Same Old Problem, New Name? Alerting Students to the Nature of the Problem-Solving Process
ERIC Educational Resources Information Center
Yerushalmi, Edit; Magen, Esther
2006-01-01
Students frequently misconceive the process of problem-solving, expecting the linear process required for solving an exercise, rather than the convoluted search process required to solve a genuine problem. In this paper we present an activity designed to foster in students realization and appreciation of the nature of the problem-solving process,…
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…
ERIC Educational Resources Information Center
Paraschiv, Irina; Olley, J. Gregory
This paper describes the "Problem Solving for Life" training program which trains adolescents and adults with mental retardation in skills for solving social problems. The program requires group participants to solve social problems by practicing two prerequisite skills (relaxation and positive self-statements) and four problem solving steps: (1)…
Social Problem Solving, Conduct Problems, and Callous-Unemotional Traits in Children
ERIC Educational Resources Information Center
Waschbusch, Daniel A.; Walsh, Trudi M.; Andrade, Brendan F.; King, Sara; Carrey, Normand J.
2007-01-01
This study examined the association between social problem solving, conduct problems (CP), and callous-unemotional (CU) traits in elementary age children. Participants were 53 children (40 boys and 13 girls) aged 7-12 years. Social problem solving was evaluated using the Social Problem Solving Test-Revised, which requires children to produce…
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…
NASA Astrophysics Data System (ADS)
Adams, Wendy Kristine
The purpose of my research was to produce a problem solving evaluation tool for physics. To do this it was necessary to gain a thorough understanding of how students solve problems. Although physics educators highly value problem solving and have put extensive effort into understanding successful problem solving, there is currently no efficient way to evaluate problem solving skill. Attempts have been made in the past; however, knowledge of the principles required to solve the subject problem are so absolutely critical that they completely overshadow any other skills students may use when solving a problem. The work presented here is unique because the evaluation tool removes the requirement that the student already have a grasp of physics concepts. It is also unique because I picked a wide range of people and picked a wide range of tasks for evaluation. This is an important design feature that helps make things emerge more clearly. This dissertation includes an extensive literature review of problem solving in physics, math, education and cognitive science as well as descriptions of studies involving student use of interactive computer simulations, the design and validation of a beliefs about physics survey and finally the design of the problem solving evaluation tool. I have successfully developed and validated a problem solving evaluation tool that identifies 44 separate assets (skills) necessary for solving problems. Rigorous validation studies, including work with an independent interviewer, show these assets identified by this content-free evaluation tool are the same assets that students use to solve problems in mechanics and quantum mechanics. Understanding this set of component assets will help teachers and researchers address problem solving within the classroom.
ERIC Educational Resources Information Center
Kiliç, Çigdem
2017-01-01
This study examined pre-service primary school teachers' performance in posing problems that require knowledge of problem-solving strategies. Quantitative and qualitative methods were combined. The 120 participants were asked to pose a problem that could be solved by using the find-a-pattern a particular problem-solving strategy. After that,…
ERIC Educational Resources Information Center
Cunningham, Robert F.; Rappa, Anthony
2016-01-01
Surveys were used to examine mathematics teachers (15) on their ability to solve similarity problems and on their likely implementation of lesson objectives for teaching similarity. All correctly solved a similarity problem requiring a traditional static perspective, but 7 out of 15 failed to correctly solve a problem that required a more…
Requisite for Honing the Problem Solving Skill of Early Adolescents in the Digital Era
ERIC Educational Resources Information Center
Sumitha, S.; Jose, Rexlin
2016-01-01
Problems can be the cause of stress, tension, emotional instability and physical strain. Especially, adolescents should have the skill of solving a problem in order to reach his/her desired ambitions in life. The problem solving skill requires some abstract thinking to arrive at a clear solution. Problem solving ability helps them to meet their…
Lecture Notes on Requirements Elicitation
1994-03-01
ability to abstract away from the details of a problem and design a system that not only solves the problem but incorporates cutting-edge technology and...sound argument is presented. You have the uncanny ability to abstract away from the details of a problem and design a system that not only solves the... problem - solving skills on your last project, where you were the principle requirements analyst. Your undergraduate degree is in mathematics , and you
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…
The Internet: Problem Solving Friend or Foe?
ERIC Educational Resources Information Center
Wanko, Jeffrey J.
2007-01-01
Teaching problem solving to today's students requires teachers to be aware of the ways their students may use the internet as both a resource and as a tool for solving problems. In this article, I describe some of my own experiences in teaching problem solving to preservice teachers and how the existence of the internet has affected the ways in…
Problem Solving of Newton's Second Law through a System of Total Mass Motion
ERIC Educational Resources Information Center
Abdullah, Helmi
2014-01-01
Nowadays, many researchers discovered various effective strategies in teaching physics, from traditional to modern strategy. However, research on physics problem solving is still inadequate. Physics problem is an integral part of physics learning and requires strategy to solve it. Besides that, problem solving is the best way to convey principle,…
ERIC Educational Resources Information Center
Chandralekha; Singh
2008-01-01
In this paper, we explore the use of isomorphic problem pairs (IPPs) to assess introductory physics students' ability to solve and successfully transfer problem-solving knowledge from one context to another in mechanics. We call the paired problems "isomorphic" because they require the same physics principle to solve them. We analyze written…
Spontaneous gestures influence strategy choices in problem solving.
Alibali, Martha W; Spencer, Robert C; Knox, Lucy; Kita, Sotaro
2011-09-01
Do gestures merely reflect problem-solving processes, or do they play a functional role in problem solving? We hypothesized that gestures highlight and structure perceptual-motor information, and thereby make such information more likely to be used in problem solving. Participants in two experiments solved problems requiring the prediction of gear movement, either with gesture allowed or with gesture prohibited. Such problems can be correctly solved using either a perceptual-motor strategy (simulation of gear movements) or an abstract strategy (the parity strategy). Participants in the gesture-allowed condition were more likely to use perceptual-motor strategies than were participants in the gesture-prohibited condition. Gesture promoted use of perceptual-motor strategies both for participants who talked aloud while solving the problems (Experiment 1) and for participants who solved the problems silently (Experiment 2). Thus, spontaneous gestures influence strategy choices in problem solving.
A Rubric for Assessing Students' Experimental Problem-Solving Ability
ERIC Educational Resources Information Center
Shadle, Susan E.; Brown, Eric C.; Towns, Marcy H.; Warner, Don L.
2012-01-01
The ability to couple problem solving both to the understanding of chemical concepts and to laboratory practices is an essential skill for undergraduate chemistry programs to foster in our students. Therefore, chemistry programs must offer opportunities to answer real problems that require use of problem-solving processes used by practicing…
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.
A Crisis in Space--A Futuristic Simulation Using Creative Problem Solving.
ERIC Educational Resources Information Center
Clode, Linda
1992-01-01
An enrichment program developed for sixth-grade gifted students combined creative problem solving with future studies in a way that would simulate real life crisis problem solving. The program involved forecasting problems of the future requiring evacuation of Earth, assuming roles on a spaceship, and simulating crises as the spaceship traveled to…
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.
NASA Astrophysics Data System (ADS)
Hafner, Robert; Stewart, Jim
Past problem-solving research has provided a basis for helping students structure their knowledge and apply appropriate problem-solving strategies to solve problems for which their knowledge (or mental models) of scientific phenomena is adequate (model-using problem solving). This research examines how problem solving in the domain of Mendelian genetics proceeds in situations where solvers' mental models are insufficient to solve problems at hand (model-revising problem solving). Such situations require solvers to use existing models to recognize anomalous data and to revise those models to accommodate the data. The study was conducted in the context of 9-week high school genetics course and addressed: the heuristics charactenstic of successful model-revising problem solving: the nature of the model revisions, made by students as well as the nature of model development across problem types; and the basis upon which solvers decide that a revised model is sufficient (that t has both predictive and explanatory power).
Process Inquiry: Analysis of Oral Problem-Solving Skills in Mathematics of Engineering Students
ERIC Educational Resources Information Center
Trance, Naci John C.
2013-01-01
This paper presents another effort in determining the difficulty of engineering students in terms of solving word problems. Students were presented with word problems in algebra. Then, they were asked to solve the word problems orally; that is, before they presented their written solutions, they were required to explain how they understood the…
ERIC Educational Resources Information Center
Nelson, Tenneisha; Squires, Vicki
2017-01-01
Organizations are faced with solving increasingly complex problems. Addressing these issues requires effective leadership that can facilitate a collaborative problem solving approach where multiple perspectives are leveraged. In this conceptual paper, we critique the effectiveness of earlier leadership models in tackling complex organizational…
Enhanced and Conventional Project-Based Learning in an Engineering Design Module
ERIC Educational Resources Information Center
Chua, K. J.; Yang, W. M.; Leo, H. L.
2014-01-01
Engineering education focuses chiefly on students' ability to solve problems. While most engineering students are proficient in solving paper questions, they may not be proficient at providing optimal solutions to pragmatic project-based problems that require systematic learning strategy, innovation, problem-solving, and execution. The…
Decision-Making and Problem-Solving Approaches in Pharmacy Education
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.
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.
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…
ERIC Educational Resources Information Center
Hu, Yiling; Wu, Bian; Gu, Xiaoqing
2017-01-01
Test results from the Program for International Student Assessment (PISA) reveal that Shanghai students performed less well in solving interactive problems (those that require uncovering necessary information) than in solving analytical problems (those having all information disclosed at the outset). Accordingly, this study investigates…
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.…
The Evolution of a Flipped Classroom: Evidence-Based Recommendations
ERIC Educational Resources Information Center
Velegol, Stephanie Butler; Zappe, Sarah E.; Mahoney, Emily
2015-01-01
Engineering students benefit from an active and interactive classroom environment where they can be guided through the problem solving process. Typically faculty members spend class time presenting the technical content required to solve problems, leaving students to apply this knowledge and problem solve on their own at home. There has recently…
NASA Astrophysics Data System (ADS)
Nasution, M. L.; Yerizon, Y.; Gusmiyanti, R.
2018-04-01
One of the purpose mathematic learning is to develop problem solving abilities. Problem solving is obtained through experience in questioning non-routine. Improving students’ mathematical problem-solving abilities required an appropriate strategy in learning activities one of them is models problem based learning (PBL). Thus, the purpose of this research is to determine whether the problem solving abilities of mathematical students’ who learn to use PBL better than on the ability of students’ mathematical problem solving by applying conventional learning. This research included quasi experiment with static group design and population is students class XI MIA SMAN 1 Lubuk Alung. Class experiment in the class XI MIA 5 and class control in the class XI MIA 6. The instrument of final test students’ mathematical problem solving used essay form. The result of data final test in analyzed with t-test. The result is students’ mathematical problem solving abilities with PBL better then on the ability of students’ mathematical problem solving by applying conventional learning. It’s seen from the high percentage achieved by the group of students who learn to use PBL for each indicator of students’ mathematical problem solving.
Safari, Yahya; Meskini, Habibeh
2016-01-01
Background: Learning requires application of such processes as planning, supervision, monitoring and reflection that are included in the metacognition. Studies have shown that metacognition is associated with problem solving skills. The current research was conducted to investigate the impact of metacognitive instruction on students’ problem solving skills. Methods: The study sample included 40 students studying in the second semester at Kermanshah University of Medical Sciences, 2013-2014. They were selected through convenience sampling technique and were randomly assigned into two equal groups of experimental and control. For the experimental group, problem solving skills were taught through metacognitive instruction during ten two-hour sessions and for the control group, problem solving skills were taught via conventional teaching method. The instrument for data collection included problem solving inventory (Heppner, 1988), which was administered before and after instruction. The validity and reliability of the questionnaire had been previously confirmed. The collected data were analyzed by descriptive statistics, mean and standard deviation and the hypotheses were tested by t-test and ANCOVA. Results: The findings of the posttest showed that the total mean scores of problem solving skills in the experimental and control groups were 151.90 and 101.65, respectively, indicating a significant difference between them (p<0.001). This difference was also reported to be statistically significant between problem solving skills and its components, including problem solving confidence, orientation-avoidance coping style and personal control (p<0.001). No significant difference, however, was found between the students’ mean scores in terms of gender and major. Conclusion: Since metacognitive instruction has positive effects on students’ problem solving skills and is required to enhance academic achievement, metacognitive strategies are recommended to be taught to the students. PMID:26234970
Safari, Yahya; Meskini, Habibeh
2015-05-17
Learning requires application of such processes as planning, supervision, monitoring and reflection that are included in the metacognition. Studies have shown that metacognition is associated with problem solving skills. The current research was conducted to investigate the impact of metacognitive instruction on students' problem solving skills. The study sample included 40 students studying in the second semester at Kermanshah University of Medical Sciences, 2013-2014. They were selected through convenience sampling technique and were randomly assigned into two equal groups of experimental and control. For the experimental group, problem solving skills were taught through metacognitive instruction during ten two-hour sessions and for the control group, problem solving skills were taught via conventional teaching method. The instrument for data collection included problem solving inventory (Heppner, 1988), which was administered before and after instruction. The validity and reliability of the questionnaire had been previously confirmed. The collected data were analyzed by descriptive statistics, mean and standard deviation and the hypotheses were tested by t-test and ANCOVA. The findings of the posttest showed that the total mean scores of problem solving skills in the experimental and control groups were 151.90 and 101.65, respectively, indicating a significant difference between them (p<0.001). This difference was also reported to be statistically significant between problem solving skills and its components, including problem solving confidence, orientation-avoidance coping style and personal control (p<0.001). No significant difference, however, was found between the students' mean scores in terms of gender and major. Since metacognitive instruction has positive effects on students' problem solving skills and is required to enhance academic achievement, metacognitive strategies are recommended to be taught to the students.
ERIC Educational Resources Information Center
Robert, Nicole D.; LeFevre, Jo-Anne
2013-01-01
Does solving subtraction problems with negative answers (e.g., 5-14) require different cognitive processes than solving problems with positive answers (e.g., 14-5)? In a dual-task experiment, young adults (N=39) combined subtraction with two working memory tasks, verbal memory and visual-spatial memory. All of the subtraction problems required…
ERIC Educational Resources Information Center
Reusser, Kurt; And Others
The main concern of this paper is on the psychological processes of how students understand and solve mathematical word problems, and on how this knowledge can be applied to computer-based tutoring. It is argued that only a better understanding of the psychological requirements for understanding and solving those problems will lead to…
Using a general problem-solving strategy to promote transfer.
Youssef-Shalala, Amina; Ayres, Paul; Schubert, Carina; Sweller, John
2014-09-01
Cognitive load theory was used to hypothesize that a general problem-solving strategy based on a make-as-many-moves-as-possible heuristic could facilitate problem solutions for transfer problems. In four experiments, school students were required to learn about a topic through practice with a general problem-solving strategy, through a conventional problem solving strategy or by studying worked examples. In Experiments 1 and 2 using junior high school students learning geometry, low knowledge students in the general problem-solving group scored significantly higher on near or far transfer tests than the conventional problem-solving group. In Experiment 3, an advantage for a general problem-solving group over a group presented worked examples was obtained on far transfer tests using the same curriculum materials, again presented to junior high school students. No differences between conditions were found in Experiments 1, 2, or 3 using test problems similar to the acquisition problems. Experiment 4 used senior high school students studying economics and found the general problem-solving group scored significantly higher than the conventional problem-solving group on both similar and transfer tests. It was concluded that the general problem-solving strategy was helpful for novices, but not for students that had access to domain-specific knowledge. PsycINFO Database Record (c) 2014 APA, all rights reserved.
South African Grade 9 Mathematics Teachers' Views on the Teaching of Problem Solving
ERIC Educational Resources Information Center
Chirinda, Brantina; Barmby, Patrick
2018-01-01
The South African curriculum emphasizes the teaching of problem solving in mathematics. However, little is known about South African teachers' views on the teaching of mathematical problem solving (MPS). The purpose of this study was to establish Grade 9 South African teachers' views, teaching strategies and the support required in their teaching…
The Effects of Polya's Heuristic and Diary Writing on Children's Problem Solving
ERIC Educational Resources Information Center
Hensberry, Karina K. R.; Jacobbe, Tim
2012-01-01
This paper presents the results of a study that aimed at increasing students' problem-solving skills. Polya's (1985) heuristic for problem solving was used and students were required to articulate their thought processes through the use of a structured diary. The diary prompted students to answer questions designed to engage them in the phases of…
ERIC Educational Resources Information Center
Hong, Jon-Chao; Chen, Mei-Yung; Wong, Ashley; Hsu, Tsui-Fang; Peng, Chih-Chi
2012-01-01
In a contest featuring hands-on projects, college students were required to design a simple crawling worm using planning, self-monitoring and self-evaluation processes to solve contradictive problems. To enhance the efficiency of problem solving, one needs to practice meta-cognition based on an application of related scientific concepts. The…
Class and Home Problems: Optimization Problems
ERIC Educational Resources Information Center
Anderson, Brian J.; Hissam, Robin S.; Shaeiwitz, Joseph A.; Turton, Richard
2011-01-01
Optimization problems suitable for all levels of chemical engineering students are available. These problems do not require advanced mathematical techniques, since they can be solved using typical software used by students and practitioners. The method used to solve these problems forces students to understand the trends for the different terms…
ERIC Educational Resources Information Center
Hwang, Jiwon; Riccomini, Paul J.
2016-01-01
Requirements for reasoning, explaining, and generalizing mathematical concepts increase as students advance through the educational system; hence, improving overall mathematical proficiency is critical. Mathematical proficiency requires students to interpret quantities and their corresponding relationships during problem-solving tasks as well as…
Assessment Position Affects Problem-Solving Behaviors in a Child With Motor Impairments.
OʼGrady, Michael G; Dusing, Stacey C
2016-01-01
The purpose of this report was to examine problem-solving behaviors of a child with significant motor impairments in positions she could maintain independently, in supine and prone positions, as well as a position that required support, sitting. The child was a 22-month-old girl who could not sit independently and had limited independent mobility. Her problem-solving behaviors were assessed using the Early Problem Solving Indicator, while she was placed in supine or prone position, and again in manually supported sitting position. In manually supported sitting position, the subject demonstrated a higher frequency of problem-solving behaviors and her most developmentally advanced problem-solving behavior. Because a child's position may affect cognitive test results, position should be documented at the time of testing.
ERIC Educational Resources Information Center
Verderber, Nadine L.
1992-01-01
Presents the use of spreadsheets as an alternative method for precalculus students to solve maximum or minimum problems involving surface area and volume. Concludes that students with less technical backgrounds can solve problems normally requiring calculus and suggests sources for additional problems. (MDH)
Måseide, Per
2006-01-01
Ethnographic research was conducted in the thoracic ward of a Norwegian university hospital in order to study collaborative medical problem solving. As a general principle, evidence-based medicine is supposed to lead the process of medical problem solving. However, medical problem solving also requires evidence of a different kind. This is the more concrete form of evidence, such as X rays and other representations, that guides medical practice and makes sure that decisions are grounded in sound empirical facts and knowledge. In medicine, 'evidence' is on the one hand an abstract category; on the other hand, it is a tool that is practically enacted during the problem-solving work. Medical evidence does not 'show itself'. As such it has an emergent quality. Medical evidence has to be established and made practically useful in the collaborative settings by the participants in order to make conclusions about diagnoses and treatment. Hence, evidence is an interactional product; it is discursively generated and its applicability requires discourse. In addition, the production of medical evidence requires more than medical discourse and professional considerations. This paper looks at the production processes and use of medical evidence and the ambiguous meaning of this term in practical medicine.
The Senior Experience: Applied, Team Problem Solving in Business Education.
ERIC Educational Resources Information Center
Jessup, Leonard M.
1995-01-01
A yearlong senior experience course requires teams of business students to solve real problems for organizations in the community. Students enhanced responsibility, confidence, and organizational skills. Problems centered on differentiating the course from internships and improving staffing. Students had problems with group dynamics, team…
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…
An Overview of Problem Solving Studies in Physics Education
ERIC Educational Resources Information Center
Ince, Elif
2018-01-01
Education policies today aim to raise individuals with 21st Century skills considered as a universal necessity and problem-solving skill is the one of the skills that have emerged as a requirement of the 21st century. Teaching problem solving is one of the most important topics of physics education, it is also the field where students have the…
The Missing Curriculum in Physics Problem-Solving Education
NASA Astrophysics Data System (ADS)
Williams, Mobolaji
2018-05-01
Physics is often seen as an excellent introduction to science because it allows students to learn not only the laws governing the world around them, but also, through the problems students solve, a way of thinking which is conducive to solving problems outside of physics and even outside of science. In this article, we contest this latter idea and argue that in physics classes, students do not learn widely applicable problem-solving skills because physics education almost exclusively requires students to solve well-defined problems rather than the less-defined problems which better model problem solving outside of a formal class. Using personal, constructed, and the historical accounts of Schrödinger's development of the wave equation and Feynman's development of path integrals, we argue that what is missing in problem-solving education is practice in identifying gaps in knowledge and in framing these knowledge gaps as questions of the kind answerable using techniques students have learned. We discuss why these elements are typically not taught as part of the problem-solving curriculum and end with suggestions on how to incorporate these missing elements into physics classes.
Analytical derivation: An epistemic game for solving mathematically based physics problems
NASA Astrophysics Data System (ADS)
Bajracharya, Rabindra R.; Thompson, John R.
2016-06-01
Problem solving, which often involves multiple steps, is an integral part of physics learning and teaching. Using the perspective of the epistemic game, we documented a specific game that is commonly pursued by students while solving mathematically based physics problems: the analytical derivation game. This game involves deriving an equation through symbolic manipulations and routine mathematical operations, usually without any physical interpretation of the processes. This game often creates cognitive obstacles in students, preventing them from using alternative resources or better approaches during problem solving. We conducted hour-long, semi-structured, individual interviews with fourteen introductory physics students. Students were asked to solve four "pseudophysics" problems containing algebraic and graphical representations. The problems required the application of the fundamental theorem of calculus (FTC), which is one of the most frequently used mathematical concepts in physics problem solving. We show that the analytical derivation game is necessary, but not sufficient, to solve mathematically based physics problems, specifically those involving graphical representations.
Interleaved Practice Improves Mathematics Learning
ERIC Educational Resources Information Center
Rohrer, Doug; Dedrick, Robert F.; Stershic, Sandra
2015-01-01
A typical mathematics assignment consists primarily of practice problems requiring the strategy introduced in the immediately preceding lesson (e.g., a dozen problems that are solved by using the Pythagorean theorem). This means that students know which strategy is needed to solve each problem before they read the problem. In an alternative…
Constructing a Coherent Problem Model to Facilitate Algebra Problem Solving in a Chemistry Context
ERIC Educational Resources Information Center
Ngu, Bing Hiong; Yeung, Alexander Seeshing; Phan, Huy P.
2015-01-01
An experiment using a sample of 11th graders compared text editing and worked examples approaches in learning to solve dilution and molarity algebra word problems in a chemistry context. Text editing requires students to assess the structure of a word problem by specifying whether the problem text contains sufficient, missing, or irrelevant…
Optimality conditions for the numerical solution of optimization problems with PDE constraints :
DOE Office of Scientific and Technical Information (OSTI.GOV)
Aguilo Valentin, Miguel Alejandro; Ridzal, Denis
2014-03-01
A theoretical framework for the numerical solution of partial di erential equation (PDE) constrained optimization problems is presented in this report. This theoretical framework embodies the fundamental infrastructure required to e ciently implement and solve this class of problems. Detail derivations of the optimality conditions required to accurately solve several parameter identi cation and optimal control problems are also provided in this report. This will allow the reader to further understand how the theoretical abstraction presented in this report translates to the 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)
Mathematics at Work in Alberta.
ERIC Educational Resources Information Center
Glanfield, Florence, Ed.; Tilroe, Daryle, Ed.
This document is designed to assist teachers by providing practical examples of real world applications of high school mathematics. Fifteen problems are presented that individuals in industry and business solve using mathematics. Each problem provides the contributor's name, suggested skills required to solve the problem, background information…
Procedural versus Content-Related Hints for Word Problem Solving: An Exploratory Study
ERIC Educational Resources Information Center
Kock, W. D.; Harskamp, E. G.
2016-01-01
For primary school students, mathematical word problems are often more difficult to solve than straightforward number problems. Word problems require reading and analysis skills, and in order to explain their situational contexts, the proper mathematical knowledge and number operations have to be selected. To improve students' ability in solving…
NASA Astrophysics Data System (ADS)
Safadi, Rafi'; Safadi, Ekhlass; Meidav, Meir
2017-01-01
This study compared students’ learning in troubleshooting and problem solving activities. The troubleshooting activities provided students with solutions to conceptual problems in the form of refutation texts; namely, solutions that portray common misconceptions, refute them, and then present the accepted scientific ideas. They required students to individually diagnose these solutions; that is, to identify the erroneous and correct parts of the solutions and explain in what sense they differed, and later share their work in whole class discussions. The problem solving activities required the students to individually solve these same problems, and later share their work in whole class discussions. We compared the impact of the individual work stage in the troubleshooting and problem solving activities on promoting argumentation in the subsequent class discussions, and the effects of these activities on students’ engagement in self-repair processes; namely, in learning processes that allowed the students to self-repair their misconceptions, and by extension on advancing their conceptual knowledge. Two 8th grade classes studying simple electric circuits with the same teacher took part. One class (28 students) carried out four troubleshooting activities and the other (31 students) four problem solving activities. These activities were interwoven into a twelve lesson unit on simple electric circuits that was spread over a period of 2 months. The impact of the troubleshooting activities on students’ conceptual knowledge was significantly higher than that of the problem solving activities. This result is consistent with the finding that the troubleshooting activities engaged students in self-repair processes whereas the problem solving activities did not. The results also indicated that diagnosing solutions to conceptual problems in the form of refutation texts, as opposed to solving these same problems, apparently triggered argumentation in subsequent class discussions, even though the teacher was unfamiliar with the best ways to conduct argumentative classroom discussions. We account for these results and suggest possible directions for future research.
Holden, Richard J; Rivera-Rodriguez, A Joy; Faye, Héléne; Scanlon, Matthew C; Karsh, Ben-Tzion
2013-08-01
The most common change facing nurses today is new technology, particularly bar coded medication administration technology (BCMA). However, there is a dearth of knowledge on how BCMA alters nursing work. This study investigated how BCMA technology affected nursing work, particularly nurses' operational problem-solving behavior. Cognitive systems engineering observations and interviews were conducted after the implementation of BCMA in three nursing units of a freestanding pediatric hospital. Problem-solving behavior, associated problems, and goals, were specifically defined and extracted from observed episodes of care. Three broad themes regarding BCMA's impact on problem solving were identified. First, BCMA allowed nurses to invent new problem-solving behavior to deal with pre-existing problems. Second, BCMA made it difficult or impossible to apply some problem-solving behaviors that were commonly used pre-BCMA, often requiring nurses to use potentially risky workarounds to achieve their goals. Third, BCMA created new problems that nurses were either able to solve using familiar or novel problem-solving behaviors, or unable to solve effectively. Results from this study shed light on hidden hazards and suggest three critical design needs: (1) ecologically valid design; (2) anticipatory control; and (3) basic usability. Principled studies of the actual nature of clinicians' work, including problem solving, are necessary to uncover hidden hazards and to inform health information technology design and redesign.
Holden, Richard J.; Rivera-Rodriguez, A. Joy; Faye, Héléne; Scanlon, Matthew C.; Karsh, Ben-Tzion
2012-01-01
The most common change facing nurses today is new technology, particularly bar coded medication administration technology (BCMA). However, there is a dearth of knowledge on how BCMA alters nursing work. This study investigated how BCMA technology affected nursing work, particularly nurses’ operational problem-solving behavior. Cognitive systems engineering observations and interviews were conducted after the implementation of BCMA in three nursing units of a freestanding pediatric hospital. Problem-solving behavior, associated problems, and goals, were specifically defined and extracted from observed episodes of care. Three broad themes regarding BCMA’s impact on problem solving were identified. First, BCMA allowed nurses to invent new problem-solving behavior to deal with pre-existing problems. Second, BCMA made it difficult or impossible to apply some problem-solving behaviors that were commonly used pre-BCMA, often requiring nurses to use potentially risky workarounds to achieve their goals. Third, BCMA created new problems that nurses were either able to solve using familiar or novel problem-solving behaviors, or unable to solve effectively. Results from this study shed light on hidden hazards and suggest three critical design needs: (1) ecologically valid design; (2) anticipatory control; and (3) basic usability. Principled studies of the actual nature of clinicians’ work, including problem solving, are necessary to uncover hidden hazards and to inform health information technology design and redesign. PMID:24443642
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.
Hoskinson, A-M; Caballero, M D; Knight, J K
2013-06-01
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.
Is Word-Problem Solving a Form of Text Comprehension?
ERIC Educational Resources Information Center
Fuchs, Lynn S.; Fuchs, Douglas; Compton, Donald L.; Hamlett, Carol L.; Wang, Amber Y.
2015-01-01
This study's hypotheses were that (a) word-problem (WP) solving is a form of text comprehension that involves language comprehension processes, working memory, and reasoning, but (b) WP solving differs from other forms of text comprehension by requiring WP-specific language comprehension as well as general language comprehension. At the start of…
Li, Shuai; Li, Yangming; Wang, Zheng
2013-03-01
This paper presents a class of recurrent neural networks to solve quadratic programming problems. Different from most existing recurrent neural networks for solving quadratic programming problems, the proposed neural network model converges in finite time and the activation function is not required to be a hard-limiting function for finite convergence time. The stability, finite-time convergence property and the optimality of the proposed neural network for solving the original quadratic programming problem are proven in theory. Extensive simulations are performed to evaluate the performance of the neural network with different parameters. In addition, the proposed neural network is applied to solving the k-winner-take-all (k-WTA) problem. Both theoretical analysis and numerical simulations validate the effectiveness of our method for solving the k-WTA problem. Copyright © 2012 Elsevier Ltd. All rights reserved.
An Initial Model of Requirements Traceability an Empirical Study
1992-09-22
procedures have been used extensively in the study of human problem-solving, including such areas as general problem-solving behavior, physics problem...heen doing unless you have traceability." " Humans don’t go back to the requirements enough." "Traceabi!ity should be extremely helpful with...by constraints on its usage: ("Traceability needs to be something that humans can work with, not just a whip held over people." "Traceability should
Sleep Does Not Promote Solving Classical Insight Problems and Magic Tricks
Schönauer, Monika; Brodt, Svenja; Pöhlchen, Dorothee; Breßmer, Anja; Danek, Amory H.; Gais, Steffen
2018-01-01
During creative problem solving, initial solution attempts often fail because of self-imposed constraints that prevent us from thinking out of the box. In order to solve a problem successfully, the problem representation has to be restructured by combining elements of available knowledge in novel and creative ways. It has been suggested that sleep supports the reorganization of memory representations, ultimately aiding problem solving. In this study, we systematically tested the effect of sleep and time on problem solving, using classical insight tasks and magic tricks. Solving these tasks explicitly requires a restructuring of the problem representation and may be accompanied by a subjective feeling of insight. In two sessions, 77 participants had to solve classical insight problems and magic tricks. The two sessions either occurred consecutively or were spaced 3 h apart, with the time in between spent either sleeping or awake. We found that sleep affected neither general solution rates nor the number of solutions accompanied by sudden subjective insight. Our study thus adds to accumulating evidence that sleep does not provide an environment that facilitates the qualitative restructuring of memory representations and enables problem solving. PMID:29535620
NASA Astrophysics Data System (ADS)
Lundahl, Allison A.
