greiff, Samuel; Spinath, Frank M.

2016-01-01

Successful completion of a university degree is a complex matter. Based on considerations regarding the demands of acquiring a university degree, the aim of this paper was to investigate the utility of complex problem-solving (CPS) skills in the prediction of objective and subjective university success (SUS). The key finding of this study was that…

Dynamic Scaffolding in a Cloud-Based Problem Representation System: Empowering Pre-Service Teachers' Problem Solving

ERIC Educational Resources Information Center

Lee, Chwee Beng; Ling, Keck Voon; Reimann, Peter; Diponegoro, Yudho Ahmad; Koh, Chia Heng; Chew, Derwin

2014-01-01

Purpose: The purpose of this paper is to argue for the need to develop pre-service teachers' problem solving ability, in particular, in the context of real-world complex problems. Design/methodology/approach: To argue for the need to develop pre-service teachers' problem solving skills, the authors describe a web-based problem representation…

Complex Problem Solving in L1 Education: Senior High School Students' Knowledge of the Language Problem-Solving Process

ERIC Educational Resources Information Center

van Velzen, Joke H.

2017-01-01

The solving of reasoning problems in first language (L1) education can produce an understanding of language, and student autonomy in language problem solving, both of which are contemporary goals in senior high school education. The purpose of this study was to obtain a better understanding of senior high school students' knowledge of the language…

Complexity in Nature and Society: Complexity Management in the Age of Globalization

NASA Astrophysics Data System (ADS)

Mainzer, Klaus

The theory of nonlinear complex systems has become a proven problem-solving approach in the natural sciences from cosmic and quantum systems to cellular organisms and the brain. Even in modern engineering science self-organizing systems are developed to manage complex networks and processes. It is now recognized that many of our ecological, social, economic, and political problems are also of a global, complex, and nonlinear nature. What are the laws of sociodynamics? Is there a socio-engineering of nonlinear problem solving? What can we learn from nonlinear dynamics for complexity management in social, economic, financial and political systems? Is self-organization an acceptable strategy to handle the challenges of complexity in firms, institutions and other organizations? It is a main thesis of the talk that nature and society are basically governed by nonlinear and complex information dynamics. How computational is sociodynamics? What can we hope for social, economic and political problem solving in the age of globalization?.

Investigating Pre-Service Chemistry Teachers' Problem Solving Strategies: Towards Developing a Framework in Teaching Stoichiometry

ERIC Educational Resources Information Center

Espinosa, Allen A.; Nueva España, Rebecca C.; Marasigan, Arlyne C.

2016-01-01

The present study investigated pre-service chemistry teachers' problem solving strategies and alternative conceptions in solving stoichiometric problems and later on formulate a teaching framework based from the result of the study. The pre-service chemistry teachers were given four stoichiometric problems with increasing complexity and they need…

Problems of Complex Systems: A Model of System Problem Solving Applied to Schools.

ERIC Educational Resources Information Center

Cooke, Robert A.; Rousseau, Denise M.

Research of 25 Michigan elementary and secondary public schools is used to test a model relating organizations' problem-solving adequacy to their available inputs or resources and to the appropriateness of their structures. Problems that all organizations must solve, to avoid disorganization or entropy, include (1) getting inputs and producing…

Complex Problem Solving--More than Reasoning?

ERIC Educational Resources Information Center

Wustenberg, Sascha; Greiff, Samuel; Funke, Joachim

2012-01-01

This study investigates the internal structure and construct validity of Complex Problem Solving (CPS), which is measured by a "Multiple-Item-Approach." It is tested, if (a) three facets of CPS--"rule identification" (adequateness of strategies), "rule knowledge" (generated knowledge) and "rule application"…

Student Learning of Complex Earth Systems: A Model to Guide Development of Student Expertise in Problem-Solving

ERIC Educational Resources Information Center

Holder, Lauren N.; Scherer, Hannah H.; Herbert, Bruce E.

2017-01-01

Engaging students in problem-solving concerning environmental issues in near-surface complex Earth systems involves developing student conceptualization of the Earth as a system and applying that scientific knowledge to the problems using practices that model those used by professionals. In this article, we review geoscience education research…

A complexity theory model in science education problem solving: random walks for working memory and mental capacity.

PubMed

Stamovlasis, Dimitrios; Tsaparlis, Georgios

2003-07-01

The present study examines the role of limited human channel capacity from a science education perspective. A model of science problem solving has been previously validated by applying concepts and tools of complexity theory (the working memory, random walk method). The method correlated the subjects' rank-order achievement scores in organic-synthesis chemistry problems with the subjects' working memory capacity. In this work, we apply the same nonlinear approach to a different data set, taken from chemical-equilibrium problem solving. In contrast to the organic-synthesis problems, these problems are algorithmic, require numerical calculations, and have a complex logical structure. As a result, these problems cause deviations from the model, and affect the pattern observed with the nonlinear method. In addition to Baddeley's working memory capacity, the Pascual-Leone's mental (M-) capacity is examined by the same random-walk method. As the complexity of the problem increases, the fractal dimension of the working memory random walk demonstrates a sudden drop, while the fractal dimension of the M-capacity random walk decreases in a linear fashion. A review of the basic features of the two capacities and their relation is included. The method and findings have consequences for problem solving not only in chemistry and science education, but also in other disciplines.

Simple and complex mental subtraction: strategy choice and speed-of-processing differences in younger and older adults.

PubMed

Geary, D C; Frensch, P A; Wiley, J G

1993-06-01

Thirty-six younger adults (10 male, 26 female; ages 18 to 38 years) and 36 older adults (14 male, 22 female; ages 61 to 80 years) completed simple and complex paper-and-pencil subtraction tests and solved a series of simple and complex computer-presented subtraction problems. For the computer task, strategies and solution times were recorded on a trial-by-trial basis. Older Ss used a developmentally more mature mix of problem-solving strategies to solve both simple and complex subtraction problems. Analyses of component scores derived from the solution times suggest that the older Ss are slower at number encoding and number production but faster at executing the borrow procedure. In contrast, groups did not appear to differ in the speed of subtraction fact retrieval. Results from a computational simulation are consistent with the interpretation that older adults' advantage for strategy choices and for the speed of executing the borrow procedure might result from more practice solving subtraction problems.

Complex collaborative problem-solving processes in mission control.

PubMed

Fiore, Stephen M; Wiltshire, Travis J; Oglesby, James M; O'Keefe, William S; Salas, Eduardo

2014-04-01

NASA's Mission Control Center (MCC) is responsible for control of the International Space Station (ISS), which includes responding to problems that obstruct the functioning of the ISS and that may pose a threat to the health and well-being of the flight crew. These problems are often complex, requiring individuals, teams, and multiteam systems, to work collaboratively. Research is warranted to examine individual and collaborative problem-solving processes in this context. Specifically, focus is placed on how Mission Control personnel-each with their own skills and responsibilities-exchange information to gain a shared understanding of the problem. The Macrocognition in Teams Model describes the processes that individuals and teams undertake in order to solve problems and may be applicable to Mission Control teams. Semistructured interviews centering on a recent complex problem were conducted with seven MCC professionals. In order to assess collaborative problem-solving processes in MCC with those predicted by the Macrocognition in Teams Model, a coding scheme was developed to analyze the interview transcriptions. Findings are supported with excerpts from participant transcriptions and suggest that team knowledge-building processes accounted for approximately 50% of all coded data and are essential for successful collaborative problem solving in mission control. Support for the internalized and externalized team knowledge was also found (19% and 20%, respectively). The Macrocognition in Teams Model was shown to be a useful depiction of collaborative problem solving in mission control and further research with this as a guiding framework is warranted.

Development and validation of a physics problem-solving assessment rubric

NASA Astrophysics Data System (ADS)

Docktor, Jennifer Lynn

Problem solving is a complex process that is important for everyday life and crucial for learning physics. Although there is a great deal of effort to improve student problem solving throughout the educational system, there is no standard way to evaluate written problem solving that is valid, reliable, and easy to use. Most tests of problem solving performance given in the classroom focus on the correctness of the end result or partial results rather than the quality of the procedures and reasoning leading to the result, which gives an inadequate description of a student's skills. A more detailed and meaningful measure is necessary if different curricular materials or pedagogies are to be compared. This measurement tool could also allow instructors to diagnose student difficulties and focus their coaching. It is important that the instrument be applicable to any problem solving format used by a student and to a range of problem types and topics typically used by instructors. Typically complex processes such as problem solving are assessed by using a rubric, which divides a skill into multiple quasi-independent categories and defines criteria to attain a score in each. This dissertation describes the development of a problem solving rubric for the purpose of assessing written solutions to physics problems and presents evidence for the validity, reliability, and utility of score interpretations on the instrument.

Working Memory, Visual-Spatial-Intelligence and Their Relationship to Problem-Solving

ERIC Educational Resources Information Center

Buhner, Markus; Kroner, Stephan; Ziegler, Matthias

2008-01-01

The relationship between working memory, intelligence and problem-solving is explored. Wittmann and Suss [Wittmann, W.W., & Suss, H.M. (1999). Investigating the paths between working memory, intelligence, knowledge, and complex problem-solving performances via Brunswik symmetry. In P.L. Ackerman, R.D. Roberts (Ed.), "Learning and individual…

The Role of Problem Solving in Complex Intraverbal Repertoires

ERIC Educational Resources Information Center

Sautter, Rachael A.; LeBlanc, Linda A.; Jay, Allison A.; Goldsmith, Tina R.; Carr, James E.

2011-01-01

We examined whether typically developing preschoolers could learn to use a problem-solving strategy that involved self-prompting with intraverbal chains to provide multiple responses to intraverbal categorization questions. Teaching the children to use the problem-solving strategy did not produce significant increases in target responses until…

The Future Problem Solving Program.

ERIC Educational Resources Information Center

Crabbe, Anne B.

1989-01-01

Describes the Future Problem Solving Program, in which students from the U.S. and around the world are tackling some complex challenges facing society, ranging from acid rain to terrorism. The program uses a creative problem solving process developed for business and industry. A sixth-grade toxic waste cleanup project illustrates the process.…

Coaching Family Caregivers to Become Better Problem Solvers When Caring for Persons with Advanced Cancer.

PubMed

Dionne-Odom, J Nicholas; Lyons, Kathleen D; Akyar, Imatullah; Bakitas, Marie A

2016-01-01

Family caregivers of persons with advanced cancer often take on responsibilities that present daunting and complex problems. Serious problems that go unresolved may be burdensome and result in negative outcomes for caregivers' psychological and physical health and affect the quality of care delivered to the care recipients with cancer, especially at the end of life. Formal problem-solving training approaches have been developed over the past several decades to assist individuals with managing problems faced in daily life. Several of these problem-solving principles and techniques were incorporated into ENABLE (Educate, Nurture, Advise, Before Life End), an "early" palliative care telehealth intervention for individuals diagnosed with advanced cancer and their family caregivers. A hypothetical case resembling the situations of actual caregiver participants in ENABLE that exemplifies the complex problems that caregivers face is presented, followed by presentation of an overview of ENABLE's problem-solving key principles, techniques, and steps in problem-solving support. Though more research is needed to formally test the use of problem-solving support in social work practice, social workers can easily incorporate these techniques into everyday practice.

From Poor Performance to Success under Stress: Working Memory, Strategy Selection, and Mathematical Problem Solving under Pressure

ERIC Educational Resources Information Center

Beilock, Sian L.; DeCaro, Marci S.

2007-01-01

Two experiments demonstrate how individual differences in working memory (WM) impact the strategies used to solve complex math problems and how consequential testing situations alter strategy use. In Experiment 1, individuals performed multistep math problems under low- or high-pressure conditions and reported their problem-solving strategies.…

The Roles of Internal Representation and Processing in Problem Solving Involving Insight: A Computational Complexity Perspective

ERIC Educational Resources Information Center

Wareham, Todd

2017-01-01

In human problem solving, there is a wide variation between individuals in problem solution time and success rate, regardless of whether or not this problem solving involves insight. In this paper, we apply computational and parameterized analysis to a plausible formalization of extended representation change theory (eRCT), an integration of…

Individual Differences in Students' Complex Problem Solving Skills: How They Evolve and What They Imply

ERIC Educational Resources Information Center

Wüstenberg, Sascha; Greiff, Samuel; Vainikainen, Mari-Pauliina; Murphy, Kevin

2016-01-01

Changes in the demands posed by increasingly complex workplaces in the 21st century have raised the importance of nonroutine skills such as complex problem solving (CPS). However, little is known about the antecedents and outcomes of CPS, especially with regard to malleable external factors such as classroom climate. To investigate the relations…

Efficient dual approach to distance metric learning.

PubMed

Shen, Chunhua; Kim, Junae; Liu, Fayao; Wang, Lei; van den Hengel, Anton

2014-02-01

Distance metric learning is of fundamental interest in machine learning because the employed distance metric can significantly affect the performance of many learning methods. Quadratic Mahalanobis metric learning is a popular approach to the problem, but typically requires solving a semidefinite programming (SDP) problem, which is computationally expensive. The worst case complexity of solving an SDP problem involving a matrix variable of size D×D with O(D) linear constraints is about O(D(6.5)) using interior-point methods, where D is the dimension of the input data. Thus, the interior-point methods only practically solve problems exhibiting less than a few thousand variables. Because the number of variables is D(D+1)/2, this implies a limit upon the size of problem that can practically be solved around a few hundred dimensions. The complexity of the popular quadratic Mahalanobis metric learning approach thus limits the size of problem to which metric learning can be applied. Here, we propose a significantly more efficient and scalable approach to the metric learning problem based on the Lagrange dual formulation of the problem. The proposed formulation is much simpler to implement, and therefore allows much larger Mahalanobis metric learning problems to be solved. The time complexity of the proposed method is roughly O(D(3)), which is significantly lower than that of the SDP approach. Experiments on a variety of data sets demonstrate that the proposed method achieves an accuracy comparable with the state of the art, but is applicable to significantly larger problems. We also show that the proposed method can be applied to solve more general Frobenius norm regularized SDP problems approximately.

Aiding the search: Examining individual differences in multiply-constrained problem solving.

PubMed

Ellis, Derek M; Brewer, Gene A

2018-07-01

Understanding and resolving complex problems is of vital importance in daily life. Problems can be defined by the limitations they place on the problem solver. Multiply-constrained problems are traditionally examined with the compound remote associates task (CRAT). Performance on the CRAT is partially dependent on an individual's working memory capacity (WMC). These findings suggest that executive processes are critical for problem solving and that there are reliable individual differences in multiply-constrained problem solving abilities. The goals of the current study are to replicate and further elucidate the relation between WMC and CRAT performance. To achieve these goals, we manipulated preexposure to CRAT solutions and measured WMC with complex-span tasks. In Experiment 1, we report evidence that preexposure to CRAT solutions improved problem solving accuracy, WMC was correlated with problem solving accuracy, and that WMC did not moderate the effect of preexposure on problem solving accuracy. In Experiment 2, we preexposed participants to correct and incorrect solutions. We replicated Experiment 1 and found that WMC moderates the effect of exposure to CRAT solutions such that high WMC participants benefit more from preexposure to correct solutions than low WMC (although low WMC participants have preexposure benefits as well). Broadly, these results are consistent with theories of working memory and problem solving that suggest a mediating role of attention control processes. Published by Elsevier Inc.

Controlling Uncertainty: A Review of Human Behavior in Complex Dynamic Environments

ERIC Educational Resources Information Center

Osman, Magda

2010-01-01

Complex dynamic control (CDC) tasks are a type of problem-solving environment used for examining many cognitive activities (e.g., attention, control, decision making, hypothesis testing, implicit learning, memory, monitoring, planning, and problem solving). Because of their popularity, there have been many findings from diverse domains of research…

The Design Process in the Art Classroom: Building Problem Solving Skills for Life and Careers

ERIC Educational Resources Information Center

Vande Zande, Robin; Warnock, Lauren; Nikoomanesh, Barbara; Van Dexter, Kurt

2014-01-01

Problem solving is essential to everyone's life. People survive if they are nourished, sheltered, and protected--and they construct ways to obtain nourishment, shelter, and protection through problem solving. Though problems vary in complexity--survival at the one end and the pursuit of comfort at the other--we are reliant on our ability to…

The Universal Traveler, A Soft-Systems Guide to: Creativity, Problem Solving, and the Process of Reaching Goals. [Revised Edition.

ERIC Educational Resources Information Center

Koberg, Don; Bagnall, Jim

This publication provides an organizational scheme for a creative problem solving process. The authors indicate that all problems can benefit from the same logical and orderly process now employed to solve many complex problems. The principles remain constant; only specific methods change. Chapter 1 analyzes the development of creativity and fear…

High School Students' Use of Meiosis When Solving Genetics Problems.

ERIC Educational Resources Information Center

Wynne, Cynthia F.; Stewart, Jim; Passmore, Cindy

2001-01-01

Paints a different picture of students' reasoning with meiosis as they solved complex, computer-generated genetics problems, some of which required them to revise their understanding of meiosis in response to anomalous data. Students were able to develop a rich understanding of meiosis and can utilize that knowledge to solve genetics problems.…

Toward Group Problem Solving Guidelines for 21st Century Teams

ERIC Educational Resources Information Center

Ranieri, Kathryn L.

2004-01-01

Effective problem-solving skills are critical in dealing with ambiguous and often complex issues in the present-day leaner and globally diverse organizations. Yet respected, well-established problem-solving models may be misaligned within the current work environment, particularly within a team context. Models learned from a more bureaucratic,…

Students Problem-Solving Difficulties and Implications in Physics: An Empirical Study on Influencing Factors

ERIC Educational Resources Information Center

Reddy, M. Vijaya Bhaskara; Panacharoensawad, Buncha

2017-01-01

In twenty first century, abundant innovative tools have been identified by the researchers to evaluate the conceptual understandings, problem solving, beliefs and attitudes about physics. Nevertheless, lacking of wide variety of evaluation instruments with respect to problem solving in physics. It indicates that the complexity of the domain fields…

SOFIA's Choice: Automating the Scheduling of Airborne Observations

NASA Technical Reports Server (NTRS)

Frank, Jeremy; Norvig, Peter (Technical Monitor)

1999-01-01

This paper describes the problem of scheduling observations for an airborne telescope. Given a set of prioritized observations to choose from, and a wide range of complex constraints governing legitimate choices and orderings, how can we efficiently and effectively create a valid flight plan which supports high priority observations? This problem is quite different from scheduling problems which are routinely solved automatically in industry. For instance, the problem requires making choices which lead to other choices later, and contains many interacting complex constraints over both discrete and continuous variables. Furthermore, new types of constraints may be added as the fundamental problem changes. As a result of these features, this problem cannot be solved by traditional scheduling techniques. The problem resembles other problems in NASA and industry, from observation scheduling for rovers and other science instruments to vehicle routing. The remainder of the paper is organized as follows. In 2 we describe the observatory in order to provide some background. In 3 we describe the problem of scheduling a single flight. In 4 we compare flight planning and other scheduling problems and argue that traditional techniques are not sufficient to solve this problem. We also mention similar complex scheduling problems which may benefit from efforts to solve this problem. In 5 we describe an approach for solving this problem based on research into a similar problem, that of scheduling observations for a space-borne probe. In 6 we discuss extensions of the flight planning problem as well as other problems which are similar to flight planning. In 7 we conclude and discuss future work.

Insight and analysis problem solving in microbes to machines.

PubMed

Clark, Kevin B

2015-11-01

A key feature for obtaining solutions to difficult problems, insight is oftentimes vaguely regarded as a special discontinuous intellectual process and/or a cognitive restructuring of problem representation or goal approach. However, this nearly century-old state of art devised by the Gestalt tradition to explain the non-analytical or non-trial-and-error, goal-seeking aptitude of primate mentality tends to neglect problem-solving capabilities of lower animal phyla, Kingdoms other than Animalia, and advancing smart computational technologies built from biological, artificial, and composite media. Attempting to provide an inclusive, precise definition of insight, two major criteria of insight, discontinuous processing and problem restructuring, are here reframed using terminology and statistical mechanical properties of computational complexity classes. Discontinuous processing becomes abrupt state transitions in algorithmic/heuristic outcomes or in types of algorithms/heuristics executed by agents using classical and/or quantum computational models. And problem restructuring becomes combinatorial reorganization of resources, problem-type substitution, and/or exchange of computational models. With insight bounded by computational complexity, humans, ciliated protozoa, and complex technological networks, for example, show insight when restructuring time requirements, combinatorial complexity, and problem type to solve polynomial and nondeterministic polynomial decision problems. Similar effects are expected from other problem types, supporting the idea that insight might be an epiphenomenon of analytical problem solving and consequently a larger information processing framework. Thus, this computational complexity definition of insight improves the power, external and internal validity, and reliability of operational parameters with which to classify, investigate, and produce the phenomenon for computational agents ranging from microbes to man-made devices. Copyright © 2015 Elsevier Ltd. All rights reserved.

Problem solving in great apes (Pan paniscus, Pan troglodytes, Gorilla gorilla, and Pongo abelii): the effect of visual feedback.

PubMed

Völter, Christoph J; Call, Josep

2012-09-01

What kind of information animals use when solving problems is a controversial topic. Previous research suggests that, in some situations, great apes prefer to use causally relevant cues over arbitrary ones. To further examine to what extent great apes are able to use information about causal relations, we presented three different puzzle box problems to the four nonhuman great ape species. Of primary interest here was a comparison between one group of apes that received visual access to the functional mechanisms of the puzzle boxes and one group that did not. Apes' performance in the first two, less complex puzzle boxes revealed that they are able to solve such problems by means of trial-and-error learning, requiring no information about the causal structure of the problem. However, visual inspection of the functional mechanisms of the puzzle boxes reduced the amount of time needed to solve the problems. In the case of the most complex problem, which required the use of a crank, visual feedback about what happened when the handle of the crank was turned was necessary for the apes to solve the task. Once the solution was acquired, however, visual feedback was no longer required. We conclude that visual feedback about the consequences of their actions helps great apes to solve complex problems. As the crank task matches the basic requirements of vertical string pulling in birds, the present results are discussed in light of recent findings with corvids.

Utilizing a Sense of Community Theory in Order to Optimize Interagency Response to Complex Contingencies

DTIC Science & Technology

2010-06-01

of Not at all Somewhat Mostly Completely membership such as clothes , signs, art, architecture, logos , landmarks, and flags that people can...on a ?whole of nation? approach to solving complex problems. Psychological sense of community (PSOC) theory provides the link that explains how an...States during complex contingency operations depends on a “whole of nation” approach to solving complex problems. Psychological sense of community

Self-Regulation in the Midst of Complexity: A Case Study of High School Physics Students Engaged in Ill-Structured Problem Solving

ERIC Educational Resources Information Center

Milbourne, Jeffrey David

2016-01-01

The purpose of this dissertation study was to explore the experiences of high school physics students who were solving complex, ill-structured problems, in an effort to better understand how self-regulatory behavior mediated the project experience. Consistent with Voss, Green, Post, and Penner's (1983) conception of an ill-structured problem in…

Decision-Making and Problem-Solving Approaches in Pharmacy Education

PubMed Central

Martin, Lindsay C.; Holdford, David A.

2016-01-01

Domain 3 of the Center for the Advancement of Pharmacy Education (CAPE) 2013 Educational Outcomes recommends that pharmacy school curricula prepare students to be better problem solvers, but are silent on the type of problems they should be prepared to solve. We identified five basic approaches to problem solving in the curriculum at a pharmacy school: clinical, ethical, managerial, economic, and legal. These approaches were compared to determine a generic process that could be applied to all pharmacy decisions. Although there were similarities in the approaches, generic problem solving processes may not work for all problems. Successful problem solving requires identification of the problems faced and application of the right approach to the situation. We also advocate that the CAPE Outcomes make explicit the importance of different approaches to problem solving. Future pharmacists will need multiple approaches to problem solving to adapt to the complexity of health care. PMID:27170823

Decision-Making and Problem-Solving Approaches in Pharmacy Education.

PubMed

Martin, Lindsay C; Donohoe, Krista L; Holdford, David A

2016-04-25

Domain 3 of the Center for the Advancement of Pharmacy Education (CAPE) 2013 Educational Outcomes recommends that pharmacy school curricula prepare students to be better problem solvers, but are silent on the type of problems they should be prepared to solve. We identified five basic approaches to problem solving in the curriculum at a pharmacy school: clinical, ethical, managerial, economic, and legal. These approaches were compared to determine a generic process that could be applied to all pharmacy decisions. Although there were similarities in the approaches, generic problem solving processes may not work for all problems. Successful problem solving requires identification of the problems faced and application of the right approach to the situation. We also advocate that the CAPE Outcomes make explicit the importance of different approaches to problem solving. Future pharmacists will need multiple approaches to problem solving to adapt to the complexity of health care.

Diverse knowledges and competing interests: an essay on socio-technical problem-solving.

PubMed

di Norcia, Vincent

2002-01-01

Solving complex socio-technical problems, this paper claims, involves diverse knowledges (cognitive diversity), competing interests (social diversity), and pragmatism. To explain this view, this paper first explores two different cases: Canadian pulp and paper mill pollution and siting nuclear reactors in systematically sensitive areas of California. Solving such socio-technically complex problems involves cognitive diversity as well as social diversity and pragmatism. Cognitive diversity requires one to not only recognize relevant knowledges but also to assess their validity. Finally, it is suggested, integrating the resultant set of diverse relevant and valid knowledges determines the parameters of the solution space for the problem.

Verification of Algebra Step Problems: A Chronometric Study of Human Problem Solving. Technical Report No. 253. Psychology and Education Series.

ERIC Educational Resources Information Center

Matthews, Paul G.; Atkinson, Richard C.

This paper reports an experiment designed to test theoretical relations among fast problem solving, more complex and slower problem solving, and research concerning fundamental memory processes. Using a cathode ray tube, subjects were presented with propositions of the form "Y is in list X" which they memorized. In later testing they were asked to…

Students' Explanations in Complex Learning of Disciplinary Programming

ERIC Educational Resources Information Center

Vieira, Camilo

2016-01-01

Computational Science and Engineering (CSE) has been denominated as the third pillar of science and as a set of important skills to solve the problems of a global society. Along with the theoretical and the experimental approaches, computation offers a third alternative to solve complex problems that require processing large amounts of data, or…

Computer-Based Assessment of Complex Problem Solving: Concept, Implementation, and Application

ERIC Educational Resources Information Center

Greiff, Samuel; Wustenberg, Sascha; Holt, Daniel V.; Goldhammer, Frank; Funke, Joachim

2013-01-01

Complex Problem Solving (CPS) skills are essential to successfully deal with environments that change dynamically and involve a large number of interconnected and partially unknown causal influences. The increasing importance of such skills in the 21st century requires appropriate assessment and intervention methods, which in turn rely on adequate…

Calculating Probabilistic Distance to Solution in a Complex Problem Solving Domain

ERIC Educational Resources Information Center

Sudol, Leigh Ann; Rivers, Kelly; Harris, Thomas K.

2012-01-01

In complex problem solving domains, correct solutions are often comprised of a combination of individual components. Students usually go through several attempts, each attempt reflecting an individual solution state that can be observed during practice. Classic metrics to measure student performance over time rely on counting the number of…

The Development of Complex Problem Solving in Adolescence: A Latent Growth Curve Analysis

ERIC Educational Resources Information Center

Frischkorn, Gidon T.; Greiff, Samuel; Wüstenberg, Sascha

2014-01-01

Complex problem solving (CPS) as a cross-curricular competence has recently attracted more attention in educational psychology as indicated by its implementation in international educational large-scale assessments such as the Programme for International Student Assessment. However, research on the development of CPS is scarce, and the few…

Validity of the MicroDYN Approach: Complex Problem Solving Predicts School Grades beyond Working Memory Capacity

ERIC Educational Resources Information Center

Schweizer, Fabian; Wustenberg, Sascha; Greiff, Samuel

2013-01-01

This study examines the validity of the complex problem solving (CPS) test MicroDYN by investigating a) the relation between its dimensions--rule identification (exploration strategy), rule knowledge (acquired knowledge), rule application (control performance)--and working memory capacity (WMC), and b) whether CPS predicts school grades in…

Coaching Family Caregivers to become Better Problem Solvers when Caring for Persons with Advanced Cancer

PubMed Central

Dionne-Odom, J. Nicholas; Lyons, Kathleen D.; Akyar, Imatullah; Bakitas, Marie

2016-01-01

Family caregivers of persons with advanced cancer often take on responsibilities that present daunting and complex problems. Serious problems that go unresolved may be burdensome and result in negative outcomes for caregivers’ psychological and physical health and affect the quality of care delivered to the care recipients with cancer, especially at the end of life. Formal problem-solving training approaches have been developed over the past several decades to assist individuals with managing problems faced in daily life. Several of these problem-solving principles and techniques were incorporated into ENABLE (Educate, Nurture, Advise, Before Life End), an ‘early’ palliative care telehealth intervention for individuals diagnosed with advanced cancer and their family caregivers. A hypothetical case resembling the situations of actual caregiver participants in ENABLE that exemplifies the complex problems that caregivers face is presented followed by presentation of an overview of ENABLE’s problem-solving key principles, techniques and steps in problem-solving support. Though more research is needed to formally test the use of problem-solving support in social work practice, social workers can easily incorporate these techniques into everyday practice. PMID:27143574

Problem Solving in Technology Rich Contexts: Mathematics Sense Making in Out-of-School Environments

ERIC Educational Resources Information Center

Lowrie, Tom

2005-01-01

This investigation describes the way in which a case study participant (aged 7) represented, posed and solved problems in a technology game-based environment. The out-of-school problem-solving context placed numeracy demands on the participant that were more complex and sophisticated than the type of mathematics experiences he encountered in…

Learning Problem-Solving through Making Games at the Game Design and Learning Summer Program

ERIC Educational Resources Information Center

Akcaoglu, Mete

2014-01-01

Today's complex and fast-evolving world necessitates young students to possess design and problem-solving skills more than ever. One alternative method of teaching children problem-solving or thinking skills has been using computer programming, and more recently, game-design tasks. In this pre-experimental study, a group of middle school…

The Effects of Successful versus Failure-Based Cases on Argumentation while Solving Decision-Making Problems

ERIC Educational Resources Information Center

Tawfik, Andrew; Jonassen, David

2013-01-01

Solving complex, ill-structured problems may be effectively supported by case-based reasoning through case libraries that provide just-in-time domain-specific principles in the form of stories. The cases not only articulate previous experiences of practitioners, but also serve as problem-solving narratives from which learners can acquire meaning.…

Training Preschool Children to Use Visual Imagining as a Problem-Solving Strategy for Complex Categorization Tasks

ERIC Educational Resources Information Center

Kisamore, April N.; Carr, James E.; LeBlanc, Linda A.

2011-01-01

It has been suggested that verbally sophisticated individuals engage in a series of precurrent behaviors (e.g., covert intraverbal behavior, grouping stimuli, visual imagining) to solve problems such as answering questions (Palmer, 1991; Skinner, 1953). We examined the effects of one problem solving strategy--visual imagining--on increasing…

Socio-Demographic and Practice-Oriented Factors Related to Proficiency in Problem Solving: A Lifelong Learning Perspective

ERIC Educational Resources Information Center

Desjardins, Richard; Ederer, Peer

2015-01-01

This article explores the relative importance of different socio-demographic and practice-oriented factors that are related to proficiency in problem solving in technology-rich environments (PSTREs) and by extension may be related to complex problem solving (CPS). The empirical analysis focuses on the proficiency measurements of PSTRE made…

Inducing mental set constrains procedural flexibility and conceptual understanding in mathematics.

PubMed

DeCaro, Marci S

2016-10-01

An important goal in mathematics is to flexibly use and apply multiple, efficient procedures to solve problems and to understand why these procedures work. One factor that may limit individuals' ability to notice and flexibly apply strategies is the mental set induced by the problem context. Undergraduate (N = 41, Experiment 1) and fifth- and sixth-grade students (N = 87, Experiment 2) solved mathematical equivalence problems in one of two set-inducing conditions. Participants in the complex-first condition solved problems without a repeated addend on both sides of the equal sign (e.g., 7 + 5 + 9 = 3 + _), which required multistep strategies. Then these students solved problems with a repeated addend (e.g., 7 + 5 + 9 = 7 + _), for which a shortcut strategy could be readily used (i.e., adding 5 + 9). Participants in the shortcut-first condition solved the same problem set but began with the shortcut problems. Consistent with laboratory studies of mental set, participants in the complex-first condition were less likely to use the more efficient shortcut strategy when possible. In addition, these participants were less likely to demonstrate procedural flexibility and conceptual understanding on a subsequent assessment of mathematical equivalence knowledge. These findings suggest that certain problem-solving contexts can help or hinder both flexibility in strategy use and deeper conceptual thinking about the problems.

Designing for Decision Making

ERIC Educational Resources Information Center

Jonassen, David H.

2012-01-01

Decision making is the most common kind of problem solving. It is also an important component skill in other more ill-structured and complex kinds of problem solving, including policy problems and design problems. There are different kinds of decisions, including choices, acceptances, evaluations, and constructions. After describing the centrality…

Discovering Steiner Triple Systems through Problem Solving

ERIC Educational Resources Information Center

Sriraman, Bharath

2004-01-01

An attempt to implement problem solving as a teacher of ninth grade algebra is described. The problems selected were not general ones, they involved combinations and represented various situations and were more complex which lead to the discovery of Steiner triple systems.

The Problems with Problem Solving: Reflections on the Rise, Current Status, and Possible Future of a Cognitive Research Paradigm

ERIC Educational Resources Information Center

Ohlsson, Stellan

2012-01-01

The research paradigm invented by Allen Newell and Herbert A. Simon in the late 1950s dominated the study of problem solving for more than three decades. But in the early 1990s, problem solving ceased to drive research on complex cognition. As part of this decline, Newell and Simon's most innovative research practices--especially their method for…

Next gen perception and cognition: augmenting perception and enhancing cognition through mobile technologies

NASA Astrophysics Data System (ADS)

Goma, Sergio R.

2015-03-01

In current times, mobile technologies are ubiquitous and the complexity of problems is continuously increasing. In the context of advancement of engineering, we explore in this paper possible reasons that could cause a saturation in technology evolution - namely the ability of problem solving based on previous results and the ability of expressing solutions in a more efficient way, concluding that `thinking outside of brain' - as in solving engineering problems that are expressed in a virtual media due to their complexity - would benefit from mobile technology augmentation. This could be the necessary evolutionary step that would provide the efficiency required to solve new complex problems (addressing the `running out of time' issue) and remove the communication of results barrier (addressing the human `perception/expression imbalance' issue). Some consequences are discussed, as in this context the artificial intelligence becomes an automation tool aid instead of a necessary next evolutionary step. The paper concludes that research in modeling as problem solving aid and data visualization as perception aid augmented with mobile technologies could be the path to an evolutionary step in advancing engineering.

Application of NASA management approach to solve complex problems on earth

NASA Technical Reports Server (NTRS)

Potate, J. S.

1972-01-01

The application of NASA management approach to solving complex problems on earth is discussed. The management of the Apollo program is presented as an example of effective management techniques. Four key elements of effective management are analyzed. Photographs of the Cape Kennedy launch sites and supporting equipment are included to support the discussions.

Spawning Ideas--Moving from Ideas to Action: Quality Tools for Collective Problem-Solving and Continuous Learning.

ERIC Educational Resources Information Center

Flor, Richard F.; Troskey, Matthew D.

This paper explores the dynamics of managing collective problem solving and decision making, and the application of tools and strategies to deal with the emergent complexity of systems in which educators work. Schools and educational programs are complex adaptive systems that respond to changes in internal and external environments. Functioning…

Complex Problem Solving in Educational Contexts--Something beyond "g": Concept, Assessment, Measurement Invariance, and Construct Validity

ERIC Educational Resources Information Center

Greiff, Samuel; Wustenberg, Sascha; Molnar, Gyongyver; Fischer, Andreas; Funke, Joachim; Csapo, Beno

2013-01-01

Innovative assessments of cross-curricular competencies such as complex problem solving (CPS) have currently received considerable attention in large-scale educational studies. This study investigated the nature of CPS by applying a state-of-the-art approach to assess CPS in high school. We analyzed whether two processes derived from cognitive…

Learning by Preparing to Teach: Fostering Self-Regulatory Processes and Achievement during Complex Mathematics Problem Solving

ERIC Educational Resources Information Center

Muis, Krista R.; Psaradellis, Cynthia; Chevrier, Marianne; Di Leo, Ivana; Lajoie, Susanne P.

2016-01-01

We developed an intervention based on the learning by teaching paradigm to foster self-regulatory processes and better learning outcomes during complex mathematics problem solving in a technology-rich learning environment. Seventy-eight elementary students were randomly assigned to 1 of 2 conditions: learning by preparing to teach, or learning for…

Differential Relations between Facets of Complex Problem Solving and Students' Immigration Background

ERIC Educational Resources Information Center

Sonnleitner, Philipp; Brunner, Martin; Keller, Ulrich; Martin, Romain

2014-01-01

Whereas the assessment of complex problem solving (CPS) has received increasing attention in the context of international large-scale assessments, its fairness in regard to students' cultural background has gone largely unexplored. On the basis of a student sample of 9th-graders (N = 299), including a representative number of immigrant students (N…

What Do Employers Pay for Employees' Complex Problem Solving Skills?

ERIC Educational Resources Information Center

Ederer, Peer; Nedelkoska, Ljubica; Patt, Alexander; Castellazzi, Silvia

2015-01-01

We estimate the market value that employers assign to the complex problem solving (CPS) skills of their employees, using individual-level Mincer-style wage regressions. For the purpose of the study, we collected new and unique data using psychometric measures of CPS and an extensive background questionnaire on employees' personal and work history.…

Assessment of Complex Problem Solving: What We Know and What We Don't Know

ERIC Educational Resources Information Center

Herde, Christoph Nils; Wüstenberg, Sascha; Greiff, Samuel

2016-01-01

Complex Problem Solving (CPS) is seen as a cross-curricular 21st century skill that has attracted interest in large-scale-assessments. In the Programme for International Student Assessment (PISA) 2012, CPS was assessed all over the world to gain information on students' skills to acquire and apply knowledge while dealing with nontransparent…

Examining the Effects of Principals' Transformational Leadership on Teachers' Creative Practices and Students' Performance in Problem-Solving

ERIC Educational Resources Information Center

Owoh, Jeremy Strickland

2015-01-01

In today's technology enriched schools and workforces, creative problem-solving is involved in many aspects of a person's life. The educational systems of developed nations are designed to raise students who are creative and skillful in solving complex problems. Technology and the age of information require nations to develop generations of…

Quantum Computing: Solving Complex Problems

ScienceCinema

DiVincenzo, David

2018-05-22

One of the motivating ideas of quantum computation was that there could be a new kind of machine that would solve hard problems in quantum mechanics. There has been significant progress towards the experimental realization of these machines (which I will review), but there are still many questions about how such a machine could solve computational problems of interest in quantum physics. New categorizations of the complexity of computational problems have now been invented to describe quantum simulation. The bad news is that some of these problems are believed to be intractable even on a quantum computer, falling into a quantum analog of the NP class. The good news is that there are many other new classifications of tractability that may apply to several situations of physical interest.

Arithmetic Word-Problem-Solving in Huntington's Disease

ERIC Educational Resources Information Center

Allain, P.; Verny, C.; Aubin, G.; Pinon, K.; Bonneau, D.; Dubas, F.; Gall, D.L.

2005-01-01

The purpose of this study was to examine executive functioning in patients with Huntington's disease using an arithmetic word-problem-solving task including eight solvable problems of increasing complexity and four aberrant problems. Ten patients with Huntington's disease and 12 normal control subjects matched by age and education were tested.…

Complex Problem Solving in Teams: The Impact of Collective Orientation on Team Process Demands.

PubMed

Hagemann, Vera; Kluge, Annette

2017-01-01

Complex problem solving is challenging and a high-level cognitive process for individuals. When analyzing complex problem solving in teams, an additional, new dimension has to be considered, as teamwork processes increase the requirements already put on individual team members. After introducing an idealized teamwork process model, that complex problem solving teams pass through, and integrating the relevant teamwork skills for interdependently working teams into the model and combining it with the four kinds of team processes (transition, action, interpersonal, and learning processes), the paper demonstrates the importance of fulfilling team process demands for successful complex problem solving within teams. Therefore, results from a controlled team study within complex situations are presented. The study focused on factors that influence action processes, like coordination, such as emergent states like collective orientation, cohesion, and trust and that dynamically enable effective teamwork in complex situations. Before conducting the experiments, participants were divided by median split into two-person teams with either high ( n = 58) or low ( n = 58) collective orientation values. The study was conducted with the microworld C3Fire, simulating dynamic decision making, and acting in complex situations within a teamwork context. The microworld includes interdependent tasks such as extinguishing forest fires or protecting houses. Two firefighting scenarios had been developed, which takes a maximum of 15 min each. All teams worked on these two scenarios. Coordination within the team and the resulting team performance were calculated based on a log-file analysis. The results show that no relationships between trust and action processes and team performance exist. Likewise, no relationships were found for cohesion. Only collective orientation of team members positively influences team performance in complex environments mediated by action processes such as coordination within the team. The results are discussed in relation to previous empirical findings and to learning processes within the team with a focus on feedback strategies.

Complex Problem Solving in Teams: The Impact of Collective Orientation on Team Process Demands

PubMed Central

Hagemann, Vera; Kluge, Annette

2017-01-01

Complex problem solving is challenging and a high-level cognitive process for individuals. When analyzing complex problem solving in teams, an additional, new dimension has to be considered, as teamwork processes increase the requirements already put on individual team members. After introducing an idealized teamwork process model, that complex problem solving teams pass through, and integrating the relevant teamwork skills for interdependently working teams into the model and combining it with the four kinds of team processes (transition, action, interpersonal, and learning processes), the paper demonstrates the importance of fulfilling team process demands for successful complex problem solving within teams. Therefore, results from a controlled team study within complex situations are presented. The study focused on factors that influence action processes, like coordination, such as emergent states like collective orientation, cohesion, and trust and that dynamically enable effective teamwork in complex situations. Before conducting the experiments, participants were divided by median split into two-person teams with either high (n = 58) or low (n = 58) collective orientation values. The study was conducted with the microworld C3Fire, simulating dynamic decision making, and acting in complex situations within a teamwork context. The microworld includes interdependent tasks such as extinguishing forest fires or protecting houses. Two firefighting scenarios had been developed, which takes a maximum of 15 min each. All teams worked on these two scenarios. Coordination within the team and the resulting team performance were calculated based on a log-file analysis. The results show that no relationships between trust and action processes and team performance exist. Likewise, no relationships were found for cohesion. Only collective orientation of team members positively influences team performance in complex environments mediated by action processes such as coordination within the team. The results are discussed in relation to previous empirical findings and to learning processes within the team with a focus on feedback strategies. PMID:29033886

Cross-national comparisons of complex problem-solving strategies in two microworlds.

PubMed

Güss, C Dominik; Tuason, Ma Teresa; Gerhard, Christiane

2010-04-01

Research in the fields of complex problem solving (CPS) and dynamic decision making using microworlds has been mainly conducted in Western industrialized countries. This study analyzes the CPS process by investigating thinking-aloud protocols in five countries. Participants were 511 students from Brazil, Germany, India, the Philippines, and the United States who worked on two microworlds. On the basis of cultural-psychological theories, specific cross-national differences in CPS strategies were hypothesized. Following theories of situatedness of cognition, hypotheses about the specific frequency of problem-solving strategies in the two microworlds were developed. Results of the verbal protocols showed (a) modification of the theoretical CPS model, (b) task dependence of CPS strategies, and (c) cross-national differences in CPS strategies. Participants' CPS processes were particularly influenced by country-specific problem-solving strategies. Copyright © 2009 Cognitive Science Society, Inc.

Rumination, Social Problem Solving and Suicide Intent Among Egyptians With a Recent Suicide Attempt.

PubMed

Sharaf, Amira Y; Lachine, Ola A; Thompson, Elaine A

2018-02-01

The more complex influences of social problem-solving abilities and rumination-specifically brooding and reflection-on suicide intent is not well understood. We hypothesized that social problem solving would moderate the association between reflection and suicide intent, and mediate the influence of brooding on suicide intent. A convenience sample (N=186) of individuals hospitalized for recent suicide attempt was interviewed, assessing suicide intent, social problem solving, brooding, reflection and depression. Brooding and reflection were positively associated with suicide intent. The mediating, but not the moderating, hypothesis was supported. Brooding was not significant (β=0.15, t=1.92, p=0.06) with social problem solving controlled. Interventions to disengage rumination and improve social problem-solving skills are underscored. Copyright © 2017 Elsevier Inc. All rights reserved.

The Efficacy and Development of Students' Problem-Solving Strategies During Compulsory Schooling: Logfile Analyses

PubMed Central

Molnár, Gyöngyvér; Csapó, Benő

2018-01-01

The purpose of this study was to examine the role of exploration strategies students used in the first phase of problem solving. The sample for the study was drawn from 3rd- to 12th-grade students (aged 9–18) in Hungarian schools (n = 4,371). Problems designed in the MicroDYN approach with different levels of complexity were administered to the students via the eDia online platform. Logfile analyses were performed to ascertain the impact of strategy use on the efficacy of problem solving. Students' exploration behavior was coded and clustered through Latent Class Analyses. Several theoretically effective strategies were identified, including the vary-one-thing-at-a-time (VOTAT) strategy and its sub-strategies. The results of the analyses indicate that the use of a theoretically effective strategy, which extract all information required to solve the problem, did not always lead to high performance. Conscious VOTAT strategy users proved to be the best problem solvers followed by non-conscious VOTAT strategy users and non-VOTAT strategy users. In the primary school sub-sample, six qualitatively different strategy class profiles were distinguished. The results shed new light on and provide a new interpretation of previous analyses of the processes involved in complex problem solving. They also highlight the importance of explicit enhancement of problem-solving skills and problem-solving strategies as a tool for knowledge acquisition in new contexts during and beyond school lessons. PMID:29593606

The Efficacy and Development of Students' Problem-Solving Strategies During Compulsory Schooling: Logfile Analyses.

PubMed

Molnár, Gyöngyvér; Csapó, Benő

2018-01-01

The purpose of this study was to examine the role of exploration strategies students used in the first phase of problem solving. The sample for the study was drawn from 3 rd - to 12 th -grade students (aged 9-18) in Hungarian schools ( n = 4,371). Problems designed in the MicroDYN approach with different levels of complexity were administered to the students via the eDia online platform. Logfile analyses were performed to ascertain the impact of strategy use on the efficacy of problem solving. Students' exploration behavior was coded and clustered through Latent Class Analyses. Several theoretically effective strategies were identified, including the vary-one-thing-at-a-time (VOTAT) strategy and its sub-strategies. The results of the analyses indicate that the use of a theoretically effective strategy, which extract all information required to solve the problem, did not always lead to high performance. Conscious VOTAT strategy users proved to be the best problem solvers followed by non-conscious VOTAT strategy users and non-VOTAT strategy users. In the primary school sub-sample, six qualitatively different strategy class profiles were distinguished. The results shed new light on and provide a new interpretation of previous analyses of the processes involved in complex problem solving. They also highlight the importance of explicit enhancement of problem-solving skills and problem-solving strategies as a tool for knowledge acquisition in new contexts during and beyond school lessons.