Schools implementing Response to Intervention (RtI) procedures frequently engage in team problem-solving processes to address the needs of students who require intensive and individualized services. Because the effectiveness of the problem-solving process will impact the overall success of RtI systems, the present study was designed to learn more about how to strengthen the integrity of the problem-solving process. Research suggests that school districts must ensure high quality training and ongoing support to enhance the effectiveness, acceptability, and sustainability of the problem-solving process within an RtI model; however, there is a dearth of research examining the effectiveness of methods to provide this training and support. Consequently, this study investigated the effects of performance feedback and coaching strategies on the integrity with which teams of educators conducted the problem-solving process in schools. In addition, the relationships between problem-solving integrity, teacher acceptability, and student outcomes were examined. Results suggested that the performance feedback increased problem-solving procedural integrity across two of the three participating schools. Conclusions about the effectiveness of the (a) coaching intervention and (b) interventions implemented in the third school were inconclusive. Regression analyses indicated that the integrity with which the teams conducted the problem-solving process was a significant predictor of student outcomes. However, the relationship between problem-solving procedural integrity and teacher acceptability was not statistically significant.
An adaptive grid algorithm for one-dimensional nonlinear equations
NASA Technical Reports Server (NTRS)
Gutierrez, William E.; Hills, Richard G.
1990-01-01
Richards' equation, which models the flow of liquid through unsaturated porous media, is highly nonlinear and difficult to solve. Step gradients in the field variables require the use of fine grids and small time step sizes. The numerical instabilities caused by the nonlinearities often require the use of iterative methods such as Picard or Newton interation. These difficulties result in large CPU requirements in solving Richards equation. With this in mind, adaptive and multigrid methods are investigated for use with nonlinear equations such as Richards' equation. Attention is focused on one-dimensional transient problems. To investigate the use of multigrid and adaptive grid methods, a series of problems are studied. First, a multigrid program is developed and used to solve an ordinary differential equation, demonstrating the efficiency with which low and high frequency errors are smoothed out. The multigrid algorithm and an adaptive grid algorithm is used to solve one-dimensional transient partial differential equations, such as the diffusive and convective-diffusion equations. The performance of these programs are compared to that of the Gauss-Seidel and tridiagonal methods. The adaptive and multigrid schemes outperformed the Gauss-Seidel algorithm, but were not as fast as the tridiagonal method. The adaptive grid scheme solved the problems slightly faster than the multigrid method. To solve nonlinear problems, Picard iterations are introduced into the adaptive grid and tridiagonal methods. Burgers' equation is used as a test problem for the two algorithms. Both methods obtain solutions of comparable accuracy for similar time increments. For the Burgers' equation, the adaptive grid method finds the solution approximately three times faster than the tridiagonal method. Finally, both schemes are used to solve the water content formulation of the Richards' equation. For this problem, the adaptive grid method obtains a more accurate solution in fewer work units and less computation time than required by the tridiagonal method. The performance of the adaptive grid method tends to degrade as the solution process proceeds in time, but still remains faster than the tridiagonal scheme.
Computer-Mediated Assessment of Higher-Order Thinking Development
ERIC Educational Resources Information Center
Tilchin, Oleg; Raiyn, Jamal
2015-01-01
Solving complicated problems in a contemporary knowledge-based society requires higher-order thinking (HOT). The most productive way to encourage development of HOT in students is through use of the Problem-based Learning (PBL) model. This model organizes learning by solving corresponding problems relative to study courses. Students are directed…
ERIC Educational Resources Information Center
Pollak, Ave
This guide is intended for use in presenting a three-session course designed to develop the problem-solving skills required of persons employed in the manufacturing and service industries. The course is structured so that, upon its completion, students will be able to accomplish the following: describe and analyze problems encountered at work;…
Using Clickers to Facilitate Development of Problem-Solving Skills
ERIC Educational Resources Information Center
Levesque, Aime A.
2011-01-01
Classroom response systems, or clickers, have become pedagogical staples of the undergraduate science curriculum at many universities. In this study, the effectiveness of clickers in promoting problem-solving skills in a genetics class was investigated. Students were presented with problems requiring application of concepts covered in lecture and…
Cognitive Development, Genetics Problem Solving, and Genetics Instruction: A Critical Review.
ERIC Educational Resources Information Center
Smith, Mike U.; Sims, O. Suthern, Jr.
1992-01-01
Review of literature concerning problem solving in genetics and Piagetian stage theory. Authors conclude the research suggests that formal-operational thought is not strictly required for the solution of the majority of classical genetics problems; however, some genetic concepts are difficult for concrete operational students to understand.…
Cognitive Principles of Problem Solving and Instruction. Final Report.
ERIC Educational Resources Information Center
Greeno, James G.; And Others
Research in this project studied cognitive processes involved in understanding and solving problems used in instruction in the domain of mathematics, and explored implications of these cognitive analyses for the design of instruction. Three general issues were addressed: knowledge required for understanding problems, knowledge of the conditions…
NASA Astrophysics Data System (ADS)
Azila Che Musa, Nor; Mahmud, Zamalia; Baharun, Norhayati
2017-09-01
One of the important skills that is required from any student who are learning statistics is knowing how to solve statistical problems correctly using appropriate statistical methods. This will enable them to arrive at a conclusion and make a significant contribution and decision for the society. In this study, a group of 22 students majoring in statistics at UiTM Shah Alam were given problems relating to topics on testing of hypothesis which require them to solve the problems using confidence interval, traditional and p-value approach. Hypothesis testing is one of the techniques used in solving real problems and it is listed as one of the difficult concepts for students to grasp. The objectives of this study is to explore students’ perceived and actual ability in solving statistical problems and to determine which item in statistical problem solving that students find difficult to grasp. Students’ perceived and actual ability were measured based on the instruments developed from the respective topics. Rasch measurement tools such as Wright map and item measures for fit statistics were used to accomplish the objectives. Data were collected and analysed using Winsteps 3.90 software which is developed based on the Rasch measurement model. The results showed that students’ perceived themselves as moderately competent in solving the statistical problems using confidence interval and p-value approach even though their actual performance showed otherwise. Item measures for fit statistics also showed that the maximum estimated measures were found on two problems. These measures indicate that none of the students have attempted these problems correctly due to reasons which include their lack of understanding in confidence interval and probability values.
ERIC Educational Resources Information Center
Spires, Hiller A.; Rowe, Jonathan P.; Mott, Bradford W.; Lester, James C.
2011-01-01
Targeted as a highly desired skill for contemporary work and life, problem solving is central to game-based learning research. In this study, middle grade students achieved significant learning gains from gameplay interactions that required solving a science mystery based on microbiology content. Student trace data results indicated that effective…
Towards lexicographic multi-objective linear programming using grossone methodology
NASA Astrophysics Data System (ADS)
Cococcioni, Marco; Pappalardo, Massimo; Sergeyev, Yaroslav D.
2016-10-01
Lexicographic Multi-Objective Linear Programming (LMOLP) problems can be solved in two ways: preemptive and nonpreemptive. The preemptive approach requires the solution of a series of LP problems, with changing constraints (each time the next objective is added, a new constraint appears). The nonpreemptive approach is based on a scalarization of the multiple objectives into a single-objective linear function by a weighted combination of the given objectives. It requires the specification of a set of weights, which is not straightforward and can be time consuming. In this work we present both mathematical and software ingredients necessary to solve LMOLP problems using a recently introduced computational methodology (allowing one to work numerically with infinities and infinitesimals) based on the concept of grossone. The ultimate goal of such an attempt is an implementation of a simplex-like algorithm, able to solve the original LMOLP problem by solving only one single-objective problem and without the need to specify finite weights. The expected advantages are therefore obvious.
Boonen, Anton J. H.; de Koning, Björn B.; Jolles, Jelle; van der Schoot, Menno
2016-01-01
Successfully solving mathematical word problems requires both mental representation skills and reading comprehension skills. In Realistic Math Education (RME), however, students primarily learn to apply the first of these skills (i.e., representational skills) in the context of word problem solving. Given this, it seems legitimate to assume that students from a RME curriculum experience difficulties when asked to solve semantically complex word problems. We investigated this assumption under 80 sixth grade students who were classified as successful and less successful word problem solvers based on a standardized mathematics test. To this end, students completed word problems that ask for both mental representation skills and reading comprehension skills. The results showed that even successful word problem solvers had a low performance on semantically complex word problems, despite adequate performance on semantically less complex word problems. Based on this study, we concluded that reading comprehension skills should be given a (more) prominent role during word problem solving instruction in RME. PMID:26925012
Boonen, Anton J H; de Koning, Björn B; Jolles, Jelle; van der Schoot, Menno
2016-01-01
Successfully solving mathematical word problems requires both mental representation skills and reading comprehension skills. In Realistic Math Education (RME), however, students primarily learn to apply the first of these skills (i.e., representational skills) in the context of word problem solving. Given this, it seems legitimate to assume that students from a RME curriculum experience difficulties when asked to solve semantically complex word problems. We investigated this assumption under 80 sixth grade students who were classified as successful and less successful word problem solvers based on a standardized mathematics test. To this end, students completed word problems that ask for both mental representation skills and reading comprehension skills. The results showed that even successful word problem solvers had a low performance on semantically complex word problems, despite adequate performance on semantically less complex word problems. Based on this study, we concluded that reading comprehension skills should be given a (more) prominent role during word problem solving instruction in RME.
Assertiveness and problem solving in midwives.
Yurtsal, Zeliha Burcu; Özdemir, Levent
2015-01-01
Midwifery profession is required to bring solutions to problems and a midwife is expected to be an assertive person and to develop midwifery care. This study was planned to examine the relationship between assertiveness and problem-solving skills of midwives. This cross-sectional study was conducted with 201 midwives between July 2008 and February 2009 in the city center of Sivas. The Rathus Assertiveness Schedule (RAS) and Problem Solving Inventory (PSI) were used to determine the level of assertiveness and problem-solving skills of midwives. Statistical methods were used as mean, standard deviation, percentage, Student's T, ANOVA and Tukey HSD, Kruskal Wallis, Fisher Exact, Pearson Correlation and Chi-square tests and P < 0.05. The RAS mean scores and the PSI mean scores showed statistically significant differences in terms of a midwife's considering herself as a member of the health team, expressing herself within the health care team, being able to say "no" when necessary, cooperating with her colleagues, taking part in problem-solving skills training. A statistically significant negative correlation was found between the RAS and PSI scores. The RAS scores decreased while the problem-solving scores increased (r: -0451, P < 0.01). There were significant statistical differences between assertiveness levels and problem solving skills of midwives, and midwives who were assertive solved their problems better than did others. Assertiveness and problem-solving skills training will contribute to the success of the midwifery profession. Midwives able to solve problems, and display assertive behaviors will contribute to the development of midwifery profession.
Multiple representations and free-body diagrams: Do students benefit from using them?
NASA Astrophysics Data System (ADS)
Rosengrant, David R.
2007-12-01
Introductory physics students have difficulties understanding concepts and solving problems. When they solve problems, they use surface features of the problems to find an equation to calculate a numerical answer often not understanding the physics in the problem. How do we help students approach problem solving in an expert manner? A possible answer is to help them learn to represent knowledge in multiple ways and then use these different representations for conceptual understanding and problem solving. This solution follows from research in cognitive science and in physics education. However, there are no studies in physics that investigate whether students who learn to use multiple representations are in fact better problem solvers. This study focuses on one specific representation used in physics--a free body diagram. A free-body diagram is a graphical representation of forces exerted on an object of interest by other objects. I used the free-body diagram to investigate five main questions: (1) If students are in a course where they consistently use free body diagrams to construct and test concepts in mechanics, electricity and magnetism and to solve problems in class and in homework, will they draw free-body diagrams on their own when solving exam problems? (2) Are students who use free-body diagrams to solve problems more successful then those who do not? (3) Why do students draw free-body diagrams when solving problems? (4) Are students consistent in constructing diagrams for different concepts in physics and are they consistent in the quality of their diagrams? (5) What are possible relationships between features of a problem and how likely a student will draw a free body diagram to help them solve the problem? I utilized a mixed-methods approach to answer these questions. Questions 1, 2, 4 and 5 required a quantitative approach while question 3 required a qualitative approach, a case study. When I completed my study, I found that if students are in an environment which fosters the use of representations for problem solving and for concept development, then the majority of students will consistently construct helpful free-body diagrams and use them on their own to solve problems. Additionally, those that construct correct free-body diagrams are significantly more likely to successfully solve the problem. Finally, those students that are high achieving tend to use diagrams more and for more reasons then students who have low course grades. These findings will have major impacts on how introductory physics instructors run their classes and how curriculums are designed. These results favor a problem solving strategy that is rich with representations.
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.
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
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.
Helping Students with Emotional and Behavioral Disorders Solve Mathematics Word Problems
ERIC Educational Resources Information Center
Alter, Peter
2012-01-01
The author presents a strategy for helping students with emotional and behavioral disorders become more proficient at solving math word problems. Math word problems require students to go beyond simple computation in mathematics (e.g., adding, subtracting, multiplying, and dividing) and use higher level reasoning that includes recognizing relevant…
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…
Shifting College Students' Epistemological Framing Using Hypothetical Debate Problems
ERIC Educational Resources Information Center
Hu, Dehui; Rebello, N. Sanjay
2014-01-01
Developing expertise in physics problem solving requires the ability to use mathematics effectively in physical scenarios. Novices and experts often perceive the use of mathematics in physics differently. Students' perceptions and how they frame the use of mathematics in physics play an important role in their physics problem solving. In this…
Teaching Problem-Solving Competency in Business Studies at Secondary School Level
ERIC Educational Resources Information Center
Meintjes, Aloe; Henrico, Alfred; Kroon, Japie
2015-01-01
The high unemployment rate in South Africa compels potential entrepreneurs to start their own businesses in order to survive. Often this is with little or no formal training or education in entrepreneurship. Since problem recognition and problem-solving are amongst the most crucial competencies required for a successful entrepreneurial career,…
Asking the Right Questions: Action Learning and PMT 401
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
Innovation and problem solving: a review of common mechanisms.
Griffin, Andrea S; Guez, David
2014-11-01
Behavioural innovations have become central to our thinking about how animals adjust to changing environments. It is now well established that animals vary in their ability to innovate, but understanding why remains a challenge. This is because innovations are rare, so studying innovation requires alternative experimental assays that create opportunities for animals to express their ability to invent new behaviours, or use pre-existing ones in new contexts. Problem solving of extractive foraging tasks has been put forward as a suitable experimental assay. We review the rapidly expanding literature on problem solving of extractive foraging tasks in order to better understand to what extent the processes underpinning problem solving, and the factors influencing problem solving, are in line with those predicted, and found, to underpin and influence innovation in the wild. Our aim is to determine whether problem solving can be used as an experimental proxy of innovation. We find that in most respects, problem solving is determined by the same underpinning mechanisms, and is influenced by the same factors, as those predicted to underpin, and to influence, innovation. We conclude that problem solving is a valid experimental assay for studying innovation, propose a conceptual model of problem solving in which motor diversity plays a more central role than has been considered to date, and provide recommendations for future research using problem solving to investigate innovation. This article is part of a Special Issue entitled: Cognition in the wild. Copyright © 2014 Elsevier B.V. All rights reserved.
Development and Evaluation of a Casualty Evacuation Model for a European Conflict.
1985-12-01
EVAC, the computer code which implements our technique, has been used to solve a series of test problems in less time and requiring less memory than...the order of 1/K the amount of main memory for a K-commodity problem, so it can solve significantly larger problems than MCNF. I . 10 CHAPTER II A...technique may require only half the memory of the general L.P. package [6]. These advances are due to the efficient data structures which have been
Crudden, Adele; O'Mally, Jamie; Antonelli, Karla
2016-01-01
Social problem-solving skills and transportation self-efficacy were assessed for 48 vocational rehabilitation consumers with visual disabilities who required assistance securing work transportation. Social problem solving was at the upper end of the normed average; transportation self-efficacy averaged 101.5 out of 140. Level of vision loss was not associated with score differences; urban residence related to slightly higher self-efficacy than suburban or rural residency. Participants appeared to have the skills necessary to secure employment transportation, but were less confident about transportation-seeking activities that required more initiative of social interaction. Training and information might help consumers gain confidence in these tasks and increase viable transportation options.
Crooks, Noelle M.; Alibali, Martha W.
2013-01-01
This study investigated whether activating elements of prior knowledge can influence how problem solvers encode and solve simple mathematical equivalence problems (e.g., 3 + 4 + 5 = 3 + __). Past work has shown that such problems are difficult for elementary school students (McNeil and Alibali, 2000). One possible reason is that children's experiences in math classes may encourage them to think about equations in ways that are ultimately detrimental. Specifically, children learn a set of patterns that are potentially problematic (McNeil and Alibali, 2005a): the perceptual pattern that all equations follow an “operations = answer” format, the conceptual pattern that the equal sign means “calculate the total”, and the procedural pattern that the correct way to solve an equation is to perform all of the given operations on all of the given numbers. Upon viewing an equivalence problem, knowledge of these patterns may be reactivated, leading to incorrect problem solving. We hypothesized that these patterns may negatively affect problem solving by influencing what people encode about a problem. To test this hypothesis in children would require strengthening their misconceptions, and this could be detrimental to their mathematical development. Therefore, we tested this hypothesis in undergraduate participants. Participants completed either control tasks or tasks that activated their knowledge of the three patterns, and were then asked to reconstruct and solve a set of equivalence problems. Participants in the knowledge activation condition encoded the problems less well than control participants. They also made more errors in solving the problems, and their errors resembled the errors children make when solving equivalence problems. Moreover, encoding performance mediated the effect of knowledge activation on equivalence problem solving. Thus, one way in which experience may affect equivalence problem solving is by influencing what students encode about the equations. PMID:24324454
Formative feedback and scaffolding for developing complex problem solving and modelling outcomes
NASA Astrophysics Data System (ADS)
Frank, Brian; Simper, Natalie; Kaupp, James
2018-07-01
This paper discusses the use and impact of formative feedback and scaffolding to develop outcomes for complex problem solving in a required first-year course in engineering design and practice at a medium-sized research-intensive Canadian university. In 2010, the course began to use team-based, complex, open-ended contextualised problems to develop problem solving, communications, teamwork, modelling, and professional skills. Since then, formative feedback has been incorporated into: task and process-level feedback on scaffolded tasks in-class, formative assignments, and post-assignment review. Development in complex problem solving and modelling has been assessed through analysis of responses from student surveys, direct criterion-referenced assessment of course outcomes from 2013 to 2015, and an external longitudinal study. The findings suggest that students are improving in outcomes related to complex problem solving over the duration of the course. Most notably, the addition of new feedback and scaffolding coincided with improved student performance.
NASA Astrophysics Data System (ADS)
Singh, Chandralekha
2009-07-01
One finding of cognitive research is that people do not automatically acquire usable knowledge by spending lots of time on task. Because students' knowledge hierarchy is more fragmented, "knowledge chunks" are smaller than those of experts. The limited capacity of short term memory makes the cognitive load high during problem solving tasks, leaving few cognitive resources available for meta-cognition. The abstract nature of the laws of physics and the chain of reasoning required to draw meaningful inferences makes these issues critical. In order to help students, it is crucial to consider the difficulty of a problem from the perspective of students. We are developing and evaluating interactive problem-solving tutorials to help students in the introductory physics courses learn effective problem-solving strategies while solidifying physics concepts. The self-paced tutorials can provide guidance and support for a variety of problem solving techniques, and opportunity for knowledge and skill acquisition.
Dreams and creative problem-solving.
Barrett, Deirdre
2017-10-01
Dreams have produced art, music, novels, films, mathematical proofs, designs for architecture, telescopes, and computers. Dreaming is essentially our brain thinking in another neurophysiologic state-and therefore it is likely to solve some problems on which our waking minds have become stuck. This neurophysiologic state is characterized by high activity in brain areas associated with imagery, so problems requiring vivid visualization are also more likely to get help from dreaming. This article reviews great historical dreams and modern laboratory research to suggest how dreams can aid creativity and problem-solving. © 2017 New York Academy of Sciences.
The use of questions as problem-solving strategies during early childhood.
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.
Assertiveness and problem solving in midwives
Yurtsal, Zeliha Burcu; Özdemir, Levent
2015-01-01
Background: Midwifery profession is required to bring solutions to problems and a midwife is expected to be an assertive person and to develop midwifery care. This study was planned to examine the relationship between assertiveness and problem-solving skills of midwives. Materials and Methods: This cross-sectional study was conducted with 201 midwives between July 2008 and February 2009 in the city center of Sivas. The Rathus Assertiveness Schedule (RAS) and Problem Solving Inventory (PSI) were used to determine the level of assertiveness and problem-solving skills of midwives. Statistical methods were used as mean, standard deviation, percentage, Student's T, ANOVA and Tukey HSD, Kruskal Wallis, Fisher Exact, Pearson Correlation and Chi-square tests and P < 0.05. Results: The RAS mean scores and the PSI mean scores showed statistically significant differences in terms of a midwife's considering herself as a member of the health team, expressing herself within the health care team, being able to say “no” when necessary, cooperating with her colleagues, taking part in problem-solving skills training. A statistically significant negative correlation was found between the RAS and PSI scores. The RAS scores decreased while the problem-solving scores increased (r: -0451, P < 0.01). Conclusions: There were significant statistical differences between assertiveness levels and problem solving skills of midwives, and midwives who were assertive solved their problems better than did others. Assertiveness and problem-solving skills training will contribute to the success of the midwifery profession. Midwives able to solve problems, and display assertive behaviors will contribute to the development of midwifery profession. PMID:26793247
Reliable use of determinants to solve nonlinear structural eigenvalue problems efficiently
NASA Technical Reports Server (NTRS)
Williams, F. W.; Kennedy, D.
1988-01-01
The analytical derivation, numerical implementation, and performance of a multiple-determinant parabolic interpolation method (MDPIM) for use in solving transcendental eigenvalue (critical buckling or undamped free vibration) problems in structural mechanics are presented. The overall bounding, eigenvalue-separation, qualified parabolic interpolation, accuracy-confirmation, and convergence-recovery stages of the MDPIM are described in detail, and the numbers of iterations required to solve sample plane-frame problems using the MDPIM are compared with those for a conventional bisection method and for the Newtonian method of Simpson (1984) in extensive tables. The MDPIM is shown to use 31 percent less computation time than bisection when accuracy of 0.0001 is required, but 62 percent less when accuracy of 10 to the -8th is required; the time savings over the Newtonian method are about 10 percent.
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.
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...
A hybrid symbolic/finite-element algorithm for solving nonlinear optimal control problems
NASA Technical Reports Server (NTRS)
Bless, Robert R.; Hodges, Dewey H.
1991-01-01
The general code described is capable of solving difficult nonlinear optimal control problems by using finite elements and a symbolic manipulator. Quick and accurate solutions are obtained with a minimum for user interaction. Since no user programming is required for most problems, there are tremendous savings to be gained in terms of time and money.
ERIC Educational Resources Information Center
Safadi, Rafi; Safadi, Ekhlass; Meidav, Meir
2017-01-01
This study compared students' learning in troubleshooting and problem solving activities. The troubleshooting activities provided students with solutions to conceptual problems in the form of refutation texts; namely, solutions that portray common misconceptions, refute them, and then present the accepted scientific ideas. They required students…
Writing for Business: A Graduate-Level Course in Problem-Solving
ERIC Educational Resources Information Center
Seifert, Christine
2009-01-01
This paper details an assignment sequence that requires graduate students in an applied communication program to identify problems that clients may not be aware of. Good writing and good problem-solving are "inextricably linked to [a student's] ability to frame an issue, gather, and analyze information, and to structure a helpful response" (Musso,…
Problem Solving Process Research of Everyone Involved in Innovation Based on CAI Technology
NASA Astrophysics Data System (ADS)
Chen, Tao; Shao, Yunfei; Tang, Xiaowo
It is very important that non-technical department personnel especially bottom line employee serve as innovators under the requirements of everyone involved in innovation. According the view of this paper, it is feasible and necessary to build everyone involved in innovation problem solving process under Total Innovation Management (TIM) based on the Theory of Inventive Problem Solving (TRIZ). The tools under the CAI technology: How TO mode and science effects database could be very useful for all employee especially non-technical department and bottom line for innovation. The problem solving process put forward in the paper focus on non-technical department personnel especially bottom line employee for innovation.
Finite element modeling of electromagnetic fields and waves using NASTRAN
NASA Technical Reports Server (NTRS)
Moyer, E. Thomas, Jr.; Schroeder, Erwin
1989-01-01
The various formulations of Maxwell's equations are reviewed with emphasis on those formulations which most readily form analogies with Navier's equations. Analogies involving scalar and vector potentials and electric and magnetic field components are presented. Formulations allowing for media with dielectric and conducting properties are emphasized. It is demonstrated that many problems in electromagnetism can be solved using the NASTRAN finite element code. Several fundamental problems involving time harmonic solutions of Maxwell's equations with known analytic solutions are solved using NASTRAN to demonstrate convergence and mesh requirements. Mesh requirements are studied as a function of frequency, conductivity, and dielectric properties. Applications in both low frequency and high frequency are highlighted. The low frequency problems demonstrate the ability to solve problems involving media inhomogeneity and unbounded domains. The high frequency applications demonstrate the ability to handle problems with large boundary to wavelength ratios.
NASA Astrophysics Data System (ADS)
Maries, Alexandru; Singh, Chandralekha
2018-01-01
An appropriate diagram is a required element of a solution building process in physics problem solving and it can transform a given problem into a representation that is easier to exploit for solving the problem. A major focus while helping introductory physics students learn problem solving is to help them appreciate that drawing diagrams facilitates problem solving. We conducted an investigation in which two different interventions were implemented during recitation quizzes throughout the semester in a large enrolment, algebra-based introductory physics course. Students were either (1) asked to solve problems in which the diagrams were drawn for them or (2) explicitly told to draw a diagram. A comparison group was not given any instruction regarding diagrams. We developed a rubric to score the problem solving performance of students in different intervention groups. We investigated two problems involving electric field and electric force and found that students who drew productive diagrams were more successful problem solvers and that a higher level of relevant detail in a student’s diagram corresponded to a better score. We also conducted think-aloud interviews with nine students who were at the time taking an equivalent introductory algebra-based physics course in order to gain insight into how drawing diagrams affects the problem solving process. These interviews supported some of the interpretations of the quantitative results. We end by discussing instructional implications of the findings.
Problem Solving with Guided Repeated Oral Reading Instruction
ERIC Educational Resources Information Center
Conderman, Greg; Strobel, Debra
2006-01-01
Many students with disabilities require specialized instructional interventions and frequent progress monitoring in reading. The guided repeated oral reading technique promotes oral reading fluency while providing a reliable data-based monitoring system. This article emphasizes the importance of problem-solving when using this reading approach.
Problem solving strategies used by RN-to-BSN students in an online problem-based learning course.
Oldenburg, Nancy L; Hung, Wei-Chen
2010-04-01
It is essential that nursing students develop the problem solving and critical thinking skills required in the current health care environment. Problem-based learning has been promoted as a way to help students acquire those skills; however, gaps exist in the knowledge base of the strategies used by learners. The purpose of this case study was to gain insight into the problem solving experience of a group of six RN-to-BSN students in an online problem-based learning course. Data, including discussion transcripts, reflective papers, and interview transcripts, were analyzed using a qualitative approach. Students expanded their use of resources and resolved the cases, identifying relevant facts and clinical applications. They had difficulty communicating their findings, establishing the credibility of sources, and offering challenging feedback. Increased support and direction are needed to facilitate the development of problem solving abilities of students in the problem-based learning environment.
Using Clickers to Facilitate Development of Problem-Solving Skills
Levesque, Aime A.
2011-01-01
Classroom response systems, or clickers, have become pedagogical staples of the undergraduate science curriculum at many universities. In this study, the effectiveness of clickers in promoting problem-solving skills in a genetics class was investigated. Students were presented with problems requiring application of concepts covered in lecture and were polled for the correct answer. A histogram of class responses was displayed, and students were encouraged to discuss the problem, which enabled them to better understand the correct answer. Students were then presented with a similar problem and were again polled. My results indicate that those students who were initially unable to solve the problem were then able to figure out how to solve similar types of problems through a combination of trial and error and class discussion. This was reflected in student performance on exams, where there was a statistically significant positive correlation between grades and the percentage of clicker questions answered. Interestingly, there was no clear correlation between exam grades and the percentage of clicker questions answered correctly. These results suggest that students who attempt to solve problems in class are better equipped to solve problems on exams. PMID:22135374
Real-time trajectory optimization on parallel processors
NASA Technical Reports Server (NTRS)
Psiaki, Mark L.
1993-01-01
A parallel algorithm has been developed for rapidly solving trajectory optimization problems. The goal of the work has been to develop an algorithm that is suitable to do real-time, on-line optimal guidance through repeated solution of a trajectory optimization problem. The algorithm has been developed on an INTEL iPSC/860 message passing parallel processor. It uses a zero-order-hold discretization of a continuous-time problem and solves the resulting nonlinear programming problem using a custom-designed augmented Lagrangian nonlinear programming algorithm. The algorithm achieves parallelism of function, derivative, and search direction calculations through the principle of domain decomposition applied along the time axis. It has been encoded and tested on 3 example problems, the Goddard problem, the acceleration-limited, planar minimum-time to the origin problem, and a National Aerospace Plane minimum-fuel ascent guidance problem. Execution times as fast as 118 sec of wall clock time have been achieved for a 128-stage Goddard problem solved on 32 processors. A 32-stage minimum-time problem has been solved in 151 sec on 32 processors. A 32-stage National Aerospace Plane problem required 2 hours when solved on 32 processors. A speed-up factor of 7.2 has been achieved by using 32-nodes instead of 1-node to solve a 64-stage Goddard problem.
Orangutans (Pongo spp.) may prefer tools with rigid properties to flimsy tools.
Walkup, Kristina R; Shumaker, Robert W; Pruetz, Jill D
2010-11-01
Preference for tools with either rigid or flexible properties was explored in orangutans (Pongo spp.) through an extension of D. J. Povinelli, J. E. Reaux, and L. A. Theall's (2000) flimsy-tool problem. Three captive orangutans were presented with three unfamiliar pairs of tools to solve a novel problem. Although each orangutan has spontaneously used tools in the past, the tools presented in this study were novel to the apes. Each pair of tools contained one tool with rigid properties (functional) and one tool with flimsy properties (nonfunctional). Solving the problem required selection of a rigid tool to retrieve a food reward. The functional tool was selected in nearly all trials. Moreover, two of the orangutans demonstrated this within the first test trials with each of the three tool types. Although further research is required to test this statistically, it suggests either a preexisting preference for rigid tools or comprehension of the relevant features required in a tool to solve the task. The results of this study demonstrate that orangutans can recognize, or learn to recognize, relevant tool properties and can choose an appropriate tool to solve a problem. (PsycINFO Database Record (c) 2010 APA, all rights reserved).
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.
Inquiry-based problem solving in introductory physics
NASA Astrophysics Data System (ADS)
Koleci, Carolann
What makes problem solving in physics difficult? How do students solve physics problems, and how does this compare to an expert physicist's strategy? Over the past twenty years, physics education research has revealed several differences between novice and expert problem solving. The work of Chi, Feltovich, and Glaser demonstrates that novices tend to categorize problems based on surface features, while experts categorize according to theory, principles, or concepts1. If there are differences between how problems are categorized, then are there differences between how physics problems are solved? Learning more about the problem solving process, including how students like to learn and what is most effective, requires both qualitative and quantitative analysis. In an effort to learn how novices and experts solve introductory electricity problems, a series of in-depth interviews were conducted, transcribed, and analyzed, using both qualitative and quantitative methods. One-way ANOVA tests were performed in order to learn if there are any significant problem solving differences between: (a) novices and experts, (b) genders, (c) students who like to answer questions in class and those who don't, (d) students who like to ask questions in class and those who don't, (e) students employing an interrogative approach to problem solving and those who don't, and (f) those who like physics and those who dislike it. The results of both the qualitative and quantitative methods reveal that inquiry-based problem solving is prevalent among novices and experts, and frequently leads to the correct physics. These findings serve as impetus for the third dimension of this work: the development of Choose Your Own Adventure Physics(c) (CYOAP), an innovative teaching tool in physics which encourages inquiry-based problem solving. 1Chi, M., P. Feltovich, R. Glaser, "Categorization and Representation of Physics Problems by Experts and Novices", Cognitive Science, 5, 121--152 (1981).