HSTLBO: A hybrid algorithm based on Harmony Search and Teaching-Learning-Based Optimization for complex high-dimensional optimization problems

PubMed Central

Tuo, Shouheng; Yong, Longquan; Deng, Fang’an; Li, Yanhai; Lin, Yong; Lu, Qiuju

2017-01-01

Harmony Search (HS) and Teaching-Learning-Based Optimization (TLBO) as new swarm intelligent optimization algorithms have received much attention in recent years. Both of them have shown outstanding performance for solving NP-Hard optimization problems. However, they also suffer dramatic performance degradation for some complex high-dimensional optimization problems. Through a lot of experiments, we find that the HS and TLBO have strong complementarity each other. The HS has strong global exploration power but low convergence speed. Reversely, the TLBO has much fast convergence speed but it is easily trapped into local search. In this work, we propose a hybrid search algorithm named HSTLBO that merges the two algorithms together for synergistically solving complex optimization problems using a self-adaptive selection strategy. In the HSTLBO, both HS and TLBO are modified with the aim of balancing the global exploration and exploitation abilities, where the HS aims mainly to explore the unknown regions and the TLBO aims to rapidly exploit high-precision solutions in the known regions. Our experimental results demonstrate better performance and faster speed than five state-of-the-art HS variants and show better exploration power than five good TLBO variants with similar run time, which illustrates that our method is promising in solving complex high-dimensional optimization problems. The experiment on portfolio optimization problems also demonstrate that the HSTLBO is effective in solving complex read-world application. PMID:28403224

HSTLBO: A hybrid algorithm based on Harmony Search and Teaching-Learning-Based Optimization for complex high-dimensional optimization problems.

PubMed

Tuo, Shouheng; Yong, Longquan; Deng, Fang'an; Li, Yanhai; Lin, Yong; Lu, Qiuju

2017-01-01

Harmony Search (HS) and Teaching-Learning-Based Optimization (TLBO) as new swarm intelligent optimization algorithms have received much attention in recent years. Both of them have shown outstanding performance for solving NP-Hard optimization problems. However, they also suffer dramatic performance degradation for some complex high-dimensional optimization problems. Through a lot of experiments, we find that the HS and TLBO have strong complementarity each other. The HS has strong global exploration power but low convergence speed. Reversely, the TLBO has much fast convergence speed but it is easily trapped into local search. In this work, we propose a hybrid search algorithm named HSTLBO that merges the two algorithms together for synergistically solving complex optimization problems using a self-adaptive selection strategy. In the HSTLBO, both HS and TLBO are modified with the aim of balancing the global exploration and exploitation abilities, where the HS aims mainly to explore the unknown regions and the TLBO aims to rapidly exploit high-precision solutions in the known regions. Our experimental results demonstrate better performance and faster speed than five state-of-the-art HS variants and show better exploration power than five good TLBO variants with similar run time, which illustrates that our method is promising in solving complex high-dimensional optimization problems. The experiment on portfolio optimization problems also demonstrate that the HSTLBO is effective in solving complex read-world application.

Using Programmable Calculators to Solve Electrostatics Problems.

ERIC Educational Resources Information Center

Yerian, Stephen C.; Denker, Dennis A.

1985-01-01

Provides a simple routine which allows first-year physics students to use programmable calculators to solve otherwise complex electrostatic problems. These problems involve finding electrostatic potential and electric field on the axis of a uniformly charged ring. Modest programing skills are required of students. (DH)

Solving complex band structure problems with the FEAST eigenvalue algorithm

NASA Astrophysics Data System (ADS)

Laux, S. E.

2012-08-01

With straightforward extension, the FEAST eigenvalue algorithm [Polizzi, Phys. Rev. B 79, 115112 (2009)] is capable of solving the generalized eigenvalue problems representing traveling-wave problems—as exemplified by the complex band-structure problem—even though the matrices involved are complex, non-Hermitian, and singular, and hence outside the originally stated range of applicability of the algorithm. The obtained eigenvalues/eigenvectors, however, contain spurious solutions which must be detected and removed. The efficiency and parallel structure of the original algorithm are unaltered. The complex band structures of Si layers of varying thicknesses and InAs nanowires of varying radii are computed as test problems.

Linking Complex Problem Solving and General Mental Ability to Career Advancement: Does a Transversal Skill Reveal Incremental Predictive Validity?

ERIC Educational Resources Information Center

Mainert, Jakob; Kretzschmar, André; Neubert, Jonas C.; Greiff, Samuel

2015-01-01

Transversal skills, such as complex problem solving (CPS) are viewed as central twenty-first-century skills. Recent empirical findings have already supported the importance of CPS for early academic advancement. We wanted to determine whether CPS could also contribute to the understanding of career advancement later in life. Towards this end, we…

The Computer-Based Assessment of Complex Problem Solving and How It Is Influenced by Students' Information and Communication Technology Literacy

ERIC Educational Resources Information Center

Greiff, Samuel; Kretzschmar, André; Müller, Jonas C.; Spinath, Birgit; Martin, Romain

2014-01-01

The 21st-century work environment places strong emphasis on nonroutine transversal skills. In an educational context, complex problem solving (CPS) is generally considered an important transversal skill that includes knowledge acquisition and its application in new and interactive situations. The dynamic and interactive nature of CPS requires a…

An Application of Generalizability Theory and Many-Facet Rasch Measurement Using a Complex Problem-Solving Skills Assessment

ERIC Educational Resources Information Center

Smith, Jr., Everett V.; Kulikowich, Jonna M.

2004-01-01

This study describes the use of generalizability theory (GT) and many-facet Rasch measurement (MFRM) to evaluate psychometric properties of responses obtained from an assessment designed to measure complex problem-solving skills. The assessment revolved around the school activity of kickball. The task required of each student was to decide on a…

Chinese Algebra: Using Historical Problems to Think about Current Curricula

ERIC Educational Resources Information Center

Tillema, Erik

2005-01-01

The Chinese used the idea of generating equivalent expressions for solving problems where the problems from a historical Chinese text are studied to understand the ways in which the ideas can lead into algebraic calculations and help students to learn algebra. The texts unify algebraic problem solving through complex algebraic thought and afford…

Eye-Tracking Study of Complexity in Gas Law Problems

ERIC Educational Resources Information Center

Tang, Hui; Pienta, Norbert

2012-01-01

This study, part of a series investigating students' use of online tools to assess problem solving, uses eye-tracking hardware and software to explore the effect of problem difficulty and cognitive processes when students solve gas law word problems. Eye movements are indices of cognition; eye-tracking data typically include the location,…

Advice to Policy Makers Who Would Tackle Syria: The Problem with Problem Solving

DTIC Science & Technology

2014-01-01

consensus on the specific way forward in Syria, there is one thing most do agree on; Syria is complex. It is complex in the familiar use of that term...SYRIA SYRIA SUPPLEMENTAL FEATURES | 125 strengthen stabilizing loops (ones that keep things from getting worse) or virtuous cycles (ones that make... things worse and worse over time). Second, and more importantly, affecting patterns can be the key to solving the problem of strained or insufficient

Others' anger makes people work harder not smarter: the effect of observing anger and sarcasm on creative and analytic thinking.

PubMed

Miron-Spektor, Ella; Efrat-Treister, Dorit; Rafaeli, Anat; Schwarz-Cohen, Orit

2011-09-01

The authors examine whether and how observing anger influences thinking processes and problem-solving ability. In 3 studies, the authors show that participants who listened to an angry customer were more successful in solving analytic problems, but less successful in solving creative problems compared with participants who listened to an emotionally neutral customer. In Studies 2 and 3, the authors further show that observing anger communicated through sarcasm enhances complex thinking and solving of creative problems. Prevention orientation is argued to be the latent variable that mediated the effect of observing anger on complex thinking. The present findings help reconcile inconsistent findings in previous research, promote theory about the effects of observing anger and sarcasm, and contribute to understanding the effects of anger in the workplace. PsycINFO Database Record (c) 2011 APA, all rights reserved

The Effect of an Extended Wilderness Education Experience on Ill-Structured Problem-Solving Skill Development in Emerging Adult Students

ERIC Educational Resources Information Center

Collins, Rachel H.

2014-01-01

In a society that is becoming more dynamic, complex, and diverse, the ability to solve ill-structured problems has become an increasingly critical skill. Emerging adults are at a critical life stage that is an ideal time to develop the skills needed to solve ill-structured problems (ISPs) as they are transitioning to adult roles and starting to…

On the Role of Situational Stressors in the Disruption of Global Neural Network Stability during Problem Solving.

PubMed

Liu, Mengting; Amey, Rachel C; Forbes, Chad E

2017-12-01

When individuals are placed in stressful situations, they are likely to exhibit deficits in cognitive capacity over and above situational demands. Despite this, individuals may still persevere and ultimately succeed in these situations. Little is known, however, about neural network properties that instantiate success or failure in both neutral and stressful situations, particularly with respect to regions integral for problem-solving processes that are necessary for optimal performance on more complex tasks. In this study, we outline how hidden Markov modeling based on multivoxel pattern analysis can be used to quantify unique brain states underlying complex network interactions that yield either successful or unsuccessful problem solving in more neutral or stressful situations. We provide evidence that brain network stability and states underlying synchronous interactions in regions integral for problem-solving processes are key predictors of whether individuals succeed or fail in stressful situations. Findings also suggested that individuals utilize discriminate neural patterns in successfully solving problems in stressful or neutral situations. Findings overall highlight how hidden Markov modeling can provide myriad possibilities for quantifying and better understanding the role of global network interactions in the problem-solving process and how the said interactions predict success or failure in different contexts.

Implementing a Case-Based E-Learning Environment in a Lecture-Oriented Anaesthesiology Class: Do Learning Styles Matter in Complex Problem Solving over Time?

ERIC Educational Resources Information Center

Choi, Ikseon; Lee, Sang Joon; Kang, Jeongwan

2009-01-01

This study explores how students' learning styles influence their learning while solving complex problems when a case-based e-learning environment is implemented in a conventional lecture-oriented classroom. Seventy students from an anaesthesiology class at a dental school participated in this study over a 3-week period. Five learning-outcome…

Design concepts for the development of cooperative problem-solving systems

NASA Technical Reports Server (NTRS)

Smith, Philip J.; Mccoy, Elaine; Layton, Chuck; Bihari, Tom

1992-01-01

There are many problem-solving tasks that are too complex to fully automate given the current state of technology. Nevertheless, significant improvements in overall system performance could result from the introduction of well-designed computer aids. We have been studying the development of cognitive tools for one such problem-solving task, enroute flight path planning for commercial airlines. Our goal was two-fold. First, we were developing specific systems designs to help with this important practical problem. Second, we are using this context to explore general design concepts to guide in the development of cooperative problem-solving systems. These designs concepts are described.

A restricted Steiner tree problem is solved by Geometric Method II

NASA Astrophysics Data System (ADS)

Lin, Dazhi; Zhang, Youlin; Lu, Xiaoxu

2013-03-01

The minimum Steiner tree problem has wide application background, such as transportation system, communication network, pipeline design and VISL, etc. It is unfortunately that the computational complexity of the problem is NP-hard. People are common to find some special problems to consider. In this paper, we first put forward a restricted Steiner tree problem, which the fixed vertices are in the same side of one line L and we find a vertex on L such the length of the tree is minimal. By the definition and the complexity of the Steiner tree problem, we know that the complexity of this problem is also Np-complete. In the part one, we have considered there are two fixed vertices to find the restricted Steiner tree problem. Naturally, we consider there are three fixed vertices to find the restricted Steiner tree problem. And we also use the geometric method to solve such the problem.

How Instructional Designers Solve Workplace Problems

ERIC Educational Resources Information Center

Fortney, Kathleen S.; Yamagata-Lynch, Lisa C.

2013-01-01

This naturalistic inquiry investigated how instructional designers engage in complex and ambiguous problem solving across organizational boundaries in two corporations. Participants represented a range of instructional design experience, from novices to experts. Research methods included a participant background survey, observations of…

Amoeba-inspired nanoarchitectonic computing: solving intractable computational problems using nanoscale photoexcitation transfer dynamics.

PubMed

Aono, Masashi; Naruse, Makoto; Kim, Song-Ju; Wakabayashi, Masamitsu; Hori, Hirokazu; Ohtsu, Motoichi; Hara, Masahiko

2013-06-18

Biologically inspired computing devices and architectures are expected to overcome the limitations of conventional technologies in terms of solving computationally demanding problems, adapting to complex environments, reducing energy consumption, and so on. We previously demonstrated that a primitive single-celled amoeba (a plasmodial slime mold), which exhibits complex spatiotemporal oscillatory dynamics and sophisticated computing capabilities, can be used to search for a solution to a very hard combinatorial optimization problem. We successfully extracted the essential spatiotemporal dynamics by which the amoeba solves the problem. This amoeba-inspired computing paradigm can be implemented by various physical systems that exhibit suitable spatiotemporal dynamics resembling the amoeba's problem-solving process. In this Article, we demonstrate that photoexcitation transfer phenomena in certain quantum nanostructures mediated by optical near-field interactions generate the amoebalike spatiotemporal dynamics and can be used to solve the satisfiability problem (SAT), which is the problem of judging whether a given logical proposition (a Boolean formula) is self-consistent. SAT is related to diverse application problems in artificial intelligence, information security, and bioinformatics and is a crucially important nondeterministic polynomial time (NP)-complete problem, which is believed to become intractable for conventional digital computers when the problem size increases. We show that our amoeba-inspired computing paradigm dramatically outperforms a conventional stochastic search method. These results indicate the potential for developing highly versatile nanoarchitectonic computers that realize powerful solution searching with low energy consumption.

Toward Modeling the Intrinsic Complexity of Test Problems

ERIC Educational Resources Information Center

Shoufan, Abdulhadi

2017-01-01

The concept of intrinsic complexity explains why different problems of the same type, tackled by the same problem solver, can require different times to solve and yield solutions of different quality. This paper proposes a general four-step approach that can be used to establish a model for the intrinsic complexity of a problem class in terms of…

Investigating the Effect of Complexity Factors in Stoichiometry Problems Using Logistic Regression and Eye Tracking

ERIC Educational Resources Information Center

Tang, Hui; Kirk, John; Pienta, Norbert J.

2014-01-01

This paper includes two experiments, one investigating complexity factors in stoichiometry word problems, and the other identifying students' problem-solving protocols by using eye-tracking technology. The word problems used in this study had five different complexity factors, which were randomly assigned by a Web-based tool that we developed. The…

Tracking problem solving by multivariate pattern analysis and Hidden Markov Model algorithms.

PubMed

Anderson, John R

2012-03-01

Multivariate pattern analysis can be combined with Hidden Markov Model algorithms to track the second-by-second thinking as people solve complex problems. Two applications of this methodology are illustrated with a data set taken from children as they interacted with an intelligent tutoring system for algebra. The first "mind reading" application involves using fMRI activity to track what students are doing as they solve a sequence of algebra problems. The methodology achieves considerable accuracy at determining both what problem-solving step the students are taking and whether they are performing that step correctly. The second "model discovery" application involves using statistical model evaluation to determine how many substates are involved in performing a step of algebraic problem solving. This research indicates that different steps involve different numbers of substates and these substates are associated with different fluency in algebra problem solving. Copyright © 2011 Elsevier Ltd. All rights reserved.

Diagrams benefit symbolic problem-solving.

PubMed

Chu, Junyi; Rittle-Johnson, Bethany; Fyfe, Emily R

2017-06-01

The format of a mathematics problem often influences students' problem-solving performance. For example, providing diagrams in conjunction with story problems can benefit students' understanding, choice of strategy, and accuracy on story problems. However, it remains unclear whether providing diagrams in conjunction with symbolic equations can benefit problem-solving performance as well. We tested the impact of diagram presence on students' performance on algebra equation problems to determine whether diagrams increase problem-solving success. We also examined the influence of item- and student-level factors to test the robustness of the diagram effect. We worked with 61 seventh-grade students who had received 2 months of pre-algebra instruction. Students participated in an experimenter-led classroom session. Using a within-subjects design, students solved algebra problems in two matched formats (equation and equation-with-diagram). The presence of diagrams increased equation-solving accuracy and the use of informal strategies. This diagram benefit was independent of student ability and item complexity. The benefits of diagrams found previously for story problems generalized to symbolic problems. The findings are consistent with cognitive models of problem-solving and suggest that diagrams may be a useful additional representation of symbolic problems. © 2017 The British Psychological Society.

Acquisition and performance of a problem-solving skill.

NASA Technical Reports Server (NTRS)

Morgan, B. B., Jr.; Alluisi, E. A.

1971-01-01

The acquisition of skill in the performance of a three-phase code transformation task (3P-COTRAN) was studied with 20 subjects who solved 27 3P-COTRAN problems during each of 8 successive sessions. The purpose of the study was to determine the changes in the 3P-COTRAN factor structure resulting from practice, the distribution of practice-related gains in performance over the nine measures of the five 3P-COTRAN factors, and the effects of transformation complexities on the 3P-COTRAN performance of subjects. A significant performance gain due to practice was observed, with improvements in speed continuing even when accuracy reached asymptotic levels. Transformation complexity showed no effect on early performances but the 3- and 4-element transformations were solved quicker than the 5-element transformation in the problem-solving Phase III of later skilled performances.

Facilitating Learners' Web-Based Information Problem-Solving by Query Expansion-Based Concept Mapping

ERIC Educational Resources Information Center

Huang, Yueh-Min; Liu, Ming-Chi; Chen, Nian-Shing; Kinshuk; Wen, Dunwei

2014-01-01

Web-based information problem-solving has been recognised as a critical ability for learners. However, the development of students' abilities in this area often faces several challenges, such as difficulty in building well-organised knowledge structures to support complex problems that require higher-order skills (e.g., system thinking). To…

Asking the Right Questions: Action Learning and PMT 401

DTIC Science & Technology

2016-08-01

program aimed at improving leadership, critical thinking , problem solving and decision­making skills. Participants in this rigorous, in­residence...problem • Skill Development • Urgent and complex problems requiring unique systems thinking • Groups charged with implementing the solution as...most pressing organi­ zational issues: problem solving, organizational learning, team building, leadership development, and professional growth and

Divide et impera: subgoaling reduces the complexity of probabilistic inference and problem solving

PubMed Central

Maisto, Domenico; Donnarumma, Francesco; Pezzulo, Giovanni

2015-01-01

It has long been recognized that humans (and possibly other animals) usually break problems down into smaller and more manageable problems using subgoals. Despite a general consensus that subgoaling helps problem solving, it is still unclear what the mechanisms guiding online subgoal selection are during the solution of novel problems for which predefined solutions are not available. Under which conditions does subgoaling lead to optimal behaviour? When is subgoaling better than solving a problem from start to finish? Which is the best number and sequence of subgoals to solve a given problem? How are these subgoals selected during online inference? Here, we present a computational account of subgoaling in problem solving. Following Occam's razor, we propose that good subgoals are those that permit planning solutions and controlling behaviour using less information resources, thus yielding parsimony in inference and control. We implement this principle using approximate probabilistic inference: subgoals are selected using a sampling method that considers the descriptive complexity of the resulting sub-problems. We validate the proposed method using a standard reinforcement learning benchmark (four-rooms scenario) and show that the proposed method requires less inferential steps and permits selecting more compact control programs compared to an equivalent procedure without subgoaling. Furthermore, we show that the proposed method offers a mechanistic explanation of the neuronal dynamics found in the prefrontal cortex of monkeys that solve planning problems. Our computational framework provides a novel integrative perspective on subgoaling and its adaptive advantages for planning, control and learning, such as for example lowering cognitive effort and working memory load. PMID:25652466

Enroute flight planning: Evaluating design concepts for the development of cooperative problem-solving systems

NASA Technical Reports Server (NTRS)

Smith, Philip J.

1995-01-01

There are many problem-solving tasks that are too complex to fully automate given the current state of technology. Nevertheless, significant improvements in overall system performance could result from the introduction of well-designed computer aids. We have been studying the development of cognitive tools for one such problem-solving task, enroute flight path planning for commercial airlines. Our goal has been two-fold. First, we have been developing specific system designs to help with this important practical problem. Second, we have been using this context to explore general design concepts to guide in the development of cooperative problem-solving systems. These design concepts are described below, along with illustrations of their application.

On a New Approach to Education about Ethics for Engineers at Meijou University

NASA Astrophysics Data System (ADS)

Fukaya, Minoru; Morimoto, Tsukasa; Kimura, Noritsugu

We propose a new approach to education of so called “engineering ethics”. This approach has two important elements in its teaching system. One is “problem-solving learning”, and the other is “discussion ability”. So far, engineering ethics started at the ethical standpoint. But we put the viewpoint of problem-solving learning at the educational base of engineering ethics. Because many problems have complicated structures, so if we want to solve them, we should discuss each other. Problem-solving ability and discussion ability, they help engineers to solve the complex problems in their social everyday life. Therefore, Meijo University names engineering ethics “ethics for engineers”. At Meijou University about 1300 students take classes in both ethics for engineers and environmental ethics for one year.

The Bright Side of Being Blue: Depression as an Adaptation for Analyzing Complex Problems

ERIC Educational Resources Information Center

Andrews, Paul W.; Thomson, J. Anderson, Jr.

2009-01-01

Depression is the primary emotional condition for which help is sought. Depressed people often report persistent rumination, which involves analysis, and complex social problems in their lives. Analysis is often a useful approach for solving complex problems, but it requires slow, sustained processing, so disruption would interfere with problem…

Numerical Leak Detection in a Pipeline Network of Complex Structure with Unsteady Flow

NASA Astrophysics Data System (ADS)

Aida-zade, K. R.; Ashrafova, E. R.

2017-12-01

An inverse problem for a pipeline network of complex loopback structure is solved numerically. The problem is to determine the locations and amounts of leaks from unsteady flow characteristics measured at some pipeline points. The features of the problem include impulse functions involved in a system of hyperbolic differential equations, the absence of classical initial conditions, and boundary conditions specified as nonseparated relations between the states at the endpoints of adjacent pipeline segments. The problem is reduced to a parametric optimal control problem without initial conditions, but with nonseparated boundary conditions. The latter problem is solved by applying first-order optimization methods. Results of numerical experiments are presented.

Calculation and word problem-solving skills in primary grades - Impact of cognitive abilities and longitudinal interrelations with task-persistent behaviour.

PubMed

Jõgi, Anna-Liisa; Kikas, Eve

2016-06-01

Primary school math skills form a basis for academic success down the road. Different math skills have different antecedents and there is a reason to believe that more complex math tasks require better self-regulation. The study aimed to investigate longitudinal interrelations of calculation and problem-solving skills, and task-persistent behaviour in Grade 1 and Grade 3, and the effect of non-verbal intelligence, linguistic abilities, and executive functioning on math skills and task persistence. Participants were 864 students (52.3% boys) from 33 different schools in Estonia. Students were tested twice - at the end of Grade1 and at the end of Grade 3. Calculation and problem-solving skills, and teacher-rated task-persistent behaviour were measured at both time points. Non-verbal intelligence, linguistic abilities, and executive functioning were measured in Grade 1. Cross-lagged structural equation modelling indicated that calculation skills depend on previous math skills and linguistic abilities, while problem-solving skills require also non-verbal intelligence, executive functioning, and task persistence. Task-persistent behaviour in Grade 3 was predicted by previous problem-solving skills, linguistic abilities, and executive functioning. Gender and mother's educational level were added as covariates. The findings indicate that math skills and self-regulation are strongly related in primary grades and that solving complex tasks requires executive functioning and task persistence from children. Findings support the idea that instructional practices might benefit from supporting self-regulation in order to gain domain-specific, complex skill achievement. © 2015 The British Psychological Society.

Models of resource allocation optimization when solving the control problems in organizational systems

NASA Astrophysics Data System (ADS)

Menshikh, V.; Samorokovskiy, A.; Avsentev, O.

2018-03-01

The mathematical model of optimizing the allocation of resources to reduce the time for management decisions and algorithms to solve the general problem of resource allocation. The optimization problem of choice of resources in organizational systems in order to reduce the total execution time of a job is solved. This problem is a complex three-level combinatorial problem, for the solving of which it is necessary to implement the solution to several specific problems: to estimate the duration of performing each action, depending on the number of performers within the group that performs this action; to estimate the total execution time of all actions depending on the quantitative composition of groups of performers; to find such a distribution of the existing resource of performers in groups to minimize the total execution time of all actions. In addition, algorithms to solve the general problem of resource allocation are proposed.

Collaborative learning in networks.

PubMed

Mason, Winter; Watts, Duncan J

2012-01-17

Complex problems in science, business, and engineering typically require some tradeoff between exploitation of known solutions and exploration for novel ones, where, in many cases, information about known solutions can also disseminate among individual problem solvers through formal or informal networks. Prior research on complex problem solving by collectives has found the counterintuitive result that inefficient networks, meaning networks that disseminate information relatively slowly, can perform better than efficient networks for problems that require extended exploration. In this paper, we report on a series of 256 Web-based experiments in which groups of 16 individuals collectively solved a complex problem and shared information through different communication networks. As expected, we found that collective exploration improved average success over independent exploration because good solutions could diffuse through the network. In contrast to prior work, however, we found that efficient networks outperformed inefficient networks, even in a problem space with qualitative properties thought to favor inefficient networks. We explain this result in terms of individual-level explore-exploit decisions, which we find were influenced by the network structure as well as by strategic considerations and the relative payoff between maxima. We conclude by discussing implications for real-world problem solving and possible extensions.

Collaborative learning in networks

PubMed Central

Mason, Winter; Watts, Duncan J.

2012-01-01

Complex problems in science, business, and engineering typically require some tradeoff between exploitation of known solutions and exploration for novel ones, where, in many cases, information about known solutions can also disseminate among individual problem solvers through formal or informal networks. Prior research on complex problem solving by collectives has found the counterintuitive result that inefficient networks, meaning networks that disseminate information relatively slowly, can perform better than efficient networks for problems that require extended exploration. In this paper, we report on a series of 256 Web-based experiments in which groups of 16 individuals collectively solved a complex problem and shared information through different communication networks. As expected, we found that collective exploration improved average success over independent exploration because good solutions could diffuse through the network. In contrast to prior work, however, we found that efficient networks outperformed inefficient networks, even in a problem space with qualitative properties thought to favor inefficient networks. We explain this result in terms of individual-level explore-exploit decisions, which we find were influenced by the network structure as well as by strategic considerations and the relative payoff between maxima. We conclude by discussing implications for real-world problem solving and possible extensions. PMID:22184216

Empirical results on scheduling and dynamic backtracking

NASA Technical Reports Server (NTRS)

Boddy, Mark S.; Goldman, Robert P.

1994-01-01

At the Honeywell Technology Center (HTC), we have been working on a scheduling problem related to commercial avionics. This application is large, complex, and hard to solve. To be a little more concrete: 'large' means almost 20,000 activities, 'complex' means several activity types, periodic behavior, and assorted types of temporal constraints, and 'hard to solve' means that we have been unable to eliminate backtracking through the use of search heuristics. At this point, we can generate solutions, where solutions exist, or report failure and sometimes why the system failed. To the best of our knowledge, this is among the largest and most complex scheduling problems to have been solved as a constraint satisfaction problem, at least that has appeared in the published literature. This abstract is a preliminary report on what we have done and how. In the next section, we present our approach to treating scheduling as a constraint satisfaction problem. The following sections present the application in more detail and describe how we solve scheduling problems in the application domain. The implemented system makes use of Ginsberg's Dynamic Backtracking algorithm, with some minor extensions to improve its utility for scheduling. We describe those extensions and the performance of the resulting system. The paper concludes with some general remarks, open questions and plans for future work.

Performance of subjects with and without severe mental illness on a clinical test of problem solving.

PubMed

Marshall, R C; McGurk, S R; Karow, C M; Kairy, T J; Flashman, L A

2006-06-01

Severe mental illness is associated with impairments in executive functions, such as conceptual reasoning, planning, and strategic thinking all of which impact problem solving. The present study examined the utility of a novel assessment tool for problem solving, the Rapid Assessment of Problem Solving Test (RAPS) in persons with severe mental illness. Subjects were 47 outpatients with severe mental illness and an equal number healthy controls matched for age and gender. Results confirmed all hypotheses with respect to how subjects with severe mental illness would perform on the RAPS. Specifically, the severely mentally ill subjects (1) solved fewer problems on the RAPS, (2) when they did solve problems on the test, they did so far less efficiently than their healthy counterparts, and (3) the two groups differed markedly in the types of questions asked on the RAPS. The healthy control subjects tended to take a systematic, organized, but not always optimal approach to solving problems on the RAPS. The subjects with severe mental illness used some of the problem solving strategies of the healthy controls, but their performance was less consistent and tended to deteriorate when the complexity of the problem solving task increased. This was reflected by a high degree of guessing in lieu of asking constraint questions, particularly if a category-limited question was insufficient to continue the problem solving effort.

Nonlinearly Activated Neural Network for Solving Time-Varying Complex Sylvester Equation.

PubMed

Li, Shuai; Li, Yangming

2013-10-28

The Sylvester equation is often encountered in mathematics and control theory. For the general time-invariant Sylvester equation problem, which is defined in the domain of complex numbers, the Bartels-Stewart algorithm and its extensions are effective and widely used with an O(n³) time complexity. When applied to solving the time-varying Sylvester equation, the computation burden increases intensively with the decrease of sampling period and cannot satisfy continuous realtime calculation requirements. For the special case of the general Sylvester equation problem defined in the domain of real numbers, gradient-based recurrent neural networks are able to solve the time-varying Sylvester equation in real time, but there always exists an estimation error while a recently proposed recurrent neural network by Zhang et al [this type of neural network is called Zhang neural network (ZNN)] converges to the solution ideally. The advancements in complex-valued neural networks cast light to extend the existing real-valued ZNN for solving the time-varying real-valued Sylvester equation to its counterpart in the domain of complex numbers. In this paper, a complex-valued ZNN for solving the complex-valued Sylvester equation problem is investigated and the global convergence of the neural network is proven with the proposed nonlinear complex-valued activation functions. Moreover, a special type of activation function with a core function, called sign-bi-power function, is proven to enable the ZNN to converge in finite time, which further enhances its advantage in online processing. In this case, the upper bound of the convergence time is also derived analytically. Simulations are performed to evaluate and compare the performance of the neural network with different parameters and activation functions. Both theoretical analysis and numerical simulations validate the effectiveness of the proposed method.

Medical Problem-Solving: A Critique of the Literature.

ERIC Educational Resources Information Center

McGuire, Christine H.

1985-01-01

Prescriptive, decision-analysis of medical problem-solving has been based on decision theory that involves calculation and manipulation of complex probability and utility values to arrive at optimal decisions that will maximize patient benefits. The studies offer a methodology for improving clinical judgment. (Author/MLW)

Applying ant colony optimization metaheuristic to solve forest transportation planning problems with side constraints

Treesearch

Marco A. Contreras; Woodam Chung; Greg Jones

2008-01-01

Forest transportation planning problems (FTPP) have evolved from considering only the financial aspects of timber management to more holistic problems that also consider the environmental impacts of roads. These additional requirements have introduced side constraints, making FTPP larger and more complex. Mixed-integer programming (MIP) has been used to solve FTPP, but...

Recognizing and Managing Complexity: Teaching Advanced Programming Concepts and Techniques Using the Zebra Puzzle

ERIC Educational Resources Information Center

Crabtree, John; Zhang, Xihui

2015-01-01

Teaching advanced programming can be a challenge, especially when the students are pursuing different majors with diverse analytical and problem-solving capabilities. The purpose of this paper is to explore the efficacy of using a particular problem as a vehicle for imparting a broad set of programming concepts and problem-solving techniques. We…

Complex Problem Solving in Radiologic Technology: Understanding the Roles of Experience, Reflective Judgment, and Workplace Culture

ERIC Educational Resources Information Center

Yates, Jennifer L.

2011-01-01

The purpose of this research study was to explore the process of learning and development of problem solving skills in radiologic technologists. The researcher sought to understand the nature of difficult problems encountered in clinical practice, to identify specific learning practices leading to the development of professional expertise, and to…

Can Students Identify the Relevant Information to Solve a Problem?

ERIC Educational Resources Information Center

Zhang, Lishan; Yu, Shengquan; Li, Baoping; Wang, Jing

2017-01-01

Solving non-routine problems is one of the most important skills for the 21st century. Traditional paper-pencil tests cannot assess this type of skill well because of their lack of interactivity and inability to capture procedural data. Tools such as MicroDYN and MicroFIN have proved to be trustworthy in assessing complex problem-solving…

The Teaching of Creativity in Information Systems Programmes at South African Higher Education Institutions

ERIC Educational Resources Information Center

Turpin, Marita; Matthee, Machdel; Kruger, Anine

2015-01-01

The development of problem solving skills is a shared goal in science, engineering, mathematics and technology education. In the applied sciences, problems are often open-ended and complex, requiring a multidisciplinary approach as well as new designs. In such cases, problem solving requires not only analytical capabilities, but also creativity…

Problems in Staff and Educational Development Leadership: Solving, Framing, and Avoiding

ERIC Educational Resources Information Center

Blackmore, Paul; Wilson, Andrew

2005-01-01

Analysis of interviews using critical incident technique with a sample of leaders in staff and educational development in higher education institutions reveals a limited use of classical problem-solving approaches. However, many leaders are able to articulate ways in which they frame problems. Framing has to do with goals, which may be complex,…

Multiple Problem-Solving Strategies Provide Insight into Students' Understanding of Open-Ended Linear Programming Problems

ERIC Educational Resources Information Center

Sole, Marla A.

2016-01-01

Open-ended questions that can be solved using different strategies help students learn and integrate content, and provide teachers with greater insights into students' unique capabilities and levels of understanding. This article provides a problem that was modified to allow for multiple approaches. Students tended to employ high-powered, complex,…

Promoting Experimental Problem-Solving Ability in Sixth-Grade Students through Problem-Oriented Teaching of Ecology: Findings of an Intervention Study in a Complex Domain

ERIC Educational Resources Information Center

Roesch, Frank; Nerb, Josef; Riess, Werner

2015-01-01

Our study investigated whether problem-oriented designed ecology lessons with phases of direct instruction and of open experimentation foster the development of cross-domain and domain-specific components of "experimental problem-solving ability" better than conventional lessons in science. We used a paper-and-pencil test to assess…

Temperament and problem solving in a population of adolescent guide dogs.

PubMed

Bray, Emily E; Sammel, Mary D; Seyfarth, Robert M; Serpell, James A; Cheney, Dorothy L

2017-09-01

It is often assumed that measures of temperament within individuals are more correlated to one another than to measures of problem solving. However, the exact relationship between temperament and problem-solving tasks remains unclear because large-scale studies have typically focused on each independently. To explore this relationship, we tested 119 prospective adolescent guide dogs on a battery of 11 temperament and problem-solving tasks. We then summarized the data using both confirmatory factor analysis and exploratory principal components analysis. Results of confirmatory analysis revealed that a priori separation of tests as measuring either temperament or problem solving led to weak results, poor model fit, some construct validity, and no predictive validity. In contrast, results of exploratory analysis were best summarized by principal components that mixed temperament and problem-solving traits. These components had both construct and predictive validity (i.e., association with success in the guide dog training program). We conclude that there is complex interplay between tasks of "temperament" and "problem solving" and that the study of both together will be more informative than approaches that consider either in isolation.

Assessing student written problem solutions: A problem-solving rubric with application to introductory physics

NASA Astrophysics Data System (ADS)

Docktor, Jennifer L.; Dornfeld, Jay; Frodermann, Evan; Heller, Kenneth; Hsu, Leonardo; Jackson, Koblar Alan; Mason, Andrew; Ryan, Qing X.; Yang, Jie

2016-06-01

Problem solving is a complex process valuable in everyday life and crucial for learning in the STEM fields. To support the development of problem-solving skills it is important for researchers and curriculum developers to have practical tools that can measure the difference between novice and expert problem-solving performance in authentic classroom work. It is also useful if such tools can be employed by instructors to guide their pedagogy. We describe the design, development, and testing of a simple rubric to assess written solutions to problems given in undergraduate introductory physics courses. In particular, we present evidence for the validity, reliability, and utility of the instrument. The rubric identifies five general problem-solving processes and defines the criteria to attain a score in each: organizing problem information into a Useful Description, selecting appropriate principles (Physics Approach), applying those principles to the specific conditions in the problem (Specific Application of Physics), using Mathematical Procedures appropriately, and displaying evidence of an organized reasoning pattern (Logical Progression).

A problem-solving approach to effective insulin injection for patients at either end of the body mass index.

PubMed

Juip, Micki; Fitzner, Karen

2012-06-01

People with diabetes require skills and knowledge to adhere to medication regimens and self-manage this complex disease. Effective self-management is contingent upon effective problem solving and decision making. Gaps existed regarding useful approaches to problem solving by individuals with very low and very high body mass index (BMI) who self-administer insulin injections. This article addresses those gaps by presenting findings from a patient survey, a symposium on the topic of problem solving, and recent interviews with diabetes educators to facilitate problem-solving approaches for people with diabetes with high and low BMI who inject insulin and/or other medications. In practice, problem solving involves problem identification, definition, and specification; goal and barrier identification are a prelude to generating a set of potential strategies for problem resolution and applying these strategies to implement a solution. Teaching techniques, such as site rotation and ensuring that people with diabetes use the appropriate equipment, increase confidence with medication adherence. Medication taking is more effective when people with diabetes are equipped with the knowledge, skills, and problem-solving behaviors to effectively self-manage their injections.

Computer Systems for Teaching Complex Concepts.

ERIC Educational Resources Information Center

Feurzeig, Wallace

Four Programing systems--Mentor, Stringcomp, Simon, and Logo--were designed and implemented as integral parts of research into the various ways computers may be used for teaching problem-solving concepts and skills. Various instructional contexts, among them medicine, mathematics, physics, and basic problem-solving for elementary school children,…

Assessing Design Activity in Complex CMOS Circuit Design.

ERIC Educational Resources Information Center

Biswas, Gautam; And Others

This report characterizes human problem solving in digital circuit design. Protocols of 11 different designers with varying degrees of training were analyzed by identifying the designers' problem solving strategies and discussing activity patterns that differentiate the designers. These methods are proposed as a tentative basis for assessing…

A Collaborative Problem-Solving Process through Environmental Field Studies

ERIC Educational Resources Information Center

Kim, Mijung; Tan, Hoe Teck

2013-01-01

This study explored and documented students' responses to opportunities for collective knowledge building and collaboration in a problem-solving process within complex environmental challenges and pressing issues with various dimensions of knowledge and skills. Middle-school students ("n" =?16; age 14) and high-school students…

Environmental problem-solving: Psychosocial factors

NASA Astrophysics Data System (ADS)

Miller, Alan

1982-11-01

This is a study of individual differences in environmental problem-solving, the probable roots of these differences, and their implications for the education of resource professionals. A group of student Resource Managers were required to elaborate their conception of a complex resource issue (Spruce Budworm management) and to generate some ideas on management policy. Of particular interest was the way in which subjects dealt with the psychosocial aspects of the problem. A structural and content analysis of responses indicated a predominance of relatively compartmentalized styles, a technological orientation, and a tendency to ignore psychosocial issues. A relationship between problem-solving behavior and personal (psychosocial) style was established which, in the context of other evidence, suggests that problem-solving behavior is influenced by more deep seated personality factors. The educational implication drawn was that problem-solving cannot be viewed simply as an intellectual-technical activity but one that involves, and requires the education of, the whole person.

Divide et impera: subgoaling reduces the complexity of probabilistic inference and problem solving.

PubMed

Maisto, Domenico; Donnarumma, Francesco; Pezzulo, Giovanni

2015-03-06

It has long been recognized that humans (and possibly other animals) usually break problems down into smaller and more manageable problems using subgoals. Despite a general consensus that subgoaling helps problem solving, it is still unclear what the mechanisms guiding online subgoal selection are during the solution of novel problems for which predefined solutions are not available. Under which conditions does subgoaling lead to optimal behaviour? When is subgoaling better than solving a problem from start to finish? Which is the best number and sequence of subgoals to solve a given problem? How are these subgoals selected during online inference? Here, we present a computational account of subgoaling in problem solving. Following Occam's razor, we propose that good subgoals are those that permit planning solutions and controlling behaviour using less information resources, thus yielding parsimony in inference and control. We implement this principle using approximate probabilistic inference: subgoals are selected using a sampling method that considers the descriptive complexity of the resulting sub-problems. We validate the proposed method using a standard reinforcement learning benchmark (four-rooms scenario) and show that the proposed method requires less inferential steps and permits selecting more compact control programs compared to an equivalent procedure without subgoaling. Furthermore, we show that the proposed method offers a mechanistic explanation of the neuronal dynamics found in the prefrontal cortex of monkeys that solve planning problems. Our computational framework provides a novel integrative perspective on subgoaling and its adaptive advantages for planning, control and learning, such as for example lowering cognitive effort and working memory load. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

Kinematical simulation of robotic complex operation for implementing full-scale additive technologies of high-end materials, composites, structures, and buildings

NASA Astrophysics Data System (ADS)

Antsiferov, S. I.; Eltsov, M. Iu; Khakhalev, P. A.

2018-03-01

This paper considers a newly designed electronic digital model of a robotic complex for implementing full-scale additive technologies, funded under a Federal Target Program. The electronic and digital model was used to solve the problem of simulating the movement of a robotic complex using the NX CAD/CAM/CAE system. The virtual mechanism was built and the main assemblies, joints, and drives were identified as part of solving the problem. In addition, the maximum allowed printable area size was identified for the robotic complex, and a simulation of printing a rectangular-shaped article was carried out.

Predicting Development of Mathematical Word Problem Solving Across the Intermediate Grades

PubMed Central

Tolar, Tammy D.; Fuchs, Lynn; Cirino, Paul T.; Fuchs, Douglas; Hamlett, Carol L.; Fletcher, Jack M.

2012-01-01

This study addressed predictors of the development of word problem solving (WPS) across the intermediate grades. At beginning of 3rd grade, 4 cohorts of students (N = 261) were measured on computation, language, nonverbal reasoning skills, and attentive behavior and were assessed 4 times from beginning of 3rd through end of 5th grade on 2 measures of WPS at low and high levels of complexity. Language skills were related to initial performance at both levels of complexity and did not predict growth at either level. Computational skills had an effect on initial performance in low- but not high-complexity problems and did not predict growth at either level of complexity. Attentive behavior did not predict initial performance but did predict growth in low-complexity, whereas it predicted initial performance but not growth for high-complexity problems. Nonverbal reasoning predicted initial performance and growth for low-complexity WPS, but only growth for high-complexity WPS. This evidence suggests that although mathematical structure is fixed, different cognitive resources may act as limiting factors in WPS development when the WPS context is varied. PMID:23325985

Instruction Emphasizing Effort Improves Physics Problem Solving

ERIC Educational Resources Information Center

Li, Daoquan

2012-01-01

Effectively using strategies to solve complex problems is an important educational goal and is implicated in successful academic performance. However, people often do not spontaneously use the effective strategies unless they are motivated to do so. The present study was designed to test whether educating students about the importance of effort in…

Developing Problem-Solving Skills through Retrosynthetic Analysis and Clickers in Organic Chemistry

ERIC Educational Resources Information Center

Flynn, Alison B.

2011-01-01

A unique approach to teaching and learning problem-solving and critical-thinking skills in the context of retrosynthetic analysis is described. In this approach, introductory organic chemistry students, who typically see only simple organic structures, undertook partial retrosynthetic analyses of real and complex synthetic targets. Multiple…

Design and Implementation of the Game-Design and Learning Program

ERIC Educational Resources Information Center

Akcaoglu, Mete

2016-01-01

Design involves solving complex, ill-structured problems. Design tasks are consequently, appropriate contexts for children to exercise higher-order thinking and problem-solving skills. Although creating engaging and authentic design contexts for young children is difficult within the confines of traditional schooling, recently, game-design has…

How Young Students Communicate Their Mathematical Problem Solving in Writing

ERIC Educational Resources Information Center

Teledahl, Anna

2017-01-01

This study investigates young students' writing in connection to mathematical problem solving. Students' written communication has traditionally been used by mathematics teachers in the assessment of students' mathematical knowledge. This study rests on the notion that this writing represents a particular activity which requires a complex set of…

Mathematical Thinking and Creativity through Mathematical Problem Posing and Solving

ERIC Educational Resources Information Center

Ayllón, María F.; Gómez, Isabel A.; Ballesta-Claver, Julio

2016-01-01

This work shows the relationship between the development of mathematical thinking and creativity with mathematical problem posing and solving. Creativity and mathematics are disciplines that do not usually appear together. Both concepts constitute complex processes sharing elements, such as fluency (number of ideas), flexibility (range of ideas),…

Interaction Network Estimation: Predicting Problem-Solving Diversity in Interactive Environments

ERIC Educational Resources Information Center

Eagle, Michael; Hicks, Drew; Barnes, Tiffany

2015-01-01

Intelligent tutoring systems and computer aided learning environments aimed at developing problem solving produce large amounts of transactional data which make it a challenge for both researchers and educators to understand how students work within the environment. Researchers have modeled student-tutor interactions using complex networks in…

The Smarties-Box Challenge: Supporting Systematic Approaches to Problem Solving

ERIC Educational Resources Information Center

Russo, James

2016-01-01

The Smarties-Box Challenge encourages students to apply several different mathematical capabilities and concepts--such as, estimation, multiplication, and the notion of being systematic--to solve a complex, multistep problem. To effectively engage in the Smarties-Box Challenge, students are required to demonstrate aspects of all four proficiency…

Automating the Detection of Reflection-on-Action

ERIC Educational Resources Information Center

Saucerman, Jenny; Ruis, A. R.; Shaffer, David Williamson

2017-01-01

Learning to solve "complex problems"--problems whose solutions require the application of more than basic facts and skills--is critical to meaningful participation in the economic, social, and cultural life of the digital age. In this paper, we use a theoretical understanding of how professionals use reflection-in-action to solve complex…

Problem-Solving Practices and Complexity in School Psychology

ERIC Educational Resources Information Center

Brady, John; Espinosa, William R.

2017-01-01

How do experienced school psychologists solve problems in their practice? What can trainers of school psychologists learn about how to structure training and mentoring of graduate students from what actually happens in schools, and how can this inform our teaching at the university? This qualitative multi-interview study explored the processes…

Problem-Solving in the Pre-Clinical Curriculum: The Uses of Computer Simulations.

ERIC Educational Resources Information Center

Michael, Joel A.; Rovick, Allen A.

1986-01-01

Promotes the use of computer-based simulations in the pre-clinical medical curriculum as a means of providing students with opportunities for problem solving. Describes simple simulations of skeletal muscle loads, complex simulations of major organ systems and comprehensive simulation models of the entire human body. (TW)

Case study method and problem-based learning: utilizing the pedagogical model of progressive complexity in nursing education.

PubMed

McMahon, Michelle A; Christopher, Kimberly A

2011-08-19

As the complexity of health care delivery continues to increase, educators are challenged to determine educational best practices to prepare BSN students for the ambiguous clinical practice setting. Integrative, active, and student-centered curricular methods are encouraged to foster student ability to use clinical judgment for problem solving and informed clinical decision making. The proposed pedagogical model of progressive complexity in nursing education suggests gradually introducing students to complex and multi-contextual clinical scenarios through the utilization of case studies and problem-based learning activities, with the intention to transition nursing students into autonomous learners and well-prepared practitioners at the culmination of a nursing program. Exemplar curricular activities are suggested to potentiate student development of a transferable problem solving skill set and a flexible knowledge base to better prepare students for practice in future novel clinical experiences, which is a mutual goal for both educators and students.

Cognitive functioning and social problem-solving skills in schizophrenia.