Cooley, R.L.; Hill, M.C.
1992-01-01
Three methods of solving nonlinear least-squares problems were compared for robustness and efficiency using a series of hypothetical and field problems. A modified Gauss-Newton/full Newton hybrid method (MGN/FN) and an analogous method for which part of the Hessian matrix was replaced by a quasi-Newton approximation (MGN/QN) solved some of the problems with appreciably fewer iterations than required using only a modified Gauss-Newton (MGN) method. In these problems, model nonlinearity and a large variance for the observed data apparently caused MGN to converge more slowly than MGN/FN or MGN/QN after the sum of squared errors had almost stabilized. Other problems were solved as efficiently with MGN as with MGN/FN or MGN/QN. Because MGN/FN can require significantly more computer time per iteration and more computer storage for transient problems, it is less attractive for a general purpose algorithm than MGN/QN.
Evaluation of a transfinite element numerical solution method for nonlinear heat transfer problems
NASA Technical Reports Server (NTRS)
Cerro, J. A.; Scotti, S. J.
1991-01-01
Laplace transform techniques have been widely used to solve linear, transient field problems. A transform-based algorithm enables calculation of the response at selected times of interest without the need for stepping in time as required by conventional time integration schemes. The elimination of time stepping can substantially reduce computer time when transform techniques are implemented in a numerical finite element program. The coupling of transform techniques with spatial discretization techniques such as the finite element method has resulted in what are known as transfinite element methods. Recently attempts have been made to extend the transfinite element method to solve nonlinear, transient field problems. This paper examines the theoretical basis and numerical implementation of one such algorithm, applied to nonlinear heat transfer problems. The problem is linearized and solved by requiring a numerical iteration at selected times of interest. While shown to be acceptable for weakly nonlinear problems, this algorithm is ineffective as a general nonlinear solution method.
The effects of cumulative practice on mathematics problem solving.
Mayfield, Kristin H; Chase, Philip N
2002-01-01
This study compared three different methods of teaching five basic algebra rules to college students. All methods used the same procedures to teach the rules and included four 50-question review sessions interspersed among the training of the individual rules. The differences among methods involved the kinds of practice provided during the four review sessions. Participants who received cumulative practice answered 50 questions covering a mix of the rules learned prior to each review session. Participants who received a simple review answered 50 questions on one previously trained rule. Participants who received extra practice answered 50 extra questions on the rule they had just learned. Tests administered after each review included new questions for applying each rule (application items) and problems that required novel combinations of the rules (problem-solving items). On the final test, the cumulative group outscored the other groups on application and problem-solving items. In addition, the cumulative group solved the problem-solving items significantly faster than the other groups. These results suggest that cumulative practice of component skills is an effective method of training problem solving.
The effects of cumulative practice on mathematics problem solving.
Mayfield, Kristin H; Chase, Philip N
2002-01-01
This study compared three different methods of teaching five basic algebra rules to college students. All methods used the same procedures to teach the rules and included four 50-question review sessions interspersed among the training of the individual rules. The differences among methods involved the kinds of practice provided during the four review sessions. Participants who received cumulative practice answered 50 questions covering a mix of the rules learned prior to each review session. Participants who received a simple review answered 50 questions on one previously trained rule. Participants who received extra practice answered 50 extra questions on the rule they had just learned. Tests administered after each review included new questions for applying each rule (application items) and problems that required novel combinations of the rules (problem-solving items). On the final test, the cumulative group outscored the other groups on application and problem-solving items. In addition, the cumulative group solved the problem-solving items significantly faster than the other groups. These results suggest that cumulative practice of component skills is an effective method of training problem solving. PMID:12102132
Cultural Differences in Social Interaction during Group Problem Solving.
ERIC Educational Resources Information Center
Gabrenya, William K., Jr.; Barba, Lourdes
Cross-cultural psychology has begun to analyze cultural differences on collectivism and the implications of these differences for social processes such as group productivity. This study examined natural social interaction during a problem-solving task that required discussion and the establishment of a consensus. The relationship of collectivist…
Identification and Analysis of Student Conceptions Used To Solve Chemical Equilibrium Problems.
ERIC Educational Resources Information Center
Voska, Kirk W.; Heikkinen, Henry W.
2000-01-01
Identifies and quantifies the chemistry conceptions used by students when solving chemical equilibrium problems requiring application of LeChatelier's Principle, and explores the feasibility of designing a paper and pencil test to accomplish these purposes. Eleven prevalent incorrect student conceptions about chemical equilibrium were identified…
Introducing Mathematics to Information Problem-Solving Tasks: Surface or Substance?
ERIC Educational Resources Information Center
Erickson, Ander
2017-01-01
This study employs a cross-case analysis in order to explore the demands and opportunities that arise when information problem-solving tasks are introduced into college mathematics classes. Professors at three universities collaborated with me to develop statistics-related activities that required students to engage in research outside the…
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…
DOT National Transportation Integrated Search
1971-06-01
A study was conducted in which performance on a non-verbal problem- solving task was correlated with the Otis Quick Scoring Mental Ability Test and the Raven Progressive Matrices Test. The problem-solving task, called 'code- lock' required the subjec...
Word Fluency: A Task Analysis.
ERIC Educational Resources Information Center
Laine, Matti
It is suggested that models of human problem solving are useful in the analysis of word fluency (WF) test performance. In problem-solving terms, WF tasks would require the subject to define and clarify the conditions of the task (task acquisition), select and employ appropriate strategies, and monitor one's performance. In modern neuropsychology,…
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…
Teachers' Use of Agricultural Laboratories in Secondary Agricultural Education
ERIC Educational Resources Information Center
Shoulders, Catherine W.; Myers, Brian E.
2012-01-01
Trends in the agriculture industry require students to have the ability to solve problems associated with scientific content. Agricultural laboratories are considered a main component of secondary agricultural education, and are well suited to provide students with opportunities to develop problem-solving skills through experiential learning. This…
The Effects of Motivation and Emotion upon Problem Solving.
ERIC Educational Resources Information Center
Sanders, Michele; Matsumoto, David
Recent research has refuted the behaviorist approach by establishing a relationship between emotion and behavior. The data collection procedure, however, has often involved an inferred emotional state from a hypothetical situation. As partial fulfillment of a class requirement, 60 college students were asked to perform two problem solving tasks…
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…
Young Children's Drawings in Problem Solving
ERIC Educational Resources Information Center
Bakar, Kamariah Abu; Way, Jennifer; Bobis, Janette
2016-01-01
This paper explores young children's drawings (6 years old) in early number and addition activities in Malaysia. Observation, informal interviews and analysis of drawings revealed two types of drawing, and gave insight into the transitional process required for children to utilise drawings in problem solving. We argue the importance of valuing and…
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.
Directed Bee Colony Optimization Algorithm to Solve the Nurse Rostering Problem.
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
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
NASA Astrophysics Data System (ADS)
Aurora, Tarlok
2005-04-01
In a calculus-based introductory physics course, students were assigned to write the statements of word problems (along with the accompanying diagrams if any), analyze these, identify important concepts/equations and try to solve these end-of- chapter homework problems. They were required to bring to class their written assignment until the chapter was completed in lecture. These were quickly checked at the beginning of the class. In addition, re-doing selected solved examples in the textbook were assigned as homework. Where possible, students were asked to look for similarities between the solved-examples and the end-of-the-chapter problems, or occasionally these were brought to the students' attention. It was observed that many students were able to solve several of the solved-examples on the test even though the instructor had not solved these in class. This was seen as an improvement over the previous years. It made the students more responsible for their learning. Another benefit was that it alleviated the problems previously created by many students not bringing the textbooks to class. It allowed more time for problem solving/discussions in class.
ERIC Educational Resources Information Center
Redondo, Miguel A.; Bravo, Crescencio; Ortega, Manuel; Verdejo, M. Felisa
2007-01-01
Experimental learning environments based on simulation usually require monitoring and adaptation to the actions the users carry out. Some systems provide this functionality, but they do so in a way which is static or cannot be applied to problem solving tasks. In response to this problem, we propose a method based on the use of intermediate…
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.
Solving multi-objective optimization problems in conservation with the reference point method
Dujardin, Yann; Chadès, Iadine
2018-01-01
Managing the biodiversity extinction crisis requires wise decision-making processes able to account for the limited resources available. In most decision problems in conservation biology, several conflicting objectives have to be taken into account. Most methods used in conservation either provide suboptimal solutions or use strong assumptions about the decision-maker’s preferences. Our paper reviews some of the existing approaches to solve multi-objective decision problems and presents new multi-objective linear programming formulations of two multi-objective optimization problems in conservation, allowing the use of a reference point approach. Reference point approaches solve multi-objective optimization problems by interactively representing the preferences of the decision-maker with a point in the criteria (objectives) space, called the reference point. We modelled and solved the following two problems in conservation: a dynamic multi-species management problem under uncertainty and a spatial allocation resource management problem. Results show that the reference point method outperforms classic methods while illustrating the use of an interactive methodology for solving combinatorial problems with multiple objectives. The method is general and can be adapted to a wide range of ecological combinatorial problems. PMID:29293650
Impact of ageing on problem size and proactive interference in arithmetic facts solving.
Archambeau, Kim; De Visscher, Alice; Noël, Marie-Pascale; Gevers, Wim
2018-02-01
Arithmetic facts (AFs) are required when solving problems such as "3 × 4" and refer to calculations for which the correct answer is retrieved from memory. Currently, two important effects that modulate the performance in AFs have been highlighted: the problem size effect and the proactive interference effect. The aim of this study is to investigate possible age-related changes of the problem size effect and the proactive interference effect in AF solving. To this end, the performance of young and older adults was compared in a multiplication production task. Furthermore, an independent measure of proactive interference was assessed to further define the architecture underlying this effect in multiplication solving. The results indicate that both young and older adults were sensitive to the effects of interference and of the problem size. That is, both interference and problem size affected performance negatively: the time needed to solve a multiplication problem increases as the level of interference and the size of the problem increase. Regarding the effect of ageing, the problem size effect remains constant with age, indicating a preserved AF network in older adults. Interestingly, sensitivity to proactive interference in multiplication solving was less pronounced in older than in younger adults suggesting that part of the proactive interference has been overcome with age.
Inducing mental set constrains procedural flexibility and conceptual understanding in mathematics.
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.
Network planning under uncertainties
NASA Astrophysics Data System (ADS)
Ho, Kwok Shing; Cheung, Kwok Wai
2008-11-01
One of the main focuses for network planning is on the optimization of network resources required to build a network under certain traffic demand projection. Traditionally, the inputs to this type of network planning problems are treated as deterministic. In reality, the varying traffic requirements and fluctuations in network resources can cause uncertainties in the decision models. The failure to include the uncertainties in the network design process can severely affect the feasibility and economics of the network. Therefore, it is essential to find a solution that can be insensitive to the uncertain conditions during the network planning process. As early as in the 1960's, a network planning problem with varying traffic requirements over time had been studied. Up to now, this kind of network planning problems is still being active researched, especially for the VPN network design. Another kind of network planning problems under uncertainties that has been studied actively in the past decade addresses the fluctuations in network resources. One such hotly pursued research topic is survivable network planning. It considers the design of a network under uncertainties brought by the fluctuations in topology to meet the requirement that the network remains intact up to a certain number of faults occurring anywhere in the network. Recently, the authors proposed a new planning methodology called Generalized Survivable Network that tackles the network design problem under both varying traffic requirements and fluctuations of topology. Although all the above network planning problems handle various kinds of uncertainties, it is hard to find a generic framework under more general uncertainty conditions that allows a more systematic way to solve the problems. With a unified framework, the seemingly diverse models and algorithms can be intimately related and possibly more insights and improvements can be brought out for solving the problem. This motivates us to seek a generic framework for solving the network planning problem under uncertainties. In addition to reviewing the various network planning problems involving uncertainties, we also propose that a unified framework based on robust optimization can be used to solve a rather large segment of network planning problem under uncertainties. Robust optimization is first introduced in the operations research literature and is a framework that incorporates information about the uncertainty sets for the parameters in the optimization model. Even though robust optimization is originated from tackling the uncertainty in the optimization process, it can serve as a comprehensive and suitable framework for tackling generic network planning problems under uncertainties. In this paper, we begin by explaining the main ideas behind the robust optimization approach. Then we demonstrate the capabilities of the proposed framework by giving out some examples of how the robust optimization framework can be applied to the current common network planning problems under uncertain environments. Next, we list some practical considerations for solving the network planning problem under uncertainties with the proposed framework. Finally, we conclude this article with some thoughts on the future directions for applying this framework to solve other network planning problems.
Diverse knowledges and competing interests: an essay on socio-technical problem-solving.
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.
Response Mode Effects on Computer Based Problem Solving. Report Series 1979.
ERIC Educational Resources Information Center
Brown, Bobby R.; Sustik, Joan M.
This response mode study attempts to determine whether different response modes are helpful or not in facilitating the thought process in a given problem solving situation. The Luchins Water Jar Test (WJT) used in this study illustrates the phenomena "Einstelling" (mechanization of response) because it does not require any specialized content…
Aha! Voila! Eureka! Bilingualism and Insightful Problem Solving
ERIC Educational Resources Information Center
Cushen, Patrick J.; Wiley, Jennifer
2011-01-01
What makes a person able to solve problems creatively? One interesting factor that may contribute is experience with multiple languages from an early age. Bilingual individuals who acquire two languages by the age of 6 have been shown to demonstrate superior performance on a number of thinking tasks that require flexibility. However, bilingual…
Problem solving or social change? The Applegate and Grand Canyon Forest Partnerships
Cassandra Moseley; Brett KenCairn
2001-01-01
Natural resource conflicts have resulted in attempts at better collaboration between public and private sectors. The resulting partnerships approach collaboration either by problem solving through better information and management, or by requiring substantial social change. The Applegate Partnership in Oregon and the Grand Canyon Forest Partnership in Arizona...
Imitation in Infancy: The Wealth of the Stimulus
ERIC Educational Resources Information Center
Ray, Elizabeth; Heyes, Cecilia
2011-01-01
Imitation requires the imitator to solve the correspondence problem--to translate visual information from modelled action into matching motor output. It has been widely accepted for some 30 years that the correspondence problem is solved by a specialized, innate cognitive mechanism. This is the conclusion of a poverty of the stimulus argument,…
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…
Grading Homework to Emphasize Problem-Solving Process Skills
ERIC Educational Resources Information Center
Harper, Kathleen A.
2012-01-01
This article describes a grading approach that encourages students to employ particular problem-solving skills. Some strengths of this method, called "process-based grading," are that it is easy to implement, requires minimal time to grade, and can be used in conjunction with either an online homework delivery system or paper-based homework.
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…
Tying Theory To Practice: Cognitive Aspects of Computer Interaction in the Design Process.
ERIC Educational Resources Information Center
Mikovec, Amy E.; Dake, Dennis M.
The new medium of computer-aided design requires changes to the creative problem-solving methodologies typically employed in the development of new visual designs. Most theoretical models of creative problem-solving suggest a linear progression from preparation and incubation to some type of evaluative study of the "inspiration." These…
An Enhanced Memetic Algorithm for Single-Objective Bilevel Optimization Problems.
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.
Revisiting software specification and design for large astronomy projects
NASA Astrophysics Data System (ADS)
Wiant, Scott; Berukoff, Steven
2016-07-01
The separation of science and engineering in the delivery of software systems overlooks the true nature of the problem being solved and the organization that will solve it. Use of a systems engineering approach to managing the requirements flow between these two groups as between a customer and contractor has been used with varying degrees of success by well-known entities such as the U.S. Department of Defense. However, treating science as the customer and engineering as the contractor fosters unfavorable consequences that can be avoided and opportunities that are missed. For example, the "problem" being solved is only partially specified through the requirements generation process since it focuses on detailed specification guiding the parties to a technical solution. Equally important is the portion of the problem that will be solved through the definition of processes and staff interacting through them. This interchange between people and processes is often underrepresented and under appreciated. By concentrating on the full problem and collaborating on a strategy for its solution a science-implementing organization can realize the benefits of driving towards common goals (not just requirements) and a cohesive solution to the entire problem. The initial phase of any project when well executed is often the most difficult yet most critical and thus it is essential to employ a methodology that reinforces collaboration and leverages the full suite of capabilities within the team. This paper describes an integrated approach to specifying the needs induced by a problem and the design of its solution.
Improving insight and non-insight problem solving with brief interventions.
Wen, Ming-Ching; Butler, Laurie T; Koutstaal, Wilma
2013-02-01
Developing brief training interventions that benefit different forms of problem solving is challenging. In earlier research, Chrysikou (2006) showed that engaging in a task requiring generation of alternative uses of common objects improved subsequent insight problem solving. These benefits were attributed to a form of implicit transfer of processing involving enhanced construction of impromptu, on-the-spot or 'ad hoc' goal-directed categorizations of the problem elements. Following this, it is predicted that the alternative uses exercise should benefit abilities that govern goal-directed behaviour, such as fluid intelligence and executive functions. Similarly, an indirect intervention - self-affirmation (SA) - that has been shown to enhance cognitive and executive performance after self-regulation challenge and when under stereotype threat, may also increase adaptive goal-directed thinking and likewise should bolster problem-solving performance. In Experiment 1, brief single-session interventions, involving either alternative uses generation or SA, significantly enhanced both subsequent insight and visual-spatial fluid reasoning problem solving. In Experiment 2, we replicated the finding of benefits of both alternative uses generation and SA on subsequent insight problem-solving performance, and demonstrated that the underlying mechanism likely involves improved executive functioning. Even brief cognitive- and social-psychological interventions may substantially bolster different types of problem solving and may exert largely similar facilitatory effects on goal-directed behaviours. © 2012 The British Psychological Society.
A localized model of spatial cognition in chemistry
NASA Astrophysics Data System (ADS)
Stieff, Mike
This dissertation challenges the assumption that spatial cognition, particularly visualization, is the key component to problem solving in chemistry. In contrast to this assumption, I posit a localized, or task-specific, model of spatial cognition in chemistry problem solving to locate the exact tasks in a traditional organic chemistry curriculum that require students to use visualization strategies to problem solve. Instead of assuming that visualization is required for most chemistry tasks simply because chemistry concerns invisible three-dimensional entities, I instead use the framework of the localized model to identify how students do and do not make use of visualization strategies on a wide variety of assessment tasks regardless of each task's explicit demand for spatial cognition. I establish the dimensions of the localized model with five studies. First, I designed two novel psychometrics to reveal how students selectively use visualization strategies to interpret and analyze molecular structures. The third study comprised a document analysis of the organic chemistry assessments that empirically determined only 12% of these tasks explicitly require visualization. The fourth study concerned a series of correlation analyses between measures of visuo-spatial ability and chemistry performance to clarify the impact of individual differences. Finally, I performed a series of micro-genetic analyses of student problem solving that confirmed the earlier findings and revealed students prefer to visualize molecules from alternative perspectives without using mental rotation. The results of each study reveal that occurrences of sophisticated spatial cognition are relatively infrequent in chemistry, despite instructors' ostensible emphasis on the visualization of three-dimensional structures. To the contrary, students eschew visualization strategies and instead rely on the use of molecular diagrams to scaffold spatial cognition. Visualization does play a key role, however, in problem solving on a select group of chemistry tasks that require students to translate molecular representations or fundamentally alter the morphology of a molecule. Ultimately, this dissertation calls into question the assumption that individual differences in visuo-spatial ability play a critical role in determining who succeeds in chemistry. The results of this work establish a foundation for defining the precise manner in which visualization tools can best support problem solving.
Barakat, Lamia P.; Daniel, Lauren C.; Smith, Kelsey; Robinson, M. Renée; Patterson, Chavis A.
2013-01-01
Children with sickle cell disease (SCD) are at risk for poor health-related quality of life (HRQOL). The current analysis sought to explore parent problem-solving abilities/skills as a moderator between SCD complications and HRQOL to evaluate applicability to pediatric SCD. At baseline, 83 children ages 6–12 years and their primary caregiver completed measures of the child HRQOL. Primary caregivers also completed a measure of social problem-solving. A SCD complications score was computed from medical record review. Parent problem-solving abilities significantly moderated the association of SCD complications with child self-report psychosocial HRQOL (p = .006). SCD complications had a direct effect on parent proxy physical and psychosocial child HRQOL. Enhancing parent problem-solving abilities may be one approach to improve HRQOL for children with high SCD complications; however, modification of parent perceptions of HRQOL may require direct intervention to improve knowledge and skills involved in disease management. PMID:24222378
Barakat, Lamia P; Daniel, Lauren C; Smith, Kelsey; Renée Robinson, M; Patterson, Chavis A
2014-03-01
Children with sickle cell disease (SCD) are at risk for poor health-related quality of life (HRQOL). The current analysis sought to explore parent problem-solving abilities/skills as a moderator between SCD complications and HRQOL to evaluate applicability to pediatric SCD. At baseline, 83 children ages 6-12 years and their primary caregiver completed measures of child HRQOL. Primary caregivers also completed a measure of social problem-solving. A SCD complications score was computed from medical record review. Parent problem-solving abilities significantly moderated the association of SCD complications with child self-report psychosocial HRQOL (p = .006). SCD complications had a direct effect on parent proxy physical and psychosocial child HRQOL. Enhancing parent problem-solving abilities may be one approach to improve HRQOL for children with high SCD complications; however, modification of parent perceptions of HRQOL may require direct intervention to improve knowledge and skills involved in disease management.
NASA Astrophysics Data System (ADS)
Chandra, Rishabh
Partial differential equation-constrained combinatorial optimization (PDECCO) problems are a mixture of continuous and discrete optimization problems. PDECCO problems have discrete controls, but since the partial differential equations (PDE) are continuous, the optimization space is continuous as well. Such problems have several applications, such as gas/water network optimization, traffic optimization, micro-chip cooling optimization, etc. Currently, no efficient classical algorithm which guarantees a global minimum for PDECCO problems exists. A new mapping has been developed that transforms PDECCO problem, which only have linear PDEs as constraints, into quadratic unconstrained binary optimization (QUBO) problems that can be solved using an adiabatic quantum optimizer (AQO). The mapping is efficient, it scales polynomially with the size of the PDECCO problem, requires only one PDE solve to form the QUBO problem, and if the QUBO problem is solved correctly and efficiently on an AQO, guarantees a global optimal solution for the original PDECCO problem.
Goldberg, Daniel N.; Narayanan, Sri Hari Krishna; Hascoet, Laurent; ...
2016-05-20
We apply an optimized method to the adjoint generation of a time-evolving land ice model through algorithmic differentiation (AD). The optimization involves a special treatment of the fixed-point iteration required to solve the nonlinear stress balance, which differs from a straightforward application of AD software, and leads to smaller memory requirements and in some cases shorter computation times of the adjoint. The optimization is done via implementation of the algorithm of Christianson (1994) for reverse accumulation of fixed-point problems, with the AD tool OpenAD. For test problems, the optimized adjoint is shown to have far lower memory requirements, potentially enablingmore » larger problem sizes on memory-limited machines. In the case of the land ice model, implementation of the algorithm allows further optimization by having the adjoint model solve a sequence of linear systems with identical (as opposed to varying) matrices, greatly improving performance. Finally, the methods introduced here will be of value to other efforts applying AD tools to ice models, particularly ones which solve a hybrid shallow ice/shallow shelf approximation to the Stokes equations.« less
Sheldon, S; Vandermorris, S; Al-Haj, M; Cohen, S; Winocur, G; Moscovitch, M
2015-02-01
It is well accepted that the medial temporal lobes (MTL), and the hippocampus specifically, support episodic memory processes. Emerging evidence suggests that these processes also support the ability to effectively solve ill-defined problems which are those that do not have a set routine or solution. To test the relation between episodic memory and problem solving, we examined the ability of individuals with single domain amnestic mild cognitive impairment (aMCI), a condition characterized by episodic memory impairment, to solve ill-defined social problems. Participants with aMCI and age and education matched controls were given a battery of tests that included standardized neuropsychological measures, the Autobiographical Interview (Levine et al., 2002) that scored for episodic content in descriptions of past personal events, and a measure of ill-defined social problem solving. Corroborating previous findings, the aMCI group generated less episodically rich narratives when describing past events. Individuals with aMCI also generated less effective solutions when solving ill-defined problems compared to the control participants. Correlation analyses demonstrated that the ability to recall episodic elements from autobiographical memories was positively related to the ability to effectively solve ill-defined problems. The ability to solve these ill-defined problems was related to measures of activities of daily living. In conjunction with previous reports, the results of the present study point to a new functional role of episodic memory in ill-defined goal-directed behavior and other non-memory tasks that require flexible thinking. Our findings also have implications for the cognitive and behavioural profile of aMCI by suggesting that the ability to effectively solve ill-defined problems is related to sustained functional independence. Copyright © 2015 Elsevier Ltd. All rights reserved.
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
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.
Development and Evaluation of Problem-Solving Skills in Microbiology.
ERIC Educational Resources Information Center
Schuytema, Eunice C.; And Others
A problem solving, laboratory experience was devised in which first-year medical students were given a case description and then required to make judgments about what microbiology specimens should be collected and to analyze the results of laboratory tests in terms of implications for patient care. Over a four-year period revisions were made in…
ERIC Educational Resources Information Center
Caviglia, Francesco; Delfino, Manuela
2016-01-01
Active participation in the information society requires the ability to find some order in the chaotic nature of the Web and not to get lost within the endemic presence of inaccurate, misleading, biased and false information. This article presents an approach to Information Problem Solving (IPS)--that is, finding, understanding and assessing…
Collaborative Problem Solving in Young Typical Development and HFASD
ERIC Educational Resources Information Center
Kimhi, Yael; Bauminger-Zviely, Nirit
2012-01-01
Collaborative problem solving (CPS) requires sharing goals/attention and coordinating actions--all deficient in HFASD. Group differences were examined in CPS (HFASD/typical), with a friend versus with a non-friend. Participants included 28 HFASD and 30 typical children aged 3-6 years and their 58 friends and 58 non-friends. Groups were matched on…
Relationship between Teachers' Perceptions of Mobbing and Their Problem Solving Skills
ERIC Educational Resources Information Center
Mutlu Gö?men, Nejla; Güle?, Selma
2018-01-01
The purpose of this study is to determine the relationship between classroom teachers' perception of mobbing phenomenon and their problem solving skills. The sample of the study is composed of 208 classroom teachers working in the primary schools in the Osmangazi district of Bursa during the 2013-2014 educational year. The data required for the…
ERIC Educational Resources Information Center
Chao, Jen-Yi; Chao, Shu-Jen; Yao, Lo-Yi; Liu, Chuan-His
2016-01-01
This study used Focus Group to analyze user requirements for user interface so as to understand what capabilities of the Collaborative Problem Solving (CPS) Instructional Platform were expected by users. After 12 focus group interviews, the following four functions had been identified as essential to the CPS Instructional Platform: CPS…
ERIC Educational Resources Information Center
Perry, Lee R.
2012-01-01
In response to the diverse requirements of 21st-century police work and the increasing emphasis on community-policing philosophy, the Los Angeles Police Department has implemented changes within its academy curricula and methods of instruction, including the use of adult-learning concepts, a community policing problem-solving model known as…
ERIC Educational Resources Information Center
Aydogdu, Bülent; Erkol, Mehmet; Erten, Nuran
2014-01-01
Individuals benefit from science process skills while trying to solve problems through research (Bagci-Kiliç, 2003). To solve these problems individuals must acquire sufficient science process skills. Teachers must be able to understand these skills so that students can obtain the required proficiency (Mutisya, Rotich & Rotich, 2013). This…
Dividing Fractions Using an Area Model: A Look at In-Service Teachers' Understanding
ERIC Educational Resources Information Center
Lamberg, Teruni; Wiest, Lynda R.
2015-01-01
The paper reports an investigation into how a group of elementary and middle school teachers collectively attempted to solve and understand a fraction division problem using an area model. Solving the word problem required that teachers determine how many two-thirds fit into three-fourths. The teachers struggled to conceptualise fraction division,…
Fast Combinatorial Algorithm for the Solution of Linearly Constrained Least Squares Problems
Van Benthem, Mark H.; Keenan, Michael R.
2008-11-11
A fast combinatorial algorithm can significantly reduce the computational burden when solving general equality and inequality constrained least squares problems with large numbers of observation vectors. The combinatorial algorithm provides a mathematically rigorous solution and operates at great speed by reorganizing the calculations to take advantage of the combinatorial nature of the problems to be solved. The combinatorial algorithm exploits the structure that exists in large-scale problems in order to minimize the number of arithmetic operations required to obtain a solution.
Problem solving in the borderland between mathematics and physics
NASA Astrophysics Data System (ADS)
Jensen, Jens Højgaard; Niss, Martin; Jankvist, Uffe Thomas
2017-01-01
The article addresses the problématique of where mathematization is taught in the educational system, and who teaches it. Mathematization is usually not a part of mathematics programs at the upper secondary level, but we argue that physics teaching has something to offer in this respect, if it focuses on solving so-called unformalized problems, where a major challenge is to formalize the problems in mathematics and physics terms. We analyse four concrete examples of unformalized problems for which the formalization involves different order of mathematization and applying physics to the problem, but all require mathematization. The analysis leads to the formulation of a model by which we attempt to capture the important steps of the process of solving unformalized problems by means of mathematization and physicalization.
Ruocco, Anthony C.; Rodrigo, Achala H.; Lam, Jaeger; Di Domenico, Stefano I.; Graves, Bryanna; Ayaz, Hasan
2014-01-01
Problem-solving is an executive function subserved by a network of neural structures of which the dorsolateral prefrontal cortex (DLPFC) is central. Whereas several studies have evaluated the role of the DLPFC in problem-solving, few standardized tasks have been developed specifically for use with functional neuroimaging. The current study adapted a measure with established validity for the assessment of problem-solving abilities to design a test more suitable for functional neuroimaging protocols. The Scarborough adaptation of the Tower of London (S-TOL) was administered to 38 healthy adults while hemodynamic oxygenation of the PFC was measured using 16-channel continuous-wave functional near-infrared spectroscopy (fNIRS). Compared to a baseline condition, problems that required two or three steps to achieve a goal configuration were associated with higher activation in the left DLPFC and deactivation in the medial PFC. Individuals scoring higher in trait deliberation showed consistently higher activation in the left DLPFC regardless of task difficulty, whereas individuals lower in this trait displayed less activation when solving simple problems. Based on these results, the S-TOL may serve as a standardized task to evaluate problem-solving abilities in functional neuroimaging studies. PMID:24734017
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.
Generalizing Backtrack-Free Search: A Framework for Search-Free Constraint Satisfaction
NASA Technical Reports Server (NTRS)
Jonsson, Ari K.; Frank, Jeremy
2000-01-01
Tractable classes of constraint satisfaction problems are of great importance in artificial intelligence. Identifying and taking advantage of such classes can significantly speed up constraint problem solving. In addition, tractable classes are utilized in applications where strict worst-case performance guarantees are required, such as constraint-based plan execution. In this work, we present a formal framework for search-free (backtrack-free) constraint satisfaction. The framework is based on general procedures, rather than specific propagation techniques, and thus generalizes existing techniques in this area. We also relate search-free problem solving to the notion of decision sets and use the result to provide a constructive criterion that is sufficient to guarantee search-free problem solving.