PubMed

Hatashita-Wong, Michi; Smith, Thomas E; Silverstein, Steven M; Hull, James W; Willson, Deborah F

2002-05-01

This study examined the relationships between symptoms, cognitive functioning, and social skill deficits in schizophrenia. Few studies have incorporated measures of cognitive functioning and symptoms in predictive models for social problem solving. For our study, 44 participants were recruited from consecutive outpatient admissions. Neuropsychological tests were given to assess cognitive function, and social problem solving was assessed using structured vignettes designed to evoke the participant's ability to generate, evaluate, and apply solutions to social problems. A sequential model-fitting method of analysis was used to incorporate social problem solving, symptom presentation, and cognitive impairment into linear regression models. Predictor variables were drawn from demographic, cognitive, and symptom domains. Because this method of analysis was exploratory and not intended as hierarchical modelling, no a priori hypotheses were proposed. Participants with higher scores on tests of cognitive flexibility were better able to generate accurate, appropriate, and relevant responses to the social problem-solving vignettes. The results suggest that cognitive flexibility is a potentially important mediating factor in social problem-solving competence. While other factors are related to social problem-solving skill, this study supports the importance of cognition and understanding how it relates to the complex and multifaceted nature of social functioning.

Robotic system for non-destructive testing of complex shaped objects

NASA Astrophysics Data System (ADS)

Kavalerov, B. V.; Fayzrakhmanov, R. A.; Murzakaev, R. T.; Polyakov, A. N.; Artemev, V. V.

2018-03-01

This article describes the positioning system of defectoscopic equipment for nondestructive examination of complex shaped parts made of polymer composite materials. The purpose of the system and features of the investigated objects are described. The rationale for the development of the system and the range of problems it solves are presented. The solution of the kinematics problem for a 5-DOF manipulator is considered. The original algorithms for solving the kinematics problem are demonstrated. Methods for resolving collisions for a manipulator system are described. The results obtained in the course of experiments and studies are presented.

Robot, computer problem solving system

NASA Technical Reports Server (NTRS)

Becker, J. D.

1972-01-01

The development of a computer problem solving system is reported that considers physical problems faced by an artificial robot moving around in a complex environment. Fundamental interaction constraints with a real environment are simulated for the robot by visual scan and creation of an internal environmental model. The programming system used in constructing the problem solving system for the simulated robot and its simulated world environment is outlined together with the task that the system is capable of performing. A very general framework for understanding the relationship between an observed behavior and an adequate description of that behavior is included.

Performance comparison of some evolutionary algorithms on job shop scheduling problems

NASA Astrophysics Data System (ADS)

Mishra, S. K.; Rao, C. S. P.

2016-09-01

Job Shop Scheduling as a state space search problem belonging to NP-hard category due to its complexity and combinational explosion of states. Several naturally inspire evolutionary methods have been developed to solve Job Shop Scheduling Problems. In this paper the evolutionary methods namely Particles Swarm Optimization, Artificial Intelligence, Invasive Weed Optimization, Bacterial Foraging Optimization, Music Based Harmony Search Algorithms are applied and find tuned to model and solve Job Shop Scheduling Problems. To compare about 250 Bench Mark instances have been used to evaluate the performance of these algorithms. The capabilities of each these algorithms in solving Job Shop Scheduling Problems are outlined.

Enhancing chemistry problem-solving achievement using problem categorization

NASA Astrophysics Data System (ADS)

Bunce, Diane M.; Gabel, Dorothy L.; Samuel, John V.

The enhancement of chemistry students' skill in problem solving through problem categorization is the focus of this study. Twenty-four students in a freshman chemistry course for health professionals are taught how to solve problems using the explicit method of problem solving (EMPS) (Bunce & Heikkinen, 1986). The EMPS is an organized approach to problem analysis which includes encoding the information given in a problem (Given, Asked For), relating this to what is already in long-term memory (Recall), and planning a solution (Overall Plan) before a mathematical solution is attempted. In addition to the EMPS training, treatment students receive three 40-minute sessions following achievement tests in which they are taught how to categorize problems. Control students use this time to review the EMPS solutions of test questions. Although problem categorization is involved in one section of the EMPS (Recall), treatment students who received specific training in problem categorization demonstrate significantly higher achievement on combination problems (those problems requiring the use of more than one chemical topic for their solution) at (p = 0.01) than their counterparts. Significantly higher achievement for treatment students is also measured on an unannounced test (p = 0.02). Analysis of interview transcripts of both treatment and control students illustrates a Rolodex approach to problem solving employed by all students in this study. The Rolodex approach involves organizing equations used to solve problems on mental index cards and flipping through them, matching units given when a new problem is to be solved. A second phenomenon observed during student interviews is the absence of a link in the conceptual understanding of the chemical concepts involved in a problem and the problem-solving skills employed to correctly solve problems. This study shows that explicit training in categorization skills and the EMPS can lead to higher achievement in complex problem-solving situations (combination problems and unannounced test). However, such achievement may be limited by the lack of linkages between students' conceptual understanding and improved problem-solving skill.

Problem of quality assurance during metal constructions welding via robotic technological complexes

NASA Astrophysics Data System (ADS)

Fominykh, D. S.; Rezchikov, A. F.; Kushnikov, V. A.; Ivashchenko, V. A.; Bogomolov, A. S.; Filimonyuk, L. Yu; Dolinina, O. N.; Kushnikov, O. V.; Shulga, T. E.; Tverdokhlebov, V. A.

2018-05-01

The problem of minimizing the probability for critical combinations of events that lead to a loss in welding quality via robotic process automation is examined. The problem is formulated, models and algorithms for its solution are developed. The problem is solved by minimizing the criterion characterizing the losses caused by defective products. Solving the problem may enhance the quality and accuracy of operations performed and reduce the losses caused by defective product

Can Undergraduates Be Transdisciplinary? Promoting Transdisciplinary Engagement through Global Health Problem-Based Learning

ERIC Educational Resources Information Center

Hay, M. Cameron

2017-01-01

Undergraduate student learning focuses on the development of disciplinary strength in majors and minors so that students gain depth in particular fields, foster individual expertise, and learn problem solving from disciplinary perspectives. However, the complexities of real-world problems do not respect disciplinary boundaries. Complex problems…

How Students Process Equations in Solving Quantitative Synthesis Problems? Role of Mathematical Complexity in Students' Mathematical Performance

ERIC Educational Resources Information Center

Ibrahim, Bashirah; Ding, Lin; Heckler, Andrew F.; White, Daniel R.; Badeau, Ryan

2017-01-01

We examine students' mathematical performance on quantitative "synthesis problems" with varying mathematical complexity. Synthesis problems are tasks comprising multiple concepts typically taught in different chapters. Mathematical performance refers to the formulation, combination, and simplification of equations. Generally speaking,…

SYSTEMATIC PROCEDURE FOR DESIGNING PROCESSES WITH MULTIPLE ENVIRONMENTAL OBJECTIVES

EPA Science Inventory

Evaluation of multiple objectives is very important in designing environmentally benign processes. It requires a systematic procedure for solving multiobjective decision-making problems, due to the complex nature of the problems, the need for complex assessments, and complicated ...

Students' conceptual performance on synthesis physics problems with varying mathematical complexity

NASA Astrophysics Data System (ADS)

Ibrahim, Bashirah; Ding, Lin; Heckler, Andrew F.; White, Daniel R.; Badeau, Ryan

2017-06-01

A body of research on physics problem solving has focused on single-concept problems. In this study we use "synthesis problems" that involve multiple concepts typically taught in different chapters. We use two types of synthesis problems, sequential and simultaneous synthesis tasks. Sequential problems require a consecutive application of fundamental principles, and simultaneous problems require a concurrent application of pertinent concepts. We explore students' conceptual performance when they solve quantitative synthesis problems with varying mathematical complexity. Conceptual performance refers to the identification, follow-up, and correct application of the pertinent concepts. Mathematical complexity is determined by the type and the number of equations to be manipulated concurrently due to the number of unknowns in each equation. Data were collected from written tasks and individual interviews administered to physics major students (N =179 ) enrolled in a second year mechanics course. The results indicate that mathematical complexity does not impact students' conceptual performance on the sequential tasks. In contrast, for the simultaneous problems, mathematical complexity negatively influences the students' conceptual performance. This difference may be explained by the students' familiarity with and confidence in particular concepts coupled with cognitive load associated with manipulating complex quantitative equations. Another explanation pertains to the type of synthesis problems, either sequential or simultaneous task. The students split the situation presented in the sequential synthesis tasks into segments but treated the situation in the simultaneous synthesis tasks as a single event.

Development of a Preventive HIV Vaccine Requires Solving Inverse Problems Which Is Unattainable by Rational Vaccine Design

PubMed Central

Van Regenmortel, Marc H. V.

2018-01-01

Hypotheses and theories are essential constituents of the scientific method. Many vaccinologists are unaware that the problems they try to solve are mostly inverse problems that consist in imagining what could bring about a desired outcome. An inverse problem starts with the result and tries to guess what are the multiple causes that could have produced it. Compared to the usual direct scientific problems that start with the causes and derive or calculate the results using deductive reasoning and known mechanisms, solving an inverse problem uses a less reliable inductive approach and requires the development of a theoretical model that may have different solutions or none at all. Unsuccessful attempts to solve inverse problems in HIV vaccinology by reductionist methods, systems biology and structure-based reverse vaccinology are described. The popular strategy known as rational vaccine design is unable to solve the multiple inverse problems faced by HIV vaccine developers. The term “rational” is derived from “rational drug design” which uses the 3D structure of a biological target for designing molecules that will selectively bind to it and inhibit its biological activity. In vaccine design, however, the word “rational” simply means that the investigator is concentrating on parts of the system for which molecular information is available. The economist and Nobel laureate Herbert Simon introduced the concept of “bounded rationality” to explain why the complexity of the world economic system makes it impossible, for instance, to predict an event like the financial crash of 2007–2008. Humans always operate under unavoidable constraints such as insufficient information, a limited capacity to process huge amounts of data and a limited amount of time available to reach a decision. Such limitations always prevent us from achieving the complete understanding and optimization of a complex system that would be needed to achieve a truly rational design process. This is why the complexity of the human immune system prevents us from rationally designing an HIV vaccine by solving inverse problems. PMID:29387066

Transdisciplinary translational science and the case of preterm birth

PubMed Central

Stevenson, D K; Shaw, G M; Wise, P H; Norton, M E; Druzin, M L; Valantine, H A; McFarland, D A

2013-01-01

Medical researchers have called for new forms of translational science that can solve complex medical problems. Mainstream science has made complementary calls for heterogeneous teams of collaborators who conduct transdisciplinary research so as to solve complex social problems. Is transdisciplinary translational science what the medical community needs? What challenges must the medical community overcome to successfully implement this new form of translational science? This article makes several contributions. First, it clarifies the concept of transdisciplinary research and distinguishes it from other forms of collaboration. Second, it presents an example of a complex medical problem and a concrete effort to solve it through transdisciplinary collaboration: for example, the problem of preterm birth and the March of Dimes effort to form a transdisciplinary research center that synthesizes knowledge on it. The presentation of this example grounds discussion on new medical research models and reveals potential means by which they can be judged and evaluated. Third, this article identifies the challenges to forming transdisciplines and the practices that overcome them. Departments, universities and disciplines tend to form intellectual silos and adopt reductionist approaches. Forming a more integrated (or ‘constructionist'), problem-based science reflective of transdisciplinary research requires the adoption of novel practices to overcome these obstacles. PMID:23079774

Transdisciplinary translational science and the case of preterm birth.

PubMed

Stevenson, D K; Shaw, G M; Wise, P H; Norton, M E; Druzin, M L; Valantine, H A; McFarland, D A

2013-04-01

Medical researchers have called for new forms of translational science that can solve complex medical problems. Mainstream science has made complementary calls for heterogeneous teams of collaborators who conduct transdisciplinary research so as to solve complex social problems. Is transdisciplinary translational science what the medical community needs? What challenges must the medical community overcome to successfully implement this new form of translational science? This article makes several contributions. First, it clarifies the concept of transdisciplinary research and distinguishes it from other forms of collaboration. Second, it presents an example of a complex medical problem and a concrete effort to solve it through transdisciplinary collaboration: for example, the problem of preterm birth and the March of Dimes effort to form a transdisciplinary research center that synthesizes knowledge on it. The presentation of this example grounds discussion on new medical research models and reveals potential means by which they can be judged and evaluated. Third, this article identifies the challenges to forming transdisciplines and the practices that overcome them. Departments, universities and disciplines tend to form intellectual silos and adopt reductionist approaches. Forming a more integrated (or 'constructionist'), problem-based science reflective of transdisciplinary research requires the adoption of novel practices to overcome these obstacles.

Exploring Gender Differences in Solving Open-Ended Mathematical Problems.

ERIC Educational Resources Information Center

Cai, Jinfa

Open-ended tasks were used to examine gender differences in complex mathematical problem solving. The results of this study suggest that, overall, males perform better than females, but the gender differences vary from task to task. A qualitative analysis of student responses to those tasks with gender differences showed that male and female…

Leveraging Cultural Resources through Teacher Pedagogical Reasoning: Elementary Grade Teachers Analyze Second Language Learners' Science Problem Solving

ERIC Educational Resources Information Center

Buxton, Cory A.; Salinas, Alejandra; Mahotiere, Margarette; Lee, Okhee; Secada, Walter G.

2013-01-01

Grounded in teacher professional development addressing the intersection of student diversity and content area instruction, this study examined school teachers' pedagogical reasoning complexity as they reflected on their second language learners' science problem solving abilities using both home and school contexts. Teachers responded to interview…

A Language for the Analysis of Disciplinary Boundary Crossing: Insights from Engineering Problem-Solving Practice

ERIC Educational Resources Information Center

Wolff, Karin

2018-01-01

Poor graduate throughput and industry feedback on graduate inability to cope with the complex knowledge practices in twenty-first century engineering "problem solving" have placed pressure on educators to better conceptualise the theory-practice relationship, particularly in technology-dependent professions. The research draws on the…

Deep Learning towards Expertise Development in a Visualization-Based Learning Environment

ERIC Educational Resources Information Center

Yuan, Bei; Wang, Minhong; Kushniruk, Andre W.; Peng, Jun

2017-01-01

With limited problem-solving capability and practical experience, novices have difficulties developing expert-like performance. It is important to make the complex problem-solving process visible to learners and provide them with necessary help throughout the process. This study explores the design and effects of a model-based learning approach…

What's My Math Course Got to Do with Biology?

ERIC Educational Resources Information Center

Burks, Robert; Lindquist, Joseph; McMurran, Shawnee

2008-01-01

At United States Military Academy, a unit on biological modeling applications forms the culminating component of the first semester core mathematics course for freshmen. The course emphasizes the use of problem-solving strategies and modeling to solve complex and ill-defined problems. Topic areas include functions and their shapes, data fitting,…

Internet computer coaches for introductory physics problem solving

NASA Astrophysics Data System (ADS)

Xu Ryan, Qing

The ability to solve problems in a variety of contexts is becoming increasingly important in our rapidly changing technological society. Problem-solving is a complex process that is important for everyday life and crucial for learning physics. Although there is a great deal of effort to improve student problem solving skills throughout the educational system, national studies have shown that the majority of students emerge from such courses having made little progress toward developing good problem-solving skills. The Physics Education Research Group at the University of Minnesota has been developing Internet computer coaches to help students become more expert-like problem solvers. During the Fall 2011 and Spring 2013 semesters, the coaches were introduced into large sections (200+ students) of the calculus based introductory mechanics course at the University of Minnesota. This dissertation, will address the research background of the project, including the pedagogical design of the coaches and the assessment of problem solving. The methodological framework of conducting experiments will be explained. The data collected from the large-scale experimental studies will be discussed from the following aspects: the usage and usability of these coaches; the usefulness perceived by students; and the usefulness measured by final exam and problem solving rubric. It will also address the implications drawn from this study, including using this data to direct future coach design and difficulties in conducting authentic assessment of problem-solving.

Side effects of problem-solving strategies in large-scale nutrition science: towards a diversification of health.

PubMed

Penders, Bart; Vos, Rein; Horstman, Klasien

2009-11-01

Solving complex problems in large-scale research programmes requires cooperation and division of labour. Simultaneously, large-scale problem solving also gives rise to unintended side effects. Based upon 5 years of researching two large-scale nutrigenomic research programmes, we argue that problems are fragmented in order to be solved. These sub-problems are given priority for practical reasons and in the process of solving them, various changes are introduced in each sub-problem. Combined with additional diversity as a result of interdisciplinarity, this makes reassembling the original and overall goal of the research programme less likely. In the case of nutrigenomics and health, this produces a diversification of health. As a result, the public health goal of contemporary nutrition science is not reached in the large-scale research programmes we studied. Large-scale research programmes are very successful in producing scientific publications and new knowledge; however, in reaching their political goals they often are less successful.

The politics of insight

PubMed Central

Salvi, Carola; Cristofori, Irene; Grafman, Jordan; Beeman, Mark

2016-01-01

Previous studies showed that liberals and conservatives differ in cognitive style. Liberals are more flexible, and tolerant of complexity and novelty, whereas conservatives are more rigid, are more resistant to change, and prefer clear answers. We administered a set of compound remote associate problems, a task extensively used to differentiate problem-solving styles (via insight or analysis). Using this task, several researches have proven that self-reports, which differentiate between insight and analytic problem-solving, are reliable and are associated with two different neural circuits. In our research we found that participants self-identifying with distinct political orientations demonstrated differences in problem-solving strategy. Liberals solved significantly more problems via insight instead of in a step-by-step analytic fashion. Our findings extend previous observations that self-identified political orientations reflect differences in cognitive styles. More specifically, we show that type of political orientation is associated with problem-solving strategy. The data converge with previous neurobehavioural and cognitive studies indicating a link between cognitive style and the psychological mechanisms that mediate political beliefs. PMID:26810954

Directed Bee Colony Optimization Algorithm to Solve the Nurse Rostering Problem.

PubMed

Rajeswari, M; Amudhavel, J; Pothula, Sujatha; Dhavachelvan, P

2017-01-01

The Nurse Rostering Problem is an NP-hard combinatorial optimization, scheduling problem for assigning a set of nurses to shifts per day by considering both hard and soft constraints. A novel metaheuristic technique is required for solving Nurse Rostering Problem (NRP). This work proposes a metaheuristic technique called Directed Bee Colony Optimization Algorithm using the Modified Nelder-Mead Method for solving the NRP. To solve the NRP, the authors used a multiobjective mathematical programming model and proposed a methodology for the adaptation of a Multiobjective Directed Bee Colony Optimization (MODBCO). MODBCO is used successfully for solving the multiobjective problem of optimizing the scheduling problems. This MODBCO is an integration of deterministic local search, multiagent particle system environment, and honey bee decision-making process. The performance of the algorithm is assessed using the standard dataset INRC2010, and it reflects many real-world cases which vary in size and complexity. The experimental analysis uses statistical tools to show the uniqueness of the algorithm on assessment criteria.

Directed Bee Colony Optimization Algorithm to Solve the Nurse Rostering Problem

PubMed Central

Amudhavel, J.; Pothula, Sujatha; Dhavachelvan, P.

2017-01-01

The Nurse Rostering Problem is an NP-hard combinatorial optimization, scheduling problem for assigning a set of nurses to shifts per day by considering both hard and soft constraints. A novel metaheuristic technique is required for solving Nurse Rostering Problem (NRP). This work proposes a metaheuristic technique called Directed Bee Colony Optimization Algorithm using the Modified Nelder-Mead Method for solving the NRP. To solve the NRP, the authors used a multiobjective mathematical programming model and proposed a methodology for the adaptation of a Multiobjective Directed Bee Colony Optimization (MODBCO). MODBCO is used successfully for solving the multiobjective problem of optimizing the scheduling problems. This MODBCO is an integration of deterministic local search, multiagent particle system environment, and honey bee decision-making process. The performance of the algorithm is assessed using the standard dataset INRC2010, and it reflects many real-world cases which vary in size and complexity. The experimental analysis uses statistical tools to show the uniqueness of the algorithm on assessment criteria. PMID:28473849

The politics of insight.

PubMed

Salvi, Carola; Cristofori, Irene; Grafman, Jordan; Beeman, Mark

2016-01-01

Previous studies showed that liberals and conservatives differ in cognitive style. Liberals are more flexible, and tolerant of complexity and novelty, whereas conservatives are more rigid, are more resistant to change, and prefer clear answers. We administered a set of compound remote associate problems, a task extensively used to differentiate problem-solving styles (via insight or analysis). Using this task, several researches have proven that self-reports, which differentiate between insight and analytic problem-solving, are reliable and are associated with two different neural circuits. In our research we found that participants self-identifying with distinct political orientations demonstrated differences in problem-solving strategy. Liberals solved significantly more problems via insight instead of in a step-by-step analytic fashion. Our findings extend previous observations that self-identified political orientations reflect differences in cognitive styles. More specifically, we show that type of political orientation is associated with problem-solving strategy. The data converge with previous neurobehavioural and cognitive studies indicating a link between cognitive style and the psychological mechanisms that mediate political beliefs.

Are middle school mathematics teachers able to solve word problems without using variable?

NASA Astrophysics Data System (ADS)

Gökkurt Özdemir, Burçin; Erdem, Emrullah; Örnek, Tuğba; Soylu, Yasin

2018-01-01

Many people consider problem solving as a complex process in which variables such as x, y are used. Problems may not be solved by only using 'variable.' Problem solving can be rationalized and made easier using practical strategies. When especially the development of children at younger ages is considered, it is obvious that mathematics teachers should solve problems through concrete processes. In this context, middle school mathematics teachers' skills to solve word problems without using variables were examined in the current study. Through the case study method, this study was conducted with 60 middle school mathematics teachers who have different professional experiences in five provinces in Turkey. A test consisting of five open-ended word problems was used as the data collection tool. The content analysis technique was used to analyze the data. As a result of the analysis, it was seen that the most of the teachers used trial-and-error strategy or area model as the solution strategy. On the other hand, the teachers who solved the problems using variables such as x, a, n or symbols such as Δ, □, ○, * and who also felt into error by considering these solutions as without variable were also seen in the study.

A SYSTEMATIC PROCEDURE FOR DESIGNING PROCESSES WITH MULTIPLE ENVIRONMENTAL OBJECTIVES

EPA Science Inventory

Evaluation and analysis of multiple objectives are very important in designing environmentally benign processes. They require a systematic procedure for solving multi-objective decision-making problems due to the complex nature of the problems and the need for complex assessment....

Impact of Cognitive Abilities and Prior Knowledge on Complex Problem Solving Performance - Empirical Results and a Plea for Ecologically Valid Microworlds.

PubMed

Süß, Heinz-Martin; Kretzschmar, André

2018-01-01

The original aim of complex problem solving (CPS) research was to bring the cognitive demands of complex real-life problems into the lab in order to investigate problem solving behavior and performance under controlled conditions. Up until now, the validity of psychometric intelligence constructs has been scrutinized with regard to its importance for CPS performance. At the same time, different CPS measurement approaches competing for the title of the best way to assess CPS have been developed. In the first part of the paper, we investigate the predictability of CPS performance on the basis of the Berlin Intelligence Structure Model and Cattell's investment theory as well as an elaborated knowledge taxonomy. In the first study, 137 students managed a simulated shirt factory ( Tailorshop ; i.e., a complex real life-oriented system) twice, while in the second study, 152 students completed a forestry scenario ( FSYS ; i.e., a complex artificial world system). The results indicate that reasoning - specifically numerical reasoning (Studies 1 and 2) and figural reasoning (Study 2) - are the only relevant predictors among the intelligence constructs. We discuss the results with reference to the Brunswik symmetry principle. Path models suggest that reasoning and prior knowledge influence problem solving performance in the Tailorshop scenario mainly indirectly. In addition, different types of system-specific knowledge independently contribute to predicting CPS performance. The results of Study 2 indicate that working memory capacity, assessed as an additional predictor, has no incremental validity beyond reasoning. We conclude that (1) cognitive abilities and prior knowledge are substantial predictors of CPS performance, and (2) in contrast to former and recent interpretations, there is insufficient evidence to consider CPS a unique ability construct. In the second part of the paper, we discuss our results in light of recent CPS research, which predominantly utilizes the minimally complex systems (MCS) measurement approach. We suggest ecologically valid microworlds as an indispensable tool for future CPS research and applications.

Adaptive algorithm of selecting optimal variant of errors detection system for digital means of automation facility of oil and gas complex

NASA Astrophysics Data System (ADS)

Poluyan, A. Y.; Fugarov, D. D.; Purchina, O. A.; Nesterchuk, V. V.; Smirnova, O. V.; Petrenkova, S. B.

2018-05-01

To date, the problems associated with the detection of errors in digital equipment (DE) systems for the automation of explosive objects of the oil and gas complex are extremely actual. Especially this problem is actual for facilities where a violation of the accuracy of the DE will inevitably lead to man-made disasters and essential material damage, at such facilities, the diagnostics of the accuracy of the DE operation is one of the main elements of the industrial safety management system. In the work, the solution of the problem of selecting the optimal variant of the errors detection system of errors detection by a validation criterion. Known methods for solving these problems have an exponential valuation of labor intensity. Thus, with a view to reduce time for solving the problem, a validation criterion is compiled as an adaptive bionic algorithm. Bionic algorithms (BA) have proven effective in solving optimization problems. The advantages of bionic search include adaptability, learning ability, parallelism, the ability to build hybrid systems based on combining. [1].

Solving a class of generalized fractional programming problems using the feasibility of linear programs.

PubMed

Shen, Peiping; Zhang, Tongli; Wang, Chunfeng

2017-01-01

This article presents a new approximation algorithm for globally solving a class of generalized fractional programming problems (P) whose objective functions are defined as an appropriate composition of ratios of affine functions. To solve this problem, the algorithm solves an equivalent optimization problem (Q) via an exploration of a suitably defined nonuniform grid. The main work of the algorithm involves checking the feasibility of linear programs associated with the interesting grid points. It is proved that the proposed algorithm is a fully polynomial time approximation scheme as the ratio terms are fixed in the objective function to problem (P), based on the computational complexity result. In contrast to existing results in literature, the algorithm does not require the assumptions on quasi-concavity or low-rank of the objective function to problem (P). Numerical results are given to illustrate the feasibility and effectiveness of the proposed algorithm.

Stalking the IQ Quark.

ERIC Educational Resources Information Center

Sternberg, Robert J.

1979-01-01

An information-processing framework is presented for understanding intelligence. Two levels of processing are discussed: the steps involved in solving a complex intellectual task, and higher-order processes used to decide how to solve the problem. (MH)

The mathematical statement for the solving of the problem of N-version software system design

NASA Astrophysics Data System (ADS)

Kovalev, I. V.; Kovalev, D. I.; Zelenkov, P. V.; Voroshilova, A. A.

2015-10-01

The N-version programming, as a methodology of the fault-tolerant software systems design, allows successful solving of the mentioned tasks. The use of N-version programming approach turns out to be effective, since the system is constructed out of several parallel executed versions of some software module. Those versions are written to meet the same specification but by different programmers. The problem of developing an optimal structure of N-version software system presents a kind of very complex optimization problem. This causes the use of deterministic optimization methods inappropriate for solving the stated problem. In this view, exploiting heuristic strategies looks more rational. In the field of pseudo-Boolean optimization theory, the so called method of varied probabilities (MVP) has been developed to solve problems with a large dimensionality.

Psychosocial dimensions of solving an indoor air problem.

PubMed

Lahtinen, Marjaana; Huuhtanen, Pekka; Kähkönen, Erkki; Reijula, Kari

2002-03-01

This investigation focuses on the psychological and social dimensions of managing and solving indoor air problems. The data were collected in nine workplaces by interviews (n = 85) and questionnaires (n = 375). Indoor air problems in office environments have traditionally utilized industrial hygiene or technical expertise. However, indoor air problems at workplaces are often more complex issues to solve. Technical questions are inter-related with the dynamics of the work community, and the cooperation and interaction skills of the parties involved in the solving process are also put to the test. In the present study, the interviewees were very critical of the process of solving the indoor air problem. The responsibility for coordinating the problem-managing process was generally considered vague, as were the roles and functions of the various parties. Communication problems occurred and rumors about the indoor air problem circulated widely. Conflicts were common, complicating the process in several ways. The research focused on examining different ways of managing and resolving an indoor air problem. In addition, reference material on the causal factors of the indoor air problem was also acquired. The study supported the hypothesis that psychosocial factors play a significant role in indoor air problems.

Cognitive Task Analysis: Implications for the Theory and Practice of Instructional Design.

ERIC Educational Resources Information Center

Dehoney, Joanne

Cognitive task analysis grew out of efforts by cognitive psychologists to understand problem-solving in a lab setting. It has proved a useful tool for describing expert performance in complex problem solving domains. This review considers two general models of cognitive task analysis and examines the procedures and results of analyses in three…

Designs for Operationalizing Collaborative Problem Solving for Automated Assessment

ERIC Educational Resources Information Center

Scoular, Claire; Care, Esther; Hesse, Friedrich W.

2017-01-01

Collaborative problem solving is a complex skill set that draws on social and cognitive factors. The construct remains in its infancy due to lack of empirical evidence that can be drawn upon for validation. The differences and similarities between two large-scale initiatives that reflect this state of the art, in terms of underlying assumptions…

Case-Based Learning in Virtual Groups--Collaborative Problem Solving Activities and Learning Outcomes in a Virtual Professional Training Course

ERIC Educational Resources Information Center

Kopp, Birgitta; Hasenbein, Melanie; Mandl, Heinz

2014-01-01

This article analyzes the collaborative problem solving activities and learning outcomes of five groups that worked on two different complex cases in a virtual professional training course. In this asynchronous virtual learning environment, all knowledge management content was delivered virtually and collaboration took place through forums. To…

Children's Reasoning as Collective Social Action through Problem Solving in Grade 2/3 Science Classrooms

ERIC Educational Resources Information Center

Kim, Mijung

2016-01-01

Research on young children's reasoning show the complex relationships of knowledge, theories, and evidence in their decision-making and problem solving. Most of the research on children's reasoning skills has been done in individualized and formal research settings, not collective classroom environments where children often engage in learning and…

Integrating Cost Engineering and Project Management in a Junior Engineering Economics Course and a Senior Capstone Project Design Course

ERIC Educational Resources Information Center

Tickles, Virginia C.; Li, Yadong; Walters, Wilbur L.

2013-01-01

Much criticism exists concerning a lack of focus on real-world problem-solving in the science, technology, engineering and mathematics (STEM) infrastructures. Many of these critics say that current educational infrastructures are incapable in preparing future scientists and engineers to solve the complex and multidisciplinary problems this society…

The Role of Research Centers in Fulfilling the Community Engagement Mission of Public Research Universities

ERIC Educational Resources Information Center

Toof, Robin A.

2012-01-01

Institutions of higher education are seen by the public as having unique resources to identify and solve complex societal problems. Public universities, in particular, were originally established to be of service to communities and the nation to advance public good and solve problems. However, community engagement is not an easy task for…

Tracking Problem Solving by Multivariate Pattern Analysis and Hidden Markov Model Algorithms

ERIC Educational Resources Information Center

Anderson, John R.

2012-01-01

Multivariate pattern analysis can be combined with Hidden Markov Model algorithms to track the second-by-second thinking as people solve complex problems. Two applications of this methodology are illustrated with a data set taken from children as they interacted with an intelligent tutoring system for algebra. The first "mind reading" application…

Developing Ill-Structured Problem-Solving Skills through Wilderness Education

ERIC Educational Resources Information Center

Collins, Rachel H.; Sibthorp, Jim; Gookin, John

2016-01-01

In a society that is becoming more dynamic, complex, and diverse, the ability to solve ill-structured problems (ISPs) has become an increasingly critical skill. Students who enter adult roles with the cognitive skills to address ISPs will be better able to assume roles in the emerging economies. Opportunities to develop and practice these skills…

Examining the Role of Web 2.0 Tools in Supporting Problem Solving during Case-Based Instruction

ERIC Educational Resources Information Center

Koehler, Adrie A.; Newby, Timothy J.; Ertmer, Peggy A.

2017-01-01

As learners solve complex problems, such as the ones present in case narratives, they need instructional support. Potentially, Web 2.0 applications can be useful to learners during case-based instruction (CBI), as their affordances offer creative and collaborative opportunities. However, there is limited research available on how the affordances…

A Tale of Three Cases: Examining Accuracy, Efficiency, and Process Differences in Diagnosing Virtual Patient Cases

ERIC Educational Resources Information Center

Doleck, Tenzin; Jarrell, Amanda; Poitras, Eric G.; Chaouachi, Maher; Lajoie, Susanne P.

2016-01-01

Clinical reasoning is a central skill in diagnosing cases. However, diagnosing a clinical case poses several challenges that are inherent to solving multifaceted ill-structured problems. In particular, when solving such problems, the complexity stems from the existence of multiple paths to arriving at the correct solution (Lajoie, 2003). Moreover,…

They Learn the CLIL Way, but Do They Like It? Affectivity and Cognition in Upper-Primary CLIL Classes

ERIC Educational Resources Information Center

Otwinowska, Agnieszka; Forys, Malgorzata

2017-01-01

CLIL (Content and Language Integrated Learning) is a teaching method in which learners develop linguistic competence and problem-solving abilities by learning content subjects in another language. However, learners' cognitive gains may depend on their affectivity. Negative affect hampers complex cognitive processing essential for problem-solving,…

Problem solving stages in the five square problem

PubMed Central

Fedor, Anna; Szathmáry, Eörs; Öllinger, Michael

2015-01-01

According to the restructuring hypothesis, insight problem solving typically progresses through consecutive stages of search, impasse, insight, and search again for someone, who solves the task. The order of these stages was determined through self-reports of problem solvers and has never been verified behaviorally. We asked whether individual analysis of problem solving attempts of participants revealed the same order of problem solving stages as defined by the theory and whether their subjective feelings corresponded to the problem solving stages they were in. Our participants tried to solve the Five-Square problem in an online task, while we recorded the time and trajectory of their stick movements. After the task they were asked about their feelings related to insight and some of them also had the possibility of reporting impasse while working on the task. We found that the majority of participants did not follow the classic four-stage model of insight, but had more complex sequences of problem solving stages, with search and impasse recurring several times. This means that the classic four-stage model is not sufficient to describe variability on the individual level. We revised the classic model and we provide a new model that can generate all sequences found. Solvers reported insight more often than non-solvers and non-solvers reported impasse more often than solvers, as expected; but participants did not report impasse more often during behaviorally defined impasse stages than during other stages. This shows that impasse reports might be unreliable indicators of impasse. Our study highlights the importance of individual analysis of problem solving behavior to verify insight theory. PMID:26300794

Problem solving stages in the five square problem.

PubMed

Fedor, Anna; Szathmáry, Eörs; Öllinger, Michael

2015-01-01

According to the restructuring hypothesis, insight problem solving typically progresses through consecutive stages of search, impasse, insight, and search again for someone, who solves the task. The order of these stages was determined through self-reports of problem solvers and has never been verified behaviorally. We asked whether individual analysis of problem solving attempts of participants revealed the same order of problem solving stages as defined by the theory and whether their subjective feelings corresponded to the problem solving stages they were in. Our participants tried to solve the Five-Square problem in an online task, while we recorded the time and trajectory of their stick movements. After the task they were asked about their feelings related to insight and some of them also had the possibility of reporting impasse while working on the task. We found that the majority of participants did not follow the classic four-stage model of insight, but had more complex sequences of problem solving stages, with search and impasse recurring several times. This means that the classic four-stage model is not sufficient to describe variability on the individual level. We revised the classic model and we provide a new model that can generate all sequences found. Solvers reported insight more often than non-solvers and non-solvers reported impasse more often than solvers, as expected; but participants did not report impasse more often during behaviorally defined impasse stages than during other stages. This shows that impasse reports might be unreliable indicators of impasse. Our study highlights the importance of individual analysis of problem solving behavior to verify insight theory.

A new Euler scheme based on harmonic-polygon approach for solving first order ordinary differential equation

NASA Astrophysics Data System (ADS)

Yusop, Nurhafizah Moziyana Mohd; Hasan, Mohammad Khatim; Wook, Muslihah; Amran, Mohd Fahmi Mohamad; Ahmad, Siti Rohaidah

2017-10-01

There are many benefits to improve Euler scheme for solving the Ordinary Differential Equation Problems. Among the benefits are simple implementation and low-cost computational. However, the problem of accuracy in Euler scheme persuade scholar to use complex method. Therefore, the main purpose of this research are show the construction a new modified Euler scheme that improve accuracy of Polygon scheme in various step size. The implementing of new scheme are used Polygon scheme and Harmonic mean concept that called as Harmonic-Polygon scheme. This Harmonic-Polygon can provide new advantages that Euler scheme could offer by solving Ordinary Differential Equation problem. Four set of problems are solved via Harmonic-Polygon. Findings show that new scheme or Harmonic-Polygon scheme can produce much better accuracy result.

Environmental Sensing of Expert Knowledge in a Computational Evolution System for Complex Problem Solving in Human Genetics

NASA Astrophysics Data System (ADS)

Greene, Casey S.; Hill, Douglas P.; Moore, Jason H.

The relationship between interindividual variation in our genomes and variation in our susceptibility to common diseases is expected to be complex with multiple interacting genetic factors. A central goal of human genetics is to identify which DNA sequence variations predict disease risk in human populations. Our success in this endeavour will depend critically on the development and implementation of computational intelligence methods that are able to embrace, rather than ignore, the complexity of the genotype to phenotype relationship. To this end, we have developed a computational evolution system (CES) to discover genetic models of disease susceptibility involving complex relationships between DNA sequence variations. The CES approach is hierarchically organized and is capable of evolving operators of any arbitrary complexity. The ability to evolve operators distinguishes this approach from artificial evolution approaches using fixed operators such as mutation and recombination. Our previous studies have shown that a CES that can utilize expert knowledge about the problem in evolved operators significantly outperforms a CES unable to use this knowledge. This environmental sensing of external sources of biological or statistical knowledge is important when the search space is both rugged and large as in the genetic analysis of complex diseases. We show here that the CES is also capable of evolving operators which exploit one of several sources of expert knowledge to solve the problem. This is important for both the discovery of highly fit genetic models and because the particular source of expert knowledge used by evolved operators may provide additional information about the problem itself. This study brings us a step closer to a CES that can solve complex problems in human genetics in addition to discovering genetic models of disease.

Engineering applications of metaheuristics: an introduction

NASA Astrophysics Data System (ADS)

Oliva, Diego; Hinojosa, Salvador; Demeshko, M. V.

2017-01-01

Metaheuristic algorithms are important tools that in recent years have been used extensively in several fields. In engineering, there is a big amount of problems that can be solved from an optimization point of view. This paper is an introduction of how metaheuristics can be used to solve complex problems of engineering. Their use produces accurate results in problems that are computationally expensive. Experimental results support the performance obtained by the selected algorithms in such specific problems as digital filter design, image processing and solar cells design.

A Model for Developing Improvements to Critical Thinking Skills across the Community College Curriculum

ERIC Educational Resources Information Center

McGarrity, DeShawn N.

2013-01-01

Society is faced with more complex problems than in the past because of rapid advancements in technology. These complex problems require multi-dimensional problem-solving abilities that are consistent with higher-order thinking skills. Bok (2006) posits that over 90% of U.S. faculty members consider critical thinking skills as essential for…

Factors Affecting Police Officers' Acceptance of GIS Technologies: A Study of the Turkish National Police

ERIC Educational Resources Information Center

Cakar, Bekir

2011-01-01

The situations and problems that police officers face are more complex in today's society, due in part to the increase of technology and growing complexity of globalization. Accordingly, to solve these problems and deal with the complexities, law enforcement organizations develop and apply new techniques and methods such as geographic information…

Anodal Transcranial Direct Current Stimulation of the Prefrontal Cortex Enhances Complex Verbal Associative Thought

ERIC Educational Resources Information Center

Cerruti, Carlo; Schlaug, Gottfried

2009-01-01

The remote associates test (RAT) is a complex verbal task with associations to both creative thought and general intelligence. RAT problems require not only lateral associations and the internal production of many words but a convergent focus on a single answer. Complex problem-solving of this sort may thus require both substantial verbal…

The Strength of the Strongest Ties in Collaborative Problem Solving

NASA Astrophysics Data System (ADS)

de Montjoye, Yves-Alexandre; Stopczynski, Arkadiusz; Shmueli, Erez; Pentland, Alex; Lehmann, Sune

2014-06-01

Complex problem solving in science, engineering, and business has become a highly collaborative endeavor. Teams of scientists or engineers collaborate on projects using their social networks to gather new ideas and feedback. Here we bridge the literature on team performance and information networks by studying teams' problem solving abilities as a function of both their within-team networks and their members' extended networks. We show that, while an assigned team's performance is strongly correlated with its networks of expressive and instrumental ties, only the strongest ties in both networks have an effect on performance. Both networks of strong ties explain more of the variance than other factors, such as measured or self-evaluated technical competencies, or the personalities of the team members. In fact, the inclusion of the network of strong ties renders these factors non-significant in the statistical analysis. Our results have consequences for the organization of teams of scientists, engineers, and other knowledge workers tackling today's most complex problems.

The strength of the strongest ties in collaborative problem solving.

PubMed

de Montjoye, Yves-Alexandre; Stopczynski, Arkadiusz; Shmueli, Erez; Pentland, Alex; Lehmann, Sune

2014-06-20

Complex problem solving in science, engineering, and business has become a highly collaborative endeavor. Teams of scientists or engineers collaborate on projects using their social networks to gather new ideas and feedback. Here we bridge the literature on team performance and information networks by studying teams' problem solving abilities as a function of both their within-team networks and their members' extended networks. We show that, while an assigned team's performance is strongly correlated with its networks of expressive and instrumental ties, only the strongest ties in both networks have an effect on performance. Both networks of strong ties explain more of the variance than other factors, such as measured or self-evaluated technical competencies, or the personalities of the team members. In fact, the inclusion of the network of strong ties renders these factors non-significant in the statistical analysis. Our results have consequences for the organization of teams of scientists, engineers, and other knowledge workers tackling today's most complex problems.

Wolves, dogs, rearing and reinforcement: complex interactions underlying species differences in training and problem-solving performance.

PubMed

Frank, Harry

2011-11-01

Frank and Frank et al. (1982-1987) administered a series of age-graded training and problem-solving tasks to samples of Eastern timber wolf (C. lupus lycaon) and Alaskan Malamute (C. familiaris) pups to test Frank's (Zeitschrift für Tierpsychologie 53:389-399, 1980) model of the evolution of information processing under conditions of natural and artificial selection. Results confirmed the model's prediction that wolves should perform better than dogs on problem-solving tasks and that dogs should perform better than wolves on training tasks. Further data collected at the University of Connecticut in 1983 revealed a more complex and refined picture, indicating that species differences can be mediated by a number of factors influencing wolf performance, including socialization regimen (hand-rearing vs. mother-rearing), interactive effects of socialization on the efficacy of both rewards and punishments, and the flexibility to select learning strategies that experimenters might not anticipate.

Some observations on a new numerical method for solving Navier-Stokes equations

NASA Technical Reports Server (NTRS)

Kumar, A.

1981-01-01

An explicit-implicit technique for solving Navier-Stokes equations is described which, is much less complex than other implicit methods. It is used to solve a complex, two-dimensional, steady-state, supersonic-flow problem. The computational efficiency of the method and the quality of the solution obtained from it at high Courant-Friedrich-Lewy (CFL) numbers are discussed. Modifications are discussed and certain observations are made about the method which may be helpful in using it successfully.

Improved Monkey-King Genetic Algorithm for Solving Large Winner Determination in Combinatorial Auction

NASA Astrophysics Data System (ADS)

Li, Yuzhong

Using GA solve the winner determination problem (WDP) with large bids and items, run under different distribution, because the search space is large, constraint complex and it may easy to produce infeasible solution, would affect the efficiency and quality of algorithm. This paper present improved MKGA, including three operator: preprocessing, insert bid and exchange recombination, and use Monkey-king elite preservation strategy. Experimental results show that improved MKGA is better than SGA in population size and computation. The problem that traditional branch and bound algorithm hard to solve, improved MKGA can solve and achieve better effect.

Augmented neural networks and problem structure-based heuristics for the bin-packing problem

NASA Astrophysics Data System (ADS)

Kasap, Nihat; Agarwal, Anurag

2012-08-01

In this article, we report on a research project where we applied augmented-neural-networks (AugNNs) approach for solving the classical bin-packing problem (BPP). AugNN is a metaheuristic that combines a priority rule heuristic with the iterative search approach of neural networks to generate good solutions fast. This is the first time this approach has been applied to the BPP. We also propose a decomposition approach for solving harder BPP, in which subproblems are solved using a combination of AugNN approach and heuristics that exploit the problem structure. We discuss the characteristics of problems on which such problem structure-based heuristics could be applied. We empirically show the effectiveness of the AugNN and the decomposition approach on many benchmark problems in the literature. For the 1210 benchmark problems tested, 917 problems were solved to optimality and the average gap between the obtained solution and the upper bound for all the problems was reduced to under 0.66% and computation time averaged below 33 s per problem. We also discuss the computational complexity of our approach.

To draw or not to draw? Examining the necessity of problem diagrams using massive open online course experiments

NASA Astrophysics Data System (ADS)

Chen, Zhongzhou; Demirci, Neset; Choi, Youn-Jeng; Pritchard, David E.

2017-06-01

Previous research on problem diagrams suggested that including a supportive diagram, one that does not provide necessary problem solving information, may bring little, or even negative, benefit to students' problem solving success. We tested the usefulness of problem diagrams on 12 different physics problems (6A/B experiments) in our massive open online course. By analyzing over 8000 student responses in total, we found that including a problem diagram that contains no significant additional information only slightly improves the first attempt correct rate for the few most spatially complex problems, and has little impact on either the final correct percentage or the time spent on solving the problem. On the other hand, in half of the cases, removing the diagram significantly increased the fraction of students' drawing their own diagrams during problem solving. The increase in drawing behavior is largely independent of students' physics abilities. In summary, our results suggest that for many physics problems, the benefit of a diagram is exceedingly small and may not justify the effort of creating one.

A meta-heuristic method for solving scheduling problem: crow search algorithm

NASA Astrophysics Data System (ADS)

Adhi, Antono; Santosa, Budi; Siswanto, Nurhadi

2018-04-01

Scheduling is one of the most important processes in an industry both in manufacturingand services. The scheduling process is the process of selecting resources to perform an operation on tasks. Resources can be machines, peoples, tasks, jobs or operations.. The selection of optimum sequence of jobs from a permutation is an essential issue in every research in scheduling problem. Optimum sequence becomes optimum solution to resolve scheduling problem. Scheduling problem becomes NP-hard problem since the number of job in the sequence is more than normal number can be processed by exact algorithm. In order to obtain optimum results, it needs a method with capability to solve complex scheduling problems in an acceptable time. Meta-heuristic is a method usually used to solve scheduling problem. The recently published method called Crow Search Algorithm (CSA) is adopted in this research to solve scheduling problem. CSA is an evolutionary meta-heuristic method which is based on the behavior in flocks of crow. The calculation result of CSA for solving scheduling problem is compared with other algorithms. From the comparison, it is found that CSA has better performance in term of optimum solution and time calculation than other algorithms.

The pseudo-Boolean optimization approach to form the N-version software structure

NASA Astrophysics Data System (ADS)

Kovalev, I. V.; Kovalev, D. I.; Zelenkov, P. V.; Voroshilova, A. A.