Regularization and computational methods for precise solution of perturbed orbit transfer problems
NASA Astrophysics Data System (ADS)
Woollands, Robyn Michele
The author has developed a suite of algorithms for solving the perturbed Lambert's problem in celestial mechanics. These algorithms have been implemented as a parallel computation tool that has broad applicability. This tool is composed of four component algorithms and each provides unique benefits for solving a particular type of orbit transfer problem. The first one utilizes a Keplerian solver (a-iteration) for solving the unperturbed Lambert's problem. This algorithm not only provides a "warm start" for solving the perturbed problem but is also used to identify which of several perturbed solvers is best suited for the job. The second algorithm solves the perturbed Lambert's problem using a variant of the modified Chebyshev-Picard iteration initial value solver that solves two-point boundary value problems. This method converges over about one third of an orbit and does not require a Newton-type shooting method and thus no state transition matrix needs to be computed. The third algorithm makes use of regularization of the differential equations through the Kustaanheimo-Stiefel transformation and extends the domain of convergence over which the modified Chebyshev-Picard iteration two-point boundary value solver will converge, from about one third of an orbit to almost a full orbit. This algorithm also does not require a Newton-type shooting method. The fourth algorithm uses the method of particular solutions and the modified Chebyshev-Picard iteration initial value solver to solve the perturbed two-impulse Lambert problem over multiple revolutions. The method of particular solutions is a shooting method but differs from the Newton-type shooting methods in that it does not require integration of the state transition matrix. The mathematical developments that underlie these four algorithms are derived in the chapters of this dissertation. For each of the algorithms, some orbit transfer test cases are included to provide insight on accuracy and efficiency of these individual algorithms. Following this discussion, the combined parallel algorithm, known as the unified Lambert tool, is presented and an explanation is given as to how it automatically selects which of the three perturbed solvers to compute the perturbed solution for a particular orbit transfer. The unified Lambert tool may be used to determine a single orbit transfer or for generating of an extremal field map. A case study is presented for a mission that is required to rendezvous with two pieces of orbit debris (spent rocket boosters). The unified Lambert tool software developed in this dissertation is already being utilized by several industrial partners and we are confident that it will play a significant role in practical applications, including solution of Lambert problems that arise in the current applications focused on enhanced space situational awareness.
Eye Movements Reveal Students' Strategies in Simple Equation Solving
ERIC Educational Resources Information Center
Susac, Ana; Bubic, Andreja; Kaponja, Jurica; Planinic, Maja; Palmovic, Marijan
2014-01-01
Equation rearrangement is an important skill required for problem solving in mathematics and science. Eye movements of 40 university students were recorded while they were rearranging simple algebraic equations. The participants also reported on their strategies during equation solving in a separate questionnaire. The analysis of the behavioral…
Wachtel, Ruth E.; Dexter, Franklin
2010-01-01
Background Residency programs accredited by the ACGME are required to teach core competencies, including systems-based practice (SBP). Projects are important for satisfying this competency, but the level of knowledge and problem-solving skills required presupposes a basic understanding of the field. The responsibilities of anesthesiologists include the coordination of patient flow in the surgical suite. Familiarity with this topic is crucial for many improvement projects. Intervention A course in operations research for surgical services was originally developed for hospital administration students. It satisfies 2 of the Institute of Medicine's core competencies for health professionals: evidence-based practice and work in interdisciplinary teams. The course lasts 3.5 days (eg, 2 weekends) and consists of 45 cognitive objectives taught using 7 published articles, 10 lectures, and 156 computer-assisted problem-solving exercises based on 17 case studies. We tested the hypothesis that the cognitive objectives of the curriculum provide the knowledge and problem-solving skills necessary to perform projects that satisfy the SBP competency. Standardized terminology was used to define each component of the SBP competency for the minimum level of knowledge needed. The 8 components of the competency were examined independently. Findings Most cognitive objectives contributed to at least 4 of the 8 core components of the SBP competency. Each component of SBP is addressed at the minimum requirement level of exemplify by at least 6 objectives. There is at least 1 cognitive objective at the level of summarize for each SBP component. Conclusions A curriculum in operating room management can provide the knowledge and problem-solving skills anesthesiologists need for participation in projects that satisfy the SBP competency. PMID:22132289
A multidisciplinary approach to solving computer related vision problems.
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.
Knowledge acquisition for case-based reasoning systems
NASA Technical Reports Server (NTRS)
Riesbeck, Christopher K.
1988-01-01
Case-based reasoning (CBR) is a simple idea: solve new problems by adapting old solutions to similar problems. The CBR approach offers several potential advantages over rule-based reasoning: rules are not combined blindly in a search for solutions, solutions can be explained in terms of concrete examples, and performance can improve automatically as new problems are solved and added to the case library. Moving CBR for the university research environment to the real world requires smooth interfaces for getting knowledge from experts. Described are the basic elements of an interface for acquiring three basic bodies of knowledge that any case-based reasoner requires: the case library of problems and their solutions, the analysis rules that flesh out input problem specifications so that relevant cases can be retrieved, and the adaptation rules that adjust old solutions to fit new problems.
Collaborative learning in networks.
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
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
Anderson, John R; Betts, Shawn; Ferris, Jennifer L; Fincham, Jon M
2011-03-01
Students were taught an algorithm for solving a new class of mathematical problems. Occasionally in the sequence of problems, they encountered exception problems that required that they extend the algorithm. Regular and exception problems were associated with different patterns of brain activation. Some regions showed a Cognitive pattern of being active only until the problem was solved and no difference between regular or exception problems. Other regions showed a Metacognitive pattern of greater activity for exception problems and activity that extended into the post-solution period, particularly when an error was made. The Cognitive regions included some of parietal and prefrontal regions associated with the triple-code theory of (Dehaene, S., Piazza, M., Pinel, P., & Cohen, L. (2003). Three parietal circuits for number processing. Cognitive Neuropsychology, 20, 487-506) and associated with algebra equation solving in the ACT-R theory (Anderson, J. R. (2005). Human symbol manipulation within an 911 integrated cognitive architecture. Cognitive science, 29, 313-342. Metacognitive regions included the superior prefrontal gyrus, the angular gyrus of the triple-code theory, and frontopolar regions.
Custers, Eugène J F M
2013-08-01
Recently, human reasoning, problem solving, and decision making have been viewed as products of two separate systems: "System 1," the unconscious, intuitive, or nonanalytic system, and "System 2," the conscious, analytic, or reflective system. This view has penetrated the medical education literature, yet the idea of two independent dichotomous cognitive systems is not entirely without problems.This article outlines the difficulties of this "two-system view" and presents an alternative, developed by K.R. Hammond and colleagues, called cognitive continuum theory (CCT). CCT is featured by three key assumptions. First, human reasoning, problem solving, and decision making can be arranged on a cognitive continuum, with pure intuition at one end, pure analysis at the other, and a large middle ground called "quasirationality." Second, the nature and requirements of the cognitive task, as perceived by the person performing the task, determine to a large extent whether a task will be approached more intuitively or more analytically. Third, for optimal task performance, this approach needs to match the cognitive properties and requirements of the task. Finally, the author makes a case that CCT is better able than a two-system view to describe medical problem solving and clinical reasoning and that it provides clear clues for how to organize training in clinical reasoning.
Holmberg, Leif
2007-11-01
A health-care organization simultaneously belongs to two different institutional value patterns: a professional and an administrative value pattern. At the administrative level, medical problem-solving processes are generally perceived as the efficient application of familiar chains of activities to well-defined problems; and a low task uncertainty is therefore assumed at the work-floor level. This assumption is further reinforced through clinical pathways and other administrative guidelines. However, studies have shown that in clinical practice such administrative guidelines are often considered inadequate and difficult to implement mainly because physicians generally perceive task uncertainty to be high and that the guidelines do not cover the scope of encountered deviations. The current administrative level guidelines impose uniform structural features that meet the requirement for low task uncertainty. Within these structural constraints, physicians must organize medical problem-solving processes to meet any task uncertainty that may be encountered. Medical problem-solving processes with low task uncertainty need to be organized independently of processes with high task uncertainty. Each process must be evaluated according to different performance standards and needs to have autonomous administrative guideline models. Although clinical pathways seem appropriate when there is low task uncertainty, other kinds of guidelines are required when the task uncertainty is high.
Graphing as a Problem-Solving Strategy.
ERIC Educational Resources Information Center
Cohen, Donald
1984-01-01
The focus is on how line graphs can be used to approximate solutions to rate problems and to suggest equations that offer exact algebraic solutions to the problem. Four problems requiring progressively greater graphing sophistication are presented plus four exercises. (MNS)
ERIC Educational Resources Information Center
Sousa, Fernando Cardoso; Monteiro, Ileana Pardal; Pellissier, René
2014-01-01
This article presents the development of a small-world network using an adapted version of the large-group problem-solving method "Future Search." Two management classes in a higher education setting were selected and required to plan a project. The students completed a survey focused on the frequency of communications before and after…
Thinking inside the Tool Box: Creativity, Constraints, and the Colossal Portraits of Chuck Close
ERIC Educational Resources Information Center
Stokes, Patricia D.
2014-01-01
This article presents a problem-solving model to examine the often problematic relationship between expertise and creativity. The model has two premises, each the opposite of a common cliché. The first cliché asserts that creativity requires thinking outside-the-box. The first premise argues that experts can only think and problem solve inside the…
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…
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…
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…
The Effect of Time on Difficulty of Learning (The Case of Problem Solving with Natural Numbers)
ERIC Educational Resources Information Center
Kaya, Deniz; Kesan, Cenk
2017-01-01
The main purpose of this study is to determine the time-dependent learning difficulty of "solving problems that require making four operations with natural numbers" of the sixth grade students. The study, adopting the scanning model, consisted of a total of 140 students, including 69 female and 71 male students at the sixth grade. Data…
ERIC Educational Resources Information Center
Utah State Office of Education, Salt Lake City.
This guide, which has been developed for Utah's home economics and family life education program, contains materials for use in teaching a life management course emphasizing the problem-solving skills required for independent living. Discussed first are the assumptions underlying the curriculum, development of the guide, and suggestions for its…
Complex collaborative problem-solving processes in mission control.
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.
An investigation of aviator problem-solving skills as they relate to amount of total flight time
NASA Astrophysics Data System (ADS)
Guilkey, James Elwood, Jr.
As aircraft become increasingly more reliable, safety issues have shifted towards the human component of flight, the pilot. Jensen (1995) indicated that 80% of all General Aviation (GA) accidents are the result, at least in part, of errors committed by the aviator. One major focus of current research involves aviator decision making (ADM). ADM combines a broad range of psychological factors including personality, attitude, and motivation. This approach fails to isolate certain key components such as aviator problem-solving (APS) which are paramount to safe operations. It should be noted that there is a clear delineation between problem-solving and decision making and not assume that they are homogenous. For years, researchers, industry, and the Federal Aviation Administration (FAA) have depended on total flight hours as the standard by which to judge aviator expertise. A pilot with less than a prescribed number of hours is considered a novice while those above that mark are considered experts. The reliance on time as a predictor of performance may be accurate when considering skills which are required on every flight (i.e., takeoff and landing) but we can't assume that this holds true for all aspects of aviator expertise. Complex problem-solving for example, is something that is rarely faced during the normal course of flying. In fact, there are a myriad of procedures and FAA mandated regulations designed to assist pilots in avoiding problems. Thus, one should not assume that aviator problem-solving skills will increase over time. This study investigated the relationship between problem-solving skills of general aviation pilots and total number of flight hours. It was discovered that flight time is not a good predictor of problem-solving performance. There were two distinct strategies that were identified in the study. The first, progressive problem solving (PPS) was characterized by a stepwise method in which pilots gathered information, formulated hypotheses, and evaluated outcomes. Both high time as well as low time pilots demonstrated this approach. The second method, termed knee-jerk decision making was distinguished by a lack of problem-solving abilities and involved an almost immediate decision with little if any supporting information. Again both high and low time pilots performed in this manner. The result of these findings is a recommendation that the FAA adopt new training methods which will allow pilots to develop the skills required to handle critical inflight situations.
Lions (Panthera leo) solve, learn, and remember a novel resource acquisition problem.
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.
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 application of artificial intelligence techniques to large distributed networks
NASA Technical Reports Server (NTRS)
Dubyah, R.; Smith, T. R.; Star, J. L.
1985-01-01
Data accessibility and transfer of information, including the land resources information system pilot, are structured as large computer information networks. These pilot efforts include the reduction of the difficulty to find and use data, reducing processing costs, and minimize incompatibility between data sources. Artificial Intelligence (AI) techniques were suggested to achieve these goals. The applicability of certain AI techniques are explored in the context of distributed problem solving systems and the pilot land data system (PLDS). The topics discussed include: PLDS and its data processing requirements, expert systems and PLDS, distributed problem solving systems, AI problem solving paradigms, query processing, and distributed data bases.
Donnarumma, Francesco; Maisto, Domenico; Pezzulo, Giovanni
2016-01-01
How do humans and other animals face novel problems for which predefined solutions are not available? Human problem solving links to flexible reasoning and inference rather than to slow trial-and-error learning. It has received considerable attention since the early days of cognitive science, giving rise to well known cognitive architectures such as SOAR and ACT-R, but its computational and brain mechanisms remain incompletely known. Furthermore, it is still unclear whether problem solving is a “specialized” domain or module of cognition, in the sense that it requires computations that are fundamentally different from those supporting perception and action systems. Here we advance a novel view of human problem solving as probabilistic inference with subgoaling. In this perspective, key insights from cognitive architectures are retained such as the importance of using subgoals to split problems into subproblems. However, here the underlying computations use probabilistic inference methods analogous to those that are increasingly popular in the study of perception and action systems. To test our model we focus on the widely used Tower of Hanoi (ToH) task, and show that our proposed method can reproduce characteristic idiosyncrasies of human problem solvers: their sensitivity to the “community structure” of the ToH and their difficulties in executing so-called “counterintuitive” movements. Our analysis reveals that subgoals have two key roles in probabilistic inference and problem solving. First, prior beliefs on (likely) useful subgoals carve the problem space and define an implicit metric for the problem at hand—a metric to which humans are sensitive. Second, subgoals are used as waypoints in the probabilistic problem solving inference and permit to find effective solutions that, when unavailable, lead to problem solving deficits. Our study thus suggests that a probabilistic inference scheme enhanced with subgoals provides a comprehensive framework to study problem solving and its deficits. PMID:27074140
Donnarumma, Francesco; Maisto, Domenico; Pezzulo, Giovanni
2016-04-01
How do humans and other animals face novel problems for which predefined solutions are not available? Human problem solving links to flexible reasoning and inference rather than to slow trial-and-error learning. It has received considerable attention since the early days of cognitive science, giving rise to well known cognitive architectures such as SOAR and ACT-R, but its computational and brain mechanisms remain incompletely known. Furthermore, it is still unclear whether problem solving is a "specialized" domain or module of cognition, in the sense that it requires computations that are fundamentally different from those supporting perception and action systems. Here we advance a novel view of human problem solving as probabilistic inference with subgoaling. In this perspective, key insights from cognitive architectures are retained such as the importance of using subgoals to split problems into subproblems. However, here the underlying computations use probabilistic inference methods analogous to those that are increasingly popular in the study of perception and action systems. To test our model we focus on the widely used Tower of Hanoi (ToH) task, and show that our proposed method can reproduce characteristic idiosyncrasies of human problem solvers: their sensitivity to the "community structure" of the ToH and their difficulties in executing so-called "counterintuitive" movements. Our analysis reveals that subgoals have two key roles in probabilistic inference and problem solving. First, prior beliefs on (likely) useful subgoals carve the problem space and define an implicit metric for the problem at hand-a metric to which humans are sensitive. Second, subgoals are used as waypoints in the probabilistic problem solving inference and permit to find effective solutions that, when unavailable, lead to problem solving deficits. Our study thus suggests that a probabilistic inference scheme enhanced with subgoals provides a comprehensive framework to study problem solving and its deficits.
Investigating the effect of mental set on insight problem solving.
Ollinger, Michael; Jones, Gary; Knoblich, Günther
2008-01-01
Mental set is the tendency to solve certain problems in a fixed way based on previous solutions to similar problems. The moment of insight occurs when a problem cannot be solved using solution methods suggested by prior experience and the problem solver suddenly realizes that the solution requires different solution methods. Mental set and insight have often been linked together and yet no attempt thus far has systematically examined the interplay between the two. Three experiments are presented that examine the extent to which sets of noninsight and insight problems affect the subsequent solutions of insight test problems. The results indicate a subtle interplay between mental set and insight: when the set involves noninsight problems, no mental set effects are shown for the insight test problems, yet when the set involves insight problems, both facilitation and inhibition can be seen depending on the type of insight problem presented in the set. A two process model is detailed to explain these findings that combines the representational change mechanism with that of proceduralization.
The development and nature of problem-solving among first-semester calculus students
NASA Astrophysics Data System (ADS)
Dawkins, Paul Christian; Mendoza Epperson, James A.
2014-08-01
This study investigates interactions between calculus learning and problem-solving in the context of two first-semester undergraduate calculus courses in the USA. We assessed students' problem-solving abilities in a common US calculus course design that included traditional lecture and assessment with problem-solving-oriented labs. We investigate this blended instruction as a local representative of the US calculus reform movements that helped foster it. These reform movements tended to emphasize problem-solving as well as multiple mathematical registers and quantitative modelling. Our statistical analysis reveals the influence of the blended traditional/reform calculus instruction on students' ability to solve calculus-related, non-routine problems through repeated measures over the semester. The calculus instruction in this study significantly improved students' performance on non-routine problems, though performance improved more regarding strategies and accuracy than it did for drawing conclusions and providing justifications. We identified problem-solving behaviours that characterized top performance or attrition in the course. Top-performing students displayed greater algebraic proficiency, calculus skills, and more general heuristics than their peers, but overused algebraic techniques even when they proved cumbersome or inappropriate. Students who subsequently withdrew from calculus often lacked algebraic fluency and understanding of the graphical register. The majority of participants, when given a choice, relied upon less sophisticated trial-and-error approaches in the numerical register and rarely used the graphical register, contrary to the goals of US calculus reform. We provide explanations for these patterns in students' problem-solving performance in view of both their preparation for university calculus and the courses' assessment structure, which preferentially rewarded algebraic reasoning. While instruction improved students' problem-solving performance, we observe that current instruction requires ongoing refinement to help students develop multi-register fluency and the ability to model quantitatively, as is called for in current US standards for mathematical instruction.
Review on solving the forward problem in EEG source analysis
Hallez, Hans; Vanrumste, Bart; Grech, Roberta; Muscat, Joseph; De Clercq, Wim; Vergult, Anneleen; D'Asseler, Yves; Camilleri, Kenneth P; Fabri, Simon G; Van Huffel, Sabine; Lemahieu, Ignace
2007-01-01
Background The aim of electroencephalogram (EEG) source localization is to find the brain areas responsible for EEG waves of interest. It consists of solving forward and inverse problems. The forward problem is solved by starting from a given electrical source and calculating the potentials at the electrodes. These evaluations are necessary to solve the inverse problem which is defined as finding brain sources which are responsible for the measured potentials at the EEG electrodes. Methods While other reviews give an extensive summary of the both forward and inverse problem, this review article focuses on different aspects of solving the forward problem and it is intended for newcomers in this research field. Results It starts with focusing on the generators of the EEG: the post-synaptic potentials in the apical dendrites of pyramidal neurons. These cells generate an extracellular current which can be modeled by Poisson's differential equation, and Neumann and Dirichlet boundary conditions. The compartments in which these currents flow can be anisotropic (e.g. skull and white matter). In a three-shell spherical head model an analytical expression exists to solve the forward problem. During the last two decades researchers have tried to solve Poisson's equation in a realistically shaped head model obtained from 3D medical images, which requires numerical methods. The following methods are compared with each other: the boundary element method (BEM), the finite element method (FEM) and the finite difference method (FDM). In the last two methods anisotropic conducting compartments can conveniently be introduced. Then the focus will be set on the use of reciprocity in EEG source localization. It is introduced to speed up the forward calculations which are here performed for each electrode position rather than for each dipole position. Solving Poisson's equation utilizing FEM and FDM corresponds to solving a large sparse linear system. Iterative methods are required to solve these sparse linear systems. The following iterative methods are discussed: successive over-relaxation, conjugate gradients method and algebraic multigrid method. Conclusion Solving the forward problem has been well documented in the past decades. In the past simplified spherical head models are used, whereas nowadays a combination of imaging modalities are used to accurately describe the geometry of the head model. Efforts have been done on realistically describing the shape of the head model, as well as the heterogenity of the tissue types and realistically determining the conductivity. However, the determination and validation of the in vivo conductivity values is still an important topic in this field. In addition, more studies have to be done on the influence of all the parameters of the head model and of the numerical techniques on the solution of the forward problem. PMID:18053144
Visual modeling in an analysis of multidimensional data
NASA Astrophysics Data System (ADS)
Zakharova, A. A.; Vekhter, E. V.; Shklyar, A. V.; Pak, A. J.
2018-01-01
The article proposes an approach to solve visualization problems and the subsequent analysis of multidimensional data. Requirements to the properties of visual models, which were created to solve analysis problems, are described. As a perspective direction for the development of visual analysis tools for multidimensional and voluminous data, there was suggested an active use of factors of subjective perception and dynamic visualization. Practical results of solving the problem of multidimensional data analysis are shown using the example of a visual model of empirical data on the current state of studying processes of obtaining silicon carbide by an electric arc method. There are several results of solving this problem. At first, an idea of possibilities of determining the strategy for the development of the domain, secondly, the reliability of the published data on this subject, and changes in the areas of attention of researchers over time.
Experimental realization of a one-way quantum computer algorithm solving Simon's problem.
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.
GRIPs (Group Investigation Problems) for Introductory Physics
NASA Astrophysics Data System (ADS)
Moore, Thomas A.
2006-12-01
GRIPs lie somewhere between homework problems and simple labs: they are open-ended questions that require a mixture of problem-solving skills and hands-on experimentation to solve practical puzzles involving simple physical objects. In this talk, I will describe three GRIPs that I developed for a first-semester introductory calculus-based physics course based on the "Six Ideas That Shaped Physics" text. I will discuss the design of the three GRIPs we used this past fall, our experience in working with students on these problems, and students' response as reported on course evaluations.
Automated Conflict Resolution, Arrival Management and Weather Avoidance for ATM
NASA Technical Reports Server (NTRS)
Erzberger, H.; Lauderdale, Todd A.; Chu, Yung-Cheng
2010-01-01
The paper describes a unified solution to three types of separation assurance problems that occur in en-route airspace: separation conflicts, arrival sequencing, and weather-cell avoidance. Algorithms for solving these problems play a key role in the design of future air traffic management systems such as NextGen. Because these problems can arise simultaneously in any combination, it is necessary to develop integrated algorithms for solving them. A unified and comprehensive solution to these problems provides the foundation for a future air traffic management system that requires a high level of automation in separation assurance. The paper describes the three algorithms developed for solving each problem and then shows how they are used sequentially to solve any combination of these problems. The first algorithm resolves loss-of-separation conflicts and is an evolution of an algorithm described in an earlier paper. The new version generates multiple resolutions for each conflict and then selects the one giving the least delay. Two new algorithms, one for sequencing and merging of arrival traffic, referred to as the Arrival Manager, and the other for weather-cell avoidance are the major focus of the paper. Because these three problems constitute a substantial fraction of the workload of en-route controllers, integrated algorithms to solve them is a basic requirement for automated separation assurance. The paper also reviews the Advanced Airspace Concept, a proposed design for a ground-based system that postulates redundant systems for separation assurance in order to achieve both high levels of safety and airspace capacity. It is proposed that automated separation assurance be introduced operationally in several steps, each step reducing controller workload further while increasing airspace capacity. A fast time simulation was used to determine performance statistics of the algorithm at up to 3 times current traffic levels.
Graph pyramids as models of human problem solving
NASA Astrophysics Data System (ADS)
Pizlo, Zygmunt; Li, Zheng
2004-05-01
Prior theories have assumed that human problem solving involves estimating distances among states and performing search through the problem space. The role of mental representation in those theories was minimal. Results of our recent experiments suggest that humans are able to solve some difficult problems quickly and accurately. Specifically, in solving these problems humans do not seem to rely on distances or on search. It is quite clear that producing good solutions without performing search requires a very effective mental representation. In this paper we concentrate on studying the nature of this representation. Our theory takes the form of a graph pyramid. To verify the psychological plausibility of this theory we tested subjects in a Euclidean Traveling Salesman Problem in the presence of obstacles. The role of the number and size of obstacles was tested for problems with 6-50 cities. We analyzed the effect of experimental conditions on solution time per city and on solution error. The main result is that time per city is systematically affected only by the size of obstacles, but not by their number, or by the number of cities.
NASA Astrophysics Data System (ADS)
Prasetyo, H.; Alfatsani, M. A.; Fauza, G.
2018-05-01
The main issue in vehicle routing problem (VRP) is finding the shortest route of product distribution from the depot to outlets to minimize total cost of distribution. Capacitated Closed Vehicle Routing Problem with Time Windows (CCVRPTW) is one of the variants of VRP that accommodates vehicle capacity and distribution period. Since the main problem of CCVRPTW is considered a non-polynomial hard (NP-hard) problem, it requires an efficient and effective algorithm to solve the problem. This study was aimed to develop Biased Random Key Genetic Algorithm (BRKGA) that is combined with local search to solve the problem of CCVRPTW. The algorithm design was then coded by MATLAB. Using numerical test, optimum algorithm parameters were set and compared with the heuristic method and Standard BRKGA to solve a case study on soft drink distribution. Results showed that BRKGA combined with local search resulted in lower total distribution cost compared with the heuristic method. Moreover, the developed algorithm was found to be successful in increasing the performance of Standard BRKGA.
A high-accuracy optical linear algebra processor for finite element applications
NASA Technical Reports Server (NTRS)
Casasent, D.; Taylor, B. K.
1984-01-01
Optical linear processors are computationally efficient computers for solving matrix-matrix and matrix-vector oriented problems. Optical system errors limit their dynamic range to 30-40 dB, which limits their accuray to 9-12 bits. Large problems, such as the finite element problem in structural mechanics (with tens or hundreds of thousands of variables) which can exploit the speed of optical processors, require the 32 bit accuracy obtainable from digital machines. To obtain this required 32 bit accuracy with an optical processor, the data can be digitally encoded, thereby reducing the dynamic range requirements of the optical system (i.e., decreasing the effect of optical errors on the data) while providing increased accuracy. This report describes a new digitally encoded optical linear algebra processor architecture for solving finite element and banded matrix-vector problems. A linear static plate bending case study is described which quantities the processor requirements. Multiplication by digital convolution is explained, and the digitally encoded optical processor architecture is advanced.
Efficient dual approach to distance metric learning.
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.
1984-04-01
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ERIC Educational Resources Information Center
Carlgren, Terresa
2013-01-01
The skills of communication, critical thinking, and problem solving are essential to thriving as a citizen in the 21st century. These skills are required in order to contribute as a member of society, operate effectively in post-secondary institutions, and be competitive in the global market. Unfortunately they are not always intuitive or simple…
Integrated identification, modeling and control with applications
NASA Astrophysics Data System (ADS)
Shi, Guojun
This thesis deals with the integration of system design, identification, modeling and control. In particular, six interdisciplinary engineering problems are addressed and investigated. Theoretical results are established and applied to structural vibration reduction and engine control problems. First, the data-based LQG control problem is formulated and solved. It is shown that a state space model is not necessary to solve this problem; rather a finite sequence from the impulse response is the only model data required to synthesize an optimal controller. The new theory avoids unnecessary reliance on a model, required in the conventional design procedure. The infinite horizon model predictive control problem is addressed for multivariable systems. The basic properties of the receding horizon implementation strategy is investigated and the complete framework for solving the problem is established. The new theory allows the accommodation of hard input constraints and time delays. The developed control algorithms guarantee the closed loop stability. A closed loop identification and infinite horizon model predictive control design procedure is established for engine speed regulation. The developed algorithms are tested on the Cummins Engine Simulator and desired results are obtained. A finite signal-to-noise ratio model is considered for noise signals. An information quality index is introduced which measures the essential information precision required for stabilization. The problems of minimum variance control and covariance control are formulated and investigated. Convergent algorithms are developed for solving the problems of interest. The problem of the integrated passive and active control design is addressed in order to improve the overall system performance. A design algorithm is developed, which simultaneously finds: (i) the optimal values of the stiffness and damping ratios for the structure, and (ii) an optimal output variance constrained stabilizing controller such that the active control energy is minimized. A weighted q-Markov COVER method is introduced for identification with measurement noise. The result is use to develop an iterative closed loop identification/control design algorithm. The effectiveness of the algorithm is illustrated by experimental results.
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.
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.
Divide et impera: subgoaling reduces the complexity of probabilistic inference and problem solving
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
Chalmers, Charlotte; Leathem, Janet; Bennett, Simon; McNaughton, Harry; Mahawish, Karim
2017-11-26
To investigate the efficacy of problem solving therapy for reducing the emotional distress experienced by younger stroke survivors. A non-randomized waitlist controlled design was used to compare outcome measures for the treatment group and a waitlist control group at baseline and post-waitlist/post-therapy. After the waitlist group received problem solving therapy an analysis was completed on the pooled outcome measures at baseline, post-treatment, and three-month follow-up. Changes on outcome measures between baseline and post-treatment (n = 13) were not significantly different between the two groups, treatment (n = 13), and the waitlist control group (n = 16) (between-subject design). The pooled data (n = 28) indicated that receiving problem solving therapy significantly reduced participants levels of depression and anxiety and increased quality of life levels from baseline to follow up (within-subject design), however, methodological limitations, such as the lack of a control group reduce the validity of this finding. The between-subject results suggest that there was no significant difference between those that received problem solving therapy and a waitlist control group between baseline and post-waitlist/post-therapy. The within-subject design suggests that problem solving therapy may be beneficial for younger stroke survivors when they are given some time to learn and implement the skills into their day to day life. However, additional research with a control group is required to investigate this further. This study provides limited evidence for the provision of support groups for younger stroke survivors post stroke, however, it remains unclear about what type of support this should be. Implications for Rehabilitation Problem solving therapy is no more effective for reducing post stroke distress than a wait-list control group. Problem solving therapy may be perceived as helpful and enjoyable by younger stroke survivors. Younger stroke survivors may use the skills learnt from problem solving therapy to solve problems in their day to day lives. Younger stroke survivors may benefit from age appropriate psychological support; however, future research is needed to determine what type of support this should be.
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.
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
NASA Technical Reports Server (NTRS)
Vanderplaats, Garrett; Townsend, James C. (Technical Monitor)
2002-01-01
The purpose of this research under the NASA Small Business Innovative Research program was to develop algorithms and associated software to solve very large nonlinear, constrained optimization tasks. Key issues included efficiency, reliability, memory, and gradient calculation requirements. This report describes the general optimization problem, ten candidate methods, and detailed evaluations of four candidates. The algorithm chosen for final development is a modern recreation of a 1960s external penalty function method that uses very limited computer memory and computational time. Although of lower efficiency, the new method can solve problems orders of magnitude larger than current methods. The resulting BIGDOT software has been demonstrated on problems with 50,000 variables and about 50,000 active constraints. For unconstrained optimization, it has solved a problem in excess of 135,000 variables. The method includes a technique for solving discrete variable problems that finds a "good" design, although a theoretical optimum cannot be guaranteed. It is very scalable in that the number of function and gradient evaluations does not change significantly with increased problem size. Test cases are provided to demonstrate the efficiency and reliability of the methods and software.
NASA Astrophysics Data System (ADS)
Terrell, Rosalind Stephanie
2001-12-01
Because paper-and-pencil testing provides limited knowledge about what students know about chemical phenomena, we have developed video-based demonstrations to broaden measurement of student learning. For example, students might be shown a video demonstrating equilibrium shifts. Two methods for viewing equilibrium shifts are changing the concentration of the reactants and changing the temperature of the system. The students are required to combine the data collected from the video and their knowledge of chemistry to determine which way the equilibrium shifts. Video-based demonstrations are important techniques for measuring student learning because they require students to apply conceptual knowledge learned in class to a specific chemical problem. This study explores how video-based demonstration assessment tasks affect problem-solving processes, test anxiety, chemistry anxiety and achievement in general chemistry students. Several instruments were used to determine students' knowledge about chemistry, students' test and chemistry anxiety before and after treatment. Think-aloud interviews were conducted to determine students' problem-solving processes after treatment. The treatment group was compared to a control group and a group watching video demonstrations. After treatment students' anxiety increased and achievement decreased. There were also no significant differences found in students' problem-solving processes following treatment. These negative findings may be attributed to several factors that will be explored in this study.
Climate change: could it help develop 'adaptive expertise'?
Bell, Erica; Horton, Graeme; Blashki, Grant; Seidel, Bastian M
2012-05-01
Preparing health practitioners to respond to the rising burden of disease from climate change is emerging as a priority in health workforce policy and planning. However, this issue is hardly represented in the medical education research. The rapidly evolving wide range of direct and indirect consequences of climate change will require health professionals to have not only broad content knowledge but also flexibility and responsiveness to diverse regional conditions as part of complex health problem-solving and adaptation. It is known that adaptive experts may not necessarily be quick at solving familiar problems, but they do creatively seek to better solve novel problems. This may be the result of an acquired approach to practice or a pathway that can be fostered by learning environments. It is also known that building adaptive expertise in medical education involves putting students on a learning pathway that requires them to have, first, the motivation to innovatively problem-solve and, second, exposure to diverse content material, meaningfully presented. Including curriculum content on the health effects of climate change could help meet these two conditions for some students at least. A working definition and illustrative competencies for adaptive expertise for climate change, as well as examples of teaching and assessment approaches extrapolated from rural curricula, are provided.
High school students' understanding and problem solving in population genetics
NASA Astrophysics Data System (ADS)
Soderberg, Patti D.
This study is an investigation of student understanding of population genetics and how students developed, used and revised conceptual models to solve problems. The students in this study participated in three rounds of problem solving. The first round involved the use of a population genetics model to predict the number of carriers in a population. The second round required them to revise their model of simple dominance population genetics to make inferences about populations containing three phenotype variations. The third round of problem solving required the students to revise their model of population genetics to explain anomalous data where the proportions of males and females with a trait varied significantly. As the students solved problems, they were involved in basic scientific processes as they observed population phenomena, constructed explanatory models to explain the data they observed, and attempted to persuade their peers as to the adequacy of their models. In this study, the students produced new knowledge about the genetics of a trait in a population through the revision and use of explanatory population genetics models using reasoning that was similar to what scientists do. The students learned, used and revised a model of Hardy-Weinberg equilibrium to generate and test hypotheses about the genetics of phenotypes given only population data. Students were also interviewed prior to and following instruction. This study suggests that a commonly held intuitive belief about the predominance of a dominant variation in populations is resistant to change, despite instruction and interferes with a student's ability to understand Hardy-Weinberg equilibrium and microevolution.
7 CFR 4280.149 - Requirements after project construction.
Code of Federal Regulations, 2010 CFR
2010-01-01
... sanitation problem has been solved. (3) The annual income and/or energy savings of the renewable energy... maintenance or operational problems associated with the facility. (6) Recommendations for development of...
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.
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.
Schulte, Fiona; Vannatta, Kathryn; Barrera, Maru
2014-02-01
The aim of this study was to explore the ability of a group social skills intervention program for childhood brain tumor survivors to effect two steps of the social information processing model: social problem solving and social performance. Participants were 15 survivors (eight men and seven women) aged 7-15 years. The intervention consisted of eight 2-h weekly sessions focused on social skills including friendship making. Social problem solving, using hypothetical scenarios, was assessed during sessions 1 and 8. Social performance was observed during intervention sessions 1, 4, and 8. Compared with session 1, significant increases were found in social performance: frequency of maintaining eye contact and social conversations with peers over the course of the intervention. No significant changes in social problem solving were noted. This pilot study is the first to report improvements related to group social skills intervention at the level of observed social performance over the course of intervention. The lack of change in social problem solving suggests that survivors may possess the social knowledge required for social situations but have difficulty enacting social behaviors. Copyright © 2013 John Wiley & Sons, Ltd.
Code of Federal Regulations, 2010 CFR
2010-01-01
...; defining and determining the extent of the problems; and formulating alternative plans, including land treatment, nonstructural or structural measures, or combinations thereof, that would solve existing problems... require only inventories of available resources and associated problems to be used by other agencies in...
Optimization techniques applied to spectrum management for communications satellites
NASA Astrophysics Data System (ADS)
Ottey, H. R.; Sullivan, T. M.; Zusman, F. S.
This paper describes user requirements, algorithms and software design features for the application of optimization techniques to the management of the geostationary orbit/spectrum resource. Relevant problems include parameter sensitivity analyses, frequency and orbit position assignment coordination, and orbit position allotment planning. It is shown how integer and nonlinear programming as well as heuristic search techniques can be used to solve these problems. Formalized mathematical objective functions that define the problems are presented. Constraint functions that impart the necessary solution bounds are described. A versatile program structure is outlined, which would allow problems to be solved in stages while varying the problem space, solution resolution, objective function and constraints.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Bledsoe, Keith C.
2015-04-01
The DiffeRential Evolution Adaptive Metropolis (DREAM) method is a powerful optimization/uncertainty quantification tool used to solve inverse transport problems in Los Alamos National Laboratory’s INVERSE code system. The DREAM method has been shown to be adept at accurate uncertainty quantification, but it can be very computationally demanding. Previously, the DREAM method in INVERSE performed a user-defined number of particle transport calculations. This placed a burden on the user to guess the number of calculations that would be required to accurately solve any given problem. This report discusses a new approach that has been implemented into INVERSE, the Gelman-Rubin convergence metric.more » This metric automatically detects when an appropriate number of transport calculations have been completed and the uncertainty in the inverse problem has been accurately calculated. In a test problem with a spherical geometry, this method was found to decrease the number of transport calculations (and thus time required) to solve a problem by an average of over 90%. In a cylindrical test geometry, a 75% decrease was obtained.« less
Wang, Xiaofeng; Abrahamsson, Pekka
2014-01-01
For more than thirty years, it has been claimed that a way to improve software developers’ productivity and software quality is to focus on people and to provide incentives to make developers satisfied and happy. This claim has rarely been verified in software engineering research, which faces an additional challenge in comparison to more traditional engineering fields: software development is an intellectual activity and is dominated by often-neglected human factors (called human aspects in software engineering research). Among the many skills required for software development, developers must possess high analytical problem-solving skills and creativity for the software construction process. According to psychology research, affective states—emotions and moods—deeply influence the cognitive processing abilities and performance of workers, including creativity and analytical problem solving. Nonetheless, little research has investigated the correlation between the affective states, creativity, and analytical problem-solving performance of programmers. This article echoes the call to employ psychological measurements in software engineering research. We report a study with 42 participants to investigate the relationship between the affective states, creativity, and analytical problem-solving skills of software developers. The results offer support for the claim that happy developers are indeed better problem solvers in terms of their analytical abilities. The following contributions are made by this study: (1) providing a better understanding of the impact of affective states on the creativity and analytical problem-solving capacities of developers, (2) introducing and validating psychological measurements, theories, and concepts of affective states, creativity, and analytical-problem-solving skills in empirical software engineering, and (3) raising the need for studying the human factors of software engineering by employing a multidisciplinary viewpoint. PMID:24688866
Graziotin, Daniel; Wang, Xiaofeng; Abrahamsson, Pekka
2014-01-01
For more than thirty years, it has been claimed that a way to improve software developers' productivity and software quality is to focus on people and to provide incentives to make developers satisfied and happy. This claim has rarely been verified in software engineering research, which faces an additional challenge in comparison to more traditional engineering fields: software development is an intellectual activity and is dominated by often-neglected human factors (called human aspects in software engineering research). Among the many skills required for software development, developers must possess high analytical problem-solving skills and creativity for the software construction process. According to psychology research, affective states-emotions and moods-deeply influence the cognitive processing abilities and performance of workers, including creativity and analytical problem solving. Nonetheless, little research has investigated the correlation between the affective states, creativity, and analytical problem-solving performance of programmers. This article echoes the call to employ psychological measurements in software engineering research. We report a study with 42 participants to investigate the relationship between the affective states, creativity, and analytical problem-solving skills of software developers. The results offer support for the claim that happy developers are indeed better problem solvers in terms of their analytical abilities. The following contributions are made by this study: (1) providing a better understanding of the impact of affective states on the creativity and analytical problem-solving capacities of developers, (2) introducing and validating psychological measurements, theories, and concepts of affective states, creativity, and analytical-problem-solving skills in empirical software engineering, and (3) raising the need for studying the human factors of software engineering by employing a multidisciplinary viewpoint.
Adaptive leadership and person-centered care: a new approach to solving problems.
Corazzini, Kirsten N; Anderson, Ruth A
2014-01-01
Successfully transitioning to person-centered care in nursing homes requires a new approach to solving care issues. The adaptive leadership framework suggests that expert providers must support frontline caregivers in their efforts to develop high-quality, person-centered solutions.
Improvements in surface singularity analysis and design methods. [applicable to airfoils
NASA Technical Reports Server (NTRS)
Bristow, D. R.
1979-01-01
The coupling of the combined source vortex distribution of Green's potential flow function with contemporary numerical techniques is shown to provide accurate, efficient, and stable solutions to subsonic inviscid analysis and design problems for multi-element airfoils. The analysis problem is solved by direct calculation of the surface singularity distribution required to satisfy the flow tangency boundary condition. The design or inverse problem is solved by an iteration process. In this process, the geometry and the associated pressure distribution are iterated until the pressure distribution most nearly corresponding to the prescribed design distribution is obtained. Typically, five iteration cycles are required for convergence. A description of the analysis and design method is presented, along with supporting examples.
Learned navigation in unknown terrains: A retraction method
NASA Technical Reports Server (NTRS)
Rao, Nageswara S. V.; Stoltzfus, N.; Iyengar, S. Sitharama
1989-01-01
The problem of learned navigation of a circular robot R, of radius delta (is greater than or equal to 0), through a terrain whose model is not a-priori known is considered. Two-dimensional finite-sized terrains populated by an unknown (but, finite) number of simple polygonal obstacles are also considered. The number and locations of the vertices of each obstacle are unknown to R. R is equipped with a sensor system that detects all vertices and edges that are visible from its present location. In this context two problems are covered. In the visit problem, the robot is required to visit a sequence of destination points, and in the terrain model acquisition problem, the robot is required to acquire the complete model of the terrain. An algorithmic framework is presented for solving these two problems using a retraction of the freespace onto the Voronoi diagram of the terrain. Algorithms are then presented to solve the visit problem and the terrain model acquisition problem.
Analyzing Quadratic Unconstrained Binary Optimization Problems Via Multicommodity Flows
Wang, Di; Kleinberg, Robert D.
2009-01-01
Quadratic Unconstrained Binary Optimization (QUBO) problems concern the minimization of quadratic polynomials in n {0, 1}-valued variables. These problems are NP-complete, but prior work has identified a sequence of polynomial-time computable lower bounds on the minimum value, denoted by C2, C3, C4,…. It is known that C2 can be computed by solving a maximum-flow problem, whereas the only previously known algorithms for computing Ck (k > 2) require solving a linear program. In this paper we prove that C3 can be computed by solving a maximum multicommodity flow problem in a graph constructed from the quadratic function. In addition to providing a lower bound on the minimum value of the quadratic function on {0, 1}n, this multicommodity flow problem also provides some information about the coordinates of the point where this minimum is achieved. By looking at the edges that are never saturated in any maximum multicommodity flow, we can identify relational persistencies: pairs of variables that must have the same or different values in any minimizing assignment. We furthermore show that all of these persistencies can be detected by solving single-commodity flow problems in the same network. PMID:20161596
Analyzing Quadratic Unconstrained Binary Optimization Problems Via Multicommodity Flows.
Wang, Di; Kleinberg, Robert D
2009-11-28
Quadratic Unconstrained Binary Optimization (QUBO) problems concern the minimization of quadratic polynomials in n {0, 1}-valued variables. These problems are NP-complete, but prior work has identified a sequence of polynomial-time computable lower bounds on the minimum value, denoted by C(2), C(3), C(4),…. It is known that C(2) can be computed by solving a maximum-flow problem, whereas the only previously known algorithms for computing C(k) (k > 2) require solving a linear program. In this paper we prove that C(3) can be computed by solving a maximum multicommodity flow problem in a graph constructed from the quadratic function. In addition to providing a lower bound on the minimum value of the quadratic function on {0, 1}(n), this multicommodity flow problem also provides some information about the coordinates of the point where this minimum is achieved. By looking at the edges that are never saturated in any maximum multicommodity flow, we can identify relational persistencies: pairs of variables that must have the same or different values in any minimizing assignment. We furthermore show that all of these persistencies can be detected by solving single-commodity flow problems in the same network.
A systematic linear space approach to solving partially described inverse eigenvalue problems
NASA Astrophysics Data System (ADS)
Hu, Sau-Lon James; Li, Haujun
2008-06-01
Most applications of the inverse eigenvalue problem (IEP), which concerns the reconstruction of a matrix from prescribed spectral data, are associated with special classes of structured matrices. Solving the IEP requires one to satisfy both the spectral constraint and the structural constraint. If the spectral constraint consists of only one or few prescribed eigenpairs, this kind of inverse problem has been referred to as the partially described inverse eigenvalue problem (PDIEP). This paper develops an efficient, general and systematic approach to solve the PDIEP. Basically, the approach, applicable to various structured matrices, converts the PDIEP into an ordinary inverse problem that is formulated as a set of simultaneous linear equations. While solving simultaneous linear equations for model parameters, the singular value decomposition method is applied. Because of the conversion to an ordinary inverse problem, other constraints associated with the model parameters can be easily incorporated into the solution procedure. The detailed derivation and numerical examples to implement the newly developed approach to symmetric Toeplitz and quadratic pencil (including mass, damping and stiffness matrices of a linear dynamic system) PDIEPs are presented. Excellent numerical results for both kinds of problem are achieved under the situations that have either unique or infinitely many solutions.
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.
New Approach to Analyzing Physics Problems: A Taxonomy of Introductory Physics Problems
ERIC Educational Resources Information Center
Teodorescu, Raluca E.; Bennhold, Cornelius; Feldman, Gerald; Medsker, Larry
2013-01-01
This paper describes 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 in order to design educational objectives, to develop…
Solving large scale traveling salesman problems by chaotic neurodynamics.
Hasegawa, Mikio; Ikeguch, Tohru; Aihara, Kazuyuki
2002-03-01
We propose a novel approach for solving large scale traveling salesman problems (TSPs) by chaotic dynamics. First, we realize the tabu search on a neural network, by utilizing the refractory effects as the tabu effects. Then, we extend it to a chaotic neural network version. We propose two types of chaotic searching methods, which are based on two different tabu searches. While the first one requires neurons of the order of n2 for an n-city TSP, the second one requires only n neurons. Moreover, an automatic parameter tuning method of our chaotic neural network is presented for easy application to various problems. Last, we show that our method with n neurons is applicable to large TSPs such as an 85,900-city problem and exhibits better performance than the conventional stochastic searches and the tabu searches.
Video Analysis of a Plucked String: An Example of Problem-based Learning
NASA Astrophysics Data System (ADS)
Wentworth, Christopher D.; Buse, Eric
2009-11-01
Problem-based learning is a teaching methodology that grounds learning within the context of solving a real problem. Typically the problem initiates learning of concepts rather than simply being an application of the concept, and students take the lead in identifying what must be developed to solve the problem. Problem-based learning in upper-level physics courses can be challenging, because of the time and financial requirements necessary to generate real data. Here, we present a problem that motivates learning about partial differential equations and their solution in a mathematical methods for physics course. Students study a plucked elastic cord using high speed digital video. After creating video clips of the cord motion under different tensions they are asked to create a mathematical model. Ultimately, students develop and solve a model that includes damping effects that are clearly visible in the videos. The digital video files used in this project are available on the web at http://physics.doane.edu .
Divide et impera: subgoaling reduces the complexity of probabilistic inference and problem solving.
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.
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)
Recursive heuristic classification
NASA Technical Reports Server (NTRS)
Wilkins, David C.
1994-01-01
The author will describe a new problem-solving approach called recursive heuristic classification, whereby a subproblem of heuristic classification is itself formulated and solved by heuristic classification. This allows the construction of more knowledge-intensive classification programs in a way that yields a clean organization. Further, standard knowledge acquisition and learning techniques for heuristic classification can be used to create, refine, and maintain the knowledge base associated with the recursively called classification expert system. The method of recursive heuristic classification was used in the Minerva blackboard shell for heuristic classification. Minerva recursively calls itself every problem-solving cycle to solve the important blackboard scheduler task, which involves assigning a desirability rating to alternative problem-solving actions. Knowing these ratings is critical to the use of an expert system as a component of a critiquing or apprenticeship tutoring system. One innovation of this research is a method called dynamic heuristic classification, which allows selection among dynamically generated classification categories instead of requiring them to be prenumerated.
Nembhard, Ingrid M.; Cherian, Praseetha; Bradley, Elizabeth H.
2015-01-01
This article examines the effect on quality improvement of two common but distinct approaches to organizational learning: importing best practices (an externally oriented approach rooted in learning by imitating others’ best practices) and internal creative problem solving (an internally oriented approach rooted in learning by experimenting with self-generated solutions). We propose that independent and interaction effects of these approaches depend on where organizations are in their improvement journey – initial push or later phase. We examine this contingency in hospitals focused on improving treatment time for patients with heart attacks. Our results show that importing best practices helps hospitals achieve initial phase but not later phase improvement. Once hospitals enter the later phase of their efforts, however, significant improvement requires creative problem solving as well. Together, our results suggest that importing best practices delivers greater short-term improvement, but continued improvement depends on creative problem solving. PMID:24876100
On a comparison of two schemes in sequential data assimilation
NASA Astrophysics Data System (ADS)
Grishina, Anastasiia A.; Penenko, Alexey V.
2017-11-01
This paper is focused on variational data assimilation as an approach to mathematical modeling. Realization of the approach requires a sequence of connected inverse problems with different sets of observational data to be solved. Two variational data assimilation schemes, "implicit" and "explicit", are considered in the article. Their equivalence is shown and the numerical results are given on a basis of non-linear Robertson system. To avoid the "inverse problem crime" different schemes were used to produce synthetic measurement and to solve the data assimilation problem.
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.
Problem Solving and Cognitive Skill Acquisition
1988-02-01
the history of the field, most research has concerned tasks, that take minutes or hours to perform. Typically, subjects make many observable actions...may be moved at a time and a larger disk may never be placed on top of a smaller one. There are many variations of this basic puzzle. For instance...book, Human Problem Solving, is still required reading for anyone seriously interested in the field. This theory became the foundation for many detailed
How did you guess? Or, what do multiple-choice questions measure?
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.
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.
Nilsen, Liv; Frich, Jan C; Friis, Svein; Norheim, Irene; Røssberg, Jan Ivar
2016-04-01
To explore the perceived benefits for patients and family members of psychoeducational family intervention following a first episode of psychosis. A qualitative exploratory study using data from interviews with 12 patients and 14 family members who participated in a psychoeducational multi- or single-family treatment programme. Semi-structured interviews were digitally recorded and transcribed verbatim with slight modifications, after which they were analysed by systematic text condensation. Patients and family members reported benefits that could be classified in five categories: (i) developing insight and acceptance requires understanding of the fact that the patient has an illness, and recognizing the need for support; (ii) recognizing warning signs requires an understanding of early signs of deterioration in the patient; (iii) improving communication skills is linked to new understanding and better communication both within the family and in groups; (iv) Learning to plan and solve problems requires the ability to solve problems in new ways; (v) becoming more independent requires patients to take responsibility for their own life. The study suggests that developing insight and acceptance, learning about warning signs, improving communications skills, learning to plan and solve problems, and becoming more independent are perceived as benefits of a psychoeducational family intervention. © 2014 Wiley Publishing Asia Pty Ltd.
NASA Astrophysics Data System (ADS)
Suthikarnnarunai, N.; Olinick, E.
2009-01-01
We present a case study on the application of techniques for solving the Vehicle Routing Problem (VRP) to improve the transportation service provided by the University of The Thai Chamber of Commerce to its staff. The problem is modeled as VRP with time windows, split deliveries, and a mixed fleet. An exact algorithm and a heuristic solution procedure are developed to solve the problem and implemented in the AMPL modeling language and CPLEX Integer Programming solver. Empirical results indicate that the heuristic can find relatively good solutions in a small fraction of the time required by the exact method. We also perform sensitivity analysis and find that a savings in outsourcing cost can be achieved with a small increase in vehicle capacity.
Unified Lambert Tool for Massively Parallel Applications in Space Situational Awareness
NASA Astrophysics Data System (ADS)
Woollands, Robyn M.; Read, Julie; Hernandez, Kevin; Probe, Austin; Junkins, John L.
2018-03-01
This paper introduces a parallel-compiled tool that combines several of our recently developed methods for solving the perturbed Lambert problem using modified Chebyshev-Picard iteration. This tool (unified Lambert tool) consists of four individual algorithms, each of which is unique and better suited for solving a particular type of orbit transfer. The first is a Keplerian Lambert solver, which is used to provide a good initial guess (warm start) for solving the perturbed problem. It is also used to determine the appropriate algorithm to call for solving the perturbed problem. The arc length or true anomaly angle spanned by the transfer trajectory is the parameter that governs the automated selection of the appropriate perturbed algorithm, and is based on the respective algorithm convergence characteristics. The second algorithm solves the perturbed Lambert problem using the modified Chebyshev-Picard iteration two-point boundary value solver. This algorithm does not require a Newton-like shooting method and is the most efficient of the perturbed solvers presented herein, however the domain of convergence is limited to about a third of an orbit and is dependent on eccentricity. The third algorithm extends the domain of convergence of the modified Chebyshev-Picard iteration two-point boundary value solver to about 90% of an orbit, through regularization with the Kustaanheimo-Stiefel transformation. This is the second most efficient of the perturbed set of algorithms. The fourth algorithm uses the method of particular solutions and the modified Chebyshev-Picard iteration initial value solver for solving multiple revolution perturbed transfers. This method does require "shooting" but differs from Newton-like shooting methods in that it does not require propagation of a state transition matrix. The unified Lambert tool makes use of the General Mission Analysis Tool and we use it to compute thousands of perturbed Lambert trajectories in parallel on the Space Situational Awareness computer cluster at the LASR Lab, Texas A&M University. We demonstrate the power of our tool by solving a highly parallel example problem, that is the generation of extremal field maps for optimal spacecraft rendezvous (and eventual orbit debris removal). In addition we demonstrate the need for including perturbative effects in simulations for satellite tracking or data association. The unified Lambert tool is ideal for but not limited to space situational awareness applications.
Schmidhuber, Jürgen
2013-01-01
Most of computer science focuses on automatically solving given computational problems. I focus on automatically inventing or discovering problems in a way inspired by the playful behavior of animals and humans, to train a more and more general problem solver from scratch in an unsupervised fashion. Consider the infinite set of all computable descriptions of tasks with possibly computable solutions. Given a general problem-solving architecture, at any given time, the novel algorithmic framework PowerPlay (Schmidhuber, 2011) searches the space of possible pairs of new tasks and modifications of the current problem solver, until it finds a more powerful problem solver that provably solves all previously learned tasks plus the new one, while the unmodified predecessor does not. Newly invented tasks may require to achieve a wow-effect by making previously learned skills more efficient such that they require less time and space. New skills may (partially) re-use previously learned skills. The greedy search of typical PowerPlay variants uses time-optimal program search to order candidate pairs of tasks and solver modifications by their conditional computational (time and space) complexity, given the stored experience so far. The new task and its corresponding task-solving skill are those first found and validated. This biases the search toward pairs that can be described compactly and validated quickly. The computational costs of validating new tasks need not grow with task repertoire size. Standard problem solver architectures of personal computers or neural networks tend to generalize by solving numerous tasks outside the self-invented training set; PowerPlay’s ongoing search for novelty keeps breaking the generalization abilities of its present solver. This is related to Gödel’s sequence of increasingly powerful formal theories based on adding formerly unprovable statements to the axioms without affecting previously provable theorems. The continually increasing repertoire of problem-solving procedures can be exploited by a parallel search for solutions to additional externally posed tasks. PowerPlay may be viewed as a greedy but practical implementation of basic principles of creativity (Schmidhuber, 2006a, 2010). A first experimental analysis can be found in separate papers (Srivastava et al., 2012a,b, 2013). PMID:23761771
A Solution Framework for Environmental Characterization Problems
This paper describes experiences developing a grid-enabled framework for solving environmental inverse problems. The solution approach taken here couples environmental simulation models with global search methods and requires readily available computational resources of the grid ...
ERIC Educational Resources Information Center
Kaplan, Craig A.; Simon, Herbert A.
1990-01-01
Attaining the insight needed to solve the Mutilated Checkerboard problem, which requires discovery of an effective problem representation (EPR), is described. Performance on insight problems can be predicted from the availability of generators and constraints in the search for an EPR. Data for 23 undergraduates were analyzed. (TJH)
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.
Innovation and behavioral flexibility in wild redfronted lemurs (Eulemur rufifrons).
Huebner, Franziska; Fichtel, Claudia
2015-05-01
Innovations and problem-solving abilities can provide animals with important ecological advantages as they allow individuals to deal with novel social and ecological challenges. Innovation is a solution to a novel problem or a novel solution to an old problem, with the latter being especially difficult. Finding a new solution to an old problem requires individuals to inhibit previously applied solutions to invent new strategies and to behave flexibly. We examined the role of experience on cognitive flexibility to innovate and to find new problem-solving solutions with an artificial feeding task in wild redfronted lemurs (Eulemur rufifrons). Four groups of lemurs were tested with feeding boxes, each offering three different techniques to extract food, with only one technique being available at a time. After the subjects learned a technique, this solution was no longer successful and subjects had to invent a new technique. For the first transition between task 1 and 2, subjects had to rely on their experience of the previous technique to solve task 2. For the second transition, subjects had to inhibit the previously learned technique to learn the new task 3. Tasks 1 and 2 were solved by most subjects, whereas task 3 was solved by only a few subjects. In this task, besides behavioral flexibility, especially persistence, i.e., constant trying, was important for individual success during innovation. Thus, wild strepsirrhine primates are able to innovate flexibly, suggesting a general ecological relevance of behavioral flexibility and persistence during innovation and problem solving across all primates.
NASA Astrophysics Data System (ADS)
Fazayeli, Saeed; Eydi, Alireza; Kamalabadi, Isa Nakhai
2017-07-01
Nowadays, organizations have to compete with different competitors in regional, national and international levels, so they have to improve their competition capabilities to survive against competitors. Undertaking activities on a global scale requires a proper distribution system which could take advantages of different transportation modes. Accordingly, the present paper addresses a location-routing problem on multimodal transportation network. The introduced problem follows four objectives simultaneously which form main contribution of the paper; determining multimodal routes between supplier and distribution centers, locating mode changing facilities, locating distribution centers, and determining product delivery tours from the distribution centers to retailers. An integer linear programming is presented for the problem, and a genetic algorithm with a new chromosome structure proposed to solve the problem. Proposed chromosome structure consists of two different parts for multimodal transportation and location-routing parts of the model. Based on published data in the literature, two numerical cases with different sizes generated and solved. Also, different cost scenarios designed to better analyze model and algorithm performance. Results show that algorithm can effectively solve large-size problems within a reasonable time which GAMS software failed to reach an optimal solution even within much longer times.
Structural design using equilibrium programming formulations
NASA Technical Reports Server (NTRS)
Scotti, Stephen J.
1995-01-01
Solutions to increasingly larger structural optimization problems are desired. However, computational resources are strained to meet this need. New methods will be required to solve increasingly larger problems. The present approaches to solving large-scale problems involve approximations for the constraints of structural optimization problems and/or decomposition of the problem into multiple subproblems that can be solved in parallel. An area of game theory, equilibrium programming (also known as noncooperative game theory), can be used to unify these existing approaches from a theoretical point of view (considering the existence and optimality of solutions), and be used as a framework for the development of new methods for solving large-scale optimization problems. Equilibrium programming theory is described, and existing design techniques such as fully stressed design and constraint approximations are shown to fit within its framework. Two new structural design formulations are also derived. The first new formulation is another approximation technique which is a general updating scheme for the sensitivity derivatives of design constraints. The second new formulation uses a substructure-based decomposition of the structure for analysis and sensitivity calculations. Significant computational benefits of the new formulations compared with a conventional method are demonstrated.
NASA Astrophysics Data System (ADS)
Fazayeli, Saeed; Eydi, Alireza; Kamalabadi, Isa Nakhai
2018-07-01
Nowadays, organizations have to compete with different competitors in regional, national and international levels, so they have to improve their competition capabilities to survive against competitors. Undertaking activities on a global scale requires a proper distribution system which could take advantages of different transportation modes. Accordingly, the present paper addresses a location-routing problem on multimodal transportation network. The introduced problem follows four objectives simultaneously which form main contribution of the paper; determining multimodal routes between supplier and distribution centers, locating mode changing facilities, locating distribution centers, and determining product delivery tours from the distribution centers to retailers. An integer linear programming is presented for the problem, and a genetic algorithm with a new chromosome structure proposed to solve the problem. Proposed chromosome structure consists of two different parts for multimodal transportation and location-routing parts of the model. Based on published data in the literature, two numerical cases with different sizes generated and solved. Also, different cost scenarios designed to better analyze model and algorithm performance. Results show that algorithm can effectively solve large-size problems within a reasonable time which GAMS software failed to reach an optimal solution even within much longer times.
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…
Burton, Brett M; Tate, Jess D; Erem, Burak; Swenson, Darrell J; Wang, Dafang F; Steffen, Michael; Brooks, Dana H; van Dam, Peter M; Macleod, Rob S
2012-01-01
Computational modeling in electrocardiography often requires the examination of cardiac forward and inverse problems in order to non-invasively analyze physiological events that are otherwise inaccessible or unethical to explore. The study of these models can be performed in the open-source SCIRun problem solving environment developed at the Center for Integrative Biomedical Computing (CIBC). A new toolkit within SCIRun provides researchers with essential frameworks for constructing and manipulating electrocardiographic forward and inverse models in a highly efficient and interactive way. The toolkit contains sample networks, tutorials and documentation which direct users through SCIRun-specific approaches in the assembly and execution of these specific problems. PMID:22254301
Linear decomposition approach for a class of nonconvex programming problems.
Shen, Peiping; Wang, Chunfeng
2017-01-01
This paper presents a linear decomposition approach for a class of nonconvex programming problems by dividing the input space into polynomially many grids. It shows that under certain assumptions the original problem can be transformed and decomposed into a polynomial number of equivalent linear programming subproblems. Based on solving a series of liner programming subproblems corresponding to those grid points we can obtain the near-optimal solution of the original problem. Compared to existing results in the literature, the proposed algorithm does not require the assumptions of quasi-concavity and differentiability of the objective function, and it differs significantly giving an interesting approach to solving the problem with a reduced running time.
Lame problem for a multilayer viscoelastic hollow ball with regard to inhomogeneous aging
NASA Astrophysics Data System (ADS)
Davtyan, Z. A.; Mirzoyan, S. Y.; Gasparyan, A. V.
2018-04-01
Determination of characteristics of the stress strain state of compound viscoelastic bodies is of both theoretical and practical interest. In the present paper, the Lamé problem is investigated for an uneven-aged multilayer viscoelastic hollow ball in the framework of N. Kh. Arutyunyan’s theory of creep of nonhomogeneously aging bodies [1, 2]. Solving this problem reduces to solving an inhomogeneous finite-difference equation of second order that contains operators with coordinates of time and space. The obtained formulas allow one to determine the required contact stresses and other mechanical characteristics of the problem related to uneven age of contacting balls.