2015-10-01

The problem of developing an optimal structure of N-version software system presents a kind of very complex optimization problem. This causes the use of deterministic optimization methods inappropriate for solving the stated problem. In this view, exploiting heuristic strategies looks more rational. In the field of pseudo-Boolean optimization theory, the so called method of varied probabilities (MVP) has been developed to solve problems with a large dimensionality. Some additional modifications of MVP have been made to solve the problem of N-version systems design. Those algorithms take into account the discovered specific features of the objective function. The practical experiments have shown the advantage of using these algorithm modifications because of reducing a search space.

The Social Essentials of Learning: An Experimental Investigation of Collaborative Problem Solving and Knowledge Construction in Mathematics Classrooms in Australia and China

ERIC Educational Resources Information Center

Chan, Man Ching Esther; Clarke, David; Cao, Yiming

2018-01-01

Interactive problem solving and learning are priorities in contemporary education, but these complex processes have proved difficult to research. This project addresses the question "How do we optimise social interaction for the promotion of learning in a mathematics classroom?" Employing the logic of multi-theoretic research design,…

The Management of Cognitive Load During Complex Cognitive Skill Acquisition by Means of Computer-Simulated Problem Solving

ERIC Educational Resources Information Center

Kester, Liesbeth; Kirschner, Paul A.; van Merrienboer, Jeroen J.G.

2005-01-01

This study compared the effects of two information presentation formats on learning to solve problems in electrical circuits. In one condition, the split-source format, information relating to procedural aspects of the functioning of an electrical circuit was not integrated in a circuit diagram, while information in the integrated format condition…

Solving Real World Problems with Alternate Reality Gaming: Student Experiences in the Global Village Playground Capstone Course Design

ERIC Educational Resources Information Center

Dondlinger, Mary Jo; McLeod, Julie K.

2015-01-01

The Global Village Playground (GVP) was a capstone learning experience designed to address institutional assessment needs while providing an integrated and authentic learning experience for students aimed at fostering complex problem solving, as well as critical and creative thinking. In the GVP, students work on simulated and real-world problems…

New Directions in Evaluating Social Problem Solving in Childhood: Early Precursors and Links to Adolescent Social Competence

ERIC Educational Resources Information Center

Landry, Susan H.; Smith, Karen E.; Swank, Paul R.

2009-01-01

A major objective of this chapter is to present a novel, ecologically sensitive social problem-solving task for school-aged children that captures the complexity of social and cognitive demands placed on children in naturalistic situations. Competence on this task correlates with a range of skills including executive functions, verbal reasoning,…

The Complex Relationship between Students' Critical Thinking and Epistemological Beliefs in the Context of Problem Solving

ERIC Educational Resources Information Center

Hyytinen, Heidi; Holma, Katariina; Toom, Auli; Shavelson, Richard J.; Lindblom-Ylänne, Sari

2014-01-01

The study utilized a multi-method approach to explore the connection between critical thinking and epistemological beliefs in a specific problem-solving situation. Data drawn from a sample of ten third-year bioscience students were collected using a combination of a cognitive lab and a performance task from the Collegiate Learning Assessment…

Calculation and Word Problem-Solving Skills in Primary Grades--Impact of Cognitive Abilities and Longitudinal Interrelations with Task-persistent Behaviour

ERIC Educational Resources Information Center

Jõgi, Anna-Liisa; Kikas, Eve

2016-01-01

Background: Primary school math skills form a basis for academic success down the road. Different math skills have different antecedents and there is a reason to believe that more complex math tasks require better self-regulation. Aims: The study aimed to investigate longitudinal interrelations of calculation and problem-solving skills, and…

Automation of multi-agent control for complex dynamic systems in heterogeneous computational network

NASA Astrophysics Data System (ADS)

Oparin, Gennady; Feoktistov, Alexander; Bogdanova, Vera; Sidorov, Ivan

2017-01-01

The rapid progress of high-performance computing entails new challenges related to solving large scientific problems for various subject domains in a heterogeneous distributed computing environment (e.g., a network, Grid system, or Cloud infrastructure). The specialists in the field of parallel and distributed computing give the special attention to a scalability of applications for problem solving. An effective management of the scalable application in the heterogeneous distributed computing environment is still a non-trivial issue. Control systems that operate in networks, especially relate to this issue. We propose a new approach to the multi-agent management for the scalable applications in the heterogeneous computational network. The fundamentals of our approach are the integrated use of conceptual programming, simulation modeling, network monitoring, multi-agent management, and service-oriented programming. We developed a special framework for an automation of the problem solving. Advantages of the proposed approach are demonstrated on the parametric synthesis example of the static linear regulator for complex dynamic systems. Benefits of the scalable application for solving this problem include automation of the multi-agent control for the systems in a parallel mode with various degrees of its detailed elaboration.

Planning and Scheduling for Fleets of Earth Observing Satellites

NASA Technical Reports Server (NTRS)

Frank, Jeremy; Jonsson, Ari; Morris, Robert; Smith, David E.; Norvig, Peter (Technical Monitor)

2001-01-01

We address the problem of scheduling observations for a collection of earth observing satellites. This scheduling task is a difficult optimization problem, potentially involving many satellites, hundreds of requests, constraints on when and how to service each request, and resources such as instruments, recording devices, transmitters, and ground stations. High-fidelity models are required to ensure the validity of schedules; at the same time, the size and complexity of the problem makes it unlikely that systematic optimization search methods will be able to solve them in a reasonable time. This paper presents a constraint-based approach to solving the Earth Observing Satellites (EOS) scheduling problem, and proposes a stochastic heuristic search method for solving it.

Quantum speedup in solving the maximal-clique problem

NASA Astrophysics Data System (ADS)

Chang, Weng-Long; Yu, Qi; Li, Zhaokai; Chen, Jiahui; Peng, Xinhua; Feng, Mang

2018-03-01

The maximal-clique problem, to find the maximally sized clique in a given graph, is classically an NP-complete computational problem, which has potential applications ranging from electrical engineering, computational chemistry, and bioinformatics to social networks. Here we develop a quantum algorithm to solve the maximal-clique problem for any graph G with n vertices with quadratic speedup over its classical counterparts, where the time and spatial complexities are reduced to, respectively, O (√{2n}) and O (n2) . With respect to oracle-related quantum algorithms for the NP-complete problems, we identify our algorithm as optimal. To justify the feasibility of the proposed quantum algorithm, we successfully solve a typical clique problem for a graph G with two vertices and one edge by carrying out a nuclear magnetic resonance experiment involving four qubits.

What are some of the cognitive, psychological, and social factors that facilitate or hinder licensed vocational nursing students' acquisition of problem-solving skills involved with medication-dosage calculations?

NASA Astrophysics Data System (ADS)

Allen, Arthur William

The purpose of this study was to examine the cognitive and psychological factors that either enhanced or inhibited Licensed Vocational Nurse (LVN) students' abilities to solve medication-dosage calculation problems. A causal-comparative approach was adopted for use in this study which encompassed aspects of both qualitative and quantitative data collection. A purposive, maximum-variation sample of 20 LVN students was chosen from among a self-selected population of junior college LVN students. The participants' views and feelings concerning their training and clinical experiences in medication administration was explored using a semi-structured interview. In addition, data revealing the students' actual competence at solving sample medication-dosage calculation problems was gathered using a talk-aloud protocol. Results indicated that few participants anticipated difficulty with medication-dosage calculations, yet many participants reported being lost during much of the medication-dosage problem solving instruction in class. While many participants (65%) were able to solve the medication-dosage problems, some (35%) of the participants were unable to correctly solve the problems. Successful students usually spent time analyzing the problem and planning a solution path, and they tended to solve the problem faster than did unsuccessful participants. Successful participants relied on a formula or a proportional statement to solve the problem. They recognized conversion problems as a two-step process and solved the problems in that fashion. Unsuccessful participants often went directly from reading the problem statement to attempts at implementing vague plans. Some unsuccessful participants finished quickly because they just gave up. Others spent considerable time backtracking by rereading the problem and participating in aimless exploration of the problem space. When unsuccessful participants tried to use a formula or a proportion, they were unsure of the formula's or the proportion's format. A few unsuccessful participants lacked an understanding of basic algebraic procedures and of metric measurements. Even participants who had great difficulty solving medication-dosage calculation problems could expeditiously solve more complex problems if the medication used in the problem was well known to them.

Lesion mapping of social problem solving

PubMed Central

Colom, Roberto; Paul, Erick J.; Chau, Aileen; Solomon, Jeffrey; Grafman, Jordan H.

2014-01-01

Accumulating neuroscience evidence indicates that human intelligence is supported by a distributed network of frontal and parietal regions that enable complex, goal-directed behaviour. However, the contributions of this network to social aspects of intellectual function remain to be well characterized. Here, we report a human lesion study (n = 144) that investigates the neural bases of social problem solving (measured by the Everyday Problem Solving Inventory) and examine the degree to which individual differences in performance are predicted by a broad spectrum of psychological variables, including psychometric intelligence (measured by the Wechsler Adult Intelligence Scale), emotional intelligence (measured by the Mayer, Salovey, Caruso Emotional Intelligence Test), and personality traits (measured by the Neuroticism-Extraversion-Openness Personality Inventory). Scores for each variable were obtained, followed by voxel-based lesion–symptom mapping. Stepwise regression analyses revealed that working memory, processing speed, and emotional intelligence predict individual differences in everyday problem solving. A targeted analysis of specific everyday problem solving domains (involving friends, home management, consumerism, work, information management, and family) revealed psychological variables that selectively contribute to each. Lesion mapping results indicated that social problem solving, psychometric intelligence, and emotional intelligence are supported by a shared network of frontal, temporal, and parietal regions, including white matter association tracts that bind these areas into a coordinated system. The results support an integrative framework for understanding social intelligence and make specific recommendations for the application of the Everyday Problem Solving Inventory to the study of social problem solving in health and disease. PMID:25070511

Advancing water resource management in agricultural, rural, and urbanizing watersheds: Enhancing University involvement

USDA-ARS?s Scientific Manuscript database

In this research editorial we make four points relative to solving water resource issues: (1) they are complex problems and difficult to solve, (2) some progress has been made on solving these issues, (3) external non-stationary drivers such as land use changes, climate change and variability, and s...

Identification and Addressing Reduction-Related Misconceptions

ERIC Educational Resources Information Center

Gal-Ezer, Judith; Trakhtenbrot, Mark

2016-01-01

Reduction is one of the key techniques used for problem-solving in computer science. In particular, in the theory of computation and complexity (TCC), mapping and polynomial reductions are used for analysis of decidability and computational complexity of problems, including the core concept of NP-completeness. Reduction is a highly abstract…

The Relationship between Students' Performance on Conventional Standardized Mathematics Assessments and Complex Mathematical Modeling Problems

ERIC Educational Resources Information Center

Kartal, Ozgul; Dunya, Beyza Aksu; Diefes-Dux, Heidi A.; Zawojewski, Judith S.

2016-01-01

Critical to many science, technology, engineering, and mathematics (STEM) career paths is mathematical modeling--specifically, the creation and adaptation of mathematical models to solve problems in complex settings. Conventional standardized measures of mathematics achievement are not structured to directly assess this type of mathematical…

Use of artificial bee colonies algorithm as numerical approximation of differential equations solution

NASA Astrophysics Data System (ADS)

Fikri, Fariz Fahmi; Nuraini, Nuning

2018-03-01

The differential equation is one of the branches in mathematics which is closely related to human life problems. Some problems that occur in our life can be modeled into differential equations as well as systems of differential equations such as the Lotka-Volterra model and SIR model. Therefore, solving a problem of differential equations is very important. Some differential equations are difficult to solve, so numerical methods are needed to solve that problems. Some numerical methods for solving differential equations that have been widely used are Euler Method, Heun Method, Runge-Kutta and others. However, some of these methods still have some restrictions that cause the method cannot be used to solve more complex problems such as an evaluation interval that we cannot change freely. New methods are needed to improve that problems. One of the method that can be used is the artificial bees colony algorithm. This algorithm is one of metaheuristic algorithm method, which can come out from local search space and do exploration in solution search space so that will get better solution than other method.

The Impact of Adaptive Complex Assessment on the HOT Skill Development of Students

ERIC Educational Resources Information Center

Raiyn, Jamal; Tilchin, Oleg

2016-01-01

In this paper we propose a method for the adaptive complex assessment (ACA) of the higher-order thinking (HOT) skills needed by students for problem solving, and we examine the impact of the method on the development of HOT skills in a problem-based learning (PBL) environment. Complexity in the assessment is provided by initial, formative, and…

Triz in Mems

NASA Astrophysics Data System (ADS)

Apte, Prakash R.

1999-11-01

TRIZ is a Russian abbreviation. Genrich Altshuller developed it fifty years ago in the former Soviet Union. He examined thousands of inventions made in different technological systems and formulated a 'Theory of Inventive problem solving' (TRIZ). Altshuller's research of over fifty years on Creativity and Inventive Problem Solving has led to many different classifications, methods and tools of invention. Some of these are, Contradictions table, Level of inventions, Patterns in evolution of technological systems, ARIZ-Algorithm for Inventive Problem Solving, Diagnostic problem solving and Anticipatory Failure Determination. MEMS research consists of conceptual design, process technology and including of various Mechanical, ELectrical, Thermal, Magnetic, Acoustic and other effects. MEMS system s are now rapidly growing in complexity. Each system will thus follow one or more 'patterns of evolution' as given by Altshuller. This paper attempts to indicate how various TRIZ tools can be used in MEMS research activities.

Quality improvement--boon or boondoggle?

PubMed

Paterson, M A; Wendel, J

1994-01-01

Is quality improvement (QI) reducing healthcare costs while improving patient care? Researchers find that QI has improved employee satisfaction and morale, but it was designed to do more. One solution is to use problem-solving techniques to help teams identify the level at which they want to address a problem, whether that be the subinstitutional, institutional, or system level. If QI is to fulfill its promise, skilled managers must create effective teams capable of defining and solving complex problems.

Flight control with adaptive critic neural network

NASA Astrophysics Data System (ADS)

Han, Dongchen

2001-10-01

In this dissertation, the adaptive critic neural network technique is applied to solve complex nonlinear system control problems. Based on dynamic programming, the adaptive critic neural network can embed the optimal solution into a neural network. Though trained off-line, the neural network forms a real-time feedback controller. Because of its general interpolation properties, the neurocontroller has inherit robustness. The problems solved here are an agile missile control for U.S. Air Force and a midcourse guidance law for U.S. Navy. In the first three papers, the neural network was used to control an air-to-air agile missile to implement a minimum-time heading-reverse in a vertical plane corresponding to following conditions: a system without constraint, a system with control inequality constraint, and a system with state inequality constraint. While the agile missile is a one-dimensional problem, the midcourse guidance law is the first test-bed for multiple-dimensional problem. In the fourth paper, the neurocontroller is synthesized to guide a surface-to-air missile to a fixed final condition, and to a flexible final condition from a variable initial condition. In order to evaluate the adaptive critic neural network approach, the numerical solutions for these cases are also obtained by solving two-point boundary value problem with a shooting method. All of the results showed that the adaptive critic neural network could solve complex nonlinear system control problems.

Tunnel Vision in Environmental Management.

ERIC Educational Resources Information Center

Miller, Alan

1982-01-01

Discusses problem-solving styles in environmental management and the specific deficiencies in these styles that might be grouped under the label "tunnel vision," a form of selective attention contributing to inadequate problem-formulation, partial solutions to complex problems, and generation of additional problems. Includes educational…

Coordinating complex problem-solving among distributed intelligent agents

NASA Technical Reports Server (NTRS)

Adler, Richard M.

1992-01-01

A process-oriented control model is described for distributed problem solving. The model coordinates the transfer and manipulation of information across independent networked applications, both intelligent and conventional. The model was implemented using SOCIAL, a set of object-oriented tools for distributing computing. Complex sequences of distributed tasks are specified in terms of high level scripts. Scripts are executed by SOCIAL objects called Manager Agents, which realize an intelligent coordination model that routes individual tasks to suitable server applications across the network. These tools are illustrated in a prototype distributed system for decision support of ground operations for NASA's Space Shuttle fleet.

A survey of intelligent tutoring systems: Implications for complex dynamic systems

NASA Technical Reports Server (NTRS)

Chu, Rose W.

1989-01-01

An overview of the research in the field of intelligent tutorial systems (ITS) is provided. The various approaches in the design and implementation of ITS are examined and discussed in the context of problem solving in an environment of a complex dynamic system (CDS). Issues pertaining to a CDS and the nature of human problem solving especially in light of a CDS are considered. An overview of the architecture of an ITS is provided as the basis for the in-depth examination of various systems. Finally, the implications for the design and evaluation of an ITS are discussed.

Predicting protein structures with a multiplayer online game.

PubMed

Cooper, Seth; Khatib, Firas; Treuille, Adrien; Barbero, Janos; Lee, Jeehyung; Beenen, Michael; Leaver-Fay, Andrew; Baker, David; Popović, Zoran; Players, Foldit

2010-08-05

People exert large amounts of problem-solving effort playing computer games. Simple image- and text-recognition tasks have been successfully 'crowd-sourced' through games, but it is not clear if more complex scientific problems can be solved with human-directed computing. Protein structure prediction is one such problem: locating the biologically relevant native conformation of a protein is a formidable computational challenge given the very large size of the search space. Here we describe Foldit, a multiplayer online game that engages non-scientists in solving hard prediction problems. Foldit players interact with protein structures using direct manipulation tools and user-friendly versions of algorithms from the Rosetta structure prediction methodology, while they compete and collaborate to optimize the computed energy. We show that top-ranked Foldit players excel at solving challenging structure refinement problems in which substantial backbone rearrangements are necessary to achieve the burial of hydrophobic residues. Players working collaboratively develop a rich assortment of new strategies and algorithms; unlike computational approaches, they explore not only the conformational space but also the space of possible search strategies. The integration of human visual problem-solving and strategy development capabilities with traditional computational algorithms through interactive multiplayer games is a powerful new approach to solving computationally-limited scientific problems.

Design and Diagnosis Problem Solving with Multifunctional Technical Knowledge Bases

DTIC Science & Technology

1992-09-29

STRUCTURE METHODOLOGY Design problem solving is a complex activity involving a number of subtasks. and a number of alternative methods potentially available...Conference on Artificial Intelligence. London: The British Computer Society, pp. 621-633. Friedland, P. (1979). Knowledge-based experimental design ...Computing Milieuxl: Management of Computing and Information Systems- -ty,*m man- agement General Terms: Design . Methodology Additional Key Words and Phrases

Creativity: Creativity in Complex Military Systems

DTIC Science & Technology

2017-05-25

generation later in the problem-solving process. The design process is an alternative problem-solving framework individuals or groups use to orient...no person shall be subject to any penalty for failing to comply with a collection of information if it does not display a currently valid OMB control ...the potential of their formations. 15. SUBJECT TERMS Creativity, Divergent Thinking, Design , Systems Thinking, Operational Art 16. SECURITY

A DEVELOPMENTAL STUDY OF THE RELATIONSHIP BETWEEN REACTION-TIME AND PROBLEM-SOLVING EFFICIENCY. FINAL REPORT.

ERIC Educational Resources Information Center

FRIEDMAN, STANLEY R.

MANY STUDIES HAVE INDICATED THE PRESENCE OF A SLUMP OR INVERSION IN THE PROBLEM-SOLVING EFFICIENCY OF CHILDREN AT THE FOURTH GRADE LEVEL. IT HAS BEEN SUGGESTED THAT THIS MAY BE DUE TO THE INTERFERING EFFECT OF THE FORMATION OF COMPLEX HYPOTHESES BY THE CHILDREN. SINCE A TENDENCY TO RESPOND RAPIDLY WOULD PRESUMABLY INHIBIT THE FORMATION OF COMPLEX…

A new fast algorithm for solving the minimum spanning tree problem based on DNA molecules computation.

PubMed

Wang, Zhaocai; Huang, Dongmei; Meng, Huajun; Tang, Chengpei

2013-10-01

The minimum spanning tree (MST) problem is to find minimum edge connected subsets containing all the vertex of a given undirected graph. It is a vitally important NP-complete problem in graph theory and applied mathematics, having numerous real life applications. Moreover in previous studies, DNA molecular operations usually were used to solve NP-complete head-to-tail path search problems, rarely for NP-hard problems with multi-lateral path solutions result, such as the minimum spanning tree problem. In this paper, we present a new fast DNA algorithm for solving the MST problem using DNA molecular operations. For an undirected graph with n vertex and m edges, we reasonably design flexible length DNA strands representing the vertex and edges, take appropriate steps and get the solutions of the MST problem in proper length range and O(3m+n) time complexity. We extend the application of DNA molecular operations and simultaneity simplify the complexity of the computation. Results of computer simulative experiments show that the proposed method updates some of the best known values with very short time and that the proposed method provides a better performance with solution accuracy over existing algorithms. Copyright © 2013 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

A New Approach for Solving the Generalized Traveling Salesman Problem

NASA Astrophysics Data System (ADS)

Pop, P. C.; Matei, O.; Sabo, C.

The generalized traveling problem (GTSP) is an extension of the classical traveling salesman problem. The GTSP is known to be an NP-hard problem and has many interesting applications. In this paper we present a local-global approach for the generalized traveling salesman problem. Based on this approach we describe a novel hybrid metaheuristic algorithm for solving the problem using genetic algorithms. Computational results are reported for Euclidean TSPlib instances and compared with the existing ones. The obtained results point out that our hybrid algorithm is an appropriate method to explore the search space of this complex problem and leads to good solutions in a reasonable amount of time.

Performance impact of mutation operators of a subpopulation-based genetic algorithm for multi-robot task allocation problems.

PubMed

Liu, Chun; Kroll, Andreas

2016-01-01

Multi-robot task allocation determines the task sequence and distribution for a group of robots in multi-robot systems, which is one of constrained combinatorial optimization problems and more complex in case of cooperative tasks because they introduce additional spatial and temporal constraints. To solve multi-robot task allocation problems with cooperative tasks efficiently, a subpopulation-based genetic algorithm, a crossover-free genetic algorithm employing mutation operators and elitism selection in each subpopulation, is developed in this paper. Moreover, the impact of mutation operators (swap, insertion, inversion, displacement, and their various combinations) is analyzed when solving several industrial plant inspection problems. The experimental results show that: (1) the proposed genetic algorithm can obtain better solutions than the tested binary tournament genetic algorithm with partially mapped crossover; (2) inversion mutation performs better than other tested mutation operators when solving problems without cooperative tasks, and the swap-inversion combination performs better than other tested mutation operators/combinations when solving problems with cooperative tasks. As it is difficult to produce all desired effects with a single mutation operator, using multiple mutation operators (including both inversion and swap) is suggested when solving similar combinatorial optimization problems.

Restart Operator Meta-heuristics for a Problem-Oriented Evolutionary Strategies Algorithm in Inverse Mathematical MISO Modelling Problem Solving

NASA Astrophysics Data System (ADS)

Ryzhikov, I. S.; Semenkin, E. S.

2017-02-01

This study is focused on solving an inverse mathematical modelling problem for dynamical systems based on observation data and control inputs. The mathematical model is being searched in the form of a linear differential equation, which determines the system with multiple inputs and a single output, and a vector of the initial point coordinates. The described problem is complex and multimodal and for this reason the proposed evolutionary-based optimization technique, which is oriented on a dynamical system identification problem, was applied. To improve its performance an algorithm restart operator was implemented.

A new parallel DNA algorithm to solve the task scheduling problem based on inspired computational model.

PubMed

Wang, Zhaocai; Ji, Zuwen; Wang, Xiaoming; Wu, Tunhua; Huang, Wei

2017-12-01

As a promising approach to solve the computationally intractable problem, the method based on DNA computing is an emerging research area including mathematics, computer science and molecular biology. The task scheduling problem, as a well-known NP-complete problem, arranges n jobs to m individuals and finds the minimum execution time of last finished individual. In this paper, we use a biologically inspired computational model and describe a new parallel algorithm to solve the task scheduling problem by basic DNA molecular operations. In turn, we skillfully design flexible length DNA strands to represent elements of the allocation matrix, take appropriate biological experiment operations and get solutions of the task scheduling problem in proper length range with less than O(n 2 ) time complexity. Copyright © 2017. Published by Elsevier B.V.

A Kohonen-like decomposition method for the Euclidean traveling salesman problem-KNIES/spl I.bar/DECOMPOSE.

PubMed

Aras, N; Altinel, I K; Oommen, J

2003-01-01

In addition to the classical heuristic algorithms of operations research, there have also been several approaches based on artificial neural networks for solving the traveling salesman problem. Their efficiency, however, decreases as the problem size (number of cities) increases. A technique to reduce the complexity of a large-scale traveling salesman problem (TSP) instance is to decompose or partition it into smaller subproblems. We introduce an all-neural decomposition heuristic that is based on a recent self-organizing map called KNIES, which has been successfully implemented for solving both the Euclidean traveling salesman problem and the Euclidean Hamiltonian path problem. Our solution for the Euclidean TSP proceeds by solving the Euclidean HPP for the subproblems, and then patching these solutions together. No such all-neural solution has ever been reported.

On unified modeling, theory, and method for solving multi-scale global optimization problems

NASA Astrophysics Data System (ADS)

Gao, David Yang

2016-10-01

A unified model is proposed for general optimization problems in multi-scale complex systems. Based on this model and necessary assumptions in physics, the canonical duality theory is presented in a precise way to include traditional duality theories and popular methods as special applications. Two conjectures on NP-hardness are proposed, which should play important roles for correctly understanding and efficiently solving challenging real-world problems. Applications are illustrated for both nonconvex continuous optimization and mixed integer nonlinear programming.

Fighting On All Fronts: A Critical Review Of The US Strategy Against ISIL

DTIC Science & Technology

2016-05-26

developing a base sense of the sheer complexity. The Shia led Iraqi government has exacerbated tensions with the Sunnis through its heavy-handedness...only a part. In effect, only the symptom of a problem is being addressed instead of the getting at the core of the problem . Looking at ISIL through ...13 Solving the Right Problem : Framing ISIL Through Complexity Science

Embodied Interactions in Human-Machine Decision Making for Situation Awareness Enhancement Systems

DTIC Science & Technology

2016-06-09

characterize differences in spatial navigation strategies in a complex task, the Traveling Salesman Problem (TSP). For the second year, we developed...visual processing, leading to better solutions for spatial optimization problems . I will develop a framework to determine which body expressions best...methods include systematic characterization of gestures during complex problem solving. 15. SUBJECT TERMS Embodied interaction, gestures, one-shot

Application of the boundary integral method to immiscible displacement problems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Masukawa, J.; Horne, R.N.

1988-08-01

This paper presents an application of the boundary integral method (BIM) to fluid displacement problems to demonstrate its usefulness in reservoir simulation. A method for solving two-dimensional (2D), piston-like displacement for incompressible fluids with good accuracy has been developed. Several typical example problems with repeated five-spot patterns were solved for various mobility ratios. The solutions were compared with the analytical solutions to demonstrate accuracy. Singularity programming was found to be a major advantage in handling flow in the vicinity of wells. The BIM was found to be an excellent way to solve immiscible displacement problems. Unlike analytic methods, it canmore » accommodate complex boundary shapes and does not suffer from numerical dispersion at the front.« less

Simulated annealing algorithm for solving chambering student-case assignment problem

NASA Astrophysics Data System (ADS)

Ghazali, Saadiah; Abdul-Rahman, Syariza

2015-12-01

The problem related to project assignment problem is one of popular practical problem that appear nowadays. The challenge of solving the problem raise whenever the complexity related to preferences, the existence of real-world constraints and problem size increased. This study focuses on solving a chambering student-case assignment problem by using a simulated annealing algorithm where this problem is classified under project assignment problem. The project assignment problem is considered as hard combinatorial optimization problem and solving it using a metaheuristic approach is an advantage because it could return a good solution in a reasonable time. The problem of assigning chambering students to cases has never been addressed in the literature before. For the proposed problem, it is essential for law graduates to peruse in chambers before they are qualified to become legal counselor. Thus, assigning the chambering students to cases is a critically needed especially when involving many preferences. Hence, this study presents a preliminary study of the proposed project assignment problem. The objective of the study is to minimize the total completion time for all students in solving the given cases. This study employed a minimum cost greedy heuristic in order to construct a feasible initial solution. The search then is preceded with a simulated annealing algorithm for further improvement of solution quality. The analysis of the obtained result has shown that the proposed simulated annealing algorithm has greatly improved the solution constructed by the minimum cost greedy heuristic. Hence, this research has demonstrated the advantages of solving project assignment problem by using metaheuristic techniques.

Does Supporting Multiple Student Strategies Lead to Greater Learning and Motivation? Investigating a Source of Complexity in the Architecture of Intelligent Tutoring Systems

ERIC Educational Resources Information Center

Waalkens, Maaike; Aleven, Vincent; Taatgen, Niels

2013-01-01

Intelligent tutoring systems (ITS) support students in learning a complex problem-solving skill. One feature that makes an ITS architecturally complex, and hard to build, is support for strategy freedom, that is, the ability to let students pursue multiple solution strategies within a given problem. But does greater freedom mean that students…

Amnestic mild cognitive impairment: functional MR imaging study of response in posterior cingulate cortex and adjacent precuneus during problem-solving tasks.

PubMed

Jin, Guangwei; Li, Kuncheng; Hu, Yingying; Qin, Yulin; Wang, Xiangqing; Xiang, Jie; Yang, Yanhui; Lu, Jie; Zhong, Ning

2011-11-01

To compare the blood oxygen level-dependent (BOLD) response, measured with functional magnetic resonance (MR) imaging, in the posterior cingulate cortex (PCC) and adjacent precuneus regions between healthy control subjects and patients with amnestic mild cognitive impairment (MCI) during problem-solving tasks. This study was approved by the institutional review board. Each subject provided written informed consent. Thirteen patients with amnestic MCI and 13 age- and sex-matched healthy control subjects participated in the study. The functional magnetic resonance (MR) imaging tasks were simplified 4 × 4-grid number placement puzzles that were divided into a simple task (using the row rule or the column rule to solve the puzzle) and a complex task (using both the row and column rules to solve the puzzle). Behavioral results and functional imaging results between the healthy control group and the amnestic MCI group were analyzed. The accuracy for the complex task in the healthy control group was significantly higher than that in the amnestic MCI group (P < .05). The healthy control group exhibited a deactivated BOLD signal intensity (SI) change in the bilateral PCC and adjacent precuneus regions during the complex task, whereas the amnestic MCI group showed activation. The positive linear correlations between the BOLD SI change in bilateral PCC and adjacent precuneus regions and in bilateral hippocampi in the amnestic MCI group were significant (P < .001), while in the healthy control group, they were not (P ≥ .23). These findings suggest that an altered BOLD response in amnestic MCI patients during complex tasks might be related to a decline in problem-solving ability and to memory impairment and, thus, may indicate a compensatory response to memory impairment. RSNA, 2011

Impact of Cognitive Abilities and Prior Knowledge on Complex Problem Solving Performance – Empirical Results and a Plea for Ecologically Valid Microworlds

PubMed Central

Süß, Heinz-Martin; Kretzschmar, André

2018-01-01

The original aim of complex problem solving (CPS) research was to bring the cognitive demands of complex real-life problems into the lab in order to investigate problem solving behavior and performance under controlled conditions. Up until now, the validity of psychometric intelligence constructs has been scrutinized with regard to its importance for CPS performance. At the same time, different CPS measurement approaches competing for the title of the best way to assess CPS have been developed. In the first part of the paper, we investigate the predictability of CPS performance on the basis of the Berlin Intelligence Structure Model and Cattell’s investment theory as well as an elaborated knowledge taxonomy. In the first study, 137 students managed a simulated shirt factory (Tailorshop; i.e., a complex real life-oriented system) twice, while in the second study, 152 students completed a forestry scenario (FSYS; i.e., a complex artificial world system). The results indicate that reasoning – specifically numerical reasoning (Studies 1 and 2) and figural reasoning (Study 2) – are the only relevant predictors among the intelligence constructs. We discuss the results with reference to the Brunswik symmetry principle. Path models suggest that reasoning and prior knowledge influence problem solving performance in the Tailorshop scenario mainly indirectly. In addition, different types of system-specific knowledge independently contribute to predicting CPS performance. The results of Study 2 indicate that working memory capacity, assessed as an additional predictor, has no incremental validity beyond reasoning. We conclude that (1) cognitive abilities and prior knowledge are substantial predictors of CPS performance, and (2) in contrast to former and recent interpretations, there is insufficient evidence to consider CPS a unique ability construct. In the second part of the paper, we discuss our results in light of recent CPS research, which predominantly utilizes the minimally complex systems (MCS) measurement approach. We suggest ecologically valid microworlds as an indispensable tool for future CPS research and applications. PMID:29867627

Experimental realization of a one-way quantum computer algorithm solving Simon's problem.

PubMed

Tame, M S; Bell, B A; Di Franco, C; Wadsworth, W J; Rarity, J G

2014-11-14

We report an experimental demonstration of a one-way implementation of a quantum algorithm solving Simon's problem-a black-box period-finding problem that has an exponential gap between the classical and quantum runtime. Using an all-optical setup and modifying the bases of single-qubit measurements on a five-qubit cluster state, key representative functions of the logical two-qubit version's black box can be queried and solved. To the best of our knowledge, this work represents the first experimental realization of the quantum algorithm solving Simon's problem. The experimental results are in excellent agreement with the theoretical model, demonstrating the successful performance of the algorithm. With a view to scaling up to larger numbers of qubits, we analyze the resource requirements for an n-qubit version. This work helps highlight how one-way quantum computing provides a practical route to experimentally investigating the quantum-classical gap in the query complexity model.

Multi-step optimization strategy for fuel-optimal orbital transfer of low-thrust spacecraft

NASA Astrophysics Data System (ADS)

Rasotto, M.; Armellin, R.; Di Lizia, P.

2016-03-01

An effective method for the design of fuel-optimal transfers in two- and three-body dynamics is presented. The optimal control problem is formulated using calculus of variation and primer vector theory. This leads to a multi-point boundary value problem (MPBVP), characterized by complex inner constraints and a discontinuous thrust profile. The first issue is addressed by embedding the MPBVP in a parametric optimization problem, thus allowing a simplification of the set of transversality constraints. The second problem is solved by representing the discontinuous control function by a smooth function depending on a continuation parameter. The resulting trajectory optimization method can deal with different intermediate conditions, and no a priori knowledge of the control structure is required. Test cases in both the two- and three-body dynamics show the capability of the method in solving complex trajectory design problems.

Lions (Panthera leo) solve, learn, and remember a novel resource acquisition problem.

PubMed

Borrego, Natalia; Dowling, Brian

2016-09-01

The social intelligence hypothesis proposes that the challenges of complex social life bolster the evolution of intelligence, and accordingly, advanced cognition has convergently evolved in several social lineages. Lions (Panthera leo) offer an ideal model system for cognitive research in a highly social species with an egalitarian social structure. We investigated cognition in lions using a novel resource task: the suspended puzzle box. The task required lions (n = 12) to solve a novel problem, learn the techniques used to solve the problem, and remember techniques for use in future trials. The majority of lions demonstrated novel problem-solving and learning; lions (11/12) solved the task, repeated success in multiple trials, and significantly reduced the latency to success across trials. Lions also demonstrated cognitive abilities associated with memory and solved the task after up to a 7-month testing interval. We also observed limited evidence for social facilitation of the task solution. Four of five initially unsuccessful lions achieved success after being partnered with a successful lion. Overall, our results support the presence of cognition associated with novel problem-solving, learning, and memory in lions. To date, our study is only the second experimental investigation of cognition in lions and further supports expanding cognitive research to lions.

The application of dynamic programming in production planning

NASA Astrophysics Data System (ADS)

Wu, Run

2017-05-01

Nowadays, with the popularity of the computers, various industries and fields are widely applying computer information technology, which brings about huge demand for a variety of application software. In order to develop software meeting various needs with most economical cost and best quality, programmers must design efficient algorithms. A superior algorithm can not only soul up one thing, but also maximize the benefits and generate the smallest overhead. As one of the common algorithms, dynamic programming algorithms are used to solving problems with some sort of optimal properties. When solving problems with a large amount of sub-problems that needs repetitive calculations, the ordinary sub-recursive method requires to consume exponential time, and dynamic programming algorithm can reduce the time complexity of the algorithm to the polynomial level, according to which we can conclude that dynamic programming algorithm is a very efficient compared to other algorithms reducing the computational complexity and enriching the computational results. In this paper, we expound the concept, basic elements, properties, core, solving steps and difficulties of the dynamic programming algorithm besides, establish the dynamic programming model of the production planning problem.

Weak task-related modulation and stimulus representations during arithmetic problem solving in children with developmental dyscalculia

PubMed Central

Ashkenazi, Sarit; Rosenberg-Lee, Miriam; Tenison, Caitlin; Menon, Vinod

2015-01-01

Developmental dyscalculia (DD) is a disability that impacts math learning and skill acquisition in school-age children. Here we investigate arithmetic problem solving deficits in young children with DD using univariate and multivariate analysis of fMRI data. During fMRI scanning, 17 children with DD (ages 7–9, grades 2 and 3) and 17 IQ- and reading ability-matched typically developing (TD) children performed complex and simple addition problems which differed only in arithmetic complexity. While the TD group showed strong modulation of brain responses with increasing arithmetic complexity, children with DD failed to show such modulation. Children with DD showed significantly reduced activation compared to TD children in the intraparietal sulcus, superior parietal lobule, supramarginal gyrus and bilateral dorsolateral prefrontal cortex in relation to arithmetic complexity. Critically, multivariate representational similarity revealed that brain response patterns to complex and simple problems were less differentiated in the DD group in bilateral anterior IPS, independent of overall differences in signal level. Taken together, these results show that children with DD not only under-activate key brain regions implicated in mathematical cognition, but they also fail to generate distinct neural responses and representations for different arithmetic problems. Our findings provide novel insights into the neural basis of DD. PMID:22682904

Weak task-related modulation and stimulus representations during arithmetic problem solving in children with developmental dyscalculia.

PubMed

Ashkenazi, Sarit; Rosenberg-Lee, Miriam; Tenison, Caitlin; Menon, Vinod

2012-02-15

Developmental dyscalculia (DD) is a disability that impacts math learning and skill acquisition in school-age children. Here we investigate arithmetic problem solving deficits in young children with DD using univariate and multivariate analysis of fMRI data. During fMRI scanning, 17 children with DD (ages 7-9, grades 2 and 3) and 17 IQ- and reading ability-matched typically developing (TD) children performed complex and simple addition problems which differed only in arithmetic complexity. While the TD group showed strong modulation of brain responses with increasing arithmetic complexity, children with DD failed to show such modulation. Children with DD showed significantly reduced activation compared to TD children in the intraparietal sulcus, superior parietal lobule, supramarginal gyrus and bilateral dorsolateral prefrontal cortex in relation to arithmetic complexity. Critically, multivariate representational similarity revealed that brain response patterns to complex and simple problems were less differentiated in the DD group in bilateral anterior IPS, independent of overall differences in signal level. Taken together, these results show that children with DD not only under-activate key brain regions implicated in mathematical cognition, but they also fail to generate distinct neural responses and representations for different arithmetic problems. Our findings provide novel insights into the neural basis of DD. Copyright © 2011 Elsevier Ltd. All rights reserved.

The Community Collaboration Stakeholder Project

ERIC Educational Resources Information Center

Heath, Renee Guarriello

2010-01-01

Today's increasingly complex and diverse world demands 21st century communication skills to solve community and social justice problems. Interorganizational collaboration is at the heart of much community activism, such as that focused on solving environmental disputes, eradicating racially discriminating real estate practices, and bringing early…

Examining the Effects of Field Dependence-Independence on Learners' Problem-Solving Performance and Interaction with a Computer Modeling Tool: Implications for the Design of Joint Cognitive Systems

ERIC Educational Resources Information Center

Angeli, Charoula

2013-01-01

An investigation was carried out to examine the effects of cognitive style on learners' performance and interaction during complex problem solving with a computer modeling tool. One hundred and nineteen undergraduates volunteered to participate in the study. Participants were first administered a test, and based on their test scores they were…

A multiblock/multizone code (PAB 3D-v2) for the three-dimensional Navier-Stokes equations: Preliminary applications

NASA Technical Reports Server (NTRS)

Abdol-Hamid, Khaled S.

1990-01-01

The development and applications of multiblock/multizone and adaptive grid methodologies for solving the three-dimensional simplified Navier-Stokes equations are described. Adaptive grid and multiblock/multizone approaches are introduced and applied to external and internal flow problems. These new implementations increase the capabilities and flexibility of the PAB3D code in solving flow problems associated with complex geometry.

Outcomes-Based Authentic Learning, Portfolio Assessment, and a Systems Approach to "Complex Problem-Solving": Related Pillars for Enhancing the Innovative Role of PBL in Future Higher Education

ERIC Educational Resources Information Center

Richards, Cameron

2015-01-01

The challenge of better reconciling individual and collective aspects of innovative problem-solving can be productively addressed to enhance the role of PBL as a key focus of the creative process in future higher education. This should involve "active learning" approaches supported by related processes of teaching, assessment and…

Fellowship Connects Principal Learning to Student Achievement: How an External Benefactor, a Research University, and an Urban School District Build Capacity for Problem Solving

ERIC Educational Resources Information Center

Dunbar, Krista; Monson, Robert J.

2011-01-01

Much has been written about the disconnect between education research produced in graduate schools of education and the practice of school leaders. In this article, the authors share one story of an external partnership that promotes the development of a principal's capacity for complex problem solving and the early research that suggests this…

The solution of the optimization problem of small energy complexes using linear programming methods

NASA Astrophysics Data System (ADS)

Ivanin, O. A.; Director, L. B.

2016-11-01

Linear programming methods were used for solving the optimization problem of schemes and operation modes of distributed generation energy complexes. Applicability conditions of simplex method, applied to energy complexes, including installations of renewable energy (solar, wind), diesel-generators and energy storage, considered. The analysis of decomposition algorithms for various schemes of energy complexes was made. The results of optimization calculations for energy complexes, operated autonomously and as a part of distribution grid, are presented.

Design of a cooperative problem-solving system for en-route flight planning: An empirical evaluation

NASA Technical Reports Server (NTRS)

Layton, Charles; Smith, Philip J.; Mc Coy, C. Elaine

1994-01-01

Both optimization techniques and expert systems technologies are popular approaches for developing tools to assist in complex problem-solving tasks. Because of the underlying complexity of many such tasks, however, the models of the world implicitly or explicitly embedded in such tools are often incomplete and the problem-solving methods fallible. The result can be 'brittleness' in situations that were not anticipated by the system designers. To deal with this weakness, it has been suggested that 'cooperative' rather than 'automated' problem-solving systems be designed. Such cooperative systems are proposed to explicitly enhance the collaboration of the person (or a group of people) and the computer system. This study evaluates the impact of alternative design concepts on the performance of 30 airline pilots interacting with such a cooperative system designed to support en-route flight planning. The results clearly demonstrate that different system design concepts can strongly influence the cognitive processes and resultant performances of users. Based on think-aloud protocols, cognitive models are proposed to account for how features of the computer system interacted with specific types of scenarios to influence exploration and decision making by the pilots. The results are then used to develop recommendations for guiding the design of cooperative systems.

Design of a cooperative problem-solving system for en-route flight planning: An empirical evaluation

NASA Technical Reports Server (NTRS)

Layton, Charles; Smith, Philip J.; McCoy, C. Elaine

1994-01-01

Both optimization techniques and expert systems technologies are popular approaches for developing tools to assist in complex problem-solving tasks. Because of the underlying complexity of many such tasks, however, the models of the world implicitly or explicitly embedded in such tools are often incomplete and the problem-solving methods fallible. The result can be 'brittleness' in situations that were not anticipated by the system designers. To deal with this weakness, it has been suggested that 'cooperative' rather than 'automated' problem-solving systems be designed. Such cooperative systems are proposed to explicitly enhance the collaboration of the person (or a group of people) and the computer system. This study evaluates the impact of alternative design concepts on the performance of 30 airline pilots interacting with such a cooperative system designed to support enroute flight planning. The results clearly demonstrate that different system design concepts can strongly influence the cognitive processes and resultant performances of users. Based on think-aloud protocols, cognitive models are proposed to account for how features of the computer system interacted with specific types of scenarios to influence exploration and decision making by the pilots. The results are then used to develop recommendations for guiding the design of cooperative systems.

Brains, brawn and sociality: a hyaena’s tale

PubMed Central

Holekamp, Kay E.; Dantzer, Ben; Stricker, Gregory; Shaw Yoshida, Kathryn C.; Benson-Amram, Sarah

2015-01-01

Theoretically intelligence should evolve to help animals solve specific types of problems posed by the environment, but it remains unclear how environmental complexity or novelty facilitates the evolutionary enhancement of cognitive abilities, or whether domain-general intelligence can evolve in response to domain-specific selection pressures. The social complexity hypothesis, which posits that intelligence evolved to cope with the labile behaviour of conspecific group-mates, has been strongly supported by work on the sociocognitive abilities of primates and other animals. Here we review the remarkable convergence in social complexity between cercopithecine primates and spotted hyaenas, and describe our tests of predictions of the social complexity hypothesis in regard to both cognition and brain size in hyaenas. Behavioural data indicate that there has been remarkable convergence between primates and hyaenas with respect to their abilities in the domain of social cognition. Furthermore, within the family Hyaenidae, our data suggest that social complexity might have contributed to enlargement of the frontal cortex. However, social complexity failed to predict either brain volume or frontal cortex volume in a larger array of mammalian carnivores. To address the question of whether or not social complexity might be able to explain the evolution of domain-general intelligence as well as social cognition in particular, we presented simple puzzle boxes, baited with food and scaled to accommodate body size, to members of 39 carnivore species housed in zoos and found that species with larger brains relative to their body mass were more innovative and more successful at opening the boxes. However, social complexity failed to predict success in solving this problem. Overall our work suggests that, although social complexity enhances social cognition, there are no unambiguous causal links between social complexity and either brain size or performance in problem-solving tasks outside the social domain in mammalian carnivores. PMID:26160980

Using Problem-Based Learning in Accounting

ERIC Educational Resources Information Center

Hansen, James D.

2006-01-01

In this article, the author describes the process of writing a problem-based learning (PBL) problem and shows how a typical end-of-chapter accounting problem can be converted to a PBL problem. PBL uses complex, real-world problems to motivate students to identify and research the concepts and principles they need to know to solve these problems.…

Good practices in managing work-related indoor air problems: a psychosocial perspective.

PubMed

Lahtinen, Marjaana; Huuhtanen, Pekka; Vähämäki, Kari; Kähkönen, Erkki; Mussalo-Rauhamaa, Helena; Reijula, Kari

2004-07-01

Indoor air problems at workplaces are often exceedingly complex. Technical questions are interrelated with the dynamics of the work community, and the cooperation and interaction skills of the parties involved in the problem solving process are also put to the test. The objective of our study was to analyze the process of managing and solving indoor air problems from a psychosocial perspective. This collective case study was based on data from questionnaires, interviews and various documentary materials. Technical inspections of the buildings and indoor air measurements were also carried out. The following four factors best differentiated successful cases from impeded cases: extensive multiprofessional collaboration and participative action, systematic action and perseverance, investment in information and communication, and process thinking and learning. The study also proposed a theoretical model for the role of the psychosocial work environment in indoor air problems. The expertise related to social and human aspects of problem solving plays a significant role in solving indoor air problems. Failures to properly handle these aspects may lead to resources being wasted and result in a problematic situation becoming stagnant or worse. Copyright 2004 Wiley-Liss, Inc.