The application of MINIQUASI to thermal program boundary and initial value problems
NASA Technical Reports Server (NTRS)
1974-01-01
The feasibility of applying the solution techniques of Miniquasi to the set of equations which govern a thermoregulatory model is investigated. For solving nonlinear equations and/or boundary conditions, a Taylor Series expansion is required for linearization of both equations and boundary conditions. The solutions are iterative and in each iteration, a problem like the linear case is solved. It is shown that Miniquasi cannot be applied to the thermoregulatory model as originally planned.
ERIC Educational Resources Information Center
Badeau, Ryan; White, Daniel R.; Ibrahim, Bashirah; Ding, Lin; Heckler, Andrew F.
2017-01-01
The ability to solve physics problems that require multiple concepts from across the physics curriculum--"synthesis" problems--is often a goal of physics instruction. Three experiments were designed to evaluate the effectiveness of two instructional methods employing worked examples on student performance with synthesis problems; these…
Big 6 Tips: Teaching Information Problem Solving. #1 Task Definition: What Needs To Be Done.
ERIC Educational Resources Information Center
Eisenberg, Michael
1997-01-01
Explains task definition which is the first stage in the Big 6, an approach to information and technology skills instruction. Highlights include defining the problem; identifying the information requirements of the problem; transferability from curriculum-based problems to everyday tasks; and task definition logs kept by students. (LRW)
Indirect addressing and load balancing for faster solution to Mandelbrot Set on SIMD architectures
NASA Technical Reports Server (NTRS)
Tomboulian, Sherryl
1989-01-01
SIMD computers with local indirect addressing allow programs to have queues and buffers, making certain kinds of problems much more efficient. Examined here are a class of problems characterized by computations on data points where the computation is identical, but the convergence rate is data dependent. Normally, in this situation, the algorithm time is governed by the maximum number of iterations required by each point. Using indirect addressing allows a processor to proceed to the next data point when it is done, reducing the overall number of iterations required to approach the mean convergence rate when a sufficiently large problem set is solved. Load balancing techniques can be applied for additional performance improvement. Simulations of this technique applied to solving Mandelbrot Sets indicate significant performance gains.
NASA Astrophysics Data System (ADS)
Tyuleneva, Tatiana
2017-11-01
One of the problems of sustainable development of mining companies is attracting additional investment. To solve it requires access to international capital markets, in this context, enterprises need to prepare financial statements with international requirements based on the data generated by the accounting system. The article considers the basic problems of accounting in the extractive industries due to the nature of the industry, as well as evaluation of the completeness of their solution in the framework of international financial reporting standards. In addition, lists the characteristics of accounting for mining industry, due to the peculiarities of the production process that need to be considered to solve these problems. This sector is extremely important for individual countries and on a global scale.
Harmony search optimization algorithm for a novel transportation problem in a consolidation network
NASA Astrophysics Data System (ADS)
Davod Hosseini, Seyed; Akbarpour Shirazi, Mohsen; Taghi Fatemi Ghomi, Seyed Mohammad
2014-11-01
This article presents a new harmony search optimization algorithm to solve a novel integer programming model developed for a consolidation network. In this network, a set of vehicles is used to transport goods from suppliers to their corresponding customers via two transportation systems: direct shipment and milk run logistics. The objective of this problem is to minimize the total shipping cost in the network, so it tries to reduce the number of required vehicles using an efficient vehicle routing strategy in the solution approach. Solving several numerical examples confirms that the proposed solution approach based on the harmony search algorithm performs much better than CPLEX in reducing both the shipping cost in the network and computational time requirement, especially for realistic size problem instances.
Optimal mistuning for enhanced aeroelastic stability of transonic fans
NASA Technical Reports Server (NTRS)
Hall, K. C.; Crawley, E. F.
1983-01-01
An inverse design procedure was developed for the design of a mistuned rotor. The design requirements are that the stability margin of the eigenvalues of the aeroelastic system be greater than or equal to some minimum stability margin, and that the mass added to each blade be positive. The objective was to achieve these requirements with a minimal amount of mistuning. Hence, the problem was posed as a constrained optimization problem. The constrained minimization problem was solved by the technique of mathematical programming via augmented Lagrangians. The unconstrained minimization phase of this technique was solved by the variable metric method. The bladed disk was modelled as being composed of a rigid disk mounted on a rigid shaft. Each of the blades were modelled with a single tosional degree of freedom.
Perception of Peace in Students' Drawings
ERIC Educational Resources Information Center
Cengelci Kose, Tuba; Gurdogan Bayir, Omur
2016-01-01
Problem Statement: Societies are facing several kinds of problems in the world today as chaos among the countries, conflicts between different groups, wars and diseases. It can be claimed that solving these problems is impossible unless societies care about humanistic cooperation, tolerance and peace. Individuals required developing fundamental…
Control system estimation and design for aerospace vehicles with time delay
NASA Technical Reports Server (NTRS)
Allgaier, G. R.; Williams, T. L.
1972-01-01
The problems of estimation and control of discrete, linear, time-varying systems are considered. Previous solutions to these problems involved either approximate techniques, open-loop control solutions, or results which required excessive computation. The estimation problem is solved by two different methods, both of which yield the identical algorithm for determining the optimal filter. The partitioned results achieve a substantial reduction in computation time and storage requirements over the expanded solution, however. The results reduce to the Kalman filter when no delays are present in the system. The control problem is also solved by two different methods, both of which yield identical algorithms for determining the optimal control gains. The stochastic control is shown to be identical to the deterministic control, thus extending the separation principle to time delay systems. The results obtained reduce to the familiar optimal control solution when no time delays are present in the system.
Topolinski, Sascha; Bakhtiari, Giti; Erle, Thorsten M
2016-01-01
When assessing a problem, many cues can be used to predict solvability and solving effort. Some of these cues, however, can be misleading. The present approach shows that a feature of a problem that is actually related to solving difficulty is used as a cue for solving ease when assessing the problem in the first place. For anagrams, it is an established effect that easy-to-pronounce anagrams (e.g., NOGAL) take more time to being solved than hard-to-pronounce anagrams (e.g., HNWEI). However, when assessing an anagram in the first place, individuals use the feature of pronounceability to predict solving ease, because pronounceability is an instantiation of the general mechanism of processing fluency. Participants (total N=536) received short and long anagrams and nonanagrams and judged solvability and solving ease intuitively without actually solving the items. Easy-to-pronounce letter strings were more frequently judged as being solvable than hard-to-pronounce letters strings (Experiment 1), and were estimated to require less effort (Experiments 2, 4-7) and time to be solved (Experiment 3). This effect was robust for short and long items, anagrams and nonanagrams, and presentation timings from 4 down to 0.5s, and affected novices and experts alike. Spontaneous solutions did not mediate this effect. Participants were sensitive to actual solvability even for long anagrams (6-11 letters long) presented only for 500 ms. Copyright © 2015 Elsevier B.V. All rights reserved.
Examining Undergraduate Student Attitude towards Interdisciplinary Education
ERIC Educational Resources Information Center
DiBenedetto, Catherine A.; Lamm, Kevan W.; Lamm, Alexa J.; Myers, Brian E.
2016-01-01
As the global population grows, concern for a food shortage may be looming. As the next generations of agricultural and natural resource leaders are prepared to address this challenge, input throughout multiple disciplines is required to solve this dilemma. Undergraduates must be prepared to engage in problem solving and entrepreneurial thinking…
Initiating a Programmatic Assessment Report
ERIC Educational Resources Information Center
Berkaliev, Zaur; Devi, Shavila; Fasshauer, Gregory E.; Hickernell, Fred J.; Kartal, Ozgul; Li, Xiaofan; McCray, Patrick; Whitney, Stephanie; Zawojewski, Judith S.
2014-01-01
In the context of a department of applied mathematics, a program assessment was conducted to assess the departmental goal of enabling undergraduate students to recognize, appreciate, and apply the power of computational tools in solving mathematical problems that cannot be solved by hand, or would require extensive and tedious hand computation. A…
Solving Rational Expectations Models Using Excel
ERIC Educational Resources Information Center
Strulik, Holger
2004-01-01
Simple problems of discrete-time optimal control can be solved using a standard spreadsheet software. The employed-solution method of backward iteration is intuitively understandable, does not require any programming skills, and is easy to implement so that it is suitable for classroom exercises with rational-expectations models. The author…
The Evaluation of Reflective Learning Practice: Preparing College Students for Globalization
ERIC Educational Resources Information Center
Richard, Cathleen Becnel
2010-01-01
A problem facing education today is that learning typically requires rote memorization rather than the use of higher-order thinking skills. Higher-order thinking is needed in a global society to solve real world problems, therefore students should be required to develop and practice higher-order thinking skills. The purpose of this mixed method…
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…
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.
Fast, Nonlinear, Fully Probabilistic Inversion of Large Geophysical Problems
NASA Astrophysics Data System (ADS)
Curtis, A.; Shahraeeni, M.; Trampert, J.; Meier, U.; Cho, G.
2010-12-01
Almost all Geophysical inverse problems are in reality nonlinear. Fully nonlinear inversion including non-approximated physics, and solving for probability distribution functions (pdf’s) that describe the solution uncertainty, generally requires sampling-based Monte-Carlo style methods that are computationally intractable in most large problems. In order to solve such problems, physical relationships are usually linearized leading to efficiently-solved, (possibly iterated) linear inverse problems. However, it is well known that linearization can lead to erroneous solutions, and in particular to overly optimistic uncertainty estimates. What is needed across many Geophysical disciplines is a method to invert large inverse problems (or potentially tens of thousands of small inverse problems) fully probabilistically and without linearization. This talk shows how very large nonlinear inverse problems can be solved fully probabilistically and incorporating any available prior information using mixture density networks (driven by neural network banks), provided the problem can be decomposed into many small inverse problems. In this talk I will explain the methodology, compare multi-dimensional pdf inversion results to full Monte Carlo solutions, and illustrate the method with two applications: first, inverting surface wave group and phase velocities for a fully-probabilistic global tomography model of the Earth’s crust and mantle, and second inverting industrial 3D seismic data for petrophysical properties throughout and around a subsurface hydrocarbon reservoir. The latter problem is typically decomposed into 104 to 105 individual inverse problems, each solved fully probabilistically and without linearization. The results in both cases are sufficiently close to the Monte Carlo solution to exhibit realistic uncertainty, multimodality and bias. This provides far greater confidence in the results, and in decisions made on their basis.
Insightful problem solving in an Asian elephant.
Foerder, Preston; Galloway, Marie; Barthel, Tony; Moore, Donald E; Reiss, Diana
2011-01-01
The "aha" moment or the sudden arrival of the solution to a problem is a common human experience. Spontaneous problem solving without evident trial and error behavior in humans and other animals has been referred to as insight. Surprisingly, elephants, thought to be highly intelligent, have failed to exhibit insightful problem solving in previous cognitive studies. We tested whether three Asian elephants (Elephas maximus) would use sticks or other objects to obtain food items placed out-of-reach and overhead. Without prior trial and error behavior, a 7-year-old male Asian elephant showed spontaneous problem solving by moving a large plastic cube, on which he then stood, to acquire the food. In further testing he showed behavioral flexibility, using this technique to reach other items and retrieving the cube from various locations to use as a tool to acquire food. In the cube's absence, he generalized this tool utilization technique to other objects and, when given smaller objects, stacked them in an attempt to reach the food. The elephant's overall behavior was consistent with the definition of insightful problem solving. Previous failures to demonstrate this ability in elephants may have resulted not from a lack of cognitive ability but from the presentation of tasks requiring trunk-held sticks as potential tools, thereby interfering with the trunk's use as a sensory organ to locate the targeted food.
What Is Evidence-Based Behavior Analysis?
Smith, Tristram
2013-01-01
Although applied behavior analysts often say they engage in evidence-based practice, they express differing views on what constitutes “evidence” and “practice.” This article describes a practice as a service offered by a provider to help solve a problem presented by a consumer. Solving most problems (e.g., increasing or decreasing a behavior and maintaining this change) requires multiple intervention procedures (i.e., a package). Single-subject studies are invaluable in investigating individual procedures, but researchers still need to integrate the procedures into a package. The package must be standardized enough for independent providers to replicate yet flexible enough to allow individualization; intervention manuals are the primary technology for achieving this balance. To test whether the package is effective in solving consumers' problems, researchers must evaluate outcomes of the package as a whole, usually in group studies such as randomized controlled trials. From this perspective, establishing an evidence-based practice involves more than analyzing the effects of discrete intervention procedures on behavior; it requires synthesizing information so as to offer thorough solutions to problems. Recognizing the need for synthesis offers behavior analysts many promising opportunities to build on their existing research to increase the quality and quantity of evidence-based practices. PMID:25729130
Teaching Creativity and Inventive Problem Solving in Science
2009-01-01
Engaging learners in the excitement of science, helping them discover the value of evidence-based reasoning and higher-order cognitive skills, and teaching them to become creative problem solvers have long been goals of science education reformers. But the means to achieve these goals, especially methods to promote creative thinking in scientific problem solving, have not become widely known or used. In this essay, I review the evidence that creativity is not a single hard-to-measure property. The creative process can be explained by reference to increasingly well-understood cognitive skills such as cognitive flexibility and inhibitory control that are widely distributed in the population. I explore the relationship between creativity and the higher-order cognitive skills, review assessment methods, and describe several instructional strategies for enhancing creative problem solving in the college classroom. Evidence suggests that instruction to support the development of creativity requires inquiry-based teaching that includes explicit strategies to promote cognitive flexibility. Students need to be repeatedly reminded and shown how to be creative, to integrate material across subject areas, to question their own assumptions, and to imagine other viewpoints and possibilities. Further research is required to determine whether college students' learning will be enhanced by these measures. PMID:19723812
Teaching creativity and inventive problem solving in science.
DeHaan, Robert L
2009-01-01
Engaging learners in the excitement of science, helping them discover the value of evidence-based reasoning and higher-order cognitive skills, and teaching them to become creative problem solvers have long been goals of science education reformers. But the means to achieve these goals, especially methods to promote creative thinking in scientific problem solving, have not become widely known or used. In this essay, I review the evidence that creativity is not a single hard-to-measure property. The creative process can be explained by reference to increasingly well-understood cognitive skills such as cognitive flexibility and inhibitory control that are widely distributed in the population. I explore the relationship between creativity and the higher-order cognitive skills, review assessment methods, and describe several instructional strategies for enhancing creative problem solving in the college classroom. Evidence suggests that instruction to support the development of creativity requires inquiry-based teaching that includes explicit strategies to promote cognitive flexibility. Students need to be repeatedly reminded and shown how to be creative, to integrate material across subject areas, to question their own assumptions, and to imagine other viewpoints and possibilities. Further research is required to determine whether college students' learning will be enhanced by these measures.
Self-interacting inelastic dark matter: a viable solution to the small scale structure problems
DOE Office of Scientific and Technical Information (OSTI.GOV)
Blennow, Mattias; Clementz, Stefan; Herrero-Garcia, Juan, E-mail: emb@kth.se, E-mail: scl@kth.se, E-mail: juan.herrero-garcia@adelaide.edu.au
2017-03-01
Self-interacting dark matter has been proposed as a solution to the small-scale structure problems, such as the observed flat cores in dwarf and low surface brightness galaxies. If scattering takes place through light mediators, the scattering cross section relevant to solve these problems may fall into the non-perturbative regime leading to a non-trivial velocity dependence, which allows compatibility with limits stemming from cluster-size objects. However, these models are strongly constrained by different observations, in particular from the requirements that the decay of the light mediator is sufficiently rapid (before Big Bang Nucleosynthesis) and from direct detection. A natural solution tomore » reconcile both requirements are inelastic endothermic interactions, such that scatterings in direct detection experiments are suppressed or even kinematically forbidden if the mass splitting between the two-states is sufficiently large. Using an exact solution when numerically solving the Schrödinger equation, we study such scenarios and find regions in the parameter space of dark matter and mediator masses, and the mass splitting of the states, where the small scale structure problems can be solved, the dark matter has the correct relic abundance and direct detection limits can be evaded.« less
Solving satisfiability problems using a novel microarray-based DNA computer.
Lin, Che-Hsin; Cheng, Hsiao-Ping; Yang, Chang-Biau; Yang, Chia-Ning
2007-01-01
An algorithm based on a modified sticker model accompanied with an advanced MEMS-based microarray technology is demonstrated to solve SAT problem, which has long served as a benchmark in DNA computing. Unlike conventional DNA computing algorithms needing an initial data pool to cover correct and incorrect answers and further executing a series of separation procedures to destroy the unwanted ones, we built solutions in parts to satisfy one clause in one step, and eventually solve the entire Boolean formula through steps. No time-consuming sample preparation procedures and delicate sample applying equipment were required for the computing process. Moreover, experimental results show the bound DNA sequences can sustain the chemical solutions during computing processes such that the proposed method shall be useful in dealing with large-scale problems.
A Monte-Carlo game theoretic approach for Multi-Criteria Decision Making under uncertainty
NASA Astrophysics Data System (ADS)
Madani, Kaveh; Lund, Jay R.
2011-05-01
Game theory provides a useful framework for studying Multi-Criteria Decision Making problems. This paper suggests modeling Multi-Criteria Decision Making problems as strategic games and solving them using non-cooperative game theory concepts. The suggested method can be used to prescribe non-dominated solutions and also can be used as a method to predict the outcome of a decision making problem. Non-cooperative stability definitions for solving the games allow consideration of non-cooperative behaviors, often neglected by other methods which assume perfect cooperation among decision makers. To deal with the uncertainty in input variables a Monte-Carlo Game Theory (MCGT) approach is suggested which maps the stochastic problem into many deterministic strategic games. The games are solved using non-cooperative stability definitions and the results include possible effects of uncertainty in input variables on outcomes. The method can handle multi-criteria multi-decision-maker problems with uncertainty. The suggested method does not require criteria weighting, developing a compound decision objective, and accurate quantitative (cardinal) information as it simplifies the decision analysis by solving problems based on qualitative (ordinal) information, reducing the computational burden substantially. The MCGT method is applied to analyze California's Sacramento-San Joaquin Delta problem. The suggested method provides insights, identifies non-dominated alternatives, and predicts likely decision outcomes.
Richard V. Field, Jr.; Emery, John M.; Grigoriu, Mircea Dan
2015-05-19
The stochastic collocation (SC) and stochastic Galerkin (SG) methods are two well-established and successful approaches for solving general stochastic problems. A recently developed method based on stochastic reduced order models (SROMs) can also be used. Herein we provide a comparison of the three methods for some numerical examples; our evaluation only holds for the examples considered in the paper. The purpose of the comparisons is not to criticize the SC or SG methods, which have proven very useful for a broad range of applications, nor is it to provide overall ratings of these methods as compared to the SROM method.more » Furthermore, our objectives are to present the SROM method as an alternative approach to solving stochastic problems and provide information on the computational effort required by the implementation of each method, while simultaneously assessing their performance for a collection of specific problems.« less
Early Design Choices: Capture, Model, Integrate, Analyze, Simulate
NASA Technical Reports Server (NTRS)
Malin, Jane T.
2004-01-01
I. Designs are constructed incrementally to meet requirements and solve problems: a) Requirements types: objectives, scenarios, constraints, ilities. etc. b) Problem/issue types: risk/safety, cost/difficulty, interaction, conflict, etc. II. Capture requirements, problems and solutions: a) Collect design and analysis products and make them accessible for integration and analysis; b) Link changes in design requirements, problems and solutions; and c) Harvest design data for design models and choice structures. III. System designs are constructed by multiple groups designing interacting subsystems a) Diverse problems, choice criteria, analysis methods and point solutions. IV. Support integration and global analysis of repercussions: a) System implications of point solutions; b) Broad analysis of interactions beyond totals of mass, cost, etc.
A feasible DY conjugate gradient method for linear equality constraints
NASA Astrophysics Data System (ADS)
LI, Can
2017-09-01
In this paper, we propose a feasible conjugate gradient method for solving linear equality constrained optimization problem. The method is an extension of the Dai-Yuan conjugate gradient method proposed by Dai and Yuan to linear equality constrained optimization problem. It can be applied to solve large linear equality constrained problem due to lower storage requirement. An attractive property of the method is that the generated direction is always feasible and descent direction. Under mild conditions, the global convergence of the proposed method with exact line search is established. Numerical experiments are also given which show the efficiency of the method.
Advanced control concepts. [for shuttle ascent vehicles
NASA Technical Reports Server (NTRS)
Sharp, J. B.; Coppey, J. M.
1973-01-01
The problems of excess control devices and insufficient trim control capability on shuttle ascent vehicles were investigated. The trim problem is solved at all time points of interest using Lagrangian multipliers and a Simplex based iterative algorithm developed as a result of the study. This algorithm has the capability to solve any bounded linear problem with physically realizable constraints, and to minimize any piecewise differentiable cost function. Both solution methods also automatically distribute the command torques to the control devices. It is shown that trim requirements are unrealizable if only the orbiter engines and the aerodynamic surfaces are used.
How many invariant polynomials are needed to decide local unitary equivalence of qubit states?
DOE Office of Scientific and Technical Information (OSTI.GOV)
Maciążek, Tomasz; Faculty of Physics, University of Warsaw, ul. Hoża 69, 00-681 Warszawa; Oszmaniec, Michał
2013-09-15
Given L-qubit states with the fixed spectra of reduced one-qubit density matrices, we find a formula for the minimal number of invariant polynomials needed for solving local unitary (LU) equivalence problem, that is, problem of deciding if two states can be connected by local unitary operations. Interestingly, this number is not the same for every collection of the spectra. Some spectra require less polynomials to solve LU equivalence problem than others. The result is obtained using geometric methods, i.e., by calculating the dimensions of reduced spaces, stemming from the symplectic reduction procedure.
Program for the solution of multipoint boundary value problems of quasilinear differential equations
NASA Technical Reports Server (NTRS)
1973-01-01
Linear equations are solved by a method of superposition of solutions of a sequence of initial value problems. For nonlinear equations and/or boundary conditions, the solution is iterative and in each iteration a problem like the linear case is solved. A simple Taylor series expansion is used for the linearization of both nonlinear equations and nonlinear boundary conditions. The perturbation method of solution is used in preference to quasilinearization because of programming ease, and smaller storage requirements; and experiments indicate that the desired convergence properties exist although no proof or convergence is given.
SUSTAINABILITY: THE NEXT GENERATION OF ENVIRONMENTAL PROTECTION
The 21st century will provide us with a new era of environmental problems that will require new approaches to solve. These problems will be more subtle than past problems, such as the pesticide poisoning at Love Canal or burning of the Cuyahoga River, but will be just as urgent,...
Toward a Comprehensive Rural Development Policy.
ERIC Educational Resources Information Center
Knutson, Ronald D.; And Others
Rural development is broader than just agriculture. Farm policy cannot solve rural community problems. Rural problems are sufficiently unique to require special emphasis and special programs. Since rural development has a broader focus than the local community, its problems need to be addressed by all levels of government as well as the private…
7 CFR 1291.10 - Reporting and oversight requirements.
Code of Federal Regulations, 2010 CFR
2010-01-01
..., identify and share the lessons learned to help expedite problem-solving. (6) Contact Person. List the... period to meet measurable outcomes for each project. (2) Problems and Delays. Note unexpected delays or... include the following: (1) Project Summary. An outline of the issue, problem, interest, or need for each...
SYSTEMATIC PROCEDURE FOR DESIGNING PROCESSES WITH MULTIPLE ENVIRONMENTAL OBJECTIVES
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 ...
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.
Berteletti, Ilaria; Prado, Jérôme; Booth, James R
2014-08-01
Greater skill in solving single-digit multiplication problems requires a progressive shift from a reliance on numerical to verbal mechanisms over development. Children with mathematical learning disability (MD), however, are thought to suffer from a specific impairment in numerical mechanisms. Here we tested the hypothesis that this impairment might prevent MD children from transitioning toward verbal mechanisms when solving single-digit multiplication problems. Brain activations during multiplication problems were compared in MD and typically developing (TD) children (3rd to 7th graders) in numerical and verbal regions which were individuated by independent localizer tasks. We used small (e.g., 2 × 3) and large (e.g., 7 × 9) problems as these problems likely differ in their reliance on verbal versus numerical mechanisms. Results indicate that MD children have reduced activations in both the verbal (i.e., left inferior frontal gyrus and left middle temporal to superior temporal gyri) and the numerical (i.e., right superior parietal lobule including intra-parietal sulcus) regions suggesting that both mechanisms are impaired. Moreover, the only reliable activation observed for MD children was in the numerical region when solving small problems. This suggests that MD children could effectively engage numerical mechanisms only for the easier problems. Conversely, TD children showed a modulation of activation with problem size in the verbal regions. This suggests that TD children were effectively engaging verbal mechanisms for the easier problems. Moreover, TD children with better language skills were more effective at engaging verbal mechanisms. In conclusion, results suggest that the numerical- and language-related processes involved in solving multiplication problems are impaired in MD children. Published by Elsevier Ltd.
ERIC Educational Resources Information Center
van Velzen, Joke H.
2016-01-01
The mathematics curriculum often provides for relatively few mathematical thinking problems or non-routine problems that focus on a deepening of understanding mathematical concepts and the problem-solving process. To develop such problems, methods are required to evaluate their suitability. The purpose of this preliminary study was to find such an…
Teaching NMR spectra analysis with nmr.cheminfo.org.
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.
A variant of nested dissection for solving n by n grid problems
NASA Technical Reports Server (NTRS)
George, A.; Poole, W. G., Jr.; Voigt, R. G.
1976-01-01
Nested dissection orderings are known to be very effective for solving the sparse positive definite linear systems which arise from n by n grid problems. In this paper nested dissection is shown to be the final step of incomplete nested dissection, an ordering which corresponds to the premature termination of dissection. Analyses of the arithmetic and storage requirements for incomplete nested dissection are given, and the ordering is shown to be competitive with nested dissection under certain conditions.
NASA Astrophysics Data System (ADS)
Kuncoro, K. S.; Junaedi, I.; Dwijanto
2018-03-01
This study aimed to reveal the effectiveness of Project Based Learning with Resource Based Learning approach computer-aided program and analyzed problem-solving abilities in terms of problem-solving steps based on Polya stages. The research method used was mixed method with sequential explanatory design. The subject of this research was the students of math semester 4. The results showed that the S-TPS (Strong Top Problem Solving) and W-TPS (Weak Top Problem Solving) had good problem-solving abilities in each problem-solving indicator. The problem-solving ability of S-MPS (Strong Middle Problem Solving) and (Weak Middle Problem Solving) in each indicator was good. The subject of S-BPS (Strong Bottom Problem Solving) had a difficulty in solving the problem with computer program, less precise in writing the final conclusion and could not reflect the problem-solving process using Polya’s step. While the Subject of W-BPS (Weak Bottom Problem Solving) had not been able to meet almost all the indicators of problem-solving. The subject of W-BPS could not precisely made the initial table of completion so that the completion phase with Polya’s step was constrained.
Right frontal gamma and beta band enhancement while solving a spatial puzzle with insight.
Rosen, A; Reiner, M
2017-12-01
Solving a problem with an "a-ha" effect is known as insight. Unlike incremental problem solving, insight is sudden and unique, and the question about its distinct brain activity, intrigues many researchers. In this study, electroencephalogram signals were recorded from 12 right handed, human participants before (baseline) and while they solved a spatial puzzle known as the '10 coin puzzle' that could be solved incrementally or by insight. Participants responded as soon as they reached a solution and reported whether the process was incremental or by sudden insight. EEG activity was recorded from 19 scalp locations. We found significant differences between insight and incremental solvers in the Gamma and Beta 2 bands in frontal areas (F8) and in the alpha band in right temporal areas (T6). The right-frontal gamma indicates a process of restructuring which leads to an insight solution, in spatial problems, further suggesting a universal role of gamma in restructuring. These results further suggest that solving a spatial puzzle via insight requires exclusive brain areas and neurological-cognitive processes which may be important for meta-cognitive components of insight solutions, including attention and monitoring of the solution. Copyright © 2016 Elsevier B.V. All rights reserved.
Harford, Joe B; Otero, Isabel V; Anderson, Benjamin O; Cazap, Eduardo; Gradishar, William J; Gralow, Julie R; Kane, Gabrielle M; Niëns, Laurens M; Porter, Peggy L; Reeler, Anne V; Rieger, Paula T; Shockney, Lillie D; Shulman, Lawrence N; Soldak, Tanya; Thomas, David B; Thompson, Beti; Winchester, David P; Zelle, Sten G; Badwe, Rajendra A
2011-04-01
International collaborations like the Breast Health Global Initiative (BHGI) can help low and middle income countries (LMCs) to establish or improve breast cancer control programs by providing evidence-based, resource-stratified guidelines for the management and control of breast cancer. The Problem Solving Working Group of the BHGI 2010 Global Summit met to develop a consensus statement on problem-solving strategies addressing breast cancer in LMCs. To better assess breast cancer burden in poorly studied populations, countries require accurate statistics regarding breast cancer incidence and mortality. To better identify health care system strengths and weaknesses, countries require reasonable indicators of true health system quality and capacity. Using qualitative and quantitative research methods, countries should formulate cancer control strategies to identify both system inefficiencies and patient barriers. Patient navigation programs linked to public advocacy efforts feed and strengthen functional early detection and treatment programs. Cost-effectiveness research and implementation science are tools that can guide and expand successful pilot programs. Copyright © 2011 Elsevier Ltd. All rights reserved.
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…
Innovation design of medical equipment based on TRIZ.
Gao, Changqing; Guo, Leiming; Gao, Fenglan; Yang, Bo
2015-01-01
Medical equipment is closely related to personal health and safety, and this can be of concern to the equipment user. Furthermore, there is much competition among medical equipment manufacturers. Innovative design is the key to success for those enterprises. The design of medical equipment usually covers vastly different domains of knowledge. The application of modern design methodology in medical equipment and technology invention is an urgent requirement. TRIZ (Russian abbreviation of what can be translated as `theory of inventive problem solving') was born in Russia, which contain some problem-solving methods developed by patent analysis around the world, including Conflict Matrix, Substance Field Analysis, Standard Solution, Effects, etc. TRIZ is an inventive methodology for problems solving. As an Engineering example, infusion system is analyzed and re-designed by TRIZ. The innovative idea is generated to liberate the caretaker from the infusion bag watching out. The research in this paper shows the process of the application of TRIZ in medical device inventions. It is proved that TRIZ is an inventive methodology for problems solving and can be used widely in medical device development.
Cosgrave, Jan; Haines, Ross; Golodetz, Stuart; Claridge, Gordon; Wulff, Katharina; van Heugten-van der Kloet, Dalena
2018-01-01
Insight problem solving is thought to underpin creative thought as it incorporates both divergent (generating multiple ideas and solutions) and convergent (arriving at the optimal solution) thinking approaches. The current literature on schizotypy and creativity is mixed and requires clarification. An alternate approach was employed by designing an exploratory web-based study using only correlates of schizotypal traits (paranoia, dissociation, cognitive failures, fantasy proneness, and unusual sleep experiences) and examining which (if any) predicted optimal performance on an insight problem-solving task. One hundred and twenty-one participants were recruited online from the general population and completed the number reduction task. The discovery of the hidden rule (HR) was used as a measure of insight. Multivariate logistic regression analyses highlighted persecutory ideation to best predict the discovery of the HR (OR = 1.05; 95% CI 1.01-1.10, p = 0.017), with a one-point increase in persecutory ideas corresponding to the participant being 5% more likely to discover the HR. This result suggests that persecutory ideation, above other schizotypy correlates, may be involved in insight problem solving.
NASA Technical Reports Server (NTRS)
Aires, Filipe; Rossow, William B.; Chedin, Alain; Hansen, James E. (Technical Monitor)
2000-01-01
The use of the Principal Component Analysis technique for the analysis of geophysical time series has been questioned in particular for its tendency to extract components that mix several physical phenomena even when the signal is just their linear sum. We demonstrate with a data simulation experiment that the Independent Component Analysis, a recently developed technique, is able to solve this problem. This new technique requires the statistical independence of components, a stronger constraint, that uses higher-order statistics, instead of the classical decorrelation a weaker constraint, that uses only second-order statistics. Furthermore, ICA does not require additional a priori information such as the localization constraint used in Rotational Techniques.
Paper simulation techniques in user requirements analysis for interactive computer systems
NASA Technical Reports Server (NTRS)
Ramsey, H. R.; Atwood, M. E.; Willoughby, J. K.
1979-01-01
This paper describes the use of a technique called 'paper simulation' in the analysis of user requirements for interactive computer systems. In a paper simulation, the user solves problems with the aid of a 'computer', as in normal man-in-the-loop simulation. In this procedure, though, the computer does not exist, but is simulated by the experimenters. This allows simulated problem solving early in the design effort, and allows the properties and degree of structure of the system and its dialogue to be varied. The technique, and a method of analyzing the results, are illustrated with examples from a recent paper simulation exercise involving a Space Shuttle flight design task
Knowledge-based control for robot self-localization
NASA Technical Reports Server (NTRS)
Bennett, Bonnie Kathleen Holte
1993-01-01
Autonomous robot systems are being proposed for a variety of missions including the Mars rover/sample return mission. Prior to any other mission objectives being met, an autonomous robot must be able to determine its own location. This will be especially challenging because location sensors like GPS, which are available on Earth, will not be useful, nor will INS sensors because their drift is too large. Another approach to self-localization is required. In this paper, we describe a novel approach to localization by applying a problem solving methodology. The term 'problem solving' implies a computational technique based on logical representational and control steps. In this research, these steps are derived from observing experts solving localization problems. The objective is not specifically to simulate human expertise but rather to apply its techniques where appropriate for computational systems. In doing this, we describe a model for solving the problem and a system built on that model, called localization control and logic expert (LOCALE), which is a demonstration of concept for the approach and the model. The results of this work represent the first successful solution to high-level control aspects of the localization problem.
Students’ Representation in Mathematical Word Problem-Solving: Exploring Students’ Self-efficacy
NASA Astrophysics Data System (ADS)
Sahendra, A.; Budiarto, M. T.; Fuad, Y.
2018-01-01
This descriptive qualitative research aims at investigating student represented in mathematical word problem solving based on self-efficacy. The research subjects are two eighth graders at a school in Surabaya with equal mathematical ability consisting of two female students with high and low self-efficacy. The subjects were chosen based on the results of test of mathematical ability, documentation of the result of middle test in even semester of 2016/2017 academic year, and results of questionnaire of mathematics word problem in terms of self-efficacy scale. The selected students were asked to do mathematical word problem solving and be interviewed. The result of this study shows that students with high self-efficacy tend to use multiple representations of sketches and mathematical models, whereas students with low self-efficacy tend to use single representation of sketches or mathematical models only in mathematical word problem-solving. This study emphasizes that teachers should pay attention of student’s representation as a consideration of designing innovative learning in order to increase the self-efficacy of each student to achieve maximum mathematical achievement although it still requires adjustment to the school situation and condition.
A hybrid nonlinear programming method for design optimization
NASA Technical Reports Server (NTRS)
Rajan, S. D.
1986-01-01
Solutions to engineering design problems formulated as nonlinear programming (NLP) problems usually require the use of more than one optimization technique. Moreover, the interaction between the user (analysis/synthesis) program and the NLP system can lead to interface, scaling, or convergence problems. An NLP solution system is presented that seeks to solve these problems by providing a programming system to ease the user-system interface. A simple set of rules is used to select an optimization technique or to switch from one technique to another in an attempt to detect, diagnose, and solve some potential problems. Numerical examples involving finite element based optimal design of space trusses and rotor bearing systems are used to illustrate the applicability of the proposed methodology.
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.
Sleep promotes analogical transfer in problem solving.
Monaghan, Padraic; Sio, Ut Na; Lau, Sum Wai; Woo, Hoi Kei; Linkenauger, Sally A; Ormerod, Thomas C
2015-10-01
Analogical problem solving requires using a known solution from one problem to apply to a related problem. Sleep is known to have profound effects on memory and information restructuring, and so we tested whether sleep promoted such analogical transfer, determining whether improvement was due to subjective memory for problems, subjective recognition of similarity across related problems, or by abstract generalisation of structure. In Experiment 1, participants were exposed to a set of source problems. Then, after a 12-h period involving sleep or wake, they attempted target problems structurally related to the source problems but with different surface features. Experiment 2 controlled for time of day effects by testing participants either in the morning or the evening. Sleep improved analogical transfer, but effects were not due to improvements in subjective memory or similarity recognition, but rather effects of structural generalisation across problems. Copyright © 2015 Elsevier B.V. All rights reserved.
Cognitive Load Mediates the Effect of Emotion on Analytical Thinking.
Trémolière, Bastien; Gagnon, Marie-Ève; Blanchette, Isabelle
2016-11-01
Although the detrimental effect of emotion on reasoning has been evidenced many times, the cognitive mechanism underlying this effect remains unclear. In the present paper, we explore the cognitive load hypothesis as a potential explanation. In an experiment, participants solved syllogistic reasoning problems with either neutral or emotional contents. Participants were also presented with a secondary task, for which the difficult version requires the mobilization of cognitive resources to be correctly solved. Participants performed overall worse and took longer on emotional problems than on neutral problems. Performance on the secondary task, in the difficult version, was poorer when participants were reasoning about emotional, compared to neutral contents, consistent with the idea that processing emotion requires more cognitive resources. Taken together, the findings afford evidence that the deleterious effect of emotion on reasoning is mediated by cognitive load.
PHYSICS REQUIRES A SIMPLE LOW MACH NUMBER FLOW TO BE COMPRESSIBLE
Radial, laminar, plane, low velocity flow represents the simplest, non-linear fluid dynamics problem. Ostensibly this apparently trivial flow could be solved using the incompressible Navier-Stokes equations, universally believed to be adequate for such problems. Most researchers ...
Digital program for solving the linear stochastic optimal control and estimation problem
NASA Technical Reports Server (NTRS)
Geyser, L. C.; Lehtinen, B.
1975-01-01
A computer program is described which solves the linear stochastic optimal control and estimation (LSOCE) problem by using a time-domain formulation. The LSOCE problem is defined as that of designing controls for a linear time-invariant system which is disturbed by white noise in such a way as to minimize a performance index which is quadratic in state and control variables. The LSOCE problem and solution are outlined; brief descriptions are given of the solution algorithms, and complete descriptions of each subroutine, including usage information and digital listings, are provided. A test case is included, as well as information on the IBM 7090-7094 DCS time and storage requirements.
Increasing the reliability of labor of railroad engineers
NASA Technical Reports Server (NTRS)
Genes, V. S.; Madiyevskiy, Y. M.
1975-01-01
It has been shown that the group of problems related to temporary overloads still require serious development with respect to further automating the basic control operation - programmed selection of speed and braking. The problem of systems for warning the engineer about the condition of the unseen track segments remains a very serious one. Systems of hygenic support of the engineer also require constructive development. The problems of ensuring the reliability of work of engineers in periods of low information load, requiring motor acts, can basically be considered theoretically solved.
Toward Solving the Problem of Problem Solving: An Analysis Framework
ERIC Educational Resources Information Center
Roesler, Rebecca A.
2016-01-01
Teaching is replete with problem solving. Problem solving as a skill, however, is seldom addressed directly within music teacher education curricula, and research in music education has not examined problem solving systematically. A framework detailing problem-solving component skills would provide a needed foundation. I observed problem solving…
Bicriteria Network Optimization Problem using Priority-based Genetic Algorithm
NASA Astrophysics Data System (ADS)
Gen, Mitsuo; Lin, Lin; Cheng, Runwei
Network optimization is being an increasingly important and fundamental issue in the fields such as engineering, computer science, operations research, transportation, telecommunication, decision support systems, manufacturing, and airline scheduling. In many applications, however, there are several criteria associated with traversing each edge of a network. For example, cost and flow measures are both important in the networks. As a result, there has been recent interest in solving Bicriteria Network Optimization Problem. The Bicriteria Network Optimization Problem is known a NP-hard. The efficient set of paths may be very large, possibly exponential in size. Thus the computational effort required to solve it can increase exponentially with the problem size in the worst case. In this paper, we propose a genetic algorithm (GA) approach used a priority-based chromosome for solving the bicriteria network optimization problem including maximum flow (MXF) model and minimum cost flow (MCF) model. The objective is to find the set of Pareto optimal solutions that give possible maximum flow with minimum cost. This paper also combines Adaptive Weight Approach (AWA) that utilizes some useful information from the current population to readjust weights for obtaining a search pressure toward a positive ideal point. Computer simulations show the several numerical experiments by using some difficult-to-solve network design problems, and show the effectiveness of the proposed method.
Solutions of the benchmark problems by the dispersion-relation-preserving scheme
NASA Technical Reports Server (NTRS)
Tam, Christopher K. W.; Shen, H.; Kurbatskii, K. A.; Auriault, L.
1995-01-01
The 7-point stencil Dispersion-Relation-Preserving scheme of Tam and Webb is used to solve all the six categories of the CAA benchmark problems. The purpose is to show that the scheme is capable of solving linear, as well as nonlinear aeroacoustics problems accurately. Nonlinearities, inevitably, lead to the generation of spurious short wave length numerical waves. Often, these spurious waves would overwhelm the entire numerical solution. In this work, the spurious waves are removed by the addition of artificial selective damping terms to the discretized equations. Category 3 problems are for testing radiation and outflow boundary conditions. In solving these problems, the radiation and outflow boundary conditions of Tam and Webb are used. These conditions are derived from the asymptotic solutions of the linearized Euler equations. Category 4 problems involved solid walls. Here, the wall boundary conditions for high-order schemes of Tam and Dong are employed. These conditions require the use of one ghost value per boundary point per physical boundary condition. In the second problem of this category, the governing equations, when written in cylindrical coordinates, are singular along the axis of the radial coordinate. The proper boundary conditions at the axis are derived by applying the limiting process of r approaches 0 to the governing equations. The Category 5 problem deals with the numerical noise issue. In the present approach, the time-independent mean flow solution is computed first. Once the residual drops to the machine noise level, the incident sound wave is turned on gradually. The solution is marched in time until a time-periodic state is reached. No exact solution is known for the Category 6 problem. Because of this, the problem is formulated in two totally different ways, first as a scattering problem then as a direct simulation problem. There is good agreement between the two numerical solutions. This offers confidence in the computed results. Both formulations are solved as initial value problems. As such, no Kutta condition is required at the trailing edge of the airfoil.
Hoppmann, Christiane A; Coats, Abby Heckman; Blanchard-Fields, Fredda
2008-07-01
Qualitative interviews on family and financial problems from 332 adolescents, young, middle-aged, and older adults, demonstrated that developmentally relevant goals predicted problem-solving strategy use over and above problem domain. Four focal goals concerned autonomy, generativity, maintaining good relationships with others, and changing another person. We examined both self- and other-focused problem-solving strategies. Autonomy goals were associated with self-focused instrumental problem solving and generative goals were related to other-focused instrumental problem solving in family and financial problems. Goals of changing another person were related to other-focused instrumental problem solving in the family domain only. The match between goals and strategies, an indicator of problem-solving adaptiveness, showed that young individuals displayed the greatest match between autonomy goals and self-focused problem solving, whereas older adults showed a greater match between generative goals and other-focused problem solving. Findings speak to the importance of considering goals in investigations of age-related differences in everyday problem solving.
ERIC Educational Resources Information Center
Walkington, Candace; Clinton, Virginia; Ritter, Steven N.; Nathan, Mitchell J.
2015-01-01
Solving mathematics story problems requires text comprehension skills. However, previous studies have found few connections between traditional measures of text readability and performance on story problems. We hypothesized that recently developed measures of readability and topic incidence measured by text-mining tools may illuminate associations…
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…
A Neural Dynamic Model Generates Descriptions of Object-Oriented Actions.
Richter, Mathis; Lins, Jonas; Schöner, Gregor
2017-01-01
Describing actions entails that relations between objects are discovered. A pervasively neural account of this process requires that fundamental problems are solved: the neural pointer problem, the binding problem, and the problem of generating discrete processing steps from time-continuous neural processes. We present a prototypical solution to these problems in a neural dynamic model that comprises dynamic neural fields holding representations close to sensorimotor surfaces as well as dynamic neural nodes holding discrete, language-like representations. Making the connection between these two types of representations enables the model to describe actions as well as to perceptually ground movement phrases-all based on real visual input. We demonstrate how the dynamic neural processes autonomously generate the processing steps required to describe or ground object-oriented actions. By solving the fundamental problems of neural pointing, binding, and emergent discrete processing, the model may be a first but critical step toward a systematic neural processing account of higher cognition. Copyright © 2017 The Authors. Topics in Cognitive Science published by Wiley Periodicals, Inc. on behalf of Cognitive Science Society.
Shaw, William S; Feuerstein, Michael; Miller, Virginia I; Wood, Patricia M
2003-08-01
Improving health and work outcomes for individuals with work related upper extremity disorders (WRUEDs) may require a broad assessment of potential return to work barriers by engaging workers in collaborative problem solving. In this study, half of all nurse case managers from a large workers' compensation system were randomly selected and invited to participate in a randomized, controlled trial of an integrated case management (ICM) approach for WRUEDs. The focus of ICM was problem solving skills training and workplace accommodation. Volunteer nurses attended a 2 day ICM training workshop including instruction in a 6 step process to engage clients in problem solving to overcome barriers to recovery. A chart review of WRUED case management reports (n = 70) during the following 2 years was conducted to extract case managers' reports of barriers to recovery and return to work. Case managers documented from 0 to 21 barriers per case (M = 6.24, SD = 4.02) within 5 domains: signs and symptoms (36%), work environment (27%), medical care (13%), functional limitations (12%), and coping (12%). Compared with case managers who did not receive the training (n = 67), workshop participants identified more barriers related to signs and symptoms, work environment, functional limitations, and coping (p < .05), but not to medical care. Problem solving skills training may help focus case management services on the most salient recovery factors affecting return to work.
Specific Features in Measuring Particle Size Distributions in Highly Disperse Aerosol Systems
NASA Astrophysics Data System (ADS)
Zagaynov, V. A.; Vasyanovich, M. E.; Maksimenko, V. V.; Lushnikov, A. A.; Biryukov, Yu. G.; Agranovskii, I. E.
2018-06-01
The distribution of highly dispersed aerosols is studied. Particular attention is given to the diffusion dynamic approach, as it is the best way to determine particle size distribution. It shown that the problem can be divided into two steps: directly measuring particle penetration through diffusion batteries and solving the inverse problem (obtaining a size distribution from the measured penetrations). No reliable way of solving the so-called inverse problem is found, but it can be done by introducing a parametrized size distribution (i.e., a gamma distribution). The integral equation is therefore reduced to a system of nonlinear equations that can be solved by elementary mathematical means. Further development of the method requires an increase in sensitivity (i.e., measuring the dimensions of molecular clusters with radioactive sources, along with the activity of diffusion battery screens).
An efficient and flexible Abel-inversion method for noisy data
NASA Astrophysics Data System (ADS)
Antokhin, Igor I.
2016-12-01
We propose an efficient and flexible method for solving the Abel integral equation of the first kind, frequently appearing in many fields of astrophysics, physics, chemistry, and applied sciences. This equation represents an ill-posed problem, thus solving it requires some kind of regularization. Our method is based on solving the equation on a so-called compact set of functions and/or using Tikhonov's regularization. A priori constraints on the unknown function, defining a compact set, are very loose and can be set using simple physical considerations. Tikhonov's regularization in itself does not require any explicit a priori constraints on the unknown function and can be used independently of such constraints or in combination with them. Various target degrees of smoothness of the unknown function may be set, as required by the problem at hand. The advantage of the method, apart from its flexibility, is that it gives uniform convergence of the approximate solution to the exact solution, as the errors of input data tend to zero. The method is illustrated on several simulated models with known solutions. An example of astrophysical application of the method is also given.
Resources in Technology: Problem-Solving.
ERIC Educational Resources Information Center
Technology Teacher, 1986
1986-01-01
This instructional module examines a key function of science and technology: problem solving. It studies the meaning of problem solving, looks at techniques for problem solving, examines case studies that exemplify the problem-solving approach, presents problems for the reader to solve, and provides a student self-quiz. (Author/CT)
Algorithm Optimally Allocates Actuation of a Spacecraft
NASA Technical Reports Server (NTRS)
Motaghedi, Shi
2007-01-01
A report presents an algorithm that solves the following problem: Allocate the force and/or torque to be exerted by each thruster and reaction-wheel assembly on a spacecraft for best performance, defined as minimizing the error between (1) the total force and torque commanded by the spacecraft control system and (2) the total of forces and torques actually exerted by all the thrusters and reaction wheels. The algorithm incorporates the matrix vector relationship between (1) the total applied force and torque and (2) the individual actuator force and torque values. It takes account of such constraints as lower and upper limits on the force or torque that can be applied by a given actuator. The algorithm divides the aforementioned problem into two optimization problems that it solves sequentially. These problems are of a type, known in the art as semi-definite programming problems, that involve linear matrix inequalities. The algorithm incorporates, as sub-algorithms, prior algorithms that solve such optimization problems very efficiently. The algorithm affords the additional advantage that the solution requires the minimum rate of consumption of fuel for the given best performance.
A SYSTEMATIC PROCEDURE FOR DESIGNING PROCESSES WITH MULTIPLE ENVIRONMENTAL OBJECTIVES
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....
Engineering neural systems for high-level problem solving.
Sylvester, Jared; Reggia, James
2016-07-01
There is a long-standing, sometimes contentious debate in AI concerning the relative merits of a symbolic, top-down approach vs. a neural, bottom-up approach to engineering intelligent machine behaviors. While neurocomputational methods excel at lower-level cognitive tasks (incremental learning for pattern classification, low-level sensorimotor control, fault tolerance and processing of noisy data, etc.), they are largely non-competitive with top-down symbolic methods for tasks involving high-level cognitive problem solving (goal-directed reasoning, metacognition, planning, etc.). Here we take a step towards addressing this limitation by developing a purely neural framework named galis. Our goal in this work is to integrate top-down (non-symbolic) control of a neural network system with more traditional bottom-up neural computations. galis is based on attractor networks that can be "programmed" with temporal sequences of hand-crafted instructions that control problem solving by gating the activity retention of, communication between, and learning done by other neural networks. We demonstrate the effectiveness of this approach by showing that it can be applied successfully to solve sequential card matching problems, using both human performance and a top-down symbolic algorithm as experimental controls. Solving this kind of problem makes use of top-down attention control and the binding together of visual features in ways that are easy for symbolic AI systems but not for neural networks to achieve. Our model can not only be instructed on how to solve card matching problems successfully, but its performance also qualitatively (and sometimes quantitatively) matches the performance of both human subjects that we had perform the same task and the top-down symbolic algorithm that we used as an experimental control. We conclude that the core principles underlying the galis framework provide a promising approach to engineering purely neurocomputational systems for problem-solving tasks that in people require higher-level cognitive functions. Copyright © 2016 Elsevier Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Ortega Gelabert, Olga; Zlotnik, Sergio; Afonso, Juan Carlos; Díez, Pedro
2017-04-01
The determination of the present-day physical state of the thermal and compositional structure of the Earth's lithosphere and sub-lithospheric mantle is one of the main goals in modern lithospheric research. All this data is essential to build Earth's evolution models and to reproduce many geophysical observables (e.g. elevation, gravity anomalies, travel time data, heat flow, etc) together with understanding the relationship between them. Determining the lithospheric state involves the solution of high-resolution inverse problems and, consequently, the solution of many direct models is required. The main objective of this work is to contribute to the existing inversion techniques in terms of improving the estimation of the elevation (topography) by including a dynamic component arising from sub-lithospheric mantle flow. In order to do so, we implement an efficient Reduced Order Method (ROM) built upon classic Finite Elements. ROM allows to reduce significantly the computational cost of solving a family of problems, for example all the direct models that are required in the solution of the inverse problem. The strategy of the method consists in creating a (reduced) basis of solutions, so that when a new problem has to be solved, its solution is sought within the basis instead of attempting to solve the problem itself. In order to check the Reduced Basis approach, we implemented the method in a 3D domain reproducing a portion of Earth that covers up to 400 km depth. Within the domain the Stokes equation is solved with realistic viscosities and densities. The different realizations (the family of problems) is created by varying viscosities and densities in a similar way as it would happen in an inversion problem. The Reduced Basis method is shown to be an extremely efficiently solver for the Stokes equation in this context.
Total-variation based velocity inversion with Bregmanized operator splitting algorithm
NASA Astrophysics Data System (ADS)
Zand, Toktam; Gholami, Ali
2018-04-01
Many problems in applied geophysics can be formulated as a linear inverse problem. The associated problems, however, are large-scale and ill-conditioned. Therefore, regularization techniques are needed to be employed for solving them and generating a stable and acceptable solution. We consider numerical methods for solving such problems in this paper. In order to tackle the ill-conditioning of the problem we use blockiness as a prior information of the subsurface parameters and formulate the problem as a constrained total variation (TV) regularization. The Bregmanized operator splitting (BOS) algorithm as a combination of the Bregman iteration and the proximal forward backward operator splitting method is developed to solve the arranged problem. Two main advantages of this new algorithm are that no matrix inversion is required and that a discrepancy stopping criterion is used to stop the iterations, which allow efficient solution of large-scale problems. The high performance of the proposed TV regularization method is demonstrated using two different experiments: 1) velocity inversion from (synthetic) seismic data which is based on Born approximation, 2) computing interval velocities from RMS velocities via Dix formula. Numerical examples are presented to verify the feasibility of the proposed method for high-resolution velocity inversion.
Block clustering based on difference of convex functions (DC) programming and DC algorithms.
Le, Hoai Minh; Le Thi, Hoai An; Dinh, Tao Pham; Huynh, Van Ngai
2013-10-01
We investigate difference of convex functions (DC) programming and the DC algorithm (DCA) to solve the block clustering problem in the continuous framework, which traditionally requires solving a hard combinatorial optimization problem. DC reformulation techniques and exact penalty in DC programming are developed to build an appropriate equivalent DC program of the block clustering problem. They lead to an elegant and explicit DCA scheme for the resulting DC program. Computational experiments show the robustness and efficiency of the proposed algorithm and its superiority over standard algorithms such as two-mode K-means, two-mode fuzzy clustering, and block classification EM.
Programming and Tuning a Quantum Annealing Device to Solve Real World Problems
NASA Astrophysics Data System (ADS)
Perdomo-Ortiz, Alejandro; O'Gorman, Bryan; Fluegemann, Joseph; Smelyanskiy, Vadim
2015-03-01
Solving real-world applications with quantum algorithms requires overcoming several challenges, ranging from translating the computational problem at hand to the quantum-machine language to tuning parameters of the quantum algorithm that have a significant impact on the performance of the device. In this talk, we discuss these challenges, strategies developed to enhance performance, and also a more efficient implementation of several applications. Although we will focus on applications of interest to NASA's Quantum Artificial Intelligence Laboratory, the methods and concepts presented here apply to a broader family of hard discrete optimization problems, including those that occur in many machine-learning algorithms.
Exploiting replication in distributed systems
NASA Technical Reports Server (NTRS)
Birman, Kenneth P.; Joseph, T. A.
1989-01-01
Techniques are examined for replicating data and execution in directly distributed systems: systems in which multiple processes interact directly with one another while continuously respecting constraints on their joint behavior. Directly distributed systems are often required to solve difficult problems, ranging from management of replicated data to dynamic reconfiguration in response to failures. It is shown that these problems reduce to more primitive, order-based consistency problems, which can be solved using primitives such as the reliable broadcast protocols. Moreover, given a system that implements reliable broadcast primitives, a flexible set of high-level tools can be provided for building a wide variety of directly distributed application programs.
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.
Variational data assimilation for the initial-value dynamo problem.
Li, Kuan; Jackson, Andrew; Livermore, Philip W
2011-11-01
The secular variation of the geomagnetic field as observed at the Earth's surface results from the complex magnetohydrodynamics taking place in the fluid core of the Earth. One way to analyze this system is to use the data in concert with an underlying dynamical model of the system through the technique of variational data assimilation, in much the same way as is employed in meteorology and oceanography. The aim is to discover an optimal initial condition that leads to a trajectory of the system in agreement with observations. Taking the Earth's core to be an electrically conducting fluid sphere in which convection takes place, we develop the continuous adjoint forms of the magnetohydrodynamic equations that govern the dynamical system together with the corresponding numerical algorithms appropriate for a fully spectral method. These adjoint equations enable a computationally fast iterative improvement of the initial condition that determines the system evolution. The initial condition depends on the three dimensional form of quantities such as the magnetic field in the entire sphere. For the magnetic field, conservation of the divergence-free condition for the adjoint magnetic field requires the introduction of an adjoint pressure term satisfying a zero boundary condition. We thus find that solving the forward and adjoint dynamo system requires different numerical algorithms. In this paper, an efficient algorithm for numerically solving this problem is developed and tested for two illustrative problems in a whole sphere: one is a kinematic problem with prescribed velocity field, and the second is associated with the Hall-effect dynamo, exhibiting considerable nonlinearity. The algorithm exhibits reliable numerical accuracy and stability. Using both the analytical and the numerical techniques of this paper, the adjoint dynamo system can be solved directly with the same order of computational complexity as that required to solve the forward problem. These numerical techniques form a foundation for ultimate application to observations of the geomagnetic field over the time scale of centuries.
New Galerkin operational matrices for solving Lane-Emden type equations
NASA Astrophysics Data System (ADS)
Abd-Elhameed, W. M.; Doha, E. H.; Saad, A. S.; Bassuony, M. A.
2016-04-01
Lane-Emden type equations model many phenomena in mathematical physics and astrophysics, such as thermal explosions. This paper is concerned with introducing third and fourth kind Chebyshev-Galerkin operational matrices in order to solve such problems. The principal idea behind the suggested algorithms is based on converting the linear or nonlinear Lane-Emden problem, through the application of suitable spectral methods, into a system of linear or nonlinear equations in the expansion coefficients, which can be efficiently solved. The main advantage of the proposed algorithm in the linear case is that the resulting linear systems are specially structured, and this of course reduces the computational effort required to solve such systems. As an application, we consider the solar model polytrope with n=3 to show that the suggested solutions in this paper are in good agreement with the numerical results.
Genetic algorithm parameters tuning for resource-constrained project scheduling problem
NASA Astrophysics Data System (ADS)
Tian, Xingke; Yuan, Shengrui
2018-04-01
Project Scheduling Problem (RCPSP) is a kind of important scheduling problem. To achieve a certain optimal goal such as the shortest duration, the smallest cost, the resource balance and so on, it is required to arrange the start and finish of all tasks under the condition of satisfying project timing constraints and resource constraints. In theory, the problem belongs to the NP-hard problem, and the model is abundant. Many combinatorial optimization problems are special cases of RCPSP, such as job shop scheduling, flow shop scheduling and so on. At present, the genetic algorithm (GA) has been used to deal with the classical RCPSP problem and achieved remarkable results. Vast scholars have also studied the improved genetic algorithm for the RCPSP problem, which makes it to solve the RCPSP problem more efficiently and accurately. However, for the selection of the main parameters of the genetic algorithm, there is no parameter optimization in these studies. Generally, we used the empirical method, but it cannot ensure to meet the optimal parameters. In this paper, the problem was carried out, which is the blind selection of parameters in the process of solving the RCPSP problem. We made sampling analysis, the establishment of proxy model and ultimately solved the optimal parameters.
A Cognitive Analysis of Students’ Mathematical Problem Solving Ability on Geometry
NASA Astrophysics Data System (ADS)
Rusyda, N. A.; Kusnandi, K.; Suhendra, S.
2017-09-01
The purpose of this research is to analyze of mathematical problem solving ability of students in one of secondary school on geometry. This research was conducted by using quantitative approach with descriptive method. Population in this research was all students of that school and the sample was twenty five students that was chosen by purposive sampling technique. Data of mathematical problem solving were collected through essay test. The results showed the percentage of achievement of mathematical problem solving indicators of students were: 1) solve closed mathematical problems with context in math was 50%; 2) solve the closed mathematical problems with the context beyond mathematics was 24%; 3) solving open mathematical problems with contexts in mathematics was 35%; And 4) solving open mathematical problems with contexts outside mathematics was 44%. Based on the percentage, it can be concluded that the level of achievement of mathematical problem solving ability in geometry still low. This is because students are not used to solving problems that measure mathematical problem solving ability, weaknesses remember previous knowledge, and lack of problem solving framework. So the students’ ability of mathematical problems solving need to be improved with implement appropriate learning strategy.
An investigation of the effects of interventions on problem-solving strategies and abilities
NASA Astrophysics Data System (ADS)
Cox, Charles Terrence, Jr.
Problem-solving has been described as being the "heart" of the chemistry classroom, and students' development of problem-solving skills is essential for their success in chemistry. Despite the importance of problem-solving, there has been little research within the chemistry domain, largely because of the lack of tools to collect data for large populations. Problem-solving was assessed using a software package known as IMMEX (for Interactive Multimedia Exercises) which has an HTML tracking feature that allows for collection of problem-solving data in the background as students work the problems. The primary goal of this research was to develop methods (known as interventions) that could promote improvements in students' problem-solving and most notably aid in their transition from the novice to competent level. Three intervention techniques that were incorporated within the chemistry curricula: collaborative grouping (face-to-face and distance), concept mapping, and peer-led team learning. The face-to-face collaborative grouping intervention was designed to probe the factors affecting the quality of the group interaction. Students' logical reasoning abilities were measured using the Group Assessment of Logical Thinking (GALT) test which classifies students as formal, transitional, or concrete. These classifications essentially provide a basis for identifying scientific aptitude. These designations were used as the basis for forming collaborative groups of two students. The six possibilities (formal-formal, formal-transitional, etc.) were formed to determine how the group composition influences the gains in student abilities observed from collaborative grouping interventions. Students were given three assignments (an individual pre-collaborative, an individual post collaborative, and a collaborative assignment) each requiring them to work an IMMEX problem set. Similar gains in performance of 10% gains were observed for each group with two exceptions. The transitional students who were paired with concrete students had a 15% gain, and the concrete students paired with other concrete students had only a marginal gain. In fact, there was no statistical difference in the pre-collaborative and post-collaborative student abilities for concrete-concrete groups. The distance collaborative intervention was completed using a new interface for the IMMEX software designed to mimic face-to-face collaboration. A stereochemistry problem set which had a solved rate of 28% prior to collaboration was chosen for incorporation into this distance collaboration study. (Abstract shortened by UMI.)
Efficient Parallel Formulations of Hierarchical Methods and Their Applications
NASA Astrophysics Data System (ADS)
Grama, Ananth Y.