Multidisciplinary approaches to climate change questions

USGS Publications Warehouse

Middleton, Beth A.; LePage, Ben A.

2011-01-01

Multidisciplinary approaches are required to address the complex environmental problems of our time. Solutions to climate change problems are good examples of situations requiring complex syntheses of ideas from a vast set of disciplines including science, engineering, social science, and the humanities. Unfortunately, most ecologists have narrow training, and are not equipped to bring their environmental skills to the table with interdisciplinary teams to help solve multidisciplinary problems. To address this problem, new graduate training programs and workshops sponsored by various organizations are providing opportunities for scientists and others to learn to work together in multidisciplinary teams. Two examples of training in multidisciplinary thinking include those organized by the Santa Fe Institute and Dahlem Workshops. In addition, many interdisciplinary programs have had successes in providing insight into climate change problems including the International Panel on Climate Change, the Joint North American Carbon Program, the National Academy of Science Research Grand Challenges Initiatives, and the National Academy of Science. These programs and initiatives have had some notable success in outlining some of the problems and solutions to climate change. Scientists who can offer their specialized expertise to interdisciplinary teams will be more successful in helping to solve the complex problems related to climate change.

Computational complexities and storage requirements of some Riccati equation solvers

NASA Technical Reports Server (NTRS)

Utku, Senol; Garba, John A.; Ramesh, A. V.

1989-01-01

The linear optimal control problem of an nth-order time-invariant dynamic system with a quadratic performance functional is usually solved by the Hamilton-Jacobi approach. This leads to the solution of the differential matrix Riccati equation with a terminal condition. The bulk of the computation for the optimal control problem is related to the solution of this equation. There are various algorithms in the literature for solving the matrix Riccati equation. However, computational complexities and storage requirements as a function of numbers of state variables, control variables, and sensors are not available for all these algorithms. In this work, the computational complexities and storage requirements for some of these algorithms are given. These expressions show the immensity of the computational requirements of the algorithms in solving the Riccati equation for large-order systems such as the control of highly flexible space structures. The expressions are also needed to compute the speedup and efficiency of any implementation of these algorithms on concurrent machines.

Teaching children with autism to explain how: A case for problem solving?

PubMed

Frampton, Sarah E; Alice Shillingsburg, M

2018-04-01

Few studies have applied Skinner's (1953) conceptualization of problem solving to teach socially significant behaviors to individuals with developmental disabilities. The current study used a multiple probe design across behavior (sets) to evaluate the effects of problem-solving strategy training (PSST) on the target behavior of explaining how to complete familiar activities. During baseline, none of the three participants with autism spectrum disorder (ASD) could respond to the problems presented to them (i.e., explain how to do the activities). Tact training of the actions in each activity alone was ineffective; however, all participants demonstrated independent explaining-how following PSST. Further, following PSST with Set 1, tact training alone was sufficient for at least one scenario in sets 2 and 3 for all 3 participants. Results have implications for generative responding for individuals with ASD and further the discussion regarding the role of problem solving in complex verbal behavior. © 2018 Society for the Experimental Analysis of Behavior.

Early in-session cognitive-emotional problem-solving predicts 12-month outcomes in depression with personality disorder.

PubMed

McCarthy, Kye L; Mergenthaler, Erhard; Grenyer, Brin F S

2014-01-01

Therapist-patient verbalizations reveal complex cognitive-emotional linguistic data. How these variables contribute to change requires further research. Emotional-cognitive text analysis using the Ulm cycles model software was applied to transcripts of the third session of psychotherapy for 20 patients with depression and personality disorder. Results showed that connecting cycle sequences of problem-solving in the third hour predicted 12-month clinical outcomes. Therapist-patient dyads most improved spent significantly more time early in session in connecting cycles, whilst the least improved moved into connecting cycles late in session. For this particular sample, it was clear that positive emotional problem-solving in therapy was beneficial.

A comparison of spontaneous problem-solving abilities in three estrildid finch (Taeniopygia guttata, Lonchura striata var. domestica, Stagonopleura guttata) species.

PubMed

Schmelz, Martin; Krüger, Oliver; Call, Josep; Krause, E Tobias

2015-11-01

Cognition has been extensively studied in primates while other, more distantly related taxa have been neglected for a long time. More recently, there has been an increased interest in avian cognition, with the focus mostly on big-brained species like parrots and corvids. However, the majority of bird species has never systematically been studied in diverse cognitive tasks other than memory and learning tasks, so not much can yet be concluded about the relevant factors for the evolution of cognition. Here we examined 3 species of the estrildid finch family in problem-solving tasks. These granivorous, non-tool-using birds are distributed across 3 continents and are not known for high levels of innovation or spontaneous problem solving in the wild. In this study, our aim was to find such abilities in these species, assess what role domestication might play with a comparison of 4 genetically separated zebra finch strains, and to look for between-species differences between zebra finches, Bengalese finches, and diamond firetails. Furthermore, we established a 3-step spontaneous problem-solving procedure with increasing levels of complexity. Results showed that some estrildid finches were generally capable of spontaneously solving problems of variable complexity to obtain food. We found striking differences in these abilities between species, but not between strains within species, and offer a discussion of potential reasons. Our established methodology can now be applied to a larger number of bird species for phylogenetic comparisons on the behavioral level to get a deeper understanding of the evolution of cognitive abilities. (c) 2015 APA, all rights reserved).

Using Stochastic Spiking Neural Networks on SpiNNaker to Solve Constraint Satisfaction Problems

PubMed Central

Fonseca Guerra, Gabriel A.; Furber, Steve B.

2017-01-01

Constraint satisfaction problems (CSP) are at the core of numerous scientific and technological applications. However, CSPs belong to the NP-complete complexity class, for which the existence (or not) of efficient algorithms remains a major unsolved question in computational complexity theory. In the face of this fundamental difficulty heuristics and approximation methods are used to approach instances of NP (e.g., decision and hard optimization problems). The human brain efficiently handles CSPs both in perception and behavior using spiking neural networks (SNNs), and recent studies have demonstrated that the noise embedded within an SNN can be used as a computational resource to solve CSPs. Here, we provide a software framework for the implementation of such noisy neural solvers on the SpiNNaker massively parallel neuromorphic hardware, further demonstrating their potential to implement a stochastic search that solves instances of P and NP problems expressed as CSPs. This facilitates the exploration of new optimization strategies and the understanding of the computational abilities of SNNs. We demonstrate the basic principles of the framework by solving difficult instances of the Sudoku puzzle and of the map color problem, and explore its application to spin glasses. The solver works as a stochastic dynamical system, which is attracted by the configuration that solves the CSP. The noise allows an optimal exploration of the space of configurations, looking for the satisfiability of all the constraints; if applied discontinuously, it can also force the system to leap to a new random configuration effectively causing a restart. PMID:29311791

A neural network simulation package in CLIPS

NASA Technical Reports Server (NTRS)

Bhatnagar, Himanshu; Krolak, Patrick D.; Mcgee, Brenda J.; Coleman, John

1990-01-01

The intrinsic similarity between the firing of a rule and the firing of a neuron has been captured in this research to provide a neural network development system within an existing production system (CLIPS). A very important by-product of this research has been the emergence of an integrated technique of using rule based systems in conjunction with the neural networks to solve complex problems. The systems provides a tool kit for an integrated use of the two techniques and is also extendible to accommodate other AI techniques like the semantic networks, connectionist networks, and even the petri nets. This integrated technique can be very useful in solving complex AI problems.

Must "Hard Problems" Be Hard?

ERIC Educational Resources Information Center

Kolata, Gina

1985-01-01

To determine how hard it is for computers to solve problems, researchers have classified groups of problems (polynomial hierarchy) according to how much time they seem to require for their solutions. A difficult and complex proof is offered which shows that a combinatorial approach (using Boolean circuits) may resolve the problem. (JN)

A novel heuristic algorithm for capacitated vehicle routing problem

NASA Astrophysics Data System (ADS)

Kır, Sena; Yazgan, Harun Reşit; Tüncel, Emre

2017-09-01

The vehicle routing problem with the capacity constraints was considered in this paper. It is quite difficult to achieve an optimal solution with traditional optimization methods by reason of the high computational complexity for large-scale problems. Consequently, new heuristic or metaheuristic approaches have been developed to solve this problem. In this paper, we constructed a new heuristic algorithm based on the tabu search and adaptive large neighborhood search (ALNS) with several specifically designed operators and features to solve the capacitated vehicle routing problem (CVRP). The effectiveness of the proposed algorithm was illustrated on the benchmark problems. The algorithm provides a better performance on large-scaled instances and gained advantage in terms of CPU time. In addition, we solved a real-life CVRP using the proposed algorithm and found the encouraging results by comparison with the current situation that the company is in.

Engineering and Computing Portal to Solve Environmental Problems

NASA Astrophysics Data System (ADS)

Gudov, A. M.; Zavozkin, S. Y.; Sotnikov, I. Y.

2018-01-01

This paper describes architecture and services of the Engineering and Computing Portal, which is considered to be a complex solution that provides access to high-performance computing resources, enables to carry out computational experiments, teach parallel technologies and solve computing tasks, including technogenic safety ones.

Investigating the Effect of Complexity Factors in Gas Law Problems

ERIC Educational Resources Information Center

Schuttlefield, Jennifer D.; Kirk, John; Pienta, Norbert J.; Tang, Hui

2012-01-01

Undergraduate students were asked to complete gas law questions using a Web-based tool as a first step in our understanding of the role of cognitive load in chemistry word questions and in helping us assess student problem-solving. Each question contained five different complexity factors, which were randomly assigned by the tool so that a…

Robot, computer problem solving system

NASA Technical Reports Server (NTRS)

Becker, J. D.; Merriam, E. W.

1973-01-01

The TENEX computer system, the ARPA network, and computer language design technology was applied to support the complex system programs. By combining the pragmatic and theoretical aspects of robot development, an approach is created which is grounded in realism, but which also has at its disposal the power that comes from looking at complex problems from an abstract analytical point of view.

Live Action Role Play and the Development of Teacher Competences: Evaluation of "Everyday Life in the Classroom"

ERIC Educational Resources Information Center

Imhof, Margarete; Starker, Ulrike; Spaude, Elena

2016-01-01

Building on Dörner's (1996) theory of complex problem-solving, a learning scenario for teacher students was created and tested. Classroom management is interpreted as a complex problem, which requires the integration of competing interests and tackling multiple, simultaneous tasks under time pressure and with limited information. In addition,…

Designing Cognitive Complexity in Mathematical Problem-Solving Items

ERIC Educational Resources Information Center

Daniel, Robert C.; Embretson, Susan E.

2010-01-01

Cognitive complexity level is important for measuring both aptitude and achievement in large-scale testing. Tests for standards-based assessment of mathematics, for example, often include cognitive complexity level in the test blueprint. However, little research exists on how mathematics items can be designed to vary in cognitive complexity level.…

Improved artificial bee colony algorithm for vehicle routing problem with time windows

PubMed Central

Yan, Qianqian; Zhang, Mengjie; Yang, Yunong

2017-01-01

This paper investigates a well-known complex combinatorial problem known as the vehicle routing problem with time windows (VRPTW). Unlike the standard vehicle routing problem, each customer in the VRPTW is served within a given time constraint. This paper solves the VRPTW using an improved artificial bee colony (IABC) algorithm. The performance of this algorithm is improved by a local optimization based on a crossover operation and a scanning strategy. Finally, the effectiveness of the IABC is evaluated on some well-known benchmarks. The results demonstrate the power of IABC algorithm in solving the VRPTW. PMID:28961252

A Message Passing Approach to Side Chain Positioning with Applications in Protein Docking Refinement *

PubMed Central

Moghadasi, Mohammad; Kozakov, Dima; Mamonov, Artem B.; Vakili, Pirooz; Vajda, Sandor; Paschalidis, Ioannis Ch.

2013-01-01

We introduce a message-passing algorithm to solve the Side Chain Positioning (SCP) problem. SCP is a crucial component of protein docking refinement, which is a key step of an important class of problems in computational structural biology called protein docking. We model SCP as a combinatorial optimization problem and formulate it as a Maximum Weighted Independent Set (MWIS) problem. We then employ a modified and convergent belief-propagation algorithm to solve a relaxation of MWIS and develop randomized estimation heuristics that use the relaxed solution to obtain an effective MWIS feasible solution. Using a benchmark set of protein complexes we demonstrate that our approach leads to more accurate docking predictions compared to a baseline algorithm that does not solve the SCP. PMID:23515575

Effect of interfacial stresses in an elastic body with a nanoinclusion

NASA Astrophysics Data System (ADS)

Vakaeva, Aleksandra B.; Grekov, Mikhail A.

2018-05-01

The 2-D problem of an infinite elastic solid with a nanoinclusion of a different from circular shape is solved. The interfacial stresses are acting at the interface. Contact of the inclusion with the matrix satisfies the ideal conditions of cohesion. The generalized Laplace - Young law defines conditions at the interface. To solve the problem, Gurtin - Murdoch surface elasticity model, Goursat - Kolosov complex potentials and the boundary perturbation method are used. The problem is reduced to the solution of two independent Riemann - Hilbert's boundary problems. For the circular inclusion, hypersingular integral equation in an unknown interfacial stress is derived. The algorithm of solving this equation is constructed. The influence of the interfacial stress and the dimension of the circular inclusion on the stress distribution and stress concentration at the interface are analyzed.

No Solutions: Resisting Certainty in Water Supply Management

NASA Astrophysics Data System (ADS)

Cockerill, K.; Armstrong, M.; Richter, J.; Okie, J. G.

2017-12-01

Although most scholars and water managers implicitly understand that managing water resources is an ongoing need, both popular and academic literature routinely use the words `solution' and `solve' in discussing water management concerns. The word `solution' reflects a quest for certainty, stability, permanence. A focus on `solving' creates a simplistic expectation that some person or institution is responsible for implementing a solution and that once `solved' the issue no longer requires attention. The reality, however, is water management is a wicked problem, meaning it is amorphous, involves multiple definitions, is embedded in complex systems, and hence is intractable. By definition, wicked problems defy solution. Our interdisciplinary project integrates research from across a broad spectrum of biological, physical, and social sciences. We find that framing a problem in terms of `solving' affects how people think, feel, behave toward the problem. Further, our work suggests that the prevalence of solution- based language has simultaneously generated expectations that science / scientists can predict and control biophysical systems and that science is not to be trusted because it has failed to deliver on previous promises to permanently `solve' events like floods or droughts. Hydrologic systems, are, of course highly uncertain. Hence, reiterating a simplistic insistence on `solving' water management concerns may result in decreased public attention to or support for more complex policy discussions that could provide long-term management strategies. Using the language of `solutions' with expectations of certainty sets hydrologic researchers and water managers up to fail. Managing water is a social responsibility and it will require consistent attention in the future, just as it has throughout human history. Scientists have a key role to play in explaining how various hydrologic systems function, but they should not be expected to `solve' pressing water management needs. Rather, reconsidering the language used to frame water management concerns can help us recognize our own culpability in creating water problems and our responsibility in continuously managing this most essential resource.

Self-Regulation in the Midst of Complexity: A Case Study of High School Physics Students Engaged in Ill-Structured Problem Solving

NASA Astrophysics Data System (ADS)

Milbourne, Jeffrey David

The purpose of this dissertation study was to explore the experiences of high school physics students who were solving complex, ill-structured problems, in an effort to better understand how self-regulatory behavior mediated the project experience. Consistent with Voss, Green, Post, and Penner's (1983) conception of an ill-structured problem in the natural sciences, the 'problems' consisted of scientific research projects that students completed under the supervision of a faculty mentor. Zimmerman and Campillo's (2003) self-regulatory framework of problem solving provided a holistic guide to data collection and analysis of this multi-case study, with five individual student cases. The study's results are explored in two manuscripts, each targeting a different audience. The first manuscript, intended for the Science Education Research community, presents a thick, rich description of the students' project experiences, consistent with a qualitative, case study analysis. Findings suggest that intrinsic interest was an important self-regulatory factor that helped motivate students throughout their project work, and that the self-regulatory cycle of forethought, performance monitoring, and self-reflection was an important component of the problem-solving process. Findings also support the application of Zimmerman and Campillo's framework to complex, ill-structured problems, particularly the cyclical nature of the framework. Finally, this study suggests that scientific research projects, with the appropriate support, can be a mechanism for improving students' selfregulatory behavior. The second manuscript, intended for Physics practitioners, combines the findings of the first manuscript with the perspectives of the primary, on-site research mentor, who has over a decade's worth of experience mentoring students doing physics research. His experience suggests that a successful research experience requires certain characteristics, including: a slow, 'on-ramp' to the research experience, space to experience productive failure, and an opportunity to enjoy the work they are doing.

Principles for Framing a Healthy Food System.

PubMed

Hamm, Michael W

2009-07-01

Wicked problems are most simply defined as ones that are impossible to solve. In other words, the range of complex interacting influences and effects; the influence of human values in all their range; and the constantly changing conditions in which the problem exists guarantee that what we strive to do is improve the situation rather than solve the wicked problem. This does not mean that we cannot move a long way toward resolving the problem but simply that there is no clean endpoint. This commentary outlines principles that could be used in moving us toward a healthy food system within the framework of it presenting as a wicked problem.

Solution of internal ballistic problem for SRM with grain of complex shape during main firing phase

NASA Astrophysics Data System (ADS)

Kiryushkin, A. E.; Minkov, L. L.

2017-10-01

Solid rocket motor (SRM) internal ballistics problems are related to the problems with moving boundaries. The algorithm able to solve similar problems in axisymmetric formulation on Cartesian mesh with an arbitrary order of accuracy is considered in this paper. The base of this algorithm is the ghost point extrapolation using inverse Lax-Wendroff procedure. Level set method is used as an implicit representation of the domain boundary. As an example, the internal ballistics problem for SRM with umbrella type grain was solved during the main firing phase. In addition, flow parameters distribution in the combustion chamber was obtained for different time moments.

Collaborative Visual Analytics: A Health Analytics Approach to Injury Prevention

PubMed Central

Fisher, Brian; Smith, Jennifer; Pike, Ian

2017-01-01

Background: Accurate understanding of complex health data is critical in order to deal with wicked health problems and make timely decisions. Wicked problems refer to ill-structured and dynamic problems that combine multidimensional elements, which often preclude the conventional problem solving approach. This pilot study introduces visual analytics (VA) methods to multi-stakeholder decision-making sessions about child injury prevention; Methods: Inspired by the Delphi method, we introduced a novel methodology—group analytics (GA). GA was pilot-tested to evaluate the impact of collaborative visual analytics on facilitating problem solving and supporting decision-making. We conducted two GA sessions. Collected data included stakeholders’ observations, audio and video recordings, questionnaires, and follow up interviews. The GA sessions were analyzed using the Joint Activity Theory protocol analysis methods; Results: The GA methodology triggered the emergence of ‘common ground’ among stakeholders. This common ground evolved throughout the sessions to enhance stakeholders’ verbal and non-verbal communication, as well as coordination of joint activities and ultimately collaboration on problem solving and decision-making; Conclusions: Understanding complex health data is necessary for informed decisions. Equally important, in this case, is the use of the group analytics methodology to achieve ‘common ground’ among diverse stakeholders about health data and their implications. PMID:28895928

Collaborative Visual Analytics: A Health Analytics Approach to Injury Prevention.

PubMed

Al-Hajj, Samar; Fisher, Brian; Smith, Jennifer; Pike, Ian

2017-09-12

Background : Accurate understanding of complex health data is critical in order to deal with wicked health problems and make timely decisions. Wicked problems refer to ill-structured and dynamic problems that combine multidimensional elements, which often preclude the conventional problem solving approach. This pilot study introduces visual analytics (VA) methods to multi-stakeholder decision-making sessions about child injury prevention; Methods : Inspired by the Delphi method, we introduced a novel methodology-group analytics (GA). GA was pilot-tested to evaluate the impact of collaborative visual analytics on facilitating problem solving and supporting decision-making. We conducted two GA sessions. Collected data included stakeholders' observations, audio and video recordings, questionnaires, and follow up interviews. The GA sessions were analyzed using the Joint Activity Theory protocol analysis methods; Results : The GA methodology triggered the emergence of ' common g round ' among stakeholders. This common ground evolved throughout the sessions to enhance stakeholders' verbal and non-verbal communication, as well as coordination of joint activities and ultimately collaboration on problem solving and decision-making; Conclusion s : Understanding complex health data is necessary for informed decisions. Equally important, in this case, is the use of the group analytics methodology to achieve ' common ground' among diverse stakeholders about health data and their implications.

Lesion mapping of social problem solving.

PubMed

Barbey, Aron K; Colom, Roberto; Paul, Erick J; Chau, Aileen; Solomon, Jeffrey; Grafman, Jordan H

2014-10-01

Accumulating neuroscience evidence indicates that human intelligence is supported by a distributed network of frontal and parietal regions that enable complex, goal-directed behaviour. However, the contributions of this network to social aspects of intellectual function remain to be well characterized. Here, we report a human lesion study (n = 144) that investigates the neural bases of social problem solving (measured by the Everyday Problem Solving Inventory) and examine the degree to which individual differences in performance are predicted by a broad spectrum of psychological variables, including psychometric intelligence (measured by the Wechsler Adult Intelligence Scale), emotional intelligence (measured by the Mayer, Salovey, Caruso Emotional Intelligence Test), and personality traits (measured by the Neuroticism-Extraversion-Openness Personality Inventory). Scores for each variable were obtained, followed by voxel-based lesion-symptom mapping. Stepwise regression analyses revealed that working memory, processing speed, and emotional intelligence predict individual differences in everyday problem solving. A targeted analysis of specific everyday problem solving domains (involving friends, home management, consumerism, work, information management, and family) revealed psychological variables that selectively contribute to each. Lesion mapping results indicated that social problem solving, psychometric intelligence, and emotional intelligence are supported by a shared network of frontal, temporal, and parietal regions, including white matter association tracts that bind these areas into a coordinated system. The results support an integrative framework for understanding social intelligence and make specific recommendations for the application of the Everyday Problem Solving Inventory to the study of social problem solving in health and disease. © The Author (2014). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

A problem with problem solving: motivational traits, but not cognition, predict success on novel operant foraging tasks.

PubMed

van Horik, Jayden O; Madden, Joah R

2016-04-01

Rates of innovative foraging behaviours and success on problem-solving tasks are often used to assay differences in cognition, both within and across species. Yet the cognitive features of some problem-solving tasks can be unclear. As such, explanations that attribute cognitive mechanisms to individual variation in problem-solving performance have revealed conflicting results. We investigated individual consistency in problem-solving performances in captive-reared pheasant chicks, Phasianus colchicus , and addressed whether success depends on cognitive processes, such as trial-and-error associative learning, or whether performances may be driven solely via noncognitive motivational mechanisms, revealed through subjects' willingness to approach, engage with and persist in their interactions with an apparatus, or via physiological traits such as body condition. While subjects' participation and success were consistent within the same problems and across similar tasks, their performances were inconsistent across different types of task. Moreover, subjects' latencies to approach each test apparatus and their attempts to access the reward were not repeatable across trials. Successful individuals did not improve their performances with experience, nor were they consistent in their techniques in repeated presentations of a task. However, individuals that were highly motivated to enter the experimental chamber were more likely to participate. Successful individuals were also faster to approach each test apparatus and more persistent in their attempts to solve the tasks than unsuccessful individuals. Our findings therefore suggest that individual differences in problem-solving success can arise from inherent motivational differences alone and hence be achieved without inferring more complex cognitive processes.

A problem with problem solving: motivational traits, but not cognition, predict success on novel operant foraging tasks

PubMed Central

van Horik, Jayden O.; Madden, Joah R.

2016-01-01

Rates of innovative foraging behaviours and success on problem-solving tasks are often used to assay differences in cognition, both within and across species. Yet the cognitive features of some problem-solving tasks can be unclear. As such, explanations that attribute cognitive mechanisms to individual variation in problem-solving performance have revealed conflicting results. We investigated individual consistency in problem-solving performances in captive-reared pheasant chicks, Phasianus colchicus, and addressed whether success depends on cognitive processes, such as trial-and-error associative learning, or whether performances may be driven solely via noncognitive motivational mechanisms, revealed through subjects' willingness to approach, engage with and persist in their interactions with an apparatus, or via physiological traits such as body condition. While subjects' participation and success were consistent within the same problems and across similar tasks, their performances were inconsistent across different types of task. Moreover, subjects' latencies to approach each test apparatus and their attempts to access the reward were not repeatable across trials. Successful individuals did not improve their performances with experience, nor were they consistent in their techniques in repeated presentations of a task. However, individuals that were highly motivated to enter the experimental chamber were more likely to participate. Successful individuals were also faster to approach each test apparatus and more persistent in their attempts to solve the tasks than unsuccessful individuals. Our findings therefore suggest that individual differences in problem-solving success can arise from inherent motivational differences alone and hence be achieved without inferring more complex cognitive processes. PMID:27122637

High-frequency CAD-based scattering model: SERMAT

NASA Astrophysics Data System (ADS)

Goupil, D.; Boutillier, M.

1991-09-01

Specifications for an industrial radar cross section (RCS) calculation code are given: it must be able to exchange data with many computer aided design (CAD) systems, it must be fast, and it must have powerful graphic tools. Classical physical optics (PO) and equivalent currents (EC) techniques have proven their efficiency on simple objects for a long time. Difficult geometric problems occur when objects with very complex shapes have to be computed. Only a specific geometric code can solve these problems. We have established that, once these problems have been solved: (1) PO and EC give good results on complex objects of large size compared to wavelength; and (2) the implementation of these objects in a software package (SERMAT) allows fast and sufficiently precise domain RCS calculations to meet industry requirements in the domain of stealth.

Problem-Solving Test: Attenuation--A Mechanism to Regulate Bacterial Tryptophan Biosynthesis

ERIC Educational Resources Information Center

Szeberenyi, Jozsef

2010-01-01

Terms to be familiar with before you start to solve the test: tryptophan, transcription unit, operon, "trp" repressor, corepressor, operator, promoter, palindrome, initiation, elongation, and termination of transcription, open reading frame, coupled transcription/translation, chromosome-polysome complex. (Contains 2 figures and 1 footnote.)

Science of the science, drug discovery and artificial neural networks.

PubMed

Patel, Jigneshkumar

2013-03-01

Drug discovery process many times encounters complex problems, which may be difficult to solve by human intelligence. Artificial Neural Networks (ANNs) are one of the Artificial Intelligence (AI) technologies used for solving such complex problems. ANNs are widely used for primary virtual screening of compounds, quantitative structure activity relationship studies, receptor modeling, formulation development, pharmacokinetics and in all other processes involving complex mathematical modeling. Despite having such advanced technologies and enough understanding of biological systems, drug discovery is still a lengthy, expensive, difficult and inefficient process with low rate of new successful therapeutic discovery. In this paper, author has discussed the drug discovery science and ANN from very basic angle, which may be helpful to understand the application of ANN for drug discovery to improve efficiency.

Engaging the creative to better build science into water resource solutions

NASA Astrophysics Data System (ADS)

Klos, P. Z.

2014-12-01

Psychological thought suggests that social engagement with an environmental problem requires 1) cognitive understanding of the problem, 2) emotional engagement with the problem, and 3) perceived efficacy that there is something we can do to solve the problem. Within the water sciences, we form problem-focused, cross-disciplinary teams to help address complex water resource problems, but often we only seek teammates from other disciplines within the realms of engineering and the natural/social sciences. Here I argue that this science-centric focus fails to fully solve these water resource problems, and often the science goes unheard because it is heavily cognitive and lacks the ability to effectively engage the audience through crucial social-psychological aspects of emotion and efficacy. To solve this, future cross-disciplinary collaborations that seek to include creative actors from the worlds of art, humanities, and design can begin to provide a much stronger overlap of the cognition, emotion, and efficacy needed to communicate the science, engage the audience, and create the solutions needed to solve or world's most complex water resource problems. Disciplines across the arts, sciences, and engineering all bring unique strengths that, through collaboration, allow for uniquely creative modes of art-science overlap that can engage people through additions of emotion and efficacy that compliment the science and go beyond the traditional cognitive approach. I highlight examples of this art-science overlap in action and argue that water resource collaborations like these will be more likely to have their hydrologic science accepted and applied by those who decide on water resource solutions. For this Pop-up Talk session, I aim to share the details of this proposed framework in the context of my own research and the work of others. I hope to incite discussion regarding the utility and relevance of this framework as a future option for other water resource collaboratives working to solve hydrologic issues across the globe.

Identification and addressing reduction-related misconceptions

NASA Astrophysics Data System (ADS)

Gal-Ezer, Judith; Trakhtenbrot, Mark

2016-07-01

Reduction is one of the key techniques used for problem-solving in computer science. In particular, in the theory of computation and complexity (TCC), mapping and polynomial reductions are used for analysis of decidability and computational complexity of problems, including the core concept of NP-completeness. Reduction is a highly abstract technique that involves revealing close non-trivial connections between problems that often seem to have nothing in common. As a result, proper understanding and application of reduction is a serious challenge for students and a source of numerous misconceptions. The main contribution of this paper is detection of such misconceptions, analysis of their roots, and proposing a way to address them in an undergraduate TCC course. Our observations suggest that the main source of the misconceptions is the false intuitive rule "the bigger is a set/problem, the harder it is to solve". Accordingly, we developed a series of exercises for proactive prevention of these misconceptions.

Faster than classical quantum algorithm for dense formulas of exact satisfiability and occupation problems

NASA Astrophysics Data System (ADS)

Mandrà, Salvatore; Giacomo Guerreschi, Gian; Aspuru-Guzik, Alán

2016-07-01

We present an exact quantum algorithm for solving the Exact Satisfiability problem, which belongs to the important NP-complete complexity class. The algorithm is based on an intuitive approach that can be divided into two parts: the first step consists in the identification and efficient characterization of a restricted subspace that contains all the valid assignments of the Exact Satisfiability; while the second part performs a quantum search in such restricted subspace. The quantum algorithm can be used either to find a valid assignment (or to certify that no solution exists) or to count the total number of valid assignments. The query complexities for the worst-case are respectively bounded by O(\\sqrt{{2}n-{M\\prime }}) and O({2}n-{M\\prime }), where n is the number of variables and {M}\\prime the number of linearly independent clauses. Remarkably, the proposed quantum algorithm results to be faster than any known exact classical algorithm to solve dense formulas of Exact Satisfiability. As a concrete application, we provide the worst-case complexity for the Hamiltonian cycle problem obtained after mapping it to a suitable Occupation problem. Specifically, we show that the time complexity for the proposed quantum algorithm is bounded by O({2}n/4) for 3-regular undirected graphs, where n is the number of nodes. The same worst-case complexity holds for (3,3)-regular bipartite graphs. As a reference, the current best classical algorithm has a (worst-case) running time bounded by O({2}31n/96). Finally, when compared to heuristic techniques for Exact Satisfiability problems, the proposed quantum algorithm is faster than the classical WalkSAT and Adiabatic Quantum Optimization for random instances with a density of constraints close to the satisfiability threshold, the regime in which instances are typically the hardest to solve. The proposed quantum algorithm can be straightforwardly extended to the generalized version of the Exact Satisfiability known as Occupation problem. The general version of the algorithm is presented and analyzed.

Managing the Complexity of Design Problems through Studio-Based Learning

ERIC Educational Resources Information Center

Cennamo, Katherine; Brandt, Carol; Scott, Brigitte; Douglas, Sarah; McGrath, Margarita; Reimer, Yolanda; Vernon, Mitzi

2011-01-01

The ill-structured nature of design problems makes them particularly challenging for problem-based learning. Studio-based learning (SBL), however, has much in common with problem-based learning and indeed has a long history of use in teaching students to solve design problems. The purpose of this ethnographic study of an industrial design class,…

Numerical Problems and Agent-Based Models for a Mass Transfer Course

ERIC Educational Resources Information Center

Murthi, Manohar; Shea, Lonnie D.; Snurr, Randall Q.

2009-01-01

Problems requiring numerical solutions of differential equations or the use of agent-based modeling are presented for use in a course on mass transfer. These problems were solved using the popular technical computing language MATLABTM. Students were introduced to MATLAB via a problem with an analytical solution. A more complex problem to which no…

A study of the performance of patients with frontal lobe lesions in a financial planning task.

PubMed

Goel, V; Grafman, J; Tajik, J; Gana, S; Danto, D

1997-10-01

It has long been argued that patients with lesions in the prefrontal cortex have difficulties in decision making and problem solving in real-world, ill-structured situations, particularly problem types involving planning and look-ahead components. Recently, several researchers have questioned our ability to capture and characterize these deficits adequately using just the standard neuropsychological test batteries, and have called for tests that reflect real-world task requirements more accurately. We present data from 10 patients with focal lesions to the prefrontal cortex and 10 normal control subjects engaged in a real-world financial planning task. We also introduce a theoretical framework and methodology developed in the cognitive science literature for quantifying and analysing the complex data generated by problem-solving tasks. Our findings indicate that patient performance is impoverished at a global level but not at the local level. Patients have difficulty in organizing and structuring their problem space. Once they begin problem solving, they have difficulty in allocating adequate effort to each problem-solving phase. Patients also have difficulty dealing with the fact that there are no right or wrong answers nor official termination points in real-world planning problems. They also find it problematic to generate their own feedback. They invariably terminate the session before the details are fleshed out and all the goals satisfied. Finally, patients do not take full advantage of the fact that constraints on real-world problems are negotiable. However, it is not necessary to postulate a 'planning' deficit. It is possible to understand the patients' difficulties in real world planning tasks in terms of the following four accepted deficits: inadequate access to 'structured event complexes', difficulty in generalizing from particulars, failure to shift between 'mental sets', and poor judgment regarding adequacy and completeness of a plan.

Moving Material into Space Without Rockets.

ERIC Educational Resources Information Center

Cheng, R. S.; Trefil, J. S.

1985-01-01

In response to conventional rocket demands on fuel supplies, electromagnetic launches were developed to give payloads high velocity using a stationary energy source. Several orbital mechanics problems are solved including a simple problem (radial launch with no rotation) and a complex problem involving air resistance and gravity. (DH)

Cross hole GPR traveltime inversion using a fast and accurate neural network as a forward model

NASA Astrophysics Data System (ADS)

Mejer Hansen, Thomas

2017-04-01

Probabilistic formulated inverse problems can be solved using Monte Carlo based sampling methods. In principle both advanced prior information, such as based on geostatistics, and complex non-linear forward physical models can be considered. However, in practice these methods can be associated with huge computational costs that in practice limit their application. This is not least due to the computational requirements related to solving the forward problem, where the physical response of some earth model has to be evaluated. Here, it is suggested to replace a numerical complex evaluation of the forward problem, with a trained neural network that can be evaluated very fast. This will introduce a modeling error, that is quantified probabilistically such that it can be accounted for during inversion. This allows a very fast and efficient Monte Carlo sampling of the solution to an inverse problem. We demonstrate the methodology for first arrival travel time inversion of cross hole ground-penetrating radar (GPR) data. An accurate forward model, based on 2D full-waveform modeling followed by automatic travel time picking, is replaced by a fast neural network. This provides a sampling algorithm three orders of magnitude faster than using the full forward model, and considerably faster, and more accurate, than commonly used approximate forward models. The methodology has the potential to dramatically change the complexity of the types of inverse problems that can be solved using non-linear Monte Carlo sampling techniques.

Developing a Service Management Strategy Facilitated by Action Learning: An Empirical Study from the UK Health & Fitness Industry

ERIC Educational Resources Information Center

Oliver, John

2006-01-01

One of the principle tenets of action learning is that it provides the potential to explore and solve complex organisational problems. The question of how best to develop a future business strategy is such a problem. Existing literature on strategy making presents a multi-faceted debate, suggesting that the complexity of competitive environments…

Using Multiple Calibration Indices in Order to Capture the Complex Picture of What Affects Students' Accuracy of Feeling of Confidence

ERIC Educational Resources Information Center

Boekaerts, Monique; Rozendaal, Jeroen S.

2010-01-01

The present study used multiple calibration indices to capture the complex picture of fifth graders' calibration of feeling of confidence in mathematics. Specifically, the effects of gender, type of mathematical problem, instruction method, and time of measurement (before and after problem solving) on calibration skills were investigated. Fourteen…

Mexican high school students' social representations of mathematics, its teaching and learning

NASA Astrophysics Data System (ADS)

Martínez-Sierra, Gustavo; Miranda-Tirado, Marisa

2015-07-01

This paper reports a qualitative research that identifies Mexican high school students' social representations of mathematics. For this purpose, the social representations of 'mathematics', 'learning mathematics' and 'teaching mathematics' were identified in a group of 50 students. Focus group interviews were carried out in order to obtain the data. The constant comparative style was the strategy used for the data analysis because it allowed the categories to emerge from the data. The students' social representations are: (A) Mathematics is…(1) important for daily life, (2) important for careers and for life, (3) important because it is in everything that surrounds us, (4) a way to solve problems of daily life, (5) calculations and operations with numbers, (6) complex and difficult, (7) exact and (6) a subject that develops thinking skills; (B) To learn mathematics is…(1) to possess knowledge to solve problems, (2) to be able to solve everyday problems, (3) to be able to make calculations and operations, and (4) to think logically to be able to solve problems; and (C) To teach mathematics is…(1) to transmit knowledge, (2) to know to share it, (3) to transmit the reasoning ability, and (4) to show how to solve problems.

The use of questions as problem-solving strategies during early childhood.

PubMed

Legare, Cristine H; Mills, Candice M; Souza, André L; Plummer, Leigh E; Yasskin, Rebecca

2013-01-01

This study examined the strategic use of questions to solve problems across early childhood. Participants (N=54, 4-, 5-, and 6-year-olds) engaged in two tasks: a novel problem-solving question task that required asking questions to an informant to determine which card in an array was located in a box and a cognitive flexibility task that required classifying stimuli by multiple dimensions. The results from the question task indicated that there were age differences in the types of questions asked, with 6-year-olds asking more constraint-seeking questions than 4- and 5-year-olds. The number of constraint-seeking questions asked was the only significant predictor of accuracy. Performance on the cognitive flexibility task correlated with both constraint-seeking strategy use and accuracy in the question task. In sum, our results provide evidence that the capacity to use questions to generate relevant information develops before the capacity to apply this information successfully and consistently to solve complex problems. We propose that the process of using questions as strategic tools is an ideal context for examining how children come to gain active and intentional control over problem solving. Copyright © 2012 Elsevier Inc. All rights reserved.

A 2-dimensional optical architecture for solving Hamiltonian path problem based on micro ring resonators

NASA Astrophysics Data System (ADS)

Shakeri, Nadim; Jalili, Saeed; Ahmadi, Vahid; Rasoulzadeh Zali, Aref; Goliaei, Sama

2015-01-01

The problem of finding the Hamiltonian path in a graph, or deciding whether a graph has a Hamiltonian path or not, is an NP-complete problem. No exact solution has been found yet, to solve this problem using polynomial amount of time and space. In this paper, we propose a two dimensional (2-D) optical architecture based on optical electronic devices such as micro ring resonators, optical circulators and MEMS based mirror (MEMS-M) to solve the Hamiltonian Path Problem, for undirected graphs in linear time. It uses a heuristic algorithm and employs n+1 different wavelengths of a light ray, to check whether a Hamiltonian path exists or not on a graph with n vertices. Then if a Hamiltonian path exists, it reports the path. The device complexity of the proposed architecture is O(n2).

Classical versus Computer Algebra Methods in Elementary Geometry

ERIC Educational Resources Information Center

Pech, Pavel

2005-01-01

Computer algebra methods based on results of commutative algebra like Groebner bases of ideals and elimination of variables make it possible to solve complex, elementary and non elementary problems of geometry, which are difficult to solve using a classical approach. Computer algebra methods permit the proof of geometric theorems, automatic…

How are things adding up? Neural differences between arithmetic operations are due to general problem solving strategies.

PubMed

Tschentscher, Nadja; Hauk, Olaf

2014-05-15

A number of previous studies have interpreted differences in brain activation between arithmetic operation types (e.g. addition and multiplication) as evidence in favor of distinct cortical representations, processes or neural systems. It is still not clear how differences in general task complexity contribute to these neural differences. Here, we used a mental arithmetic paradigm to disentangle brain areas related to general problem solving from those involved in operation type specific processes (addition versus multiplication). We orthogonally varied operation type and complexity. Importantly, complexity was defined not only based on surface criteria (for example number size), but also on the basis of individual participants' strategy ratings, which were validated in a detailed behavioral analysis. We replicated previously reported operation type effects in our analyses based on surface criteria. However, these effects vanished when controlling for individual strategies. Instead, procedural strategies contrasted with memory retrieval reliably activated fronto-parietal and motor regions, while retrieval strategies activated parietal cortices. This challenges views that operation types rely on partially different neural systems, and suggests that previously reported differences between operation types may have emerged due to invalid measures of complexity. We conclude that mental arithmetic is a powerful paradigm to study brain networks of abstract problem solving, as long as individual participants' strategies are taken into account. Copyright © 2014 Elsevier Inc. All rights reserved.

Games that Enlist Collective Intelligence to Solve Complex Scientific Problems.

PubMed

Burnett, Stephen; Furlong, Michelle; Melvin, Paul Guy; Singiser, Richard

2016-03-01

There is great value in employing the collective problem-solving power of large groups of people. Technological advances have allowed computer games to be utilized by a diverse population to solve problems. Science games are becoming more popular and cover various areas such as sequence alignments, DNA base-pairing, and protein and RNA folding. While these tools have been developed for the general population, they can also be used effectively in the classroom to teach students about various topics. Many games also employ a social component that entices students to continue playing and thereby to continue learning. The basic functions of game play and the potential of game play as a tool in the classroom are discussed in this article.

Games that Enlist Collective Intelligence to Solve Complex Scientific Problems

PubMed Central

Burnett, Stephen; Furlong, Michelle; Melvin, Paul Guy; Singiser, Richard

2016-01-01

There is great value in employing the collective problem-solving power of large groups of people. Technological advances have allowed computer games to be utilized by a diverse population to solve problems. Science games are becoming more popular and cover various areas such as sequence alignments, DNA base-pairing, and protein and RNA folding. While these tools have been developed for the general population, they can also be used effectively in the classroom to teach students about various topics. Many games also employ a social component that entices students to continue playing and thereby to continue learning. The basic functions of game play and the potential of game play as a tool in the classroom are discussed in this article. PMID:27047610

How did you guess? Or, what do multiple-choice questions measure?

PubMed

Cox, K R

1976-06-05

Multiple-choice questions classified as requiring problem-solving skills have been interpreted as measuring problem-solving skills within students, with the implicit hypothesis that questions needing an increasingly complex intellectual process should present increasing difficulty to the student. This hypothesis was tested in a 150-question paper taken by 721 students in seven Australian medical schools. No correlation was observed between difficulty and assigned process. Consequently, the question-answering process was explored with a group of final-year students. Anecdotal recall by students gave heavy weight to knowledge rather than problem solving in answering these questions. Assignment of the 150 questions to the classification by three teachers and six students showed their congruence to be a little above random probability.

Efficient Monte Carlo sampling of inverse problems using a neural network-based forward—applied to GPR crosshole traveltime inversion

NASA Astrophysics Data System (ADS)

Hansen, T. M.; Cordua, K. S.

2017-12-01

Probabilistically formulated inverse problems can be solved using Monte Carlo-based sampling methods. In principle, both advanced prior information, based on for example, complex geostatistical models and non-linear forward models can be considered using such methods. However, Monte Carlo methods may be associated with huge computational costs that, in practice, limit their application. This is not least due to the computational requirements related to solving the forward problem, where the physical forward response of some earth model has to be evaluated. Here, it is suggested to replace a numerical complex evaluation of the forward problem, with a trained neural network that can be evaluated very fast. This will introduce a modeling error that is quantified probabilistically such that it can be accounted for during inversion. This allows a very fast and efficient Monte Carlo sampling of the solution to an inverse problem. We demonstrate the methodology for first arrival traveltime inversion of crosshole ground penetrating radar data. An accurate forward model, based on 2-D full-waveform modeling followed by automatic traveltime picking, is replaced by a fast neural network. This provides a sampling algorithm three orders of magnitude faster than using the accurate and computationally expensive forward model, and also considerably faster and more accurate (i.e. with better resolution), than commonly used approximate forward models. The methodology has the potential to dramatically change the complexity of non-linear and non-Gaussian inverse problems that have to be solved using Monte Carlo sampling techniques.

Optimization of multi-objective integrated process planning and scheduling problem using a priority based optimization algorithm

NASA Astrophysics Data System (ADS)

Ausaf, Muhammad Farhan; Gao, Liang; Li, Xinyu

2015-12-01

For increasing the overall performance of modern manufacturing systems, effective integration of process planning and scheduling functions has been an important area of consideration among researchers. Owing to the complexity of handling process planning and scheduling simultaneously, most of the research work has been limited to solving the integrated process planning and scheduling (IPPS) problem for a single objective function. As there are many conflicting objectives when dealing with process planning and scheduling, real world problems cannot be fully captured considering only a single objective for optimization. Therefore considering multi-objective IPPS (MOIPPS) problem is inevitable. Unfortunately, only a handful of research papers are available on solving MOIPPS problem. In this paper, an optimization algorithm for solving MOIPPS problem is presented. The proposed algorithm uses a set of dispatching rules coupled with priority assignment to optimize the IPPS problem for various objectives like makespan, total machine load, total tardiness, etc. A fixed sized external archive coupled with a crowding distance mechanism is used to store and maintain the non-dominated solutions. To compare the results with other algorithms, a C-matric based method has been used. Instances from four recent papers have been solved to demonstrate the effectiveness of the proposed algorithm. The experimental results show that the proposed method is an efficient approach for solving the MOIPPS problem.

Engineering design: A cognitive process approach

NASA Astrophysics Data System (ADS)

Strimel, Greg Joseph

The intent of this dissertation was to identify the cognitive processes used by advanced pre-engineering students to solve complex engineering design problems. Students in technology and engineering education classrooms are often taught to use an ideal engineering design process that has been generated mostly by educators and curriculum developers. However, the review of literature showed that it is unclear as to how advanced pre-engineering students cognitively navigate solving a complex and multifaceted problem from beginning to end. Additionally, it was unclear how a student thinks and acts throughout their design process and how this affects the viability of their solution. Therefore, Research Objective 1 was to identify the fundamental cognitive processes students use to design, construct, and evaluate operational solutions to engineering design problems. Research Objective 2 was to determine identifiers within student cognitive processes for monitoring aptitude to successfully design, construct, and evaluate technological solutions. Lastly, Research Objective 3 was to create a conceptual technological and engineering problem-solving model integrating student cognitive processes for the improved development of problem-solving abilities. The methodology of this study included multiple forms of data collection. The participants were first given a survey to determine their prior experience with engineering and to provide a description of the subjects being studied. The participants were then presented an engineering design challenge to solve individually. While they completed the challenge, the participants verbalized their thoughts using an established "think aloud" method. These verbalizations were captured along with participant observational recordings using point-of-view camera technology. Additionally, the participant design journals, design artifacts, solution effectiveness data, and teacher evaluations were collected for analysis to help achieve the research objectives of this study. Two independent coders then coded the video/audio recordings and the additional design data using Halfin's (1973) 17 mental processes for technological problem-solving. The results of this study indicated that the participants employed a wide array of mental processes when solving engineering design challenges. However, the findings provide a general analysis of the number of times participants employed each mental process, as well as the amount of time consumed employing the various mental processes through the different stages of the engineering design process. The results indicated many similarities between the students solving the problem, which may highlight voids in current technology and engineering education curricula. Additionally, the findings showed differences between the processes employed by participants that created the most successful solutions and the participants who developed the least effective solutions. Upon comparing and contrasting these processes, recommendations for instructional strategies to enhance a student's capability for solving engineering design problems were developed. The results also indicated that students, when left without teacher intervention, use a simplified and more natural process to solve design challenges than the 12-step engineering design process reported in much of the literature. Lastly, these data indicated that students followed two different approaches to solving the design problem. Some students employed a sequential and logical approach, while others employed a nebulous, solution centered trial-and-error approach to solving the problem. In this study the participants who were more sequential had better performing solutions. Examining these two approaches and the student cognition data enabled the researcher to generate a conceptual engineering design model for the improved teaching and development of engineering design problem solving.

On the solution of the complex eikonal equation in acoustic VTI media: A perturbation plus optimization scheme

NASA Astrophysics Data System (ADS)

Huang, Xingguo; Sun, Jianguo; Greenhalgh, Stewart

2018-04-01

We present methods for obtaining numerical and analytic solutions of the complex eikonal equation in inhomogeneous acoustic VTI media (transversely isotropic media with a vertical symmetry axis). The key and novel point of the method for obtaining numerical solutions is to transform the problem of solving the highly nonlinear acoustic VTI eikonal equation into one of solving the relatively simple eikonal equation for the background (isotropic) medium and a system of linear partial differential equations. Specifically, to obtain the real and imaginary parts of the complex traveltime in inhomogeneous acoustic VTI media, we generalize a perturbation theory, which was developed earlier for solving the conventional real eikonal equation in inhomogeneous anisotropic media, to the complex eikonal equation in such media. After the perturbation analysis, we obtain two types of equations. One is the complex eikonal equation for the background medium and the other is a system of linearized partial differential equations for the coefficients of the corresponding complex traveltime formulas. To solve the complex eikonal equation for the background medium, we employ an optimization scheme that we developed for solving the complex eikonal equation in isotropic media. Then, to solve the system of linearized partial differential equations for the coefficients of the complex traveltime formulas, we use the finite difference method based on the fast marching strategy. Furthermore, by applying the complex source point method and the paraxial approximation, we develop the analytic solutions of the complex eikonal equation in acoustic VTI media, both for the isotropic and elliptical anisotropic background medium. Our numerical results demonstrate the effectiveness of our derivations and illustrate the influence of the beam widths and the anisotropic parameters on the complex traveltimes.

Education problems and Web-based teaching: how it impacts dental educators?

PubMed

Clark, G T

2001-01-01

This article looks at six problems that vex educators and how web-based teaching might help solve them. These problems include: (1) limited access to educational content, (2) need for asynchronous access to educational content, (3) depth and diversity of educational content, (4) training in complex problem solving, (5) promotion of lifelong learning behaviors and (6) achieving excellence in education. The advantages and disadvantage of web-based educational content for each problem are discussed. The article suggests that when a poorly organized course with inaccurate and irrelevant content is placed online, it solves no problems. However some of the above issues can be partially or fully solved by hosting well-constructed teaching modules on the web. This article also reviews the literature investigating the efficacy of off-site education as compared to that provided on-site. The conclusion of this review is that teleconference-based and web-based delivery of educational content can be as effective as traditional classroom-based teaching assuming the technologic problems sometimes associated with delivering teaching content to off-site locations do not interfere in the learning process. A suggested hierarchy for rating and comparing e-learning concepts and methods is presented for consideration.

The potential application of the blackboard model of problem solving to multidisciplinary design

NASA Technical Reports Server (NTRS)

Rogers, James L.

1989-01-01

The potential application of the blackboard model of problem solving to multidisciplinary design is discussed. Multidisciplinary design problems are complex, poorly structured, and lack a predetermined decision path from the initial starting point to the final solution. The final solution is achieved using data from different engineering disciplines. Ideally, for the final solution to be the optimum solution, there must be a significant amount of communication among the different disciplines plus intradisciplinary and interdisciplinary optimization. In reality, this is not what happens in today's sequential approach to multidisciplinary design. Therefore it is highly unlikely that the final solution is the true optimum solution from an interdisciplinary optimization standpoint. A multilevel decomposition approach is suggested as a technique to overcome the problems associated with the sequential approach, but no tool currently exists with which to fully implement this technique. A system based on the blackboard model of problem solving appears to be an ideal tool for implementing this technique because it offers an incremental problem solving approach that requires no a priori determined reasoning path. Thus it has the potential of finding a more optimum solution for the multidisciplinary design problems found in today's aerospace industries.

Guidance for modeling causes and effects in environmental problem solving

USGS Publications Warehouse

Armour, Carl L.; Williamson, Samuel C.

1988-01-01

Environmental problems are difficult to solve because their causes and effects are not easily understood. When attempts are made to analyze causes and effects, the principal challenge is organization of information into a framework that is logical, technically defensible, and easy to understand and communicate. When decisionmakers attempt to solve complex problems before an adequate cause and effect analysis is performed there are serious risks. These risks include: greater reliance on subjective reasoning, lessened chance for scoping an effective problem solving approach, impaired recognition of the need for supplemental information to attain understanding, increased chance for making unsound decisions, and lessened chance for gaining approval and financial support for a program/ Cause and effect relationships can be modeled. This type of modeling has been applied to various environmental problems, including cumulative impact assessment (Dames and Moore 1981; Meehan and Weber 1985; Williamson et al. 1987; Raley et al. 1988) and evaluation of effects of quarrying (Sheate 1986). This guidance for field users was written because of the current interest in documenting cause-effect logic as a part of ecological problem solving. Principal literature sources relating to the modeling approach are: Riggs and Inouye (1975a, b), Erickson (1981), and United States Office of Personnel Management (1986).

Probabilities and predictions: modeling the development of scientific problem-solving skills.

PubMed

Stevens, Ron; Johnson, David F; Soller, Amy

2005-01-01

The IMMEX (Interactive Multi-Media Exercises) Web-based problem set platform enables the online delivery of complex, multimedia simulations, the rapid collection of student performance data, and has already been used in several genetic simulations. The next step is the use of these data to understand and improve student learning in a formative manner. This article describes the development of probabilistic models of undergraduate student problem solving in molecular genetics that detailed the spectrum of strategies students used when problem solving, and how the strategic approaches evolved with experience. The actions of 776 university sophomore biology majors from three molecular biology lecture courses were recorded and analyzed. Each of six simulations were first grouped by artificial neural network clustering to provide individual performance measures, and then sequences of these performances were probabilistically modeled by hidden Markov modeling to provide measures of progress. The models showed that students with different initial problem-solving abilities choose different strategies. Initial and final strategies varied across different sections of the same course and were not strongly correlated with other achievement measures. In contrast to previous studies, we observed no significant gender differences. We suggest that instructor interventions based on early student performances with these simulations may assist students to recognize effective and efficient problem-solving strategies and enhance learning.

Observations on Leadership, Problem Solving, and Preferred Futures of Universities

ERIC Educational Resources Information Center

Puncochar, Judith

2013-01-01

A focus on enrollments, rankings, uncertain budgets, and branding efforts to operate universities could have serious implications for discussions of sustainable solutions to complex problems and the decision-making processes of leaders. The Authentic Leadership Model for framing ill-defined problems in higher education is posited to improve the…

Teaching Reductive Thinking

ERIC Educational Resources Information Center

Armoni, Michal; Gal-Ezer, Judith

2005-01-01

When dealing with a complex problem, solving it by reduction to simpler problems, or problems for which the solution is already known, is a common method in mathematics and other scientific disciplines, as in computer science and, specifically, in the field of computability. However, when teaching computational models (as part of computability)…

Problem Solving and Comprehension. Third Edition.

ERIC Educational Resources Information Center

Whimbey, Arthur; Lochhead, Jack

This book is directed toward increasing students' ability to analyze problems and comprehend what they read and hear. It outlines and illustrates the methods that good problem solvers use in attacking complex ideas, and provides practice in applying these methods to a variety of questions involving comprehension and reasoning. Chapter I includes a…

Problem-based learning in the NICU.

PubMed

Pilcher, Jobeth

2014-01-01

Problem-based learning (PBL) is an educational strategy that provides learners with the opportunity to investigate and solve realistic problem situations. It is also referred to as project-based learning or work-based learning. PBL combines several learning strategies including the use of case studies coupled with collaborative, facilitated, and self-directed learning. Research has demonstrated that use of PBL can result in learners having improved problem-solving skills, increased breadth and analysis of complex data, higher-level thinking skills, and improved collaboration. This article will include background information and a description of PBL, followed by examples of how this strategy can be used for learning in neonatal settings.

Numerical method for solving the nonlinear four-point boundary value problems

NASA Astrophysics Data System (ADS)

Lin, Yingzhen; Lin, Jinnan

2010-12-01

In this paper, a new reproducing kernel space is constructed skillfully in order to solve a class of nonlinear four-point boundary value problems. The exact solution of the linear problem can be expressed in the form of series and the approximate solution of the nonlinear problem is given by the iterative formula. Compared with known investigations, the advantages of our method are that the representation of exact solution is obtained in a new reproducing kernel Hilbert space and accuracy of numerical computation is higher. Meanwhile we present the convergent theorem, complexity analysis and error estimation. The performance of the new method is illustrated with several numerical examples.

Demonstration of quantum advantage in machine learning

NASA Astrophysics Data System (ADS)

Ristè, Diego; da Silva, Marcus P.; Ryan, Colm A.; Cross, Andrew W.; Córcoles, Antonio D.; Smolin, John A.; Gambetta, Jay M.; Chow, Jerry M.; Johnson, Blake R.

2017-04-01

The main promise of quantum computing is to efficiently solve certain problems that are prohibitively expensive for a classical computer. Most problems with a proven quantum advantage involve the repeated use of a black box, or oracle, whose structure encodes the solution. One measure of the algorithmic performance is the query complexity, i.e., the scaling of the number of oracle calls needed to find the solution with a given probability. Few-qubit demonstrations of quantum algorithms, such as Deutsch-Jozsa and Grover, have been implemented across diverse physical systems such as nuclear magnetic resonance, trapped ions, optical systems, and superconducting circuits. However, at the small scale, these problems can already be solved classically with a few oracle queries, limiting the obtained advantage. Here we solve an oracle-based problem, known as learning parity with noise, on a five-qubit superconducting processor. Executing classical and quantum algorithms using the same oracle, we observe a large gap in query count in favor of quantum processing. We find that this gap grows by orders of magnitude as a function of the error rates and the problem size. This result demonstrates that, while complex fault-tolerant architectures will be required for universal quantum computing, a significant quantum advantage already emerges in existing noisy systems.

An investigative framework to facilitate epidemiological thinking during herd problem-solving.

PubMed

More, Simon J; Doherty, Michael L; O'Grady, Luke

2017-01-01

Veterinary clinicians and students commonly use diagnostic approaches appropriate for individual cases when conducting herd problem-solving. However, these approaches can be problematic, in part because they make limited use of epidemiological principles and methods, which has clear application during the investigation of herd problems. In this paper, we provide an overview of diagnostic approaches that are used when investigating individual animal cases, and the challenges faced when these approaches are directly translated from the individual to the herd. Further, we propose an investigative framework to facilitate epidemiological thinking during herd problem-solving. A number of different approaches are used when making a diagnosis on an individual animal, including pattern recognition, hypothetico-deductive reasoning, and the key abnormality method. Methods commonly applied to individuals are often adapted for herd problem-solving: 'comparison with best practice' being a herd-level adaptation of pattern recognition, and 'differential diagnoses' a herd-level adaptation of hypothetico-deductive reasoning. These approaches can be effective, however, challenges can arise. Herds are complex; a collection of individual cows, but also additional layers relating to environment, management, feeding etc. It is unrealistic to expect seamless translation of diagnostic approaches from the individual to the herd. Comparison with best practice is time-consuming and prioritisation of actions can be problematic, whereas differential diagnoses can lead to 'pathogen hunting', particularly in complex cases. Epidemiology is the science of understanding disease in populations. The focus is on the population, underpinned by principles and utilising methods that seek to allow us to generate solid conclusions from apparently uncontrolled situations. In this paper, we argue for the inclusion of epidemiological principles and methods as an additional tool for herd problem-solving, and outline an investigative framework, with examples, to effectively incorporate these principles and methods with other diagnostic approaches during herd problem-solving. Relevant measures of performance are identified, and measures of case frequencies are calculated and compared across time, in space and among animal groupings, to identify patterns, clues and plausible hypotheses, consistent with potential biological processes. With this knowledge, the subsequent investigation (relevant on-farm activities, diagnostic testing and other examinations) can be focused, and actions prioritised (specifically, those actions that are likely to make the greatest difference in addressing the problem if enacted). In our experience, this investigative framework is an effective teaching tool, facilitating epidemiological thinking among students during herd problem-solving. It is a generic and robust process, suited to many herd-based problems.

A new three-dimensional manufacturing service composition method under various structures using improved Flower Pollination Algorithm

NASA Astrophysics Data System (ADS)

Zhang, Wenyu; Yang, Yushu; Zhang, Shuai; Yu, Dejian; Chen, Yong

2018-05-01

With the growing complexity of customer requirements and the increasing scale of manufacturing services, how to select and combine the single services to meet the complex demand of the customer has become a growing concern. This paper presents a new manufacturing service composition method to solve the multi-objective optimization problem based on quality of service (QoS). The proposed model not only presents different methods for calculating the transportation time and transportation cost under various structures but also solves the three-dimensional composition optimization problem, including service aggregation, service selection, and service scheduling simultaneously. Further, an improved Flower Pollination Algorithm (IFPA) is proposed to solve the three-dimensional composition optimization problem using a matrix-based representation scheme. The mutation operator and crossover operator of the Differential Evolution (DE) algorithm are also used to extend the basic Flower Pollination Algorithm (FPA) to improve its performance. Compared to Genetic Algorithm, DE, and basic FPA, the experimental results confirm that the proposed method demonstrates superior performance than other meta heuristic algorithms and can obtain better manufacturing service composition solutions.

FOURTH SEMINAR TO THE MEMORY OF D.N. KLYSHKO: Algebraic solution of the synthesis problem for coded sequences

NASA Astrophysics Data System (ADS)

Leukhin, Anatolii N.

2005-08-01

The algebraic solution of a 'complex' problem of synthesis of phase-coded (PC) sequences with the zero level of side lobes of the cyclic autocorrelation function (ACF) is proposed. It is shown that the solution of the synthesis problem is connected with the existence of difference sets for a given code dimension. The problem of estimating the number of possible code combinations for a given code dimension is solved. It is pointed out that the problem of synthesis of PC sequences is related to the fundamental problems of discrete mathematics and, first of all, to a number of combinatorial problems, which can be solved, as the number factorisation problem, by algebraic methods by using the theory of Galois fields and groups.

Numerical algebraic geometry: a new perspective on gauge and string theories

NASA Astrophysics Data System (ADS)

Mehta, Dhagash; He, Yang-Hui; Hauensteine, Jonathan D.

2012-07-01

There is a rich interplay between algebraic geometry and string and gauge theories which has been recently aided immensely by advances in computational algebra. However, symbolic (Gröbner) methods are severely limited by algorithmic issues such as exponential space complexity and being highly sequential. In this paper, we introduce a novel paradigm of numerical algebraic geometry which in a plethora of situations overcomes these shortcomings. The so-called `embarrassing parallelizability' allows us to solve many problems and extract physical information which elude symbolic methods. We describe the method and then use it to solve various problems arising from physics which could not be otherwise solved.

Application of Differential Evolutionary Optimization Methodology for Parameter Structure Identification in Groundwater Modeling

NASA Astrophysics Data System (ADS)

Chiu, Y.; Nishikawa, T.

2013-12-01

With the increasing complexity of parameter-structure identification (PSI) in groundwater modeling, there is a need for robust, fast, and accurate optimizers in the groundwater-hydrology field. For this work, PSI is defined as identifying parameter dimension, structure, and value. In this study, Voronoi tessellation and differential evolution (DE) are used to solve the optimal PSI problem. Voronoi tessellation is used for automatic parameterization, whereby stepwise regression and the error covariance matrix are used to determine the optimal parameter dimension. DE is a novel global optimizer that can be used to solve nonlinear, nondifferentiable, and multimodal optimization problems. It can be viewed as an improved version of genetic algorithms and employs a simple cycle of mutation, crossover, and selection operations. DE is used to estimate the optimal parameter structure and its associated values. A synthetic numerical experiment of continuous hydraulic conductivity distribution was conducted to demonstrate the proposed methodology. The results indicate that DE can identify the global optimum effectively and efficiently. A sensitivity analysis of the control parameters (i.e., the population size, mutation scaling factor, crossover rate, and mutation schemes) was performed to examine their influence on the objective function. The proposed DE was then applied to solve a complex parameter-estimation problem for a small desert groundwater basin in Southern California. Hydraulic conductivity, specific yield, specific storage, fault conductance, and recharge components were estimated simultaneously. Comparison of DE and a traditional gradient-based approach (PEST) shows DE to be more robust and efficient. The results of this work not only provide an alternative for PSI in groundwater models, but also extend DE applications towards solving complex, regional-scale water management optimization problems.

Knowledge Acquisition: A Review of Tools and Ideas.

DTIC Science & Technology

1987-08-01

tools. However, none could be applied directly to solving the problem of acquiring knowledge for the ASPA. RECOMMENDATIONS Develop a tool based on...the social sciences. BACKGROUND Because of the newness and complexity of the knowledge acquisition problem, the background of the knowledge...4. Minimal (does not incorporate any unnecessary complexities ) 5. Expected (experts are not in disagreement over any important aspect) (Grover 1983

What Mathematical Competencies Are Needed for Success in College.

ERIC Educational Resources Information Center

Garofalo, Joe

1990-01-01

Identifies requisite math skills for a microeconomics course, offering samples of supply curves, demand curves, equilibrium prices, elasticity, and complex graph problems. Recommends developmental mathematics competencies, including problem solving, reasoning, connections, communication, number and operation sense, algebra, relationships,…

Cognitive Complexity of Mathematics Instructional Tasks in a Taiwanese Classroom: An Examination of Task Sources

ERIC Educational Resources Information Center

Hsu, Hui-Yu; Silver, Edward A.

2014-01-01

We examined geometric calculation with number tasks used within a unit of geometry instruction in a Taiwanese classroom, identifying the source of each task used in classroom instruction and analyzing the cognitive complexity of each task with respect to 2 distinct features: diagram complexity and problem-solving complexity. We found that…

Improved multi-objective ant colony optimization algorithm and its application in complex reasoning

NASA Astrophysics Data System (ADS)

Wang, Xinqing; Zhao, Yang; Wang, Dong; Zhu, Huijie; Zhang, Qing

2013-09-01

The problem of fault reasoning has aroused great concern in scientific and engineering fields. However, fault investigation and reasoning of complex system is not a simple reasoning decision-making problem. It has become a typical multi-constraint and multi-objective reticulate optimization decision-making problem under many influencing factors and constraints. So far, little research has been carried out in this field. This paper transforms the fault reasoning problem of complex system into a paths-searching problem starting from known symptoms to fault causes. Three optimization objectives are considered simultaneously: maximum probability of average fault, maximum average importance, and minimum average complexity of test. Under the constraints of both known symptoms and the causal relationship among different components, a multi-objective optimization mathematical model is set up, taking minimizing cost of fault reasoning as the target function. Since the problem is non-deterministic polynomial-hard(NP-hard), a modified multi-objective ant colony algorithm is proposed, in which a reachability matrix is set up to constrain the feasible search nodes of the ants and a new pseudo-random-proportional rule and a pheromone adjustment mechinism are constructed to balance conflicts between the optimization objectives. At last, a Pareto optimal set is acquired. Evaluation functions based on validity and tendency of reasoning paths are defined to optimize noninferior set, through which the final fault causes can be identified according to decision-making demands, thus realize fault reasoning of the multi-constraint and multi-objective complex system. Reasoning results demonstrate that the improved multi-objective ant colony optimization(IMACO) can realize reasoning and locating fault positions precisely by solving the multi-objective fault diagnosis model, which provides a new method to solve the problem of multi-constraint and multi-objective fault diagnosis and reasoning of complex system.

Improving the learning of clinical reasoning through computer-based cognitive representation.

PubMed

Wu, Bian; Wang, Minhong; Johnson, Janice M; Grotzer, Tina A

2014-01-01

Objective Clinical reasoning is usually taught using a problem-solving approach, which is widely adopted in medical education. However, learning through problem solving is difficult as a result of the contextualization and dynamic aspects of actual problems. Moreover, knowledge acquired from problem-solving practice tends to be inert and fragmented. This study proposed a computer-based cognitive representation approach that externalizes and facilitates the complex processes in learning clinical reasoning. The approach is operationalized in a computer-based cognitive representation tool that involves argument mapping to externalize the problem-solving process and concept mapping to reveal the knowledge constructed from the problems. Methods Twenty-nine Year 3 or higher students from a medical school in east China participated in the study. Participants used the proposed approach implemented in an e-learning system to complete four learning cases in 4 weeks on an individual basis. For each case, students interacted with the problem to capture critical data, generate and justify hypotheses, make a diagnosis, recall relevant knowledge, and update their conceptual understanding of the problem domain. Meanwhile, students used the computer-based cognitive representation tool to articulate and represent the key elements and their interactions in the learning process. Results A significant improvement was found in students' learning products from the beginning to the end of the study, consistent with students' report of close-to-moderate progress in developing problem-solving and knowledge-construction abilities. No significant differences were found between the pretest and posttest scores with the 4-week period. The cognitive representation approach was found to provide more formative assessment. Conclusions The computer-based cognitive representation approach improved the learning of clinical reasoning in both problem solving and knowledge construction.

Improving the learning of clinical reasoning through computer-based cognitive representation

PubMed Central

Wu, Bian; Wang, Minhong; Johnson, Janice M.; Grotzer, Tina A.

2014-01-01

Objective Clinical reasoning is usually taught using a problem-solving approach, which is widely adopted in medical education. However, learning through problem solving is difficult as a result of the contextualization and dynamic aspects of actual problems. Moreover, knowledge acquired from problem-solving practice tends to be inert and fragmented. This study proposed a computer-based cognitive representation approach that externalizes and facilitates the complex processes in learning clinical reasoning. The approach is operationalized in a computer-based cognitive representation tool that involves argument mapping to externalize the problem-solving process and concept mapping to reveal the knowledge constructed from the problems. Methods Twenty-nine Year 3 or higher students from a medical school in east China participated in the study. Participants used the proposed approach implemented in an e-learning system to complete four learning cases in 4 weeks on an individual basis. For each case, students interacted with the problem to capture critical data, generate and justify hypotheses, make a diagnosis, recall relevant knowledge, and update their conceptual understanding of the problem domain. Meanwhile, students used the computer-based cognitive representation tool to articulate and represent the key elements and their interactions in the learning process. Results A significant improvement was found in students’ learning products from the beginning to the end of the study, consistent with students’ report of close-to-moderate progress in developing problem-solving and knowledge-construction abilities. No significant differences were found between the pretest and posttest scores with the 4-week period. The cognitive representation approach was found to provide more formative assessment. Conclusions The computer-based cognitive representation approach improved the learning of clinical reasoning in both problem solving and knowledge construction. PMID:25518871

Improving the learning of clinical reasoning through computer-based cognitive representation.

PubMed

Wu, Bian; Wang, Minhong; Johnson, Janice M; Grotzer, Tina A

2014-01-01

Clinical reasoning is usually taught using a problem-solving approach, which is widely adopted in medical education. However, learning through problem solving is difficult as a result of the contextualization and dynamic aspects of actual problems. Moreover, knowledge acquired from problem-solving practice tends to be inert and fragmented. This study proposed a computer-based cognitive representation approach that externalizes and facilitates the complex processes in learning clinical reasoning. The approach is operationalized in a computer-based cognitive representation tool that involves argument mapping to externalize the problem-solving process and concept mapping to reveal the knowledge constructed from the problems. Twenty-nine Year 3 or higher students from a medical school in east China participated in the study. Participants used the proposed approach implemented in an e-learning system to complete four learning cases in 4 weeks on an individual basis. For each case, students interacted with the problem to capture critical data, generate and justify hypotheses, make a diagnosis, recall relevant knowledge, and update their conceptual understanding of the problem domain. Meanwhile, students used the computer-based cognitive representation tool to articulate and represent the key elements and their interactions in the learning process. A significant improvement was found in students' learning products from the beginning to the end of the study, consistent with students' report of close-to-moderate progress in developing problem-solving and knowledge-construction abilities. No significant differences were found between the pretest and posttest scores with the 4-week period. The cognitive representation approach was found to provide more formative assessment. The computer-based cognitive representation approach improved the learning of clinical reasoning in both problem solving and knowledge construction.

Optical solver of combinatorial problems: nanotechnological approach.

PubMed

Cohen, Eyal; Dolev, Shlomi; Frenkel, Sergey; Kryzhanovsky, Boris; Palagushkin, Alexandr; Rosenblit, Michael; Zakharov, Victor

2013-09-01

We present an optical computing system to solve NP-hard problems. As nano-optical computing is a promising venue for the next generation of computers performing parallel computations, we investigate the application of submicron, or even subwavelength, computing device designs. The system utilizes a setup of exponential sized masks with exponential space complexity produced in polynomial time preprocessing. The masks are later used to solve the problem in polynomial time. The size of the masks is reduced to nanoscaled density. Simulations were done to choose a proper design, and actual implementations show the feasibility of such a system.

Assessing Complexity in Learning Outcomes--A Comparison between the SOLO Taxonomy and the Model of Hierarchical Complexity

ERIC Educational Resources Information Center

Stålne, Kristian; Kjellström, Sofia; Utriainen, Jukka

2016-01-01

An important aspect of higher education is to educate students who can manage complex relationships and solve complex problems. Teachers need to be able to evaluate course content with regard to complexity, as well as evaluate students' ability to assimilate complex content and express it in the form of a learning outcome. One model for evaluating…

Working Memory and Reasoning Benefit from Different Modes of Large-scale Brain Dynamics in Healthy Older Adults.

PubMed

Lebedev, Alexander V; Nilsson, Jonna; Lövdén, Martin

2018-07-01

Researchers have proposed that solving complex reasoning problems, a key indicator of fluid intelligence, involves the same cognitive processes as solving working memory tasks. This proposal is supported by an overlap of the functional brain activations associated with the two types of tasks and by high correlations between interindividual differences in performance. We replicated these findings in 53 older participants but also showed that solving reasoning and working memory problems benefits from different configurations of the functional connectome and that this dissimilarity increases with a higher difficulty load. Specifically, superior performance in a typical working memory paradigm ( n-back) was associated with upregulation of modularity (increased between-network segregation), whereas performance in the reasoning task was associated with effective downregulation of modularity. We also showed that working memory training promotes task-invariant increases in modularity. Because superior reasoning performance is associated with downregulation of modular dynamics, training may thus have fostered an inefficient way of solving the reasoning tasks. This could help explain why working memory training does little to promote complex reasoning performance. The study concludes that complex reasoning abilities cannot be reduced to working memory and suggests the need to reconsider the feasibility of using working memory training interventions to attempt to achieve effects that transfer to broader cognition.

Teaching NMR spectra analysis with nmr.cheminfo.org.

PubMed

Patiny, Luc; Bolaños, Alejandro; Castillo, Andrés M; Bernal, Andrés; Wist, Julien

2018-06-01

Teaching spectra analysis and structure elucidation requires students to get trained on real problems. This involves solving exercises of increasing complexity and when necessary using computational tools. Although desktop software packages exist for this purpose, nmr.cheminfo.org platform offers students an online alternative. It provides a set of exercises and tools to help solving them. Only a small number of exercises are currently available, but contributors are invited to submit new ones and suggest new types of problems. Copyright © 2018 John Wiley & Sons, Ltd.

Designing a Better Experience: A Qualitative Investigation of Student Engineering Internships

ERIC Educational Resources Information Center

Paknejad, Mohammad R.

2016-01-01

Science, Technology, Engineering and Mathematics (STEM) education play a very important role in preparing students with skills necessary to obtain better jobs, solve real-world challenges, and compete in the global economy. STEM education develops critical thinking and the ability to solve complex problems. Research showed that 8 out of 10 most…

Young Children "Solve for X" Using the Approximate Number System

ERIC Educational Resources Information Center

Kibbe, Melissa M.; Feigenson, Lisa

2015-01-01

The Approximate Number System (ANS) supports basic arithmetic computation in early childhood, but it is unclear whether the ANS also supports the more complex computations introduced later in formal education. "Solving for x" in addend-unknown problems is notoriously difficult for children, who often struggle with these types of problems…

Problem-Solving Test: The Mechanism of Action of a Human Papilloma Virus Oncoprotein

ERIC Educational Resources Information Center

Szeberenyi, Jozsef

2009-01-01

Terms to be familiar with before you start to solve the test: human papilloma virus; cervical cancer; oncoproteins; malignant transformation; retinoblastoma protein; cell cycle; quiescent and cycling cells; cyclin/cyclin-dependent kinase (Cdk) complexes; E2F; S-phase genes; enhancer element; proto-oncogenes; tumor suppressor genes; radioactive…

Satisfying positivity requirement in the Beyond Complex Langevin approach

NASA Astrophysics Data System (ADS)

Wyrzykowski, Adam; Ruba, Błażej Ruba

2018-03-01

The problem of finding a positive distribution, which corresponds to a given complex density, is studied. By the requirement that the moments of the positive distribution and of the complex density are equal, one can reduce the problem to solving the matching conditions. These conditions are a set of quadratic equations, thus Groebner basis method was used to find its solutions when it is restricted to a few lowest-order moments. For a Gaussian complex density, these approximate solutions are compared with the exact solution, that is known in this special case.

A multilevel finite element method for Fredholm integral eigenvalue problems

NASA Astrophysics Data System (ADS)

Xie, Hehu; Zhou, Tao

2015-12-01

In this work, we proposed a multigrid finite element (MFE) method for solving the Fredholm integral eigenvalue problems. The main motivation for such studies is to compute the Karhunen-Loève expansions of random fields, which play an important role in the applications of uncertainty quantification. In our MFE framework, solving the eigenvalue problem is converted to doing a series of integral iterations and eigenvalue solving in the coarsest mesh. Then, any existing efficient integration scheme can be used for the associated integration process. The error estimates are provided, and the computational complexity is analyzed. It is noticed that the total computational work of our method is comparable with a single integration step in the finest mesh. Several numerical experiments are presented to validate the efficiency of the proposed numerical method.

The principle of superposition and its application in ground-water hydraulics

USGS Publications Warehouse

Reilly, T.E.; Franke, O.L.; Bennett, G.D.

1984-01-01

The principle of superposition, a powerful methematical technique for analyzing certain types of complex problems in many areas of science and technology, has important application in ground-water hydraulics and modeling of ground-water systems. The principle of superposition states that solutions to individual problems can be added together to obtain solutions to complex problems. This principle applies to linear systems governed by linear differential equations. This report introduces the principle of superposition as it applies to groundwater hydrology and provides background information, discussion, illustrative problems with solutions, and problems to be solved by the reader. (USGS)

Use of a Computer Language in Teaching Dynamic Programming. Final Report.

ERIC Educational Resources Information Center

Trimble, C. J.; And Others

Most optimization problems of any degree of complexity must be solved using a computer. In the teaching of dynamic programing courses, it is often desirable to use a computer in problem solution. The solution process involves conceptual formulation and computational Solution. Generalized computer codes for dynamic programing problem solution…

Problem Solving & Comprehension. Fourth Edition.

ERIC Educational Resources Information Center

Whimbey, Arthur; Lochhead, Jack

This book shows how to increase one's power to analyze and comprehend problems. First, it outlines and illustrates the methods that good problem solvers use in attacking complex ideas. Then it gives some practice in applying these methods to a variety of questions in comprehension and reasoning. Chapters include: (1) "Test Your Mind--See How…

The Multiple Pendulum Problem via Maple[R

ERIC Educational Resources Information Center

Salisbury, K. L.; Knight, D. G.

2002-01-01

The way in which computer algebra systems, such as Maple, have made the study of physical problems of some considerable complexity accessible to mathematicians and scientists with modest computational skills is illustrated by solving the multiple pendulum problem. A solution is obtained for four pendulums with no restriction on the size of the…

Active and Healthy Ageing as a Wicked Problem: The Contribution of a Multidisciplinary Research University.

PubMed

Riva, Giuseppe; Graffigna, Guendalina; Baitieri, Maddalena; Amato, Alessandra; Bonanomi, Maria Grazia; Valentini, Paolo; Castelli, Guido

2014-01-01

The quest for an active and healthy ageing can be considered a "wicked problem." It is a social and cultural problem, which is difficult to solve because of incomplete, changing, and contradictory requirements. These problems are tough to manage because of their social complexity. They are a group of linked problems embedded in the structure of the communities in which they occur. First, they require the knowledge of the social and cultural context in which they occur. They can be solved only by understanding of what people do and why they do it. Second, they require a multidisciplinary approach. Wicked problems can have different solutions, so it is critical to capture the full range of possibilities and interpretations. Thus, we suggest that Università Cattolica del Sacro Cuore (UCSC) is well suited for accepting and managing this challenge because of its applied research orientation, multidisciplinary approach, and integrated vision. After presenting the research activity of UCSC, we describe a possible "systems thinking" strategy to consider the complexity and interdependence of active ageing and healthy living.

Active subspace: toward scalable low-rank learning.

PubMed

Liu, Guangcan; Yan, Shuicheng

2012-12-01

We address the scalability issues in low-rank matrix learning problems. Usually these problems resort to solving nuclear norm regularized optimization problems (NNROPs), which often suffer from high computational complexities if based on existing solvers, especially in large-scale settings. Based on the fact that the optimal solution matrix to an NNROP is often low rank, we revisit the classic mechanism of low-rank matrix factorization, based on which we present an active subspace algorithm for efficiently solving NNROPs by transforming large-scale NNROPs into small-scale problems. The transformation is achieved by factorizing the large solution matrix into the product of a small orthonormal matrix (active subspace) and another small matrix. Although such a transformation generally leads to nonconvex problems, we show that a suboptimal solution can be found by the augmented Lagrange alternating direction method. For the robust PCA (RPCA) (Candès, Li, Ma, & Wright, 2009 ) problem, a typical example of NNROPs, theoretical results verify the suboptimality of the solution produced by our algorithm. For the general NNROPs, we empirically show that our algorithm significantly reduces the computational complexity without loss of optimality.

The complexity of proving chaoticity and the Church-Turing thesis

NASA Astrophysics Data System (ADS)

Calude, Cristian S.; Calude, Elena; Svozil, Karl

2010-09-01

Proving the chaoticity of some dynamical systems is equivalent to solving the hardest problems in mathematics. Conversely, classical physical systems may "compute the hard or even the incomputable" by measuring observables which correspond to computationally hard or even incomputable problems.

Learning to Predict Combinatorial Structures

NASA Astrophysics Data System (ADS)

Vembu, Shankar

2009-12-01

The major challenge in designing a discriminative learning algorithm for predicting structured data is to address the computational issues arising from the exponential size of the output space. Existing algorithms make different assumptions to ensure efficient, polynomial time estimation of model parameters. For several combinatorial structures, including cycles, partially ordered sets, permutations and other graph classes, these assumptions do not hold. In this thesis, we address the problem of designing learning algorithms for predicting combinatorial structures by introducing two new assumptions: (i) The first assumption is that a particular counting problem can be solved efficiently. The consequence is a generalisation of the classical ridge regression for structured prediction. (ii) The second assumption is that a particular sampling problem can be solved efficiently. The consequence is a new technique for designing and analysing probabilistic structured prediction models. These results can be applied to solve several complex learning problems including but not limited to multi-label classification, multi-category hierarchical classification, and label ranking.

Geometric and Algebraic Approaches in the Concept of Complex Numbers

ERIC Educational Resources Information Center

Panaoura, A.; Elia, I.; Gagatsis, A.; Giatilis, G.-P.

2006-01-01

This study explores pupils' performance and processes in tasks involving equations and inequalities of complex numbers requiring conversions from a geometric representation to an algebraic representation and conversions in the reverse direction, and also in complex numbers problem solving. Data were collected from 95 pupils of the final grade from…

Neurocognitive Effects of Transcranial Direct Current Stimulation in Arithmetic Learning and Performance: A Simultaneous tDCS-fMRI Study.

PubMed

Hauser, Tobias U; Rütsche, Bruno; Wurmitzer, Karoline; Brem, Silvia; Ruff, Christian C; Grabner, Roland H

A small but increasing number of studies suggest that non-invasive brain stimulation by means of transcranial direct current stimulation (tDCS) can modulate arithmetic processes that are essential for higher-order mathematical skills and that are impaired in dyscalculic individuals. However, little is known about the neural mechanisms underlying such stimulation effects, and whether they are specific to cognitive processes involved in different arithmetic tasks. We addressed these questions by applying tDCS during simultaneous functional magnetic resonance imaging (fMRI) while participants were solving two types of complex subtraction problems: repeated problems, relying on arithmetic fact learning and problem-solving by fact retrieval, and novel problems, requiring calculation procedures. Twenty participants receiving left parietal anodal plus right frontal cathodal stimulation were compared with 20 participants in a sham condition. We found a strong cognitive and neural dissociation between repeated and novel problems. Repeated problems were solved more accurately and elicited increased activity in the bilateral angular gyri and medial plus lateral prefrontal cortices. Solving novel problems, in contrast, was accompanied by stronger activation in the bilateral intraparietal sulci and the dorsomedial prefrontal cortex. Most importantly, tDCS decreased the activation of the right inferior frontal cortex while solving novel (compared to repeated) problems, suggesting that the cathodal stimulation rendered this region unable to respond to the task-specific cognitive demand. The present study revealed that tDCS during arithmetic problem-solving can modulate the neural activity in proximity to the electrodes specifically when the current demands lead to an engagement of this area. Copyright © 2016 Elsevier Inc. All rights reserved.

Solving complex maintenance planning optimization problems using stochastic simulation and multi-criteria fuzzy decision making

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tahvili, Sahar; Österberg, Jonas; Silvestrov, Sergei

One of the most important factors in the operations of many cooperations today is to maximize profit and one important tool to that effect is the optimization of maintenance activities. Maintenance activities is at the largest level divided into two major areas, corrective maintenance (CM) and preventive maintenance (PM). When optimizing maintenance activities, by a maintenance plan or policy, we seek to find the best activities to perform at each point in time, be it PM or CM. We explore the use of stochastic simulation, genetic algorithms and other tools for solving complex maintenance planning optimization problems in terms ofmore » a suggested framework model based on discrete event simulation.« less

Solving the Problem of Bending of Multiply Connected Plates with Elastic Inclusions

NASA Astrophysics Data System (ADS)

Kaloerov, S. A.; Koshkin, A. A.

2017-11-01

This paper describes a method for determining the strain state of a thin anisotropic plate with elastic arbitrarily arranged elliptical inclusions. Complex potentials are used to reduce the problem to determining functions of generalized complex variables, which, in turn, comes down to an overdetermined system of linear algebraic equations, solved by singular expansions. This paper presents the results of numerical calculations that helped establish the influence of rigidity of elastic inclusions, distances between inclusions, and their geometric characteristics on the bending moments occurring in the plate. It is found that the specific properties of distribution of moments near the apexes of linear elastic inclusions, characterized by moment intensity coefficients, occur only in the case of sufficiently rigid and elastic inclusions.

Improve Problem Solving Skills through Adapting Programming Tools

NASA Technical Reports Server (NTRS)

Shaykhian, Linda H.; Shaykhian, Gholam Ali

2007-01-01

There are numerous ways for engineers and students to become better problem-solvers. The use of command line and visual programming tools can help to model a problem and formulate a solution through visualization. The analysis of problem attributes and constraints provide insight into the scope and complexity of the problem. The visualization aspect of the problem-solving approach tends to make students and engineers more systematic in their thought process and help them catch errors before proceeding too far in the wrong direction. The problem-solver identifies and defines important terms, variables, rules, and procedures required for solving a problem. Every step required to construct the problem solution can be defined in program commands that produce intermediate output. This paper advocates improved problem solving skills through using a programming tool. MatLab created by MathWorks, is an interactive numerical computing environment and programming language. It is a matrix-based system that easily lends itself to matrix manipulation, and plotting of functions and data. MatLab can be used as an interactive command line or a sequence of commands that can be saved in a file as a script or named functions. Prior programming experience is not required to use MatLab commands. The GNU Octave, part of the GNU project, a free computer program for performing numerical computations, is comparable to MatLab. MatLab visual and command programming are presented here.

The Davey-Stewartson Equation on the Half-Plane

NASA Astrophysics Data System (ADS)

Fokas, A. S.

2009-08-01

The Davey-Stewartson (DS) equation is a nonlinear integrable evolution equation in two spatial dimensions. It provides a multidimensional generalisation of the celebrated nonlinear Schrödinger (NLS) equation and it appears in several physical situations. The implementation of the Inverse Scattering Transform (IST) to the solution of the initial-value problem of the NLS was presented in 1972, whereas the analogous problem for the DS equation was solved in 1983. These results are based on the formulation and solution of certain classical problems in complex analysis, namely of a Riemann Hilbert problem (RH) and of either a d-bar or a non-local RH problem respectively. A method for solving the mathematically more complicated but physically more relevant case of boundary-value problems for evolution equations in one spatial dimension, like the NLS, was finally presented in 1997, after interjecting several novel ideas to the panoply of the IST methodology. Here, this method is further extended so that it can be applied to evolution equations in two spatial dimensions, like the DS equation. This novel extension involves several new steps, including the formulation of a d-bar problem for a sectionally non-analytic function, i.e. for a function which has different non-analytic representations in different domains of the complex plane. This, in addition to the computation of a d-bar derivative, also requires the computation of the relevant jumps across the different domains. This latter step has certain similarities (but is more complicated) with the corresponding step for those initial-value problems in two dimensions which can be solved via a non-local RH problem, like KPI.

An evaluation of superminicomputers for thermal analysis

NASA Technical Reports Server (NTRS)

Storaasli, O. O.; Vidal, J. B.; Jones, G. K.

1982-01-01

The use of superminicomputers for solving a series of increasingly complex thermal analysis problems is investigated. The approach involved (1) installation and verification of the SPAR thermal analyzer software on superminicomputers at Langley Research Center and Goddard Space Flight Center, (2) solution of six increasingly complex thermal problems on this equipment, and (3) comparison of solution (accuracy, CPU time, turnaround time, and cost) with solutions on large mainframe computers.

Inhibitory Control, but Not Prolonged Object-Related Experience Appears to Affect Physical Problem-Solving Performance of Pet Dogs.

PubMed

Müller, Corsin A; Riemer, Stefanie; Virányi, Zsófia; Huber, Ludwig; Range, Friederike

2016-01-01

Human infants develop an understanding of their physical environment through playful interactions with objects. Similar processes may influence also the performance of non-human animals in physical problem-solving tasks, but to date there is little empirical data to evaluate this hypothesis. In addition or alternatively to prior experiences, inhibitory control has been suggested as a factor underlying the considerable individual differences in performance reported for many species. Here we report a study in which we manipulated the extent of object-related experience for a cohort of dogs (Canis familiaris) of the breed Border Collie over a period of 18 months, and assessed their level of inhibitory control, prior to testing them in a series of four physical problem-solving tasks. We found no evidence that differences in object-related experience explain variability in performance in these tasks. It thus appears that dogs do not transfer knowledge about physical rules from one physical problem-solving task to another, but rather approach each task as a novel problem. Our results, however, suggest that individual performance in these tasks is influenced in a complex way by the subject's level of inhibitory control. Depending on the task, inhibitory control had a positive or a negative effect on performance and different aspects of inhibitory control turned out to be the best predictors of individual performance in the different tasks. Therefore, studying the interplay between inhibitory control and problem-solving performance will make an important contribution to our understanding of individual and species differences in physical problem-solving performance.

Inhibitory Control, but Not Prolonged Object-Related Experience Appears to Affect Physical Problem-Solving Performance of Pet Dogs

PubMed Central

Müller, Corsin A.; Riemer, Stefanie; Virányi, Zsófia; Huber, Ludwig; Range, Friederike

2016-01-01

Human infants develop an understanding of their physical environment through playful interactions with objects. Similar processes may influence also the performance of non-human animals in physical problem-solving tasks, but to date there is little empirical data to evaluate this hypothesis. In addition or alternatively to prior experiences, inhibitory control has been suggested as a factor underlying the considerable individual differences in performance reported for many species. Here we report a study in which we manipulated the extent of object-related experience for a cohort of dogs (Canis familiaris) of the breed Border Collie over a period of 18 months, and assessed their level of inhibitory control, prior to testing them in a series of four physical problem-solving tasks. We found no evidence that differences in object-related experience explain variability in performance in these tasks. It thus appears that dogs do not transfer knowledge about physical rules from one physical problem-solving task to another, but rather approach each task as a novel problem. Our results, however, suggest that individual performance in these tasks is influenced in a complex way by the subject’s level of inhibitory control. Depending on the task, inhibitory control had a positive or a negative effect on performance and different aspects of inhibitory control turned out to be the best predictors of individual performance in the different tasks. Therefore, studying the interplay between inhibitory control and problem-solving performance will make an important contribution to our understanding of individual and species differences in physical problem-solving performance. PMID:26863141

Improved teaching-learning-based and JAYA optimization algorithms for solving flexible flow shop scheduling problems

NASA Astrophysics Data System (ADS)

Buddala, Raviteja; Mahapatra, Siba Sankar

2017-11-01

Flexible flow shop (or a hybrid flow shop) scheduling problem is an extension of classical flow shop scheduling problem. In a simple flow shop configuration, a job having `g' operations is performed on `g' operation centres (stages) with each stage having only one machine. If any stage contains more than one machine for providing alternate processing facility, then the problem becomes a flexible flow shop problem (FFSP). FFSP which contains all the complexities involved in a simple flow shop and parallel machine scheduling problems is a well-known NP-hard (Non-deterministic polynomial time) problem. Owing to high computational complexity involved in solving these problems, it is not always possible to obtain an optimal solution in a reasonable computation time. To obtain near-optimal solutions in a reasonable computation time, a large variety of meta-heuristics have been proposed in the past. However, tuning algorithm-specific parameters for solving FFSP is rather tricky and time consuming. To address this limitation, teaching-learning-based optimization (TLBO) and JAYA algorithm are chosen for the study because these are not only recent meta-heuristics but they do not require tuning of algorithm-specific parameters. Although these algorithms seem to be elegant, they lose solution diversity after few iterations and get trapped at the local optima. To alleviate such drawback, a new local search procedure is proposed in this paper to improve the solution quality. Further, mutation strategy (inspired from genetic algorithm) is incorporated in the basic algorithm to maintain solution diversity in the population. Computational experiments have been conducted on standard benchmark problems to calculate makespan and computational time. It is found that the rate of convergence of TLBO is superior to JAYA. From the results, it is found that TLBO and JAYA outperform many algorithms reported in the literature and can be treated as efficient methods for solving the FFSP.

A Parallel Biological Optimization Algorithm to Solve the Unbalanced Assignment Problem Based on DNA Molecular Computing.

PubMed

Wang, Zhaocai; Pu, Jun; Cao, Liling; Tan, Jian

2015-10-23

The unbalanced assignment problem (UAP) is to optimally resolve the problem of assigning n jobs to m individuals (m < n), such that minimum cost or maximum profit obtained. It is a vitally important Non-deterministic Polynomial (NP) complete problem in operation management and applied mathematics, having numerous real life applications. In this paper, we present a new parallel DNA algorithm for solving the unbalanced assignment problem using DNA molecular operations. We reasonably design flexible-length DNA strands representing different jobs and individuals, take appropriate steps, and get the solutions of the UAP in the proper length range and O(mn) time. We extend the application of DNA molecular operations and simultaneity to simplify the complexity of the computation.

Computational complexity of ecological and evolutionary spatial dynamics

PubMed Central

Ibsen-Jensen, Rasmus; Chatterjee, Krishnendu; Nowak, Martin A.

2015-01-01

There are deep, yet largely unexplored, connections between computer science and biology. Both disciplines examine how information proliferates in time and space. Central results in computer science describe the complexity of algorithms that solve certain classes of problems. An algorithm is deemed efficient if it can solve a problem in polynomial time, which means the running time of the algorithm is a polynomial function of the length of the input. There are classes of harder problems for which the fastest possible algorithm requires exponential time. Another criterion is the space requirement of the algorithm. There is a crucial distinction between algorithms that can find a solution, verify a solution, or list several distinct solutions in given time and space. The complexity hierarchy that is generated in this way is the foundation of theoretical computer science. Precise complexity results can be notoriously difficult. The famous question whether polynomial time equals nondeterministic polynomial time (i.e., P = NP) is one of the hardest open problems in computer science and all of mathematics. Here, we consider simple processes of ecological and evolutionary spatial dynamics. The basic question is: What is the probability that a new invader (or a new mutant) will take over a resident population? We derive precise complexity results for a variety of scenarios. We therefore show that some fundamental questions in this area cannot be answered by simple equations (assuming that P is not equal to NP). PMID:26644569

Problem-Solving Phase Transitions During Team Collaboration.

PubMed

Wiltshire, Travis J; Butner, Jonathan E; Fiore, Stephen M

2018-01-01

Multiple theories of problem-solving hypothesize that there are distinct qualitative phases exhibited during effective problem-solving. However, limited research has attempted to identify when transitions between phases occur. We integrate theory on collaborative problem-solving (CPS) with dynamical systems theory suggesting that when a system is undergoing a phase transition it should exhibit a peak in entropy and that entropy levels should also relate to team performance. Communications from 40 teams that collaborated on a complex problem were coded for occurrence of problem-solving processes. We applied a sliding window entropy technique to each team's communications and specified criteria for (a) identifying data points that qualify as peaks and (b) determining which peaks were robust. We used multilevel modeling, and provide a qualitative example, to evaluate whether phases exhibit distinct distributions of communication processes. We also tested whether there was a relationship between entropy values at transition points and CPS performance. We found that a proportion of entropy peaks was robust and that the relative occurrence of communication codes varied significantly across phases. Peaks in entropy thus corresponded to qualitative shifts in teams' CPS communications, providing empirical evidence that teams exhibit phase transitions during CPS. Also, lower average levels of entropy at the phase transition points predicted better CPS performance. We specify future directions to improve understanding of phase transitions during CPS, and collaborative cognition, more broadly. Copyright © 2017 Cognitive Science Society, Inc.

STARS: An integrated general-purpose finite element structural, aeroelastic, and aeroservoelastic analysis computer program

NASA Technical Reports Server (NTRS)

Gupta, Kajal K.

1991-01-01

The details of an integrated general-purpose finite element structural analysis computer program which is also capable of solving complex multidisciplinary problems is presented. Thus, the SOLIDS module of the program possesses an extensive finite element library suitable for modeling most practical problems and is capable of solving statics, vibration, buckling, and dynamic response problems of complex structures, including spinning ones. The aerodynamic module, AERO, enables computation of unsteady aerodynamic forces for both subsonic and supersonic flow for subsequent flutter and divergence analysis of the structure. The associated aeroservoelastic analysis module, ASE, effects aero-structural-control stability analysis yielding frequency responses as well as damping characteristics of the structure. The program is written in standard FORTRAN to run on a wide variety of computers. Extensive graphics, preprocessing, and postprocessing routines are also available pertaining to a number of terminals.

Exploiting Bounded Signal Flow for Graph Orientation Based on Cause-Effect Pairs

NASA Astrophysics Data System (ADS)

Dorn, Britta; Hüffner, Falk; Krüger, Dominikus; Niedermeier, Rolf; Uhlmann, Johannes

We consider the following problem: Given an undirected network and a set of sender-receiver pairs, direct all edges such that the maximum number of "signal flows" defined by the pairs can be routed respecting edge directions. This problem has applications in communication networks and in understanding protein interaction based cell regulation mechanisms. Since this problem is NP-hard, research so far concentrated on polynomial-time approximation algorithms and tractable special cases. We take the viewpoint of parameterized algorithmics and examine several parameters related to the maximum signal flow over vertices or edges. We provide several fixed-parameter tractability results, and in one case a sharp complexity dichotomy between a linear-time solvable case and a slightly more general NP-hard case. We examine the value of these parameters for several real-world network instances. For many relevant cases, the NP-hard problem can be solved to optimality. In this way, parameterized analysis yields both deeper insight into the computational complexity and practical solving strategies.

Shooting method for solution of boundary-layer flows with massive blowing

NASA Technical Reports Server (NTRS)

Liu, T.-M.; Nachtsheim, P. R.

1973-01-01

A modified, bidirectional shooting method is presented for solving boundary-layer equations under conditions of massive blowing. Unlike the conventional shooting method, which is unstable when the blowing rate increases, the proposed method avoids the unstable direction and is capable of solving complex boundary-layer problems involving mass and energy balance on the surface.

Electrical Connections: Letters to Thomas Edison in Response to His Claim of Solving Incandescent Lighting, 1878.

ERIC Educational Resources Information Center

Bazerman, Charles

1994-01-01

Discusses the way in which letters sent to Thomas Edison following the report that he had solved the problem of incandescent lighting reveal the many discursive worlds that Edison's work touched. Claims these letters indicate how a technological accomplishment is also a multiple, complex social, and communicative accomplishment, creating place and…

Hybrid Metaheuristics for Solving a Fuzzy Single Batch-Processing Machine Scheduling Problem

PubMed Central

Molla-Alizadeh-Zavardehi, S.; Tavakkoli-Moghaddam, R.; Lotfi, F. Hosseinzadeh

2014-01-01

This paper deals with a problem of minimizing total weighted tardiness of jobs in a real-world single batch-processing machine (SBPM) scheduling in the presence of fuzzy due date. In this paper, first a fuzzy mixed integer linear programming model is developed. Then, due to the complexity of the problem, which is NP-hard, we design two hybrid metaheuristics called GA-VNS and VNS-SA applying the advantages of genetic algorithm (GA), variable neighborhood search (VNS), and simulated annealing (SA) frameworks. Besides, we propose three fuzzy earliest due date heuristics to solve the given problem. Through computational experiments with several random test problems, a robust calibration is applied on the parameters. Finally, computational results on different-scale test problems are presented to compare the proposed algorithms. PMID:24883359

Digitized adiabatic quantum computing with a superconducting circuit.

PubMed

Barends, R; Shabani, A; Lamata, L; Kelly, J; Mezzacapo, A; Las Heras, U; Babbush, R; Fowler, A G; Campbell, B; Chen, Yu; Chen, Z; Chiaro, B; Dunsworth, A; Jeffrey, E; Lucero, E; Megrant, A; Mutus, J Y; Neeley, M; Neill, C; O'Malley, P J J; Quintana, C; Roushan, P; Sank, D; Vainsencher, A; Wenner, J; White, T C; Solano, E; Neven, H; Martinis, John M

2016-06-09

Quantum mechanics can help to solve complex problems in physics and chemistry, provided they can be programmed in a physical device. In adiabatic quantum computing, a system is slowly evolved from the ground state of a simple initial Hamiltonian to a final Hamiltonian that encodes a computational problem. The appeal of this approach lies in the combination of simplicity and generality; in principle, any problem can be encoded. In practice, applications are restricted by limited connectivity, available interactions and noise. A complementary approach is digital quantum computing, which enables the construction of arbitrary interactions and is compatible with error correction, but uses quantum circuit algorithms that are problem-specific. Here we combine the advantages of both approaches by implementing digitized adiabatic quantum computing in a superconducting system. We tomographically probe the system during the digitized evolution and explore the scaling of errors with system size. We then let the full system find the solution to random instances of the one-dimensional Ising problem as well as problem Hamiltonians that involve more complex interactions. This digital quantum simulation of the adiabatic algorithm consists of up to nine qubits and up to 1,000 quantum logic gates. The demonstration of digitized adiabatic quantum computing in the solid state opens a path to synthesizing long-range correlations and solving complex computational problems. When combined with fault-tolerance, our approach becomes a general-purpose algorithm that is scalable.

Preparing new nurses with complexity science and problem-based learning.

PubMed

Hodges, Helen F

2011-01-01

Successful nurses function effectively with adaptability, improvability, and interconnectedness, and can see emerging and unpredictable complex problems. Preparing new nurses for complexity requires a significant change in prevalent but dated nursing education models for rising graduates. The science of complexity coupled with problem-based learning and peer review contributes a feasible framework for a constructivist learning environment to examine real-time systems data; explore uncertainty, inherent patterns, and ambiguity; and develop skills for unstructured problem solving. This article describes a pilot study of a problem-based learning strategy guided by principles of complexity science in a community clinical nursing course. Thirty-five senior nursing students participated during a 3-year period. Assessments included peer review, a final project paper, reflection, and a satisfaction survey. Results were higher than expected levels of student satisfaction, increased breadth and analysis of complex data, acknowledgment of community as complex adaptive systems, and overall higher level thinking skills than in previous years. 2011, SLACK Incorporated.

Solving optimization problems on computational grids.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wright, S. J.; Mathematics and Computer Science

2001-05-01

Multiprocessor computing platforms, which have become more and more widely available since the mid-1980s, are now heavily used by organizations that need to solve very demanding computational problems. Parallel computing is now central to the culture of many research communities. Novel parallel approaches were developed for global optimization, network optimization, and direct-search methods for nonlinear optimization. Activity was particularly widespread in parallel branch-and-bound approaches for various problems in combinatorial and network optimization. As the cost of personal computers and low-end workstations has continued to fall, while the speed and capacity of processors and networks have increased dramatically, 'cluster' platforms havemore » become popular in many settings. A somewhat different type of parallel computing platform know as a computational grid (alternatively, metacomputer) has arisen in comparatively recent times. Broadly speaking, this term refers not to a multiprocessor with identical processing nodes but rather to a heterogeneous collection of devices that are widely distributed, possibly around the globe. The advantage of such platforms is obvious: they have the potential to deliver enormous computing power. Just as obviously, however, the complexity of grids makes them very difficult to use. The Condor team, headed by Miron Livny at the University of Wisconsin, were among the pioneers in providing infrastructure for grid computations. More recently, the Globus project has developed technologies to support computations on geographically distributed platforms consisting of high-end computers, storage and visualization devices, and other scientific instruments. In 1997, we started the metaneos project as a collaborative effort between optimization specialists and the Condor and Globus groups. Our aim was to address complex, difficult optimization problems in several areas, designing and implementing the algorithms and the software infrastructure need to solve these problems on computational grids. This article describes some of the results we have obtained during the first three years of the metaneos project. Our efforts have led to development of the runtime support library MW for implementing algorithms with master-worker control structure on Condor platforms. This work is discussed here, along with work on algorithms and codes for integer linear programming, the quadratic assignment problem, and stochastic linear programmming. Our experiences in the metaneos project have shown that cheap, powerful computational grids can be used to tackle large optimization problems of various types. In an industrial or commercial setting, the results demonstrate that one may not have to buy powerful computational servers to solve many of the large problems arising in areas such as scheduling, portfolio optimization, or logistics; the idle time on employee workstations (or, at worst, an investment in a modest cluster of PCs) may do the job. For the optimization research community, our results motivate further work on parallel, grid-enabled algorithms for solving very large problems of other types. The fact that very large problems can be solved cheaply allows researchers to better understand issues of 'practical' complexity and of the role of heuristics.« less

The effect of visual representation style in problem-solving: a perspective from cognitive processes.

PubMed

Nyamsuren, Enkhbold; Taatgen, Niels A

2013-01-01

Using results from a controlled experiment and simulations based on cognitive models, we show that visual presentation style can have a significant impact on performance in a complex problem-solving task. We compared subject performances in two isomorphic, but visually different, tasks based on a card game of SET. Although subjects used the same strategy in both tasks, the difference in presentation style resulted in radically different reaction times and significant deviations in scanpath patterns in the two tasks. Results from our study indicate that low-level subconscious visual processes, such as differential acuity in peripheral vision and low-level iconic memory, can have indirect, but significant effects on decision making during a problem-solving task. We have developed two ACT-R models that employ the same basic strategy but deal with different presentations styles. Our ACT-R models confirm that changes in low-level visual processes triggered by changes in presentation style can propagate to higher-level cognitive processes. Such a domino effect can significantly affect reaction times and eye movements, without affecting the overall strategy of problem solving.

The Effect of Visual Representation Style in Problem-Solving: A Perspective from Cognitive Processes

PubMed Central

Nyamsuren, Enkhbold; Taatgen, Niels A.

2013-01-01

Using results from a controlled experiment and simulations based on cognitive models, we show that visual presentation style can have a significant impact on performance in a complex problem-solving task. We compared subject performances in two isomorphic, but visually different, tasks based on a card game of SET. Although subjects used the same strategy in both tasks, the difference in presentation style resulted in radically different reaction times and significant deviations in scanpath patterns in the two tasks. Results from our study indicate that low-level subconscious visual processes, such as differential acuity in peripheral vision and low-level iconic memory, can have indirect, but significant effects on decision making during a problem-solving task. We have developed two ACT-R models that employ the same basic strategy but deal with different presentations styles. Our ACT-R models confirm that changes in low-level visual processes triggered by changes in presentation style can propagate to higher-level cognitive processes. Such a domino effect can significantly affect reaction times and eye movements, without affecting the overall strategy of problem solving. PMID:24260415

Do New Caledonian crows solve physical problems through causal reasoning?

PubMed Central

Taylor, A.H.; Hunt, G.R.; Medina, F.S.; Gray, R.D.

2008-01-01

The extent to which animals other than humans can reason about physical problems is contentious. The benchmark test for this ability has been the trap-tube task. We presented New Caledonian crows with a series of two-trap versions of this problem. Three out of six crows solved the initial trap-tube. These crows continued to avoid the trap when the arbitrary features that had previously been associated with successful performances were removed. However, they did not avoid the trap when a hole and a functional trap were in the tube. In contrast to a recent primate study, the three crows then solved a causally equivalent but visually distinct problem—the trap-table task. The performance of the three crows across the four transfers made explanations based on chance, associative learning, visual and tactile generalization, and previous dispositions unlikely. Our findings suggest that New Caledonian crows can solve complex physical problems by reasoning both causally and analogically about causal relations. Causal and analogical reasoning may form the basis of the New Caledonian crow's exceptional tool skills. PMID:18796393

Design and performance frameworks for constructing problem-solving simulations.

PubMed

Stevens, Ron; Palacio-Cayetano, Joycelin

2003-01-01

Rapid advancements in hardware, software, and connectivity are helping to shorten the times needed to develop computer simulations for science education. These advancements, however, have not been accompanied by corresponding theories of how best to design and use these technologies for teaching, learning, and testing. Such design frameworks ideally would be guided less by the strengths/limitations of the presentation media and more by cognitive analyses detailing the goals of the tasks, the needs and abilities of students, and the resulting decision outcomes needed by different audiences. This article describes a problem-solving environment and associated theoretical framework for investigating how students select and use strategies as they solve complex science problems. A framework is first described for designing on-line problem spaces that highlights issues of content, scale, cognitive complexity, and constraints. While this framework was originally designed for medical education, it has proven robust and has been successfully applied to learning environments from elementary school through medical school. Next, a similar framework is detailed for collecting student performance and progress data that can provide evidence of students' strategic thinking and that could potentially be used to accelerate student progress. Finally, experimental validation data are presented that link strategy selection and use with other metrics of scientific reasoning and student achievement.

Design and Performance Frameworks for Constructing Problem-Solving Simulations

PubMed Central

Stevens, Ron; Palacio-Cayetano, Joycelin

2003-01-01

Rapid advancements in hardware, software, and connectivity are helping to shorten the times needed to develop computer simulations for science education. These advancements, however, have not been accompanied by corresponding theories of how best to design and use these technologies for teaching, learning, and testing. Such design frameworks ideally would be guided less by the strengths/limitations of the presentation media and more by cognitive analyses detailing the goals of the tasks, the needs and abilities of students, and the resulting decision outcomes needed by different audiences. This article describes a problem-solving environment and associated theoretical framework for investigating how students select and use strategies as they solve complex science problems. A framework is first described for designing on-line problem spaces that highlights issues of content, scale, cognitive complexity, and constraints. While this framework was originally designed for medical education, it has proven robust and has been successfully applied to learning environments from elementary school through medical school. Next, a similar framework is detailed for collecting student performance and progress data that can provide evidence of students' strategic thinking and that could potentially be used to accelerate student progress. Finally, experimental validation data are presented that link strategy selection and use with other metrics of scientific reasoning and student achievement. PMID:14506505

Environmental influences on neural systems of relational complexity

PubMed Central

Kalbfleisch, M. Layne; deBettencourt, Megan T.; Kopperman, Rebecca; Banasiak, Meredith; Roberts, Joshua M.; Halavi, Maryam

2013-01-01

Constructivist learning theory contends that we construct knowledge by experience and that environmental context influences learning. To explore this principle, we examined the cognitive process relational complexity (RC), defined as the number of visual dimensions considered during problem solving on a matrix reasoning task and a well-documented measure of mature reasoning capacity. We sought to determine how the visual environment influences RC by examining the influence of color and visual contrast on RC in a neuroimaging task. To specify the contributions of sensory demand and relational integration to reasoning, our participants performed a non-verbal matrix task comprised of color, no-color line, or black-white visual contrast conditions parametrically varied by complexity (relations 0, 1, 2). The use of matrix reasoning is ecologically valid for its psychometric relevance and for its potential to link the processing of psychophysically specific visual properties with various levels of RC during reasoning. The role of these elements is important because matrix tests assess intellectual aptitude based on these seemingly context-less exercises. This experiment is a first step toward examining the psychophysical underpinnings of performance on these types of problems. The importance of this is increased in light of recent evidence that intelligence can be linked to visual discrimination. We submit three main findings. First, color and black-white visual contrast (BWVC) add demand at a basic sensory level, but contributions from color and from BWVC are dissociable in cortex such that color engages a “reasoning heuristic” and BWVC engages a “sensory heuristic.” Second, color supports contextual sense-making by boosting salience resulting in faster problem solving. Lastly, when visual complexity reaches 2-relations, color and visual contrast relinquish salience to other dimensions of problem solving. PMID:24133465

Probabilistic data integration and computational complexity

NASA Astrophysics Data System (ADS)

Hansen, T. M.; Cordua, K. S.; Mosegaard, K.

2016-12-01

Inverse problems in Earth Sciences typically refer to the problem of inferring information about properties of the Earth from observations of geophysical data (the result of nature's solution to the `forward' problem). This problem can be formulated more generally as a problem of `integration of information'. A probabilistic formulation of data integration is in principle simple: If all information available (from e.g. geology, geophysics, remote sensing, chemistry…) can be quantified probabilistically, then different algorithms exist that allow solving the data integration problem either through an analytical description of the combined probability function, or sampling the probability function. In practice however, probabilistic based data integration may not be easy to apply successfully. This may be related to the use of sampling methods, which are known to be computationally costly. But, another source of computational complexity is related to how the individual types of information are quantified. In one case a data integration problem is demonstrated where the goal is to determine the existence of buried channels in Denmark, based on multiple sources of geo-information. Due to one type of information being too informative (and hence conflicting), this leads to a difficult sampling problems with unrealistic uncertainty. Resolving this conflict prior to data integration, leads to an easy data integration problem, with no biases. In another case it is demonstrated how imperfections in the description of the geophysical forward model (related to solving the wave-equation) can lead to a difficult data integration problem, with severe bias in the results. If the modeling error is accounted for, the data integration problems becomes relatively easy, with no apparent biases. Both examples demonstrate that biased information can have a dramatic effect on the computational efficiency solving a data integration problem and lead to biased results, and under-estimation of uncertainty. However, in both examples, one can also analyze the performance of the sampling methods used to solve the data integration problem to indicate the existence of biased information. This can be used actively to avoid biases in the available information and subsequently in the final uncertainty evaluation.

Reinforcement learning in computer vision

NASA Astrophysics Data System (ADS)

Bernstein, A. V.; Burnaev, E. V.

2018-04-01

Nowadays, machine learning has become one of the basic technologies used in solving various computer vision tasks such as feature detection, image segmentation, object recognition and tracking. In many applications, various complex systems such as robots are equipped with visual sensors from which they learn state of surrounding environment by solving corresponding computer vision tasks. Solutions of these tasks are used for making decisions about possible future actions. It is not surprising that when solving computer vision tasks we should take into account special aspects of their subsequent application in model-based predictive control. Reinforcement learning is one of modern machine learning technologies in which learning is carried out through interaction with the environment. In recent years, Reinforcement learning has been used both for solving such applied tasks as processing and analysis of visual information, and for solving specific computer vision problems such as filtering, extracting image features, localizing objects in scenes, and many others. The paper describes shortly the Reinforcement learning technology and its use for solving computer vision problems.

Influence of the large-small split effect on strategy choice in complex subtraction.

PubMed

Xiang, Yan Hui; Wu, Hao; Shang, Rui Hong; Chao, Xiaomei; Ren, Ting Ting; Zheng, Li Ling; Mo, Lei

2018-04-01

Two main theories have been used to explain the arithmetic split effect: decision-making process theory and strategy choice theory. Using the inequality paradigm, previous studies have confirmed that individuals tend to adopt a plausibility-checking strategy and a whole-calculation strategy to solve large and small split problems in complex addition arithmetic, respectively. This supports strategy choice theory, but it is unknown whether this theory also explains performance in solving different split problems in complex subtraction arithmetic. This study used small, intermediate and large split sizes, with each split condition being further divided into problems requiring and not requiring borrowing. The reaction times (RTs) for large and intermediate splits were significantly shorter than those for small splits, while accuracy was significantly higher for large and middle splits than for small splits, reflecting no speed-accuracy trade-off. Further, RTs and accuracy differed significantly between the borrow and no-borrow conditions only for small splits. This study indicates that strategy choice theory is suitable to explain the split effect in complex subtraction arithmetic. That is, individuals tend to choose the plausibility-checking strategy or the whole-calculation strategy according to the split size. © 2016 International Union of Psychological Science.

Error and Complexity Analysis for a Collocation-Grid-Projection Plus Precorrected-FFT Algorithm for Solving Potential Integral Equations with LaPlace or Helmholtz Kernels

NASA Technical Reports Server (NTRS)

Phillips, J. R.

1996-01-01

In this paper we derive error bounds for a collocation-grid-projection scheme tuned for use in multilevel methods for solving boundary-element discretizations of potential integral equations. The grid-projection scheme is then combined with a precorrected FFT style multilevel method for solving potential integral equations with 1/r and e(sup ikr)/r kernels. A complexity analysis of this combined method is given to show that for homogeneous problems, the method is order n natural log n nearly independent of the kernel. In addition, it is shown analytically and experimentally that for an inhomogeneity generated by a very finely discretized surface, the combined method slows to order n(sup 4/3). Finally, examples are given to show that the collocation-based grid-projection plus precorrected-FFT scheme is competitive with fast-multipole algorithms when considering realistic problems and 1/r kernels, but can be used over a range of spatial frequencies with only a small performance penalty.

Providing Formative Assessment to Students Solving Multipath Engineering Problems with Complex Arrangements of Interacting Parts: An Intelligent Tutor Approach

ERIC Educational Resources Information Center

Steif, Paul S.; Fu, Luoting; Kara, Levent Burak

2016-01-01

Problems faced by engineering students involve multiple pathways to solution. Students rarely receive effective formative feedback on handwritten homework. This paper examines the potential for computer-based formative assessment of student solutions to multipath engineering problems. In particular, an intelligent tutor approach is adopted and…

P1 Nonconforming Finite Element Method for the Solution of Radiation Transport Problems

NASA Technical Reports Server (NTRS)

Kang, Kab S.

2002-01-01

The simulation of radiation transport in the optically thick flux-limited diffusion regime has been identified as one of the most time-consuming tasks within large simulation codes. Due to multimaterial complex geometry, the radiation transport system must often be solved on unstructured grids. In this paper, we investigate the behavior and the benefits of the unstructured P(sub 1) nonconforming finite element method, which has proven to be flexible and effective on related transport problems, in solving unsteady implicit nonlinear radiation diffusion problems using Newton and Picard linearization methods. Key words. nonconforrning finite elements, radiation transport, inexact Newton linearization, multigrid preconditioning

Beyond rules: The next generation of expert systems

NASA Technical Reports Server (NTRS)

Ferguson, Jay C.; Wagner, Robert E.

1987-01-01

The PARAGON Representation, Management, and Manipulation system is introduced. The concepts of knowledge representation, knowledge management, and knowledge manipulation are combined in a comprehensive system for solving real world problems requiring high levels of expertise in a real time environment. In most applications the complexity of the problem and the representation used to describe the domain knowledge tend to obscure the information from which solutions are derived. This inhibits the acquisition of domain knowledge verification/validation, places severe constraints on the ability to extend and maintain a knowledge base while making generic problem solving strategies difficult to develop. A unique hybrid system was developed to overcome these traditional limitations.

The Diffusion Simulator - Teaching Geomorphic and Geologic Problems Visually.

ERIC Educational Resources Information Center

Gilbert, R.

1979-01-01

Describes a simple hydraulic simulator based on more complex models long used by engineers to develop approximate solutions. It allows students to visualize non-steady transfer, to apply a model to solve a problem, and to compare experimentally simulated information with calculated values. (Author/MA)

Leveraging Collaborative, Thematic Problem-Based Learning to Integrate Curricula

ERIC Educational Resources Information Center

Sroufe, Robert; Ramos, Diane P.

2015-01-01

This study chronicles learning from faculty who designed and delivered collaborative, problem-based learning courses that anchor a one-year MBA emphasizing sustainability. While cultivating the application of learning across the curriculum, the authors engaged MBA students in solving complex, real-world sustainability challenges using a…

Alternative Architectures for Distributed Cooperative Problem-Solving in the National Airspace System

NASA Technical Reports Server (NTRS)

Smith, Phillip J.; Billings, Charles; McCoy, C. Elaine; Orasanu, Judith

1999-01-01

The air traffic management system in the United States is an example of a distributed problem solving system. It has elements of both cooperative and competitive problem-solving. This system includes complex organizations such as Airline Operations Centers (AOCs), the FAA Air Traffic Control Systems Command Center (ATCSCC), and traffic management units (TMUs) at enroute centers and TRACONs, all of which have a major focus on strategic decision-making. It also includes individuals concerned more with tactical decisions (such as air traffic controllers and pilots). The architecture for this system has evolved over time to rely heavily on the distribution of tasks and control authority in order to keep cognitive complexity manageable for any one individual operator, and to provide redundancy (both human and technological) to serve as a safety net to catch the slips or mistakes that any one person or entity might make. Currently, major changes are being considered for this architecture, especially with respect to the locus of control, in an effort to improve efficiency and safety. This paper uses a series of case studies to help evaluate some of these changes from the perspective of system complexity, and to point out possible alternative approaches that might be taken to improve system performance. The paper illustrates the need to maintain a clear understanding of what is required to assure a high level of performance when alternative system architectures and decompositions are developed.

Perceptual learning modules in mathematics: enhancing students' pattern recognition, structure extraction, and fluency.

PubMed

Kellman, Philip J; Massey, Christine M; Son, Ji Y

2010-04-01

Learning in educational settings emphasizes declarative and procedural knowledge. Studies of expertise, however, point to other crucial components of learning, especially improvements produced by experience in the extraction of information: perceptual learning (PL). We suggest that such improvements characterize both simple sensory and complex cognitive, even symbolic, tasks through common processes of discovery and selection. We apply these ideas in the form of perceptual learning modules (PLMs) to mathematics learning. We tested three PLMs, each emphasizing different aspects of complex task performance, in middle and high school mathematics. In the MultiRep PLM, practice in matching function information across multiple representations improved students' abilities to generate correct graphs and equations from word problems. In the Algebraic Transformations PLM, practice in seeing equation structure across transformations (but not solving equations) led to dramatic improvements in the speed of equation solving. In the Linear Measurement PLM, interactive trials involving extraction of information about units and lengths produced successful transfer to novel measurement problems and fraction problem solving. Taken together, these results suggest (a) that PL techniques have the potential to address crucial, neglected dimensions of learning, including discovery and fluent processing of relations; (b) PL effects apply even to complex tasks that involve symbolic processing; and (c) appropriately designed PL technology can produce rapid and enduring advances in learning. Copyright © 2009 Cognitive Science Society, Inc.

Knee point search using cascading top-k sorting with minimized time complexity.

PubMed

Wang, Zheng; Tseng, Shian-Shyong

2013-01-01

Anomaly detection systems and many other applications are frequently confronted with the problem of finding the largest knee point in the sorted curve for a set of unsorted points. This paper proposes an efficient knee point search algorithm with minimized time complexity using the cascading top-k sorting when a priori probability distribution of the knee point is known. First, a top-k sort algorithm is proposed based on a quicksort variation. We divide the knee point search problem into multiple steps. And in each step an optimization problem of the selection number k is solved, where the objective function is defined as the expected time cost. Because the expected time cost in one step is dependent on that of the afterwards steps, we simplify the optimization problem by minimizing the maximum expected time cost. The posterior probability of the largest knee point distribution and the other parameters are updated before solving the optimization problem in each step. An example of source detection of DNS DoS flooding attacks is provided to illustrate the applications of the proposed algorithm.

Algorithms and programs complex for solving inverse problems of artificial Earth satellite dynamics with using parallel computation. (Russian Title: Программно-математическое обеспечение для решения обратных задач динамики ИСЗ с использованием параллельных вычислений )

NASA Astrophysics Data System (ADS)

Chuvashov, I. N.

2011-07-01

In this paper complex of algorithms and programs for solving inverse problems of artificial earth satellite dynamics is described. Complex has been intended for satellite orbit improvement, calculation of motion model parameters and etc. Programs complex has been worked up for cluster "Skiff Cyberia". Results of numerical experiments obtained by using new complex in common the program "Numerical model of the system artificial satellites motion" is presented in this paper.

Peculiarities of solving the problems of modern logistics in high-rise construction and industrial production

NASA Astrophysics Data System (ADS)

Rubtsov, Anatoliy E.; Ushakova, Elena V.; Chirkova, Tamara V.

2018-03-01

Basing on the analysis of the enterprise (construction organization) structure and infrastructure of the entire logistics system in which this enterprise (construction organization) operates, this article proposes an approach to solve the problems of structural optimization and a set of calculation tasks, based on customer orders as well as on the required levels of insurance stocks, transit stocks and other types of stocks in the distribution network, modes of operation of the in-company transport and storage complex and a number of other factors.

The Benefit of Being Naïve and Knowing It: The Unfavourable Impact of Perceived Context Familiarity on Learning in Complex Problem Solving Tasks

ERIC Educational Resources Information Center

Beckmann, Jens F.; Goode, Natassia

2014-01-01

Previous research has found that embedding a problem into a familiar context does not necessarily confer an advantage over a novel context in the acquisition of new knowledge about a complex, dynamic system. In fact, it has been shown that a semantically familiar context can be detrimental to knowledge acquisition. This has been described as the…

An Enhanced Memetic Algorithm for Single-Objective Bilevel Optimization Problems.

PubMed

Islam, Md Monjurul; Singh, Hemant Kumar; Ray, Tapabrata; Sinha, Ankur

2017-01-01

Bilevel optimization, as the name reflects, deals with optimization at two interconnected hierarchical levels. The aim is to identify the optimum of an upper-level  leader problem, subject to the optimality of a lower-level follower problem. Several problems from the domain of engineering, logistics, economics, and transportation have an inherent nested structure which requires them to be modeled as bilevel optimization problems. Increasing size and complexity of such problems has prompted active theoretical and practical interest in the design of efficient algorithms for bilevel optimization. Given the nested nature of bilevel problems, the computational effort (number of function evaluations) required to solve them is often quite high. In this article, we explore the use of a Memetic Algorithm (MA) to solve bilevel optimization problems. While MAs have been quite successful in solving single-level optimization problems, there have been relatively few studies exploring their potential for solving bilevel optimization problems. MAs essentially attempt to combine advantages of global and local search strategies to identify optimum solutions with low computational cost (function evaluations). The approach introduced in this article is a nested Bilevel Memetic Algorithm (BLMA). At both upper and lower levels, either a global or a local search method is used during different phases of the search. The performance of BLMA is presented on twenty-five standard test problems and two real-life applications. The results are compared with other established algorithms to demonstrate the efficacy of the proposed approach.

Metaphors we think with: the role of metaphor in reasoning.

PubMed

Thibodeau, Paul H; Boroditsky, Lera

2011-02-23

The way we talk about complex and abstract ideas is suffused with metaphor. In five experiments, we explore how these metaphors influence the way that we reason about complex issues and forage for further information about them. We find that even the subtlest instantiation of a metaphor (via a single word) can have a powerful influence over how people attempt to solve social problems like crime and how they gather information to make "well-informed" decisions. Interestingly, we find that the influence of the metaphorical framing effect is covert: people do not recognize metaphors as influential in their decisions; instead they point to more "substantive" (often numerical) information as the motivation for their problem-solving decision. Metaphors in language appear to instantiate frame-consistent knowledge structures and invite structurally consistent inferences. Far from being mere rhetorical flourishes, metaphors have profound influences on how we conceptualize and act with respect to important societal issues. We find that exposure to even a single metaphor can induce substantial differences in opinion about how to solve social problems: differences that are larger, for example, than pre-existing differences in opinion between Democrats and Republicans.

The social essentials of learning: an experimental investigation of collaborative problem solving and knowledge construction in mathematics classrooms in Australia and China

NASA Astrophysics Data System (ADS)

Chan, Man Ching Esther; Clarke, David; Cao, Yiming

2018-03-01

Interactive problem solving and learning are priorities in contemporary education, but these complex processes have proved difficult to research. This project addresses the question "How do we optimise social interaction for the promotion of learning in a mathematics classroom?" Employing the logic of multi-theoretic research design, this project uses the newly built Science of Learning Research Classroom (ARC-SR120300015) at The University of Melbourne and equivalent facilities in China to investigate classroom learning and social interactions, focusing on collaborative small group problem solving as a way to make the social aspects of learning visible. In Australia and China, intact classes of local year 7 students with their usual teacher will be brought into the research classroom facilities with built-in video cameras and audio recording equipment to participate in purposefully designed activities in mathematics. The students will undertake a sequence of tasks in the social units of individual, pair, small group (typically four students) and whole class. The conditions for student collaborative problem solving and learning will be manipulated so that student and teacher contributions to that learning process can be distinguished. Parallel and comparative analyses will identify culture-specific interactive patterns and provide the basis for hypotheses about the learning characteristics underlying collaborative problem solving performance documented in the research classrooms in each country. The ultimate goals of the project are to generate, develop and test more sophisticated hypotheses for the optimisation of social interaction in the mathematics classroom in the interest of improving learning and, particularly, student collaborative problem solving.

The contribution of general cognitive abilities and number abilities to different aspects of mathematics in children.

PubMed

Träff, Ulf

2013-10-01

This study examined the relative contributions of general cognitive abilities and number abilities to word problem solving, calculation, and arithmetic fact retrieval in a sample of 134 children aged 10 to 13 years. The following tasks were administered: listening span, visual matrix span, verbal fluency, color naming, Raven's Progressive Matrices, enumeration, number line estimation, and digit comparison. Hierarchical multiple regressions demonstrated that number abilities provided an independent contribution to fact retrieval and word problem solving. General cognitive abilities contributed to problem solving and calculation. All three number tasks accounted for a similar amount of variance in fact retrieval, whereas only the number line estimation task contributed unique variance in word problem solving. Verbal fluency and Raven's matrices accounted for an equal amount of variance in problem solving and calculation. The current findings demonstrate, in accordance with Fuchs and colleagues' developmental model of mathematical learning (Developmental Psychology, 2010, Vol. 46, pp. 1731-1746), that both number abilities and general cognitive abilities underlie 10- to 13-year-olds' proficiency in problem solving, whereas only number abilities underlie arithmetic fact retrieval. Thus, the amount and type of cognitive contribution to arithmetic proficiency varies between the different aspects of arithmetic. Furthermore, how closely linked a specific aspect of arithmetic is to the whole number representation systems is not the only factor determining the amount and type of cognitive contribution in 10- to 13-year-olds. In addition, the mathematical complexity of the task appears to influence the amount and type of cognitive support. Copyright © 2013 Elsevier Inc. All rights reserved.

Associating optical measurements and estimating orbits of geocentric objects with a Genetic Algorithm: performance limitations.

NASA Astrophysics Data System (ADS)

Zittersteijn, Michiel; Schildknecht, Thomas; Vananti, Alessandro; Dolado Perez, Juan Carlos; Martinot, Vincent

2016-07-01

Currently several thousands of objects are being tracked in the MEO and GEO regions through optical means. With the advent of improved sensors and a heightened interest in the problem of space debris, it is expected that the number of tracked objects will grow by an order of magnitude in the near future. This research aims to provide a method that can treat the correlation and orbit determination problems simultaneously, and is able to efficiently process large data sets with minimal manual intervention. This problem is also known as the Multiple Target Tracking (MTT) problem. The complexity of the MTT problem is defined by its dimension S. Current research tends to focus on the S = 2 MTT problem. The reason for this is that for S = 2 the problem has a P-complexity. However, with S = 2 the decision to associate a set of observations is based on the minimum amount of information, in ambiguous situations (e.g. satellite clusters) this will lead to incorrect associations. The S > 2 MTT problem is an NP-hard combinatorial optimization problem. In previous work an Elitist Genetic Algorithm (EGA) was proposed as a method to approximately solve this problem. It was shown that the EGA is able to find a good approximate solution with a polynomial time complexity. The EGA relies on solving the Lambert problem in order to perform the necessary orbit determinations. This means that the algorithm is restricted to orbits that are described by Keplerian motion. The work presented in this paper focuses on the impact that this restriction has on the algorithm performance.

Cognitive development in introductory physics: A research-based approach to curriculum reform

NASA Astrophysics Data System (ADS)

Teodorescu, Raluca Elena

This project describes the research on a classification of physics problems in the context of introductory physics courses. This classification, called the Taxonomy of Introductory Physics Problems (TIPP), relates physics problems to the cognitive processes required to solve them. TIPP was created for designing and clarifying educational objectives, for developing assessments that can evaluate individual component processes of the problem-solving process, and for guiding curriculum design in introductory physics courses, specifically within the context of a "thinking-skills" curriculum. TIPP relies on the following resources: (1) cognitive research findings adopted by physics education research, (2) expert-novice research discoveries acknowledged by physics education research, (3) an educational psychology taxonomy for educational objectives, and (4) various collections of physics problems created by physics education researchers or developed by textbook authors. TIPP was used in the years 2006--2008 to reform the first semester of the introductory algebra-based physics course (called Phys 11) at The George Washington University. The reform sought to transform our curriculum into a "thinking-skills" curriculum that trades "breadth for depth" by focusing on fewer topics while targeting the students' cognitive development. We employed existing research on the physics problem-solving expert-novice behavior, cognitive science and behavioral science findings, and educational psychology recommendations. Our pedagogy relies on didactic constructs such as the GW-ACCESS problem-solving protocol, learning progressions and concept maps that we have developed and implemented in our introductory physics course. These tools were designed based on TIPP. Their purpose is: (1) to help students build local and global coherent knowledge structures, (2) to develop more context-independent problem-solving abilities, (3) to gain confidence in problem solving, and (4) to establish connections between everyday phenomena and underlying physics concepts. We organize traditional and research-based physics problems such that students experience a gradual increase in complexity related to problem context, problem features and cognitive processes needed to solve the problem. The instructional environment that we designed allows for explicit monitoring, control and measurement of the cognitive processes exercised during the instruction period. It is easily adaptable to any kind of curriculum and can be readily adjusted throughout the semester. To assess the development of students' problem-solving abilities, we created rubrics that measure specific aspects of the thinking involved in physics problem solving. The Colorado Learning Attitudes about Science Survey (CLASS) was administered pre- and post-instruction to determine students' shift in dispositions towards learning physics. The Force Concept Inventory (FCI) was administered pre- and post-instruction to determine students' level of conceptual understanding. The results feature improvements in students' problem-solving abilities and in their attitudes towards learning physics.

An optimization-based approach for solving a time-harmonic multiphysical wave problem with higher-order schemes

NASA Astrophysics Data System (ADS)

Mönkölä, Sanna

2013-06-01

This study considers developing numerical solution techniques for the computer simulations of time-harmonic fluid-structure interaction between acoustic and elastic waves. The focus is on the efficiency of an iterative solution method based on a controllability approach and spectral elements. We concentrate on the model, in which the acoustic waves in the fluid domain are modeled by using the velocity potential and the elastic waves in the structure domain are modeled by using displacement. Traditionally, the complex-valued time-harmonic equations are used for solving the time-harmonic problems. Instead of that, we focus on finding periodic solutions without solving the time-harmonic problems directly. The time-dependent equations can be simulated with respect to time until a time-harmonic solution is reached, but the approach suffers from poor convergence. To overcome this challenge, we follow the approach first suggested and developed for the acoustic wave equations by Bristeau, Glowinski, and Périaux. Thus, we accelerate the convergence rate by employing a controllability method. The problem is formulated as a least-squares optimization problem, which is solved with the conjugate gradient (CG) algorithm. Computation of the gradient of the functional is done directly for the discretized problem. A graph-based multigrid method is used for preconditioning the CG algorithm.

Enhanced algorithms for stochastic programming

DOE Office of Scientific and Technical Information (OSTI.GOV)

Krishna, Alamuru S.

1993-09-01

In this dissertation, we present some of the recent advances made in solving two-stage stochastic linear programming problems of large size and complexity. Decomposition and sampling are two fundamental components of techniques to solve stochastic optimization problems. We describe improvements to the current techniques in both these areas. We studied different ways of using importance sampling techniques in the context of Stochastic programming, by varying the choice of approximation functions used in this method. We have concluded that approximating the recourse function by a computationally inexpensive piecewise-linear function is highly efficient. This reduced the problem from finding the mean ofmore » a computationally expensive functions to finding that of a computationally inexpensive function. Then we implemented various variance reduction techniques to estimate the mean of a piecewise-linear function. This method achieved similar variance reductions in orders of magnitude less time than, when we directly applied variance-reduction techniques directly on the given problem. In solving a stochastic linear program, the expected value problem is usually solved before a stochastic solution and also to speed-up the algorithm by making use of the information obtained from the solution of the expected value problem. We have devised a new decomposition scheme to improve the convergence of this algorithm.« less

Performance evaluation of different types of particle representation procedures of Particle Swarm Optimization in Job-shop Scheduling Problems

NASA Astrophysics Data System (ADS)

Izah Anuar, Nurul; Saptari, Adi

2016-02-01

This paper addresses the types of particle representation (encoding) procedures in a population-based stochastic optimization technique in solving scheduling problems known in the job-shop manufacturing environment. It intends to evaluate and compare the performance of different particle representation procedures in Particle Swarm Optimization (PSO) in the case of solving Job-shop Scheduling Problems (JSP). Particle representation procedures refer to the mapping between the particle position in PSO and the scheduling solution in JSP. It is an important step to be carried out so that each particle in PSO can represent a schedule in JSP. Three procedures such as Operation and Particle Position Sequence (OPPS), random keys representation and random-key encoding scheme are used in this study. These procedures have been tested on FT06 and FT10 benchmark problems available in the OR-Library, where the objective function is to minimize the makespan by the use of MATLAB software. Based on the experimental results, it is discovered that OPPS gives the best performance in solving both benchmark problems. The contribution of this paper is the fact that it demonstrates to the practitioners involved in complex scheduling problems that different particle representation procedures can have significant effects on the performance of PSO in solving JSP.

Optimal Planning and Problem-Solving

NASA Technical Reports Server (NTRS)

Clemet, Bradley; Schaffer, Steven; Rabideau, Gregg

2008-01-01

CTAEMS MDP Optimal Planner is a problem-solving software designed to command a single spacecraft/rover, or a team of spacecraft/rovers, to perform the best action possible at all times according to an abstract model of the spacecraft/rover and its environment. It also may be useful in solving logistical problems encountered in commercial applications such as shipping and manufacturing. The planner reasons around uncertainty according to specified probabilities of outcomes using a plan hierarchy to avoid exploring certain kinds of suboptimal actions. Also, planned actions are calculated as the state-action space is expanded, rather than afterward, to reduce by an order of magnitude the processing time and memory used. The software solves planning problems with actions that can execute concurrently, that have uncertain duration and quality, and that have functional dependencies on others that affect quality. These problems are modeled in a hierarchical planning language called C_TAEMS, a derivative of the TAEMS language for specifying domains for the DARPA Coordinators program. In realistic environments, actions often have uncertain outcomes and can have complex relationships with other tasks. The planner approaches problems by considering all possible actions that may be taken from any state reachable from a given, initial state, and from within the constraints of a given task hierarchy that specifies what tasks may be performed by which team member.

Computer-aided programming for message-passing system; Problems and a solution

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wu, M.Y.; Gajski, D.D.

1989-12-01

As the number of processors and the complexity of problems to be solved increase, programming multiprocessing systems becomes more difficult and error-prone. Program development tools are necessary since programmers are not able to develop complex parallel programs efficiently. Parallel models of computation, parallelization problems, and tools for computer-aided programming (CAP) are discussed. As an example, a CAP tool that performs scheduling and inserts communication primitives automatically is described. It also generates the performance estimates and other program quality measures to help programmers in improving their algorithms and programs.

The Daily Operational Brief: Fostering Daily Readiness, Care Coordination, and Problem-Solving Accountability in a Large Pediatric Health Care System.

PubMed

Donnelly, Lane F; Basta, Kathryne C; Dykes, Anne M; Zhang, Wei; Shook, Joan E

2018-01-01

At a pediatric health system, the Daily Operational Brief (DOB) was updated in 2015 after three years of operation. Quality and safety metrics, the patient volume and staffing assessment, and the readiness assessment are all presented. In addition, in the problem-solving accountability system, problematic issues are categorized as Quick Hits or Complex Issues. Walk-the-Wall, a biweekly meeting attended by hospital senior administrative leadership and quality and safety leaders, is conducted to chart current progress on Complex Issues. The DOB provides a daily standardized approach to evaluate readiness to provide care to current patients and improvement in the care to be provided for future patients. Copyright © 2017 The Joint Commission. Published by Elsevier Inc. All rights reserved.

Comparison of an algebraic multigrid algorithm to two iterative solvers used for modeling ground water flow and transport

USGS Publications Warehouse

Detwiler, R.L.; Mehl, S.; Rajaram, H.; Cheung, W.W.

2002-01-01

Numerical solution of large-scale ground water flow and transport problems is often constrained by the convergence behavior of the iterative solvers used to solve the resulting systems of equations. We demonstrate the ability of an algebraic multigrid algorithm (AMG) to efficiently solve the large, sparse systems of equations that result from computational models of ground water flow and transport in large and complex domains. Unlike geometric multigrid methods, this algorithm is applicable to problems in complex flow geometries, such as those encountered in pore-scale modeling of two-phase flow and transport. We integrated AMG into MODFLOW 2000 to compare two- and three-dimensional flow simulations using AMG to simulations using PCG2, a preconditioned conjugate gradient solver that uses the modified incomplete Cholesky preconditioner and is included with MODFLOW 2000. CPU times required for convergence with AMG were up to 140 times faster than those for PCG2. The cost of this increased speed was up to a nine-fold increase in required random access memory (RAM) for the three-dimensional problems and up to a four-fold increase in required RAM for the two-dimensional problems. We also compared two-dimensional numerical simulations of steady-state transport using AMG and the generalized minimum residual method with an incomplete LU-decomposition preconditioner. For these transport simulations, AMG yielded increased speeds of up to 17 times with only a 20% increase in required RAM. The ability of AMG to solve flow and transport problems in large, complex flow systems and its ready availability make it an ideal solver for use in both field-scale and pore-scale modeling.

Learning to See the (W)holes

ERIC Educational Resources Information Center

Burns, Barbara A.; Jordan, Thomas M.

2006-01-01

Business managers are faced with complex decisions involving a wide range of issues--technical, social, environmental, and financial--and their interaction. Our education system focuses heavily on presenting structured problems and teaching students to apply a set of tools or methods to solve these problems. Yet the most difficult thing to teach…

Using the DPSIR Framework to Develop a Conceptual Model: Technical Support Document

EPA Science Inventory

Modern problems (e.g., pollution, urban sprawl, environmental equity) are complex and often transcend spatial and temporal scales. Systems thinking is an approach to problem solving that is based on the belief that the component parts of a system are best understood in the contex...

JPRS Report, Soviet Union, EKO: Economics & Organization of Industrial Production.

DTIC Science & Technology

1988-03-28

us to expect a quick solution to the problem. Therefore it would be expedient to recall how they solved a similar problem with soil protection technology...on millions of hectares they introduced soil protection tech- nology and industry assimilated a complex of machines for carrying it out. The land

Outdoor Recreation Management

ERIC Educational Resources Information Center

Jubenville, Alan

The complex problems facing the manager of an outdoor recreation area are outlined and discussed. Eighteen chapters cover the following primary concerns of the manager of such a facility: (1) an overview of the management process; (2) the basic outdoor recreation management model; (3) the problem-solving process; (4) involvement of the public in…

Collaboration in an Era of Change: New Forms of Community Problem-Solving

ERIC Educational Resources Information Center

Ramaley, Judith A.

2016-01-01

Campuses are developing new ways to respond to complex social, cultural, economic and environmental problems by adapting their educational approaches and their scholarship to address a changing world order. At the same time, government agencies, nonprofit organizations and businesses are embracing collaborative approaches to community…

Moderator’s comments

Treesearch

Neil R. Honeycutt

1995-01-01

The urban and wildland interface (mix) problem exists in many communities in the United States. To effectively deal with these complex issues, cooperative approaches should be used to solve regional problems. This panel discussed the unique programs currently at work in Alameda and Contra Costa Counties in northern California. These programs were designed after the...

On Evaluating Human Problem Solving of Computationally Hard Problems

ERIC Educational Resources Information Center

Carruthers, Sarah; Stege, Ulrike

2013-01-01

This article is concerned with how computer science, and more exactly computational complexity theory, can inform cognitive science. In particular, we suggest factors to be taken into account when investigating how people deal with computational hardness. This discussion will address the two upper levels of Marr's Level Theory: the computational…

Data Science in Educational Assessment

ERIC Educational Resources Information Center

Gibson, David C.; Webb, Mary E.

2015-01-01

This article is the second of two articles in this special issue that were developed following discussions of the Assessment Working Group at EDUsummIT 2013. The article extends the analysis of assessments of collaborative problem solving (CPS) to examine the significance of the data concerning this complex assessment problem and then for…

Mexican Hat Wavelet Kernel ELM for Multiclass Classification.

PubMed

Wang, Jie; Song, Yi-Fan; Ma, Tian-Lei

2017-01-01

Kernel extreme learning machine (KELM) is a novel feedforward neural network, which is widely used in classification problems. To some extent, it solves the existing problems of the invalid nodes and the large computational complexity in ELM. However, the traditional KELM classifier usually has a low test accuracy when it faces multiclass classification problems. In order to solve the above problem, a new classifier, Mexican Hat wavelet KELM classifier, is proposed in this paper. The proposed classifier successfully improves the training accuracy and reduces the training time in the multiclass classification problems. Moreover, the validity of the Mexican Hat wavelet as a kernel function of ELM is rigorously proved. Experimental results on different data sets show that the performance of the proposed classifier is significantly superior to the compared classifiers.

A Parallel Biological Optimization Algorithm to Solve the Unbalanced Assignment Problem Based on DNA Molecular Computing

PubMed Central

Wang, Zhaocai; Pu, Jun; Cao, Liling; Tan, Jian

2015-01-01

The unbalanced assignment problem (UAP) is to optimally resolve the problem of assigning n jobs to m individuals (m < n), such that minimum cost or maximum profit obtained. It is a vitally important Non-deterministic Polynomial (NP) complete problem in operation management and applied mathematics, having numerous real life applications. In this paper, we present a new parallel DNA algorithm for solving the unbalanced assignment problem using DNA molecular operations. We reasonably design flexible-length DNA strands representing different jobs and individuals, take appropriate steps, and get the solutions of the UAP in the proper length range and O(mn) time. We extend the application of DNA molecular operations and simultaneity to simplify the complexity of the computation. PMID:26512650

Designing and Validating Assessments of Complex Thinking in Science

ERIC Educational Resources Information Center

Ryoo, Kihyun; Linn, Marcia C.

2015-01-01

Typical assessment systems often measure isolated ideas rather than the coherent understanding valued in current science classrooms. Such assessments may motivate students to memorize, rather than to use new ideas to solve complex problems. To meet the requirements of the Next Generation Science Standards, instruction needs to emphasize sustained…

Successfully Carrying out Complex Learning-Tasks through Guiding Teams' Qualitative and Quantitative Reasoning

ERIC Educational Resources Information Center

Slof, B.; Erkens, G.; Kirschner, P. A.; Janssen, J.; Jaspers, J. G. M.

2012-01-01

This study investigated whether and how scripting learners' use of representational tools in a computer supported collaborative learning (CSCL)-environment fostered their collaborative performance on a complex business-economics task. Scripting the problem-solving process sequenced and made its phase-related part-task demands explicit, namely…

A scalable plant-resolving radiative transfer model based on optimized GPU ray tracing

USDA-ARS?s Scientific Manuscript database

A new model for radiative transfer in participating media and its application to complex plant canopies is presented. The goal was to be able to efficiently solve complex canopy-scale radiative transfer problems while also representing sub-plant heterogeneity. In the model, individual leaf surfaces ...

A Conceptual Approach to Absolute Value Equations and Inequalities

ERIC Educational Resources Information Center

Ellis, Mark W.; Bryson, Janet L.

2011-01-01

The absolute value learning objective in high school mathematics requires students to solve far more complex absolute value equations and inequalities. When absolute value problems become more complex, students often do not have sufficient conceptual understanding to make any sense of what is happening mathematically. The authors suggest that the…

Solving of the coefficient inverse problems for a nonlinear singularly perturbed reaction-diffusion-advection equation with the final time data

NASA Astrophysics Data System (ADS)

Lukyanenko, D. V.; Shishlenin, M. A.; Volkov, V. T.

2018-01-01

We propose the numerical method for solving coefficient inverse problem for a nonlinear singularly perturbed reaction-diffusion-advection equation with the final time observation data based on the asymptotic analysis and the gradient method. Asymptotic analysis allows us to extract a priory information about interior layer (moving front), which appears in the direct problem, and boundary layers, which appear in the conjugate problem. We describe and implement the method of constructing a dynamically adapted mesh based on this a priory information. The dynamically adapted mesh significantly reduces the complexity of the numerical calculations and improve the numerical stability in comparison with the usual approaches. Numerical example shows the effectiveness of the proposed method.

Primer on clinical acid-base problem solving.

PubMed

Whittier, William L; Rutecki, Gregory W

2004-03-01

Acid-base problem solving has been an integral part of medical practice in recent generations. Diseases discovered in the last 30-plus years, for example, Bartter syndrome and Gitelman syndrome, D-lactic acidosis, and bulimia nervosa, can be diagnosed according to characteristic acid-base findings. Accuracy in acid-base problem solving is a direct result of a reproducible, systematic approach to arterial pH, partial pressure of carbon dioxide, bicarbonate concentration, and electrolytes. The 'Rules of Five' is one tool that enables clinicians to determine the cause of simple and complex disorders, even triple acid-base disturbances, with consistency. In addition, other electrolyte abnormalities that accompany acid-base disorders, such as hypokalemia, can be incorporated into algorithms that complement the Rules and contribute to efficient problem solving in a wide variety of diseases. Recently urine electrolytes have also assisted clinicians in further characterizing select disturbances. Acid-base patterns, in many ways, can serve as a 'common diagnostic pathway' shared by all subspecialties in medicine. From infectious disease (eg, lactic acidemia with highly active antiviral therapy therapy) through endocrinology (eg, Conn's syndrome, high urine chloride alkalemia) to the interface between primary care and psychiatry (eg, bulimia nervosa with multiple potential acid-base disturbances), acid-base problem solving is the key to unlocking otherwise unrelated diagnoses. Inasmuch as the Rules are clinical tools, they are applied throughout this monograph to diverse pathologic conditions typical in contemporary practice.

The archiving of meteor research information

NASA Technical Reports Server (NTRS)

Nechitailenko, V. A.

1987-01-01

The results obtained over the past years under GLOBMET are not reviewed but some of the problems the solution of which will guide further development of meteor investigation and international cooperation in this field for the near term are discussed. The main attention is paid to problems which the meteor community itself can solve, or at least expedite. Most of them are more or less connected with the problem of information archiving. Information archiving deals with methods and techniques of solving two closely connected groups of problems. The first is the analysis of data and information as an integral part of meteor research and deals with the solution of certain methodological problems. The second deals with gathering data and information for the designing of models of the atmosphere and/or meteor complex and its utilization. These problem solutions are discussed.

Applying Squeaky-Wheel Optimization Schedule Airborne Astronomy Observations

NASA Technical Reports Server (NTRS)

Frank, Jeremy; Kuerklue, Elif

2004-01-01

We apply the Squeaky Wheel Optimization (SWO) algorithm to the problem of scheduling astronomy observations for the Stratospheric Observatory for Infrared Astronomy, an airborne observatory. The problem contains complex constraints relating the feasibility of an astronomical observation to the position and time at which the observation begins, telescope elevation limits, special use airspace, and available fuel. Solving the problem requires making discrete choices (e.g. selection and sequencing of observations) and continuous ones (e.g. takeoff time and setting up observations by repositioning the aircraft). The problem also includes optimization criteria such as maximizing observing time while simultaneously minimizing total flight time. Previous approaches to the problem fail to scale when accounting for all constraints. We describe how to customize SWO to solve this problem, and show that it finds better flight plans, often with less computation time, than previous approaches.

Lessons Learned from Crowdsourcing Complex Engineering Tasks.

PubMed

Staffelbach, Matthew; Sempolinski, Peter; Kijewski-Correa, Tracy; Thain, Douglas; Wei, Daniel; Kareem, Ahsan; Madey, Gregory

2015-01-01

Crowdsourcing is the practice of obtaining needed ideas, services, or content by requesting contributions from a large group of people. Amazon Mechanical Turk is a web marketplace for crowdsourcing microtasks, such as answering surveys and image tagging. We explored the limits of crowdsourcing by using Mechanical Turk for a more complicated task: analysis and creation of wind simulations. Our investigation examined the feasibility of using crowdsourcing for complex, highly technical tasks. This was done to determine if the benefits of crowdsourcing could be harnessed to accurately and effectively contribute to solving complex real world engineering problems. Of course, untrained crowds cannot be used as a mere substitute for trained expertise. Rather, we sought to understand how crowd workers can be used as a large pool of labor for a preliminary analysis of complex data. We compared the skill of the anonymous crowd workers from Amazon Mechanical Turk with that of civil engineering graduate students, making a first pass at analyzing wind simulation data. For the first phase, we posted analysis questions to Amazon crowd workers and to two groups of civil engineering graduate students. A second phase of our experiment instructed crowd workers and students to create simulations on our Virtual Wind Tunnel website to solve a more complex task. With a sufficiently comprehensive tutorial and compensation similar to typical crowd-sourcing wages, we were able to enlist crowd workers to effectively complete longer, more complex tasks with competence comparable to that of graduate students with more comprehensive, expert-level knowledge. Furthermore, more complex tasks require increased communication with the workers. As tasks become more complex, the employment relationship begins to become more akin to outsourcing than crowdsourcing. Through this investigation, we were able to stretch and explore the limits of crowdsourcing as a tool for solving complex problems.

Toward a Practical Model of Cognitive/Information Task Analysis and Schema Acquisition for Complex Problem-Solving Situations.

ERIC Educational Resources Information Center

Braune, Rolf; Foshay, Wellesley R.

1983-01-01

The proposed three-step strategy for research on human information processing--concept hierarchy analysis, analysis of example sets to teach relations among concepts, and analysis of problem sets to build a progressively larger schema for the problem space--may lead to practical procedures for instructional design and task analysis. Sixty-four…

Transformations of software design and code may lead to reduced errors

NASA Technical Reports Server (NTRS)

Connelly, E. M.

1983-01-01

The capability of programmers and non-programmers to specify problem solutions by developing example-solutions and also for the programmers by writing computer programs was investigated; each method of specification was accomplished at various levels of problem complexity. The level of difficulty of each problem was reflected by the number of steps needed by the user to develop a solution. Machine processing of the user inputs permitted inferences to be developed about the algorithms required to solve a particular problem. The interactive feedback of processing results led users to a more precise definition of the desired solution. Two participant groups (programmers and bookkeepers/accountants) working with three levels of problem complexity and three levels of processor complexity were used. The experimental task employed required specification of a logic for solution of a Navy task force problem.

Best candidates for cognitive treatment of illness perceptions in chronic low back pain: results of a theory-driven predictor study.

PubMed

Siemonsma, Petra C; Stuvie, Ilse; Roorda, Leo D; Vollebregt, Joke A; Lankhorst, Gustaaf J; Lettinga, Ant T

2011-04-01

The aim of this study was to identify treatment-specific predictors of the effectiveness of a method of evidence-based treatment: cognitive treatment of illness perceptions. This study focuses on what treatment works for whom, whereas most prognostic studies focusing on chronic non-specific low back pain rehabilitation aim to reduce the heterogeneity of the population of patients who are suitable for rehabilitation treatment in general. Three treatment-specific predictors were studied in patients with chronic non-specific low back pain receiving cognitive treatment of illness perceptions: a rational approach to problem-solving, discussion skills and verbal skills. Hierarchical linear regression analysis was used to assess their predictive value. Short-term changes in physical activity, measured with the Patient-Specific Functioning List, were the outcome measure for cognitive treatment of illness perceptions effect. A total of 156 patients with chronic non-specific low back pain participated in the study. Rational problem-solving was found to be a significant predictor for the change in physical activity. Discussion skills and verbal skills were non-significant. Rational problem-solving explained 3.9% of the total variance. The rational problem-solving scale results are encouraging, because chronic non-specific low back pain problems are complex by nature and can be influenced by a variety of factors. A minimum score of 44 points on the rational problem-solving scale may assist clinicians in selecting the most appropriate candidates for cognitive treatment of illness perceptions.

Dynamic programming methods for concurrent design and dynamic allocation of vehicles embedded in a system-of-systems

NASA Astrophysics Data System (ADS)

Nusawardhana

2007-12-01

Recent developments indicate a changing perspective on how systems or vehicles should be designed. Such transition comes from the way decision makers in defense related agencies address complex problems. Complex problems are now often posed in terms of the capabilities desired, rather than in terms of requirements for a single systems. As a result, the way to provide a set of capabilities is through a collection of several individual, independent systems. This collection of individual independent systems is often referred to as a "System of Systems'' (SoS). Because of the independent nature of the constituent systems in an SoS, approaches to design an SoS, and more specifically, approaches to design a new system as a member of an SoS, will likely be different than the traditional design approaches for complex, monolithic (meaning the constituent parts have no ability for independent operation) systems. Because a system of system evolves over time, this simultaneous system design and resource allocation problem should be investigated in a dynamic context. Such dynamic optimization problems are similar to conventional control problems. However, this research considers problems which not only seek optimizing policies but also seek the proper system or vehicle to operate under these policies. This thesis presents a framework and a set of analytical tools to solve a class of SoS problems that involves the simultaneous design of a new system and allocation of the new system along with existing systems. Such a class of problems belongs to the problems of concurrent design and control of a new systems with solutions consisting of both optimal system design and optimal control strategy. Rigorous mathematical arguments show that the proposed framework solves the concurrent design and control problems. Many results exist for dynamic optimization problems of linear systems. In contrary, results on optimal nonlinear dynamic optimization problems are rare. The proposed framework is equipped with the set of analytical tools to solve several cases of nonlinear optimal control problems: continuous- and discrete-time nonlinear problems with applications on both optimal regulation and tracking. These tools are useful when mathematical descriptions of dynamic systems are available. In the absence of such a mathematical model, it is often necessary to derive a solution based on computer simulation. For this case, a set of parameterized decision may constitute a solution. This thesis presents a method to adjust these parameters based on the principle of stochastic approximation simultaneous perturbation using continuous measurements. The set of tools developed here mostly employs the methods of exact dynamic programming. However, due to the complexity of SoS problems, this research also develops suboptimal solution approaches, collectively recognized as approximate dynamic programming solutions, for large scale problems. The thesis presents, explores, and solves problems from an airline industry, in which a new aircraft is to be designed and allocated along with an existing fleet of aircraft. Because the life cycle of an aircraft is on the order of 10 to 20 years, this problem is to be addressed dynamically so that the new aircraft design is the best design for the fleet over a given time horizon.

Stop Talking and Type: Comparing Virtual and Face-to-Face Mentoring in an Epistemic Game

ERIC Educational Resources Information Center

Bagley, E. A.; Shaffer, D. W.

2015-01-01

Research has shown that computer games and other virtual environments can support significant learning gains because they allow young people to explore complex concepts in simulated form. However, in complex problem-solving domains, complex thinking is learned not only by taking action, but also with the aid of mentors who provide guidance in the…

The diminishing criterion model for metacognitive regulation of time investment.

PubMed

Ackerman, Rakefet

2014-06-01

According to the Discrepancy Reduction Model for metacognitive regulation, people invest time in cognitive tasks in a goal-driven manner until their metacognitive judgment, either judgment of learning (JOL) or confidence, meets their preset goal. This stopping rule should lead to judgments above the goal, regardless of invested time. However, in many tasks, time is negatively correlated with JOL and confidence, with low judgments after effortful processing. This pattern has often been explained as stemming from bottom-up fluency effects on the judgments. While accepting this explanation for simple tasks, like memorizing pairs of familiar words, the proposed Diminishing Criterion Model (DCM) challenges this explanation for complex tasks, like problem solving. Under the DCM, people indeed invest effort in a goal-driven manner. However, investing more time leads to increasing compromise on the goal, resulting in negative time-judgment correlations. Experiment 1 exposed that with word-pair memorization, negative correlations are found only with minimal fluency and difficulty variability, whereas in problem solving, they are found consistently. As predicted, manipulations of low incentives (Experiment 2) and time pressure (Experiment 3) in problem solving revealed greater compromise as more time was invested in a problem. Although intermediate confidence ratings rose during the solving process, the result was negative time-confidence correlations (Experiments 3, 4, and 5), and this was not eliminated by the opportunity to respond "don't know" (Experiments 4 and 5). The results suggest that negative time-judgment correlations in complex tasks stem from top-down regulatory processes with a criterion that diminishes with invested time. PsycINFO Database Record (c) 2014 APA, all rights reserved.

Comparing genetic algorithm and particle swarm optimization for solving capacitated vehicle routing problem

NASA Astrophysics Data System (ADS)

Iswari, T.; Asih, A. M. S.

2018-04-01

In the logistics system, transportation plays an important role to connect every element in the supply chain, but it can produces the greatest cost. Therefore, it is important to make the transportation costs as minimum as possible. Reducing the transportation cost can be done in several ways. One of the ways to minimizing the transportation cost is by optimizing the routing of its vehicles. It refers to Vehicle Routing Problem (VRP). The most common type of VRP is Capacitated Vehicle Routing Problem (CVRP). In CVRP, the vehicles have their own capacity and the total demands from the customer should not exceed the capacity of the vehicle. CVRP belongs to the class of NP-hard problems. These NP-hard problems make it more complex to solve such that exact algorithms become highly time-consuming with the increases in problem sizes. Thus, for large-scale problem instances, as typically found in industrial applications, finding an optimal solution is not practicable. Therefore, this paper uses two kinds of metaheuristics approach to solving CVRP. Those are Genetic Algorithm and Particle Swarm Optimization. This paper compares the results of both algorithms and see the performance of each algorithm. The results show that both algorithms perform well in solving CVRP but still needs to be improved. From algorithm testing and numerical example, Genetic Algorithm yields a better solution than Particle Swarm Optimization in total distance travelled.

29 CFR 541.402 - Executive and administrative computer employees.

Code of Federal Regulations, 2010 CFR

2010-07-01

... planning, scheduling, and coordinating activities required to develop systems to solve complex business, scientific or engineering problems of the employer or the employer's customers. Similarly, a senior or lead...

On the adaptive function of children's and adults' false memories.

PubMed

Howe, Mark L; Wilkinson, Samantha; Garner, Sarah R; Ball, Linden J

2016-09-01

Recent research has shown that memory illusions can successfully prime both children's and adults' performance on complex, insight-based problems (compound remote associates tasks or CRATs). The current research aimed to clarify the locus of these priming effects. Like before, Deese-Roediger-McDermott (DRM) lists were selected to prime subsequent CRATs such that the critical lures were also the solution words to a subset of the CRATs participants attempted to solve. Unique to the present research, recognition memory tests were used and participants were either primed during the list study phase, during the memory test phase, or both. Across two experiments, primed problems were solved more frequently and significantly faster than unprimed problems. Moreover, when participants were primed during the list study phase, subsequent solution times and rates were considerably superior to those produced by those participants who were simply primed at test. Together, these are the first results to show that false-memory priming during encoding facilitates problem-solving in both children and adults.

An Effective Hybrid Evolutionary Algorithm for Solving the Numerical Optimization Problems

NASA Astrophysics Data System (ADS)

Qian, Xiaohong; Wang, Xumei; Su, Yonghong; He, Liu

2018-04-01

There are many different algorithms for solving complex optimization problems. Each algorithm has been applied successfully in solving some optimization problems, but not efficiently in other problems. In this paper the Cauchy mutation and the multi-parent hybrid operator are combined to propose a hybrid evolutionary algorithm based on the communication (Mixed Evolutionary Algorithm based on Communication), hereinafter referred to as CMEA. The basic idea of the CMEA algorithm is that the initial population is divided into two subpopulations. Cauchy mutation operators and multiple paternal crossover operators are used to perform two subpopulations parallelly to evolve recursively until the downtime conditions are met. While subpopulation is reorganized, the individual is exchanged together with information. The algorithm flow is given and the performance of the algorithm is compared using a number of standard test functions. Simulation results have shown that this algorithm converges significantly faster than FEP (Fast Evolutionary Programming) algorithm, has good performance in global convergence and stability and is superior to other compared algorithms.

u-w formulation for dynamic problems in large deformation regime solved through an implicit meshfree scheme

NASA Astrophysics Data System (ADS)

Navas, Pedro; Sanavia, Lorenzo; López-Querol, Susana; Yu, Rena C.

2017-12-01

Solving dynamic problems for fluid saturated porous media at large deformation regime is an interesting but complex issue. An implicit time integration scheme is herein developed within the framework of the u-w (solid displacement-relative fluid displacement) formulation for the Biot's equations. In particular, liquid water saturated porous media is considered and the linearization of the linear momentum equations taking into account all the inertia terms for both solid and fluid phases is for the first time presented. The spatial discretization is carried out through a meshfree method, in which the shape functions are based on the principle of local maximum entropy LME. The current methodology is firstly validated with the dynamic consolidation of a soil column and the plastic shear band formulation of a square domain loaded by a rigid footing. The feasibility of this new numerical approach for solving large deformation dynamic problems is finally demonstrated through the application to an embankment problem subjected to an earthquake.

Amoeba-inspired nanoarchitectonic computing implemented using electrical Brownian ratchets.

PubMed

Aono, M; Kasai, S; Kim, S-J; Wakabayashi, M; Miwa, H; Naruse, M

2015-06-12

In this study, we extracted the essential spatiotemporal dynamics that allow an amoeboid organism to solve a computationally demanding problem and adapt to its environment, thereby proposing a nature-inspired nanoarchitectonic computing system, which we implemented using a network of nanowire devices called 'electrical Brownian ratchets (EBRs)'. By utilizing the fluctuations generated from thermal energy in nanowire devices, we used our system to solve the satisfiability problem, which is a highly complex combinatorial problem related to a wide variety of practical applications. We evaluated the dependency of the solution search speed on its exploration parameter, which characterizes the fluctuation intensity of EBRs, using a simulation model of our system called 'AmoebaSAT-Brownian'. We found that AmoebaSAT-Brownian enhanced the solution searching speed dramatically when we imposed some constraints on the fluctuations in its time series and it outperformed a well-known stochastic local search method. These results suggest a new computing paradigm, which may allow high-speed problem solving to be implemented by interacting nanoscale devices with low power consumption.

Making the EZ Choice

NASA Technical Reports Server (NTRS)

2001-01-01

Analytical Mechanics Associates, Inc. (AMA), of Hampton, Virginia, created the EZopt software application through Small Business Innovation Research (SBIR) funding from NASA's Langley Research Center. The new software is a user-friendly tool kit that provides quick and logical solutions to complex optimal control problems. In its most basic form, EZopt converts process data into math equations and then proceeds to utilize those equations to solve problems within control systems. EZopt successfully proved its advantage when applied to short-term mission planning and onboard flight computer implementation. The technology has also solved multiple real-life engineering problems faced in numerous commercial operations. For instance, mechanical engineers use EZopt to solve control problems with robots, while chemical plants implement the application to overcome situations with batch reactors and temperature control. In the emerging field of commercial aerospace, EZopt is able to optimize trajectories for launch vehicles and perform potential space station- keeping tasks. Furthermore, the software also helps control electromagnetic devices in the automotive industry.

Validation of a High-Order Prefactored Compact Scheme on Nonlinear Flows with Complex Geometries

NASA Technical Reports Server (NTRS)

Hixon, Ray; Mankbadi, Reda R.; Povinelli, L. A. (Technical Monitor)

2000-01-01

Three benchmark problems are solved using a sixth-order prefactored compact scheme employing an explicit 10th-order filter with optimized fourth-order Runge-Kutta time stepping. The problems solved are the following: (1) propagation of sound waves through a transonic nozzle; (2) shock-sound interaction; and (3) single airfoil gust response. In the first two problems, the spatial accuracy of the scheme is tested on a stretched grid, and the effectiveness of boundary conditions is shown. The solution stability and accuracy near a shock discontinuity is shown as well. Also, 1-D nonlinear characteristic boundary conditions will be evaluated. In the third problem, a nonlinear Euler solver will be used that solves the equations in generalized curvilinear coordinates using the chain rule transformation. This work, continuing earlier work on flat-plate cascades and Joukowski airfoils, will focus mainly on the effect of the grid and boundary conditions on the accuracy of the solution. The grids were generated using a commercially available grid generator, GridPro/az3000.

Experiences with explicit finite-difference schemes for complex fluid dynamics problems on STAR-100 and CYBER-203 computers

NASA Technical Reports Server (NTRS)

Kumar, A.; Rudy, D. H.; Drummond, J. P.; Harris, J. E.

1982-01-01

Several two- and three-dimensional external and internal flow problems solved on the STAR-100 and CYBER-203 vector processing computers are described. The flow field was described by the full Navier-Stokes equations which were then solved by explicit finite-difference algorithms. Problem results and computer system requirements are presented. Program organization and data base structure for three-dimensional computer codes which will eliminate or improve on page faulting, are discussed. Storage requirements for three-dimensional codes are reduced by calculating transformation metric data in each step. As a result, in-core grid points were increased in number by 50% to 150,000, with a 10% execution time increase. An assessment of current and future machine requirements shows that even on the CYBER-205 computer only a few problems can be solved realistically. Estimates reveal that the present situation is more storage limited than compute rate limited, but advancements in both storage and speed are essential to realistically calculate three-dimensional flow.

On the adaptive function of children's and adults’ false memories

PubMed Central

Howe, Mark L.; Wilkinson, Samantha; Garner, Sarah R.; Ball, Linden J.

2016-01-01

ABSTRACT Recent research has shown that memory illusions can successfully prime both children's and adults' performance on complex, insight-based problems (compound remote associates tasks or CRATs). The current research aimed to clarify the locus of these priming effects. Like before, Deese–Roediger–McDermott (DRM) lists were selected to prime subsequent CRATs such that the critical lures were also the solution words to a subset of the CRATs participants attempted to solve. Unique to the present research, recognition memory tests were used and participants were either primed during the list study phase, during the memory test phase, or both. Across two experiments, primed problems were solved more frequently and significantly faster than unprimed problems. Moreover, when participants were primed during the list study phase, subsequent solution times and rates were considerably superior to those produced by those participants who were simply primed at test. Together, these are the first results to show that false-memory priming during encoding facilitates problem-solving in both children and adults. PMID:26230151

Studying PubMed usages in the field for complex problem solving: Implications for tool design

PubMed Central

Song, Jean; Tonks, Jennifer Steiner; Meng, Fan; Xuan, Weijian; Ameziane, Rafiqa

2012-01-01

Many recent studies on MEDLINE-based information seeking have shed light on scientists’ behaviors and associated tool innovations that may improve efficiency and effectiveness. Few if any studies, however, examine scientists’ problem-solving uses of PubMed in actual contexts of work and corresponding needs for better tool support. Addressing this gap, we conducted a field study of novice scientists (14 upper level undergraduate majors in molecular biology) as they engaged in a problem solving activity with PubMed in a laboratory setting. Findings reveal many common stages and patterns of information seeking across users as well as variations, especially variations in cognitive search styles. Based on findings, we suggest tool improvements that both confirm and qualify many results found in other recent studies. Our findings highlight the need to use results from context-rich studies to inform decisions in tool design about when to offer improved features to users. PMID:24376375

Modified artificial bee colony algorithm for reactive power optimization

NASA Astrophysics Data System (ADS)

Sulaiman, Noorazliza; Mohamad-Saleh, Junita; Abro, Abdul Ghani

2015-05-01

Bio-inspired algorithms (BIAs) implemented to solve various optimization problems have shown promising results which are very important in this severely complex real-world. Artificial Bee Colony (ABC) algorithm, a kind of BIAs has demonstrated tremendous results as compared to other optimization algorithms. This paper presents a new modified ABC algorithm referred to as JA-ABC3 with the aim to enhance convergence speed and avoid premature convergence. The proposed algorithm has been simulated on ten commonly used benchmarks functions. Its performance has also been compared with other existing ABC variants. To justify its robust applicability, the proposed algorithm has been tested to solve Reactive Power Optimization problem. The results have shown that the proposed algorithm has superior performance to other existing ABC variants e.g. GABC, BABC1, BABC2, BsfABC dan IABC in terms of convergence speed. Furthermore, the proposed algorithm has also demonstrated excellence performance in solving Reactive Power Optimization problem.

Engineering Antifragile Systems: A Change In Design Philosophy

NASA Technical Reports Server (NTRS)

Jones, Kennie H.

2014-01-01

While technology has made astounding advances in the last century, problems are confronting the engineering community that must be solved. Cost and schedule of producing large systems are increasing at an unsustainable rate and these systems often do not perform as intended. New systems are required that may not be achieved by current methods. To solve these problems, NASA is working to infuse concepts from Complexity Science into the engineering process. Some of these problems may be solved by a change in design philosophy. Instead of designing systems to meet known requirements that will always lead to fragile systems at some degree, systems should be designed wherever possible to be antifragile: designing cognitive cyberphysical systems that can learn from their experience, adapt to unforeseen events they face in their environment, and grow stronger in the face of adversity. Several examples are presented of on ongoing research efforts to employ this philosophy.

The more the merrier? Increasing group size may be detrimental to decision-making performance in nominal groups.

PubMed

Amir, Ofra; Amir, Dor; Shahar, Yuval; Hart, Yuval; Gal, Kobi

2018-01-01

Demonstrability-the extent to which group members can recognize a correct solution to a problem-has a significant effect on group performance. However, the interplay between group size, demonstrability and performance is not well understood. This paper addresses these gaps by studying the joint effect of two factors-the difficulty of solving a problem and the difficulty of verifying the correctness of a solution-on the ability of groups of varying sizes to converge to correct solutions. Our empirical investigations use problem instances from different computational complexity classes, NP-Complete (NPC) and PSPACE-complete (PSC), that exhibit similar solution difficulty but differ in verification difficulty. Our study focuses on nominal groups to isolate the effect of problem complexity on performance. We show that NPC problems have higher demonstrability than PSC problems: participants were significantly more likely to recognize correct and incorrect solutions for NPC problems than for PSC problems. We further show that increasing the group size can actually decrease group performance for some problems of low demonstrability. We analytically derive the boundary that distinguishes these problems from others for which group performance monotonically improves with group size. These findings increase our understanding of the mechanisms that underlie group problem-solving processes, and can inform the design of systems and processes that would better facilitate collective decision-making.

An investigation of successful and unsuccessful students' problem solving in stoichiometry

NASA Astrophysics Data System (ADS)

Gulacar, Ozcan

In this study, I investigated how successful and unsuccessful students solve stoichiometry problems. I focus on three research questions: (1) To what extent do the difficulties in solving stoichiometry problems stem from poor understanding of pieces (domain-specific knowledge) versus students' inability to link those pieces together (conceptual knowledge)? (2) What are the differences between successful and unsuccessful students in knowledge, ability, and practice? (3) Is there a connection between students' (a) cognitive development levels, (b) formal (proportional) reasoning abilities, (c) working memory capacities, (d) conceptual understanding of particle nature of matter, (e) understanding of the mole concept, and their problem-solving achievement in stoichiometry? In this study, nine successful students and eight unsuccessful students participated. Both successful and unsuccessful students were selected among the students taking a general chemistry course at a mid-western university. The students taking this class were all science, non-chemistry majors. Characteristics of successful and unsuccessful students were determined through tests, audio and videotapes analyses, and subjects' written works. The Berlin Particle Concept Inventory, the Mole Concept Achievement Test, the Test of Logical Thinking, the Digits Backward Test, and the Longeot Test were used to measure students' conceptual understanding of particle nature of matter and mole concept, formal (proportional) reasoning ability, working memory capacity, and cognitive development, respectively. Think-aloud problem-solving protocols were also used to better explore the differences between successful and unsuccessful students' knowledge structures and behaviors during problem solving. Although successful students did not show significantly better performance on doing pieces (domain-specific knowledge) and solving exercises than unsuccessful counterparts did, they appeared to be more successful in linking the pieces (conceptual knowledge) and solving complex problems than the unsuccessful student did. Successful students also appeared to be different in how they approach problems, what strategies they use, and in making fewer algorithmic mistakes when compared to unsuccessful students. Successful students, however, did not seem to be statistically significantly different from the unsuccessful students in terms of quantitatively tested cognitive abilities except formal (proportional) reasoning ability and in the understanding of mole concept.

A centre-free approach for resource allocation with lower bounds

NASA Astrophysics Data System (ADS)

Obando, Germán; Quijano, Nicanor; Rakoto-Ravalontsalama, Naly

2017-09-01

Since complexity and scale of systems are continuously increasing, there is a growing interest in developing distributed algorithms that are capable to address information constraints, specially for solving optimisation and decision-making problems. In this paper, we propose a novel method to solve distributed resource allocation problems that include lower bound constraints. The optimisation process is carried out by a set of agents that use a communication network to coordinate their decisions. Convergence and optimality of the method are guaranteed under some mild assumptions related to the convexity of the problem and the connectivity of the underlying graph. Finally, we compare our approach with other techniques reported in the literature, and we present some engineering applications.

A multidisciplinary approach to solving computer related vision problems.

PubMed

Long, Jennifer; Helland, Magne

2012-09-01

This paper proposes a multidisciplinary approach to solving computer related vision issues by including optometry as a part of the problem-solving team. Computer workstation design is increasing in complexity. There are at least ten different professions who contribute to workstation design or who provide advice to improve worker comfort, safety and efficiency. Optometrists have a role identifying and solving computer-related vision issues and in prescribing appropriate optical devices. However, it is possible that advice given by optometrists to improve visual comfort may conflict with other requirements and demands within the workplace. A multidisciplinary approach has been advocated for solving computer related vision issues. There are opportunities for optometrists to collaborate with ergonomists, who coordinate information from physical, cognitive and organisational disciplines to enact holistic solutions to problems. This paper proposes a model of collaboration and examples of successful partnerships at a number of professional levels including individual relationships between optometrists and ergonomists when they have mutual clients/patients, in undergraduate and postgraduate education and in research. There is also scope for dialogue between optometry and ergonomics professional associations. A multidisciplinary approach offers the opportunity to solve vision related computer issues in a cohesive, rather than fragmented way. Further exploration is required to understand the barriers to these professional relationships. © 2012 The College of Optometrists.

Solving a real-world problem using an evolving heuristically driven schedule builder.

PubMed

Hart, E; Ross, P; Nelson, J

1998-01-01

This work addresses the real-life scheduling problem of a Scottish company that must produce daily schedules for the catching and transportation of large numbers of live chickens. The problem is complex and highly constrained. We show that it can be successfully solved by division into two subproblems and solving each using a separate genetic algorithm (GA). We address the problem of whether this produces locally optimal solutions and how to overcome this. We extend the traditional approach of evolving a "permutation + schedule builder" by concentrating on evolving the schedule builder itself. This results in a unique schedule builder being built for each daily scheduling problem, each individually tailored to deal with the particular features of that problem. This results in a robust, fast, and flexible system that can cope with most of the circumstances imaginable at the factory. We also compare the performance of a GA approach to several other evolutionary methods and show that population-based methods are superior to both hill-climbing and simulated annealing in the quality of solutions produced. Population-based methods also have the distinct advantage of producing multiple, equally fit solutions, which is of particular importance when considering the practical aspects of the problem.

On the complexity of a combined homotopy interior method for convex programming

NASA Astrophysics Data System (ADS)

Yu, Bo; Xu, Qing; Feng, Guochen

2007-03-01

In [G.C. Feng, Z.H. Lin, B. Yu, Existence of an interior pathway to a Karush-Kuhn-Tucker point of a nonconvex programming problem, Nonlinear Anal. 32 (1998) 761-768; G.C. Feng, B. Yu, Combined homotopy interior point method for nonlinear programming problems, in: H. Fujita, M. Yamaguti (Eds.), Advances in Numerical Mathematics, Proceedings of the Second Japan-China Seminar on Numerical Mathematics, Lecture Notes in Numerical and Applied Analysis, vol. 14, Kinokuniya, Tokyo, 1995, pp. 9-16; Z.H. Lin, B. Yu, G.C. Feng, A combined homotopy interior point method for convex programming problem, Appl. Math. Comput. 84 (1997) 193-211.], a combined homotopy was constructed for solving non-convex programming and convex programming with weaker conditions, without assuming the logarithmic barrier function to be strictly convex and the solution set to be bounded. It was proven that a smooth interior path from an interior point of the feasible set to a K-K-T point of the problem exists. This shows that combined homotopy interior point methods can solve the problem that commonly used interior point methods cannot solveE However, so far, there is no result on its complexity, even for linear programming. The main difficulty is that the objective function is not monotonically decreasing on the combined homotopy path. In this paper, by taking a piecewise technique, under commonly used conditions, polynomiality of a combined homotopy interior point method is given for convex nonlinear programming.

Working to Educate Global Citizens and Create Neighborly Communities Locally and Globally: Penn's Partnerships in West Philadelphia as a Democratic Experiment in Progress

ERIC Educational Resources Information Center

Harkavy, Ira; Hartley, Matthew; Hodges, Rita Axelroth; Weeks, Joann

2016-01-01

In the rapidly accelerating global era in which we now live, human beings must solve a vast array of unprecedently complex problems. Given their proclaimed dedication to critical intelligence, and their unique constellation of formidable resources to develop it, institutions of higher education have a unique responsibility to help solve these…

Developing Seventh Grade Students' Understanding of Complex Environmental Problems with Systems Tools and Representations: a Quasi-experimental Study

NASA Astrophysics Data System (ADS)

Doganca Kucuk, Zerrin; Saysel, Ali Kerem

2017-03-01

A systems-based classroom intervention on environmental education was designed for seventh grade students; the results were evaluated to see its impact on the development of systems thinking skills and standard science achievement and whether the systems approach is a more effective way to teach environmental issues that are dynamic and complex. A quasi-experimental methodology was used to compare performances of the participants in various dimensions, including systems thinking skills, competence in dynamic environmental problem solving and success in science achievement tests. The same pre-, post- and delayed tests were used with both the comparison and experimental groups in the same public middle school in Istanbul. Classroom activities designed for the comparison group (N = 20) followed the directives of the Science and Technology Curriculum, while the experimental group (N = 22) covered the same subject matter through activities benefiting from systems tools and representations such as behaviour over time graphs, causal loop diagrams, stock-flow structures and hands-on dynamic modelling. After a one-month systems-based instruction, the experimental group demonstrated significantly better systems thinking and dynamic environmental problem solving skills. Achievement in dynamic problem solving was found to be relatively stable over time. However, standard science achievement did not improve at all. This paper focuses on the quantitative analysis of the results, the weaknesses of the curriculum and educational implications.

Modular thought in the circuit analysis

NASA Astrophysics Data System (ADS)

Wang, Feng

2018-04-01

Applied to solve the problem of modular thought, provides a whole for simplification's method, the complex problems have become of, and the study of circuit is similar to the above problems: the complex connection between components, make the whole circuit topic solution seems to be more complex, and actually components the connection between the have rules to follow, this article mainly tells the story of study on the application of the circuit modular thought. First of all, this paper introduces the definition of two-terminal network and the concept of two-terminal network equivalent conversion, then summarizes the common source resistance hybrid network modular approach, containing controlled source network modular processing method, lists the common module, typical examples analysis.

Promoting Experimental Problem-solving Ability in Sixth-grade Students Through Problem-oriented Teaching of Ecology: Findings of an intervention study in a complex domain

NASA Astrophysics Data System (ADS)

Roesch, Frank; Nerb, Josef; Riess, Werner

2015-03-01

Our study investigated whether problem-oriented designed ecology lessons with phases of direct instruction and of open experimentation foster the development of cross-domain and domain-specific components of experimental problem-solving ability better than conventional lessons in science. We used a paper-and-pencil test to assess students' abilities in a quasi-experimental intervention study utilizing a pretest/posttest control-group design (N = 340; average performing sixth-grade students). The treatment group received lessons on forest ecosystems consistent with the principle of education for sustainable development. This learning environment was expected to help students enhance their ecological knowledge and their theoretical and methodological experimental competencies. Two control groups received either the teachers' usual lessons on forest ecosystems or non-specific lessons on other science topics. We found that the treatment promoted specific components of experimental problem-solving ability (generating epistemic questions, planning two-factorial experiments, and identifying correct experimental controls). However, the observed effects were small, and awareness for aspects of higher ecological experimental validity was not promoted by the treatment.

Some Legal Problems of Satellite Transmission.

ERIC Educational Resources Information Center

Siebert, Fred S.

Now that the technical aspects of satellite transmission have been solved, there remain the more complex and difficult problems of maintaining both order in outer space and the rights of nations and individuals as these rights may be affected by broadcasts transmitted by satellite stations. These broadcasts, whether beamed to a ground station or…

Interesting and Difficult Mathematical Problems: Changing Teachers' Views by Employing Multiple-Solution Tasks

ERIC Educational Resources Information Center

Guberman, Raisa; Leikin, Roza

2013-01-01

The study considers mathematical problem solving to be at the heart of mathematics teaching and learning, while mathematical challenge is a core element of any educational process. The study design addresses the complexity of teachers' knowledge. It is aimed at exploring the development of teachers' mathematical and pedagogical conceptions…

Managing Risk on the Final Frontier

NASA Technical Reports Server (NTRS)

Lengyel, David M.; Newman, J. S.

2009-01-01

The National Aeronautics and Space Administration (NASA). Exploration Systems Mission Directorate (ESMD) has combined the Continuous Risk Management (CRM) discipline with innovative knowledge management (KM) practices to more effectively enable the accomplishment of work. CRM enables proactive problem identification and problem solving in the complex world of rocket science. while KM is used to improve this process.

Nonunitary and unitary approach to Eigenvalue problem of Boson operators and squeezed coherent states

NASA Technical Reports Server (NTRS)

Wunsche, A.

1993-01-01

The eigenvalue problem of the operator a + zeta(boson creation operator) is solved for arbitrarily complex zeta by applying a nonunitary operator to the vacuum state. This nonunitary approach is compared with the unitary approach leading for the absolute value of zeta less than 1 to squeezed coherent states.

Two dimensional finite element heat transfer models for softwood

Treesearch

Hongmei Gu; John F. Hunt

2004-01-01

The anisotropy of wood creates a complex problem for solving heat and mass transfer problems that require analyses be based on fundamental material properties of the wood structure. Most heat transfer models use average thermal properties across either the radial or tangential directions and have not differentiated the effects of cellular alignment, earlywood/latewood...

The Complexity of Bit Retrieval

DOE PAGES

Elser, Veit

2018-09-20

Bit retrieval is the problem of reconstructing a periodic binary sequence from its periodic autocorrelation, with applications in cryptography and x-ray crystallography. After defining the problem, with and without noise, we describe and compare various algorithms for solving it. A geometrical constraint satisfaction algorithm, relaxed-reflect-reflect, is currently the best algorithm for noisy bit retrieval.

The Complexity of Bit Retrieval

DOE Office of Scientific and Technical Information (OSTI.GOV)

Elser, Veit

Bit retrieval is the problem of reconstructing a periodic binary sequence from its periodic autocorrelation, with applications in cryptography and x-ray crystallography. After defining the problem, with and without noise, we describe and compare various algorithms for solving it. A geometrical constraint satisfaction algorithm, relaxed-reflect-reflect, is currently the best algorithm for noisy bit retrieval.

Expanding Horizons--Into the Future with Confidence!

ERIC Educational Resources Information Center

Volk, Valerie

2006-01-01

Gifted students often show a deep interest in and profound concern for the complex issues of society. Given the leadership potential of these students and their likely responsibility for solving future social problems, they need to develop this awareness and also a sense of confidence in dealing with future issues. The Future Problem Solving…

Math Thinkercises. A Good Apple Math Activity Book for Students. Grades 4-8.

ERIC Educational Resources Information Center

Daniel, Becky

This booklet designed for students in grades 4-8 provides 52 activities, including puzzles and problems. Activities range from simple to complex, giving learners practice in finding patterns, numeration, permutation, and problem solving. Calculators should be available, and students should be encouraged to discuss solutions with classmates,…

Learning Difficulties of Diabetic Patients: A Survey of Educators.

ERIC Educational Resources Information Center

Bonnet, Caroline; Gagnayre, Remi; d'Ivernois, Jean-Francois

1998-01-01

Surveys 85 health care professionals on the learning difficulties of diabetic patients. Results show that educators find it easy to teach techniques: patients master procedures well and make few mistakes. In contrast, diabetic patients seem to have problems learning skills, such as insulin dose adjustment, that require complex problem-solving.…