1996-01-01
Hierarchical methods such as the Fast Multipole Method (FMM) and Barnes-Hut (BH) are used for rapid evaluation of potential (gravitational, electrostatic) fields in particle systems. They are also used for solving integral equations using boundary element methods. The linear systems arising from these methods are dense and are solved iteratively. Hierarchical methods reduce the complexity of the core matrix-vector product from O(n^2) to O(n log n) and the memory requirement from O(n^2) to O(n). We have developed highly scalable parallel formulations of a hybrid FMM/BH method that are capable of handling arbitrarily irregular distributions. We apply these formulations to astrophysical simulations of Plummer and Gaussian galaxies. We have used our parallel formulations to solve the integral form of the Laplace equation. We show that our parallel hierarchical mat-vecs yield high efficiency and overall performance even on relatively small problems. A problem containing approximately 200K nodes takes under a second to compute on 256 processors and yet yields over 85% efficiency. The efficiency and raw performance is expected to increase for bigger problems. For the 200K node problem, our code delivers about 5 GFLOPS of performance on a 256 processor T3D. This is impressive considering the fact that the problem has floating point divides and roots, and very little locality resulting in poor cache performance. A dense matrix-vector product of the same dimensions would require about 0.5 TeraBytes of memory and about 770 TeraFLOPS of computing speed. Clearly, if the loss in accuracy resulting from the use of hierarchical methods is acceptable, our code yields significant savings in time and memory. We also study the convergence of a GMRES solver built around this mat-vec. We accelerate the convergence of the solver using three preconditioning techniques: diagonal scaling, block-diagonal preconditioning, and inner-outer preconditioning. We study the performance and parallel efficiency of these preconditioned solvers. Using this solver, we solve dense linear systems with hundreds of thousands of unknowns. Solving a 105K unknown problem takes about 10 minutes on a 64 processor T3D. Until very recently, boundary element problems of this magnitude could not even be generated, let alone solved.
ERIC Educational Resources Information Center
Berardi, Victor L.
2012-01-01
Using information systems to solve business problems is increasingly required of everyone in an organization, not just technical specialists. In the operations management class, spreadsheet usage has intensified with the focus on building decision models to solve operations management concerns such as forecasting, process capability, and inventory…
Learning to Write about Mathematics
ERIC Educational Resources Information Center
Parker, Renee; Breyfogle, M. Lynn
2011-01-01
Beginning in third grade, Pennsylvania students are required to take the Pennsylvania State Standardized Assessment (PSSA), which presents multiple-choice mathematics questions and open-ended mathematics problems. Consistent with the Communication Standard of the National Council of Teachers of Mathematics, while solving the open-ended problems,…
Nozari, Ali Yazdanpanah; Siamian, Hasan
2014-12-01
Nowadays, regarding the learners' needs and social conditions, it is obviously needed to revise and reconsider the traditional methods and approaches in teaching. The problem solving approach is one of the new ways in Teaching and learning process. This study aimed at studying and examining the effect of "problem-solving" approach on creative thinking of high school female students. An experimental method is used for this research. In this research, 342 out of 3047 female-students from Sari high schools were randomly selected. These 342 students were divided into two groups (experimental and control) in which there were seven classrooms. The total number of students in every group was about 171. After testing them with Jamal Abedi creativity test, it was revealed that two groups were equal in creativity score. The tests were done through Requirements. The experimental group was taught by problem solving method for three months while the control group was taught by traditional method. The research results showed that using descriptive indices and t-test for the two independent sample groups in which problem solving teaching method was used in teaching processes had an effect on creativity level in comparison with traditional method used in the control group. Considering the results of this study, the application of problem-solving teaching methods increased the creativity and its components (fluidity, expansion, originality and flexibility) in learners, therefore, it is recommended that students be encouraged to take classes on frequent responses on various topics (variability) and draw attention on different issues, and expand their analysis on elements in particular courses like art (expansion). To enhance the learner's mental flexibility and attention to various aspects, they are encouraged to provide a variety of responses.
NOTE: Solving the ECG forward problem by means of a meshless finite element method
NASA Astrophysics Data System (ADS)
Li, Z. S.; Zhu, S. A.; He, Bin
2007-07-01
The conventional numerical computational techniques such as the finite element method (FEM) and the boundary element method (BEM) require laborious and time-consuming model meshing. The new meshless FEM only uses the boundary description and the node distribution and no meshing of the model is required. This paper presents the fundamentals and implementation of meshless FEM and the meshless FEM method is adapted to solve the electrocardiography (ECG) forward problem. The method is evaluated on a single-layer torso model, in which the analytical solution exists, and tested in a realistic geometry homogeneous torso model, with satisfactory results being obtained. The present results suggest that the meshless FEM may provide an alternative for ECG forward solutions.
Insight and analysis problem solving in microbes to machines.
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.
GASOLINE: Smoothed Particle Hydrodynamics (SPH) code
NASA Astrophysics Data System (ADS)
N-Body Shop
2017-10-01
Gasoline solves the equations of gravity and hydrodynamics in astrophysical problems, including simulations of planets, stars, and galaxies. It uses an SPH method that features correct mixing behavior in multiphase fluids and minimal artificial viscosity. This method is identical to the SPH method used in the ChaNGa code (ascl:1105.005), allowing users to extend results to problems requiring >100,000 cores. Gasoline uses a fast, memory-efficient O(N log N) KD-Tree to solve Poisson's Equation for gravity and avoids artificial viscosity in non-shocking compressive flows.
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.
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.
Contact in an Expanding Universe: An Instructive Exercise in Dynamic Geometry
ERIC Educational Resources Information Center
Zimmerman, Seth
2010-01-01
The particular problem solved in this paper is that of calculating the time required to overtake a distant object receding under cosmic expansion, and the speed at which that object is passed. This is a rarely investigated problem leading to some interesting apparent paradoxes. We employ the problem to promote a deeper understanding of the dynamic…
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…
Unfinished Student Answer in PISA Mathematics Contextual Problem
ERIC Educational Resources Information Center
Lutfianto, Moch.; Zulkardi; Hartono, Yusuf
2013-01-01
Solving mathematics contextual problems is one way that can be used to enable students to have the skills needed to live in the 21st century. Completion contextual problem requires a series of steps in order to properly answer the questions that are asked. The purpose of this study was to determine the steps performed students in solving…
Children's Understanding of the Inverse Relation between Multiplication and Division
ERIC Educational Resources Information Center
Robinson, Katherine M.; Dube, Adam K.
2009-01-01
Children's understanding of the inversion concept in multiplication and division problems (i.e., that on problems of the form "d multiplied by e/e" no calculations are required) was investigated. Children in Grades 6, 7, and 8 completed an inversion problem-solving task, an assessment of procedures task, and a factual knowledge task of simple…
Multidisciplinary approaches to climate change questions
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.
Designing Efficient Self-Diagnosis Activities in the Physics Classroom
NASA Astrophysics Data System (ADS)
Safadi, Rafi'
2017-12-01
Self-diagnosis (SD) activities require students to self-diagnose their solutions to problems that they solved on their own. This involves identifying where they went wrong and then explaining the nature of their errors—why they went wrong—aided by some form of support. Worked examples (WEs) are often used to support students in SD activities. A WE is a step-by-step demonstration of how to solve a problem. One unresolved issue is why students fail to exploit WEs in SD exercises. Yerushalmi et al., for instance, provided students with written WEs and asked them to self-diagnose their solutions with respect to these WEs. These authors found no correlation between students' SD performance and their subsequent problem-solving performance on transfer problems, suggesting that students had only superficially exploited the written WEs. The aim of this article is to describe a new SD activity that was developed to prompt students to effectively use written WEs when self-diagnosing, and to examine its effectiveness in advancing students' learning in physics.
Hoppmann, Christiane A; Blanchard-Fields, Fredda
2011-09-01
Problem-solving does not take place in isolation and often involves social others such as spouses. Using repeated daily life assessments from 98 older spouses (M age = 72 years; M marriage length = 42 years), the present study examined theoretical notions from social-contextual models of coping regarding (a) the origins of problem-solving variability and (b) associations between problem-solving and specific problem-, person-, and couple- characteristics. Multilevel models indicate that the lion's share of variability in everyday problem-solving is located at the level of the problem situation. Importantly, participants reported more proactive emotion regulation and collaborative problem-solving for social than nonsocial problems. We also found person-specific consistencies in problem-solving. That is, older spouses high in Neuroticism reported more problems across the study period as well as less instrumental problem-solving and more passive emotion regulation than older spouses low in Neuroticism. Contrary to expectations, relationship satisfaction was unrelated to problem-solving in the present sample. Results are in line with the stress and coping literature in demonstrating that everyday problem-solving is a dynamic process that has to be viewed in the broader context in which it occurs. Our findings also complement previous laboratory-based work on everyday problem-solving by underscoring the benefits of examining everyday problem-solving as it unfolds in spouses' own environment.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Zou, Ling; Zhao, Haihua; Zhang, Hongbin
2016-04-01
The phase appearance/disappearance issue presents serious numerical challenges in two-phase flow simulations. Many existing reactor safety analysis codes use different kinds of treatments for the phase appearance/disappearance problem. However, to our best knowledge, there are no fully satisfactory solutions. Additionally, the majority of the existing reactor system analysis codes were developed using low-order numerical schemes in both space and time. In many situations, it is desirable to use high-resolution spatial discretization and fully implicit time integration schemes to reduce numerical errors. In this work, we adapted a high-resolution spatial discretization scheme on staggered grid mesh and fully implicit time integrationmore » methods (such as BDF1 and BDF2) to solve the two-phase flow problems. The discretized nonlinear system was solved by the Jacobian-free Newton Krylov (JFNK) method, which does not require the derivation and implementation of analytical Jacobian matrix. These methods were tested with a few two-phase flow problems with phase appearance/disappearance phenomena considered, such as a linear advection problem, an oscillating manometer problem, and a sedimentation problem. The JFNK method demonstrated extremely robust and stable behaviors in solving the two-phase flow problems with phase appearance/disappearance. No special treatments such as water level tracking or void fraction limiting were used. High-resolution spatial discretization and second- order fully implicit method also demonstrated their capabilities in significantly reducing numerical errors.« less
Testing the effectiveness of problem-based learning with learning-disabled students in biology
NASA Astrophysics Data System (ADS)
Guerrera, Claudia Patrizia
The purpose of the present study was to investigate the effects of problem-based learning (PBL) with learning-disabled (LD) students. Twenty-four students (12 dyads) classified as LD and attending a school for the learning-disabled participated in the study. Students engaged in either a computer-based environment involving BioWorld, a hospital simulation designed to teach biology students problem-solving skills, or a paper-and-pencil version based on the computer program. A hybrid model of learning was adopted whereby students were provided with direct instruction on the digestive system prior to participating in a problem-solving activity. Students worked in dyads and solved three problems involving the digestive system in either a computerized or a paper-and-pencil condition. The experimenter acted as a coach to assist students throughout the problem-solving process. A follow-up study was conducted, one month later, to measure the long-term learning gains. Quantitative and qualitative methods were used to analyze three types of data: process data, outcome data, and follow-up data. Results from the process data showed that all students engaged in effective collaboration and became more systematic in their problem solving over time. Findings from the outcome and follow-up data showed that students in both treatment conditions, made both learning and motivational gains and that these benefits were still evident one month later. Overall, results demonstrated that the computer facilitated students' problem solving and scientific reasoning skills. Some differences were noted in students' collaboration and the amount of assistance required from the coach in both conditions. Thus, PBL is an effective learning approach with LD students in science, regardless of the type of learning environment. These results have implications for teaching science to LD students, as well as for future designs of educational software for this population.
Resource Letter RPS-1: Research in problem solving
NASA Astrophysics Data System (ADS)
Hsu, Leonardo; Brewe, Eric; Foster, Thomas M.; Harper, Kathleen A.
2004-09-01
This Resource Letter provides a guide to the literature on research in problem solving, especially in physics. The references were compiled with two audiences in mind: physicists who are (or might become) engaged in research on problem solving, and physics instructors who are interested in using research results to improve their students' learning of problem solving. In addition to general references, journal articles and books are cited for the following topics: cognitive aspects of problem solving, expert-novice problem-solver characteristics, problem solving in mathematics, alternative problem types, curricular interventions, and the use of computers in problem solving.
ERIC Educational Resources Information Center
Öllinger, Michael; Jones, Gary; Faber, Amory H.; Knoblich, Günther
2013-01-01
The 8-coin insight problem requires the problem solver to move 2 coins so that each coin touches exactly 3 others. Ormerod, MacGregor, and Chronicle (2002) explained differences in task performance across different versions of the 8-coin problem using the availability of particular moves in a 2-dimensional search space. We explored 2 further…
NASA Astrophysics Data System (ADS)
Nikooeinejad, Z.; Delavarkhalafi, A.; Heydari, M.
2018-03-01
The difficulty of solving the min-max optimal control problems (M-MOCPs) with uncertainty using generalised Euler-Lagrange equations is caused by the combination of split boundary conditions, nonlinear differential equations and the manner in which the final time is treated. In this investigation, the shifted Jacobi pseudospectral method (SJPM) as a numerical technique for solving two-point boundary value problems (TPBVPs) in M-MOCPs for several boundary states is proposed. At first, a novel framework of approximate solutions which satisfied the split boundary conditions automatically for various boundary states is presented. Then, by applying the generalised Euler-Lagrange equations and expanding the required approximate solutions as elements of shifted Jacobi polynomials, finding a solution of TPBVPs in nonlinear M-MOCPs with uncertainty is reduced to the solution of a system of algebraic equations. Moreover, the Jacobi polynomials are particularly useful for boundary value problems in unbounded domain, which allow us to solve infinite- as well as finite and free final time problems by domain truncation method. Some numerical examples are given to demonstrate the accuracy and efficiency of the proposed method. A comparative study between the proposed method and other existing methods shows that the SJPM is simple and accurate.
Transfer of Problem Solving Skills from Touchscreen to 3D Model by 3- to 6-Year-Olds
Tarasuik, Joanne; Demaria, Ana; Kaufman, Jordy
2017-01-01
Although much published research purports that young children struggle to solve problems from screen-based media and to transfer learning from a virtual to a physical modality, Huber et al. (2016)’s recent study on children solving the Tower of Hanoi (ToH) problem on a touchscreen app offers a clear counter example. Huber et al. (2016) reported that children transferred learning from media to the physical world. As this finding arguably differs from that of prior research in this area, the current study tests whether the Huber et al. (2016) results could be replicated. Additionally, we extended the scope of the Huber et al. (2016) work by testing a broader age range, including children as young as 3 years, and using a culturally distinct participant pool. The results of the current study verified Huber et al.’s (2016) conclusion that 4- to 6-year-old children are capable of transferring the ToH learning from touchscreen devices to the physical version of the puzzle. Children under 4 years of age, in contrast, showed little ability to improve at the ToH problem regardless of the practice modality—suggesting that a different problem-solving task is required to probe very young children’s ability to learn from touchscreen apps. PMID:28979222
Numerical solution of the quantum Lenard-Balescu equation for a non-degenerate one-component plasma
Scullard, Christian R.; Belt, Andrew P.; Fennell, Susan C.; ...
2016-09-01
We present a numerical solution of the quantum Lenard-Balescu equation using a spectral method, namely an expansion in Laguerre polynomials. This method exactly conserves both particles and kinetic energy and facilitates the integration over the dielectric function. To demonstrate the method, we solve the equilibration problem for a spatially homogeneous one-component plasma with various initial conditions. Unlike the more usual Landau/Fokker-Planck system, this method requires no input Coulomb logarithm; the logarithmic terms in the collision integral arise naturally from the equation along with the non-logarithmic order-unity terms. The spectral method can also be used to solve the Landau equation andmore » a quantum version of the Landau equation in which the integration over the wavenumber requires only a lower cutoff. We solve these problems as well and compare them with the full Lenard-Balescu solution in the weak-coupling limit. Finally, we discuss the possible generalization of this method to include spatial inhomogeneity and velocity anisotropy.« less
Leikin, Mark; Waisman, Ilana; Shaul, Shelley; Leikin, Roza
2014-03-01
This paper presents a small part of a larger interdisciplinary study that investigates brain activity (using event related potential methodology) of male adolescents when solving mathematical problems of different types. The study design links mathematics education research with neurocognitive studies. In this paper we performed a comparative analysis of brain activity associated with the translation from visual to symbolic representations of mathematical objects in algebra and geometry. Algebraic tasks require translation from graphical to symbolic representation of a function, whereas tasks in geometry require translation from a drawing of a geometric figure to a symbolic representation of its property. The findings demonstrate that electrical activity associated with the performance of geometrical tasks is stronger than that associated with solving algebraic tasks. Additionally, we found different scalp topography of the brain activity associated with algebraic and geometric tasks. Based on these results, we argue that problem solving in algebra and geometry is associated with different patterns of brain activity.
A globally convergent LCL method for nonlinear optimization.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Friedlander, M. P.; Saunders, M. A.; Mathematics and Computer Science
2005-01-01
For optimization problems with nonlinear constraints, linearly constrained Lagrangian (LCL) methods solve a sequence of subproblems of the form 'minimize an augmented Lagrangian function subject to linearized constraints.' Such methods converge rapidly near a solution but may not be reliable from arbitrary starting points. Nevertheless, the well-known software package MINOS has proved effective on many large problems. Its success motivates us to derive a related LCL algorithm that possesses three important properties: it is globally convergent, the subproblem constraints are always feasible, and the subproblems may be solved inexactly. The new algorithm has been implemented in Matlab, with an optionmore » to use either MINOS or SNOPT (Fortran codes) to solve the linearly constrained subproblems. Only first derivatives are required. We present numerical results on a subset of the COPS, HS, and CUTE test problems, which include many large examples. The results demonstrate the robustness and efficiency of the stabilized LCL procedure.« less
NASA Astrophysics Data System (ADS)
Handayani, I.; Januar, R. L.; Purwanto, S. E.
2018-01-01
This research aims to know the influence of Missouri Mathematics Project Learning Model to Mathematical Problem-solving Ability of Students at Junior High School. This research is a quantitative research and uses experimental research method of Quasi Experimental Design. The research population includes all student of grade VII of Junior High School who are enrolled in the even semester of the academic year 2016/2017. The Sample studied are 76 students from experimental and control groups. The sampling technique being used is cluster sampling method. The instrument is consisted of 7 essay questions whose validity, reliability, difficulty level and discriminating power have been tested. Before analyzing the data by using t-test, the data has fulfilled the requirement for normality and homogeneity. The result of data shows that there is the influence of Missouri mathematics project learning model to mathematical problem-solving ability of students at junior high school with medium effect.
Homotopy approach to optimal, linear quadratic, fixed architecture compensation
NASA Technical Reports Server (NTRS)
Mercadal, Mathieu
1991-01-01
Optimal linear quadratic Gaussian compensators with constrained architecture are a sensible way to generate good multivariable feedback systems meeting strict implementation requirements. The optimality conditions obtained from the constrained linear quadratic Gaussian are a set of highly coupled matrix equations that cannot be solved algebraically except when the compensator is centralized and full order. An alternative to the use of general parameter optimization methods for solving the problem is to use homotopy. The benefit of the method is that it uses the solution to a simplified problem as a starting point and the final solution is then obtained by solving a simple differential equation. This paper investigates the convergence properties and the limitation of such an approach and sheds some light on the nature and the number of solutions of the constrained linear quadratic Gaussian problem. It also demonstrates the usefulness of homotopy on an example of an optimal decentralized compensator.
An evaluation of exact methods for the multiple subset maximum cardinality selection problem.
Brusco, Michael J; Köhn, Hans-Friedrich; Steinley, Douglas
2016-05-01
The maximum cardinality subset selection problem requires finding the largest possible subset from a set of objects, such that one or more conditions are satisfied. An important extension of this problem is to extract multiple subsets, where the addition of one more object to a larger subset would always be preferred to increases in the size of one or more smaller subsets. We refer to this as the multiple subset maximum cardinality selection problem (MSMCSP). A recently published branch-and-bound algorithm solves the MSMCSP as a partitioning problem. Unfortunately, the computational requirement associated with the algorithm is often enormous, thus rendering the method infeasible from a practical standpoint. In this paper, we present an alternative approach that successively solves a series of binary integer linear programs to obtain a globally optimal solution to the MSMCSP. Computational comparisons of the methods using published similarity data for 45 food items reveal that the proposed sequential method is computationally far more efficient than the branch-and-bound approach. © 2016 The British Psychological Society.
Euclidean, Spherical, and Hyperbolic Shadows
ERIC Educational Resources Information Center
Hoban, Ryan
2013-01-01
Many classical problems in elementary calculus use Euclidean geometry. This article takes such a problem and solves it in hyperbolic and in spherical geometry instead. The solution requires only the ability to compute distances and intersections of points in these geometries. The dramatically different results we obtain illustrate the effect…
ERIC Educational Resources Information Center
Shumway, Jessica F.; Kyriopoulos, Joan
2014-01-01
Being able to find the correct answer to a math problem does not always indicate solid mathematics mastery. A student who knows how to apply the basic algorithms can correctly solve problems without understanding the relationships between numbers or why the algorithms work. The Common Core standards require that students actually understand…
Genetics problem solving and worldview
NASA Astrophysics Data System (ADS)
Dale, Esther
The research goal was to determine whether worldview relates to traditional and real-world genetics problem solving. Traditionally, scientific literacy emphasized content knowledge alone because it was sufficient to solve traditional problems. The contemporary definition of scientific literacy is, "The knowledge and understanding of scientific concepts and processes required for personal decision-making, participation in civic and cultural affairs and economic productivity" (NRC, 1996). An expanded definition of scientific literacy is needed to solve socioscientific issues (SSI), complex social issues with conceptual, procedural, or technological associations with science. Teaching content knowledge alone assumes that students will find the scientific explanation of a phenomenon to be superior to a non-science explanation. Formal science and everyday ways of thinking about science are two different cultures (Palmer, 1999). Students address this rift with cognitive apartheid, the boxing away of science knowledge from other types of knowledge (Jedege & Aikenhead, 1999). By addressing worldview, cognitive apartheid may decrease and scientific literacy may increase. Introductory biology students at the University of Minnesota during fall semester 2005 completed a written questionnaire-including a genetics content-knowledge test, four genetic dilemmas, the Worldview Assessment Instrument (WAI) and some items about demographics and religiosity. Six students responded to the interview protocol. Based on statistical analysis and interview data, this study concluded the following: (1) Worldview, in the form of metaphysics, relates to solving traditional genetic dilemmas. (2) Worldview, in the form of agency, relates to solving traditional genetics problems. (3) Thus, worldview must be addressed in curriculum, instruction, and assessment.
Evolutionary Dynamic Multiobjective Optimization Via Kalman Filter Prediction.
Muruganantham, Arrchana; Tan, Kay Chen; Vadakkepat, Prahlad
2016-12-01
Evolutionary algorithms are effective in solving static multiobjective optimization problems resulting in the emergence of a number of state-of-the-art multiobjective evolutionary algorithms (MOEAs). Nevertheless, the interest in applying them to solve dynamic multiobjective optimization problems has only been tepid. Benchmark problems, appropriate performance metrics, as well as efficient algorithms are required to further the research in this field. One or more objectives may change with time in dynamic optimization problems. The optimization algorithm must be able to track the moving optima efficiently. A prediction model can learn the patterns from past experience and predict future changes. In this paper, a new dynamic MOEA using Kalman filter (KF) predictions in decision space is proposed to solve the aforementioned problems. The predictions help to guide the search toward the changed optima, thereby accelerating convergence. A scoring scheme is devised to hybridize the KF prediction with a random reinitialization method. Experimental results and performance comparisons with other state-of-the-art algorithms demonstrate that the proposed algorithm is capable of significantly improving the dynamic optimization performance.
1988-09-01
Institute of Technology Air University In Partial Fulfillment of the Requirements for the Degree of Master of Science in Systems Management Dexter R... management system software Diag/Prob Diagnosis and problem solving or problem finding GR Graphics software Int/Transp Interoperability and...language software Plan/D.S. Planning and decision support or decision making PM Program management software SC Systems for Command, Control, Communications
Students’ difficulties in probabilistic problem-solving
NASA Astrophysics Data System (ADS)
Arum, D. P.; Kusmayadi, T. A.; Pramudya, I.
2018-03-01
There are many errors can be identified when students solving mathematics problems, particularly in solving the probabilistic problem. This present study aims to investigate students’ difficulties in solving the probabilistic problem. It focuses on analyzing and describing students errors during solving the problem. This research used the qualitative method with case study strategy. The subjects in this research involve ten students of 9th grade that were selected by purposive sampling. Data in this research involve students’ probabilistic problem-solving result and recorded interview regarding students’ difficulties in solving the problem. Those data were analyzed descriptively using Miles and Huberman steps. The results show that students have difficulties in solving the probabilistic problem and can be divided into three categories. First difficulties relate to students’ difficulties in understanding the probabilistic problem. Second, students’ difficulties in choosing and using appropriate strategies for solving the problem. Third, students’ difficulties with the computational process in solving the problem. Based on the result seems that students still have difficulties in solving the probabilistic problem. It means that students have not able to use their knowledge and ability for responding probabilistic problem yet. Therefore, it is important for mathematics teachers to plan probabilistic learning which could optimize students probabilistic thinking ability.
Using Grey Wolf Algorithm to Solve the Capacitated Vehicle Routing Problem
NASA Astrophysics Data System (ADS)
Korayem, L.; Khorsid, M.; Kassem, S. S.
2015-05-01
The capacitated vehicle routing problem (CVRP) is a class of the vehicle routing problems (VRPs). In CVRP a set of identical vehicles having fixed capacities are required to fulfill customers' demands for a single commodity. The main objective is to minimize the total cost or distance traveled by the vehicles while satisfying a number of constraints, such as: the capacity constraint of each vehicle, logical flow constraints, etc. One of the methods employed in solving the CVRP is the cluster-first route-second method. It is a technique based on grouping of customers into a number of clusters, where each cluster is served by one vehicle. Once clusters are formed, a route determining the best sequence to visit customers is established within each cluster. The recently bio-inspired grey wolf optimizer (GWO), introduced in 2014, has proven to be efficient in solving unconstrained, as well as, constrained optimization problems. In the current research, our main contributions are: combining GWO with the traditional K-means clustering algorithm to generate the ‘K-GWO’ algorithm, deriving a capacitated version of the K-GWO algorithm by incorporating a capacity constraint into the aforementioned algorithm, and finally, developing 2 new clustering heuristics. The resulting algorithm is used in the clustering phase of the cluster-first route-second method to solve the CVR problem. The algorithm is tested on a number of benchmark problems with encouraging results.
NASA Astrophysics Data System (ADS)
Mujiasih; Waluya, S. B.; Kartono; Mariani
2018-03-01
Skills in working on the geometry problems great needs of the competence of Geometric Reasoning. As a teacher candidate, State Islamic University (UIN) students need to have the competence of this Geometric Reasoning. When the geometric reasoning in solving of geometry problems has grown well, it is expected the students are able to write their ideas to be communicative for the reader. The ability of a student's mathematical communication is supposed to be used as a marker of the growth of their Geometric Reasoning. Thus, the search for the growth of geometric reasoning in solving of analytic geometry problems will be characterized by the growth of mathematical communication abilities whose work is complete, correct and sequential, especially in writing. Preceded with qualitative research, this article was the result of a study that explores the problem: Was the search for the growth of geometric reasoning in solving analytic geometry problems could be characterized by the growth of mathematical communication abilities? The main activities in this research were done through a series of activities: (1) Lecturer trains the students to work on analytic geometry problems that were not routine and algorithmic process but many problems that the process requires high reasoning and divergent/open ended. (2) Students were asked to do the problems independently, in detail, complete, order, and correct. (3) Student answers were then corrected each its stage. (4) Then taken 6 students as the subject of this research. (5) Research subjects were interviewed and researchers conducted triangulation. The results of this research, (1) Mathematics Education student of UIN Semarang, had adequate the mathematical communication ability, (2) the ability of this mathematical communication, could be a marker of the geometric reasoning in solving of problems, and (3) the geometric reasoning of UIN students had grown in a category that tends to be good.
Simulating propagation of coherent light in random media using the Fredholm type integral equation
NASA Astrophysics Data System (ADS)
Kraszewski, Maciej; Pluciński, Jerzy
2017-06-01
Studying propagation of light in random scattering materials is important for both basic and applied research. Such studies often require usage of numerical method for simulating behavior of light beams in random media. However, if such simulations require consideration of coherence properties of light, they may become a complex numerical problems. There are well established methods for simulating multiple scattering of light (e.g. Radiative Transfer Theory and Monte Carlo methods) but they do not treat coherence properties of light directly. Some variations of these methods allows to predict behavior of coherent light but only for an averaged realization of the scattering medium. This limits their application in studying many physical phenomena connected to a specific distribution of scattering particles (e.g. laser speckle). In general, numerical simulation of coherent light propagation in a specific realization of random medium is a time- and memory-consuming problem. The goal of the presented research was to develop new efficient method for solving this problem. The method, presented in our earlier works, is based on solving the Fredholm type integral equation, which describes multiple light scattering process. This equation can be discretized and solved numerically using various algorithms e.g. by direct solving the corresponding linear equations system, as well as by using iterative or Monte Carlo solvers. Here we present recent development of this method including its comparison with well-known analytical results and a finite-difference type simulations. We also present extension of the method for problems of multiple scattering of a polarized light on large spherical particles that joins presented mathematical formalism with Mie theory.
ERIC Educational Resources Information Center
Shacham, Mordechai; Cutlip, Michael B.; Brauner, Neima
2009-01-01
A continuing challenge to the undergraduate chemical engineering curriculum is the time-effective incorporation and use of computer-based tools throughout the educational program. Computing skills in academia and industry require some proficiency in programming and effective use of software packages for solving 1) single-model, single-algorithm…
SOLVE II: A Technique to Improve Efficiency and Solve Problems in Hardwood Sawmills
Edward L. Adams; Daniel E. Dunmire
1977-01-01
The squeeze between rising costs and product values is getting tighter for sawmill managers. So, they are taking a closer took at the efficiency of their sawmills by making a complete analysis of their milling situation. Such an analysis requires considerable time and expense. To aid the manager with this task, the USDA Forest Service's Northeastern Forest...
Onboard shuttle on-line software requirements system: Prototype
NASA Technical Reports Server (NTRS)
Kolkhorst, Barbara; Ogletree, Barry
1989-01-01
The prototype discussed here was developed as proof of a concept for a system which could support high volumes of requirements documents with integrated text and graphics; the solution proposed here could be extended to other projects whose goal is to place paper documents in an electronic system for viewing and printing purposes. The technical problems (such as conversion of documentation between word processors, management of a variety of graphics file formats, and difficulties involved in scanning integrated text and graphics) would be very similar for other systems of this type. Indeed, technological advances in areas such as scanning hardware and software and display terminals insure that some of the problems encountered here will be solved in the near-term (less than five years). Examples of these solvable problems include automated input of integrated text and graphics, errors in the recognition process, and the loss of image information which results from the digitization process. The solution developed for the Online Software Requirements System is modular and allows hardware and software components to be upgraded or replaced as industry solutions mature. The extensive commercial software content allows the NASA customer to apply resources to solving the problem and maintaining documents.
Blanchard-Fields, Fredda; Mienaltowski, Andrew; Seay, Renee Baldi
2007-01-01
Using the Everyday Problem Solving Inventory of Cornelius and Caspi, we examined differences in problem-solving strategy endorsement and effectiveness in two domains of everyday functioning (instrumental or interpersonal, and a mixture of the two domains) and for four strategies (avoidance-denial, passive dependence, planful problem solving, and cognitive analysis). Consistent with past research, our research showed that older adults were more problem focused than young adults in their approach to solving instrumental problems, whereas older adults selected more avoidant-denial strategies than young adults when solving interpersonal problems. Overall, older adults were also more effective than young adults when solving everyday problems, in particular for interpersonal problems.
Dixon-Gordon, Katherine L; Chapman, Alexander L; Lovasz, Nathalie; Walters, Kris
2011-10-01
Borderline personality disorder (BPD) is associated with poor social problem solving and problems with emotion regulation. In this study, the social problem-solving performance of undergraduates with high (n = 26), mid (n = 32), or low (n = 29) levels of BPD features was assessed with the Social Problem-Solving Inventory-Revised and using the means-ends problem-solving procedure before and after a social rejection stressor. The high-BP group, but not the low-BP group, showed a significant reduction in relevant solutions to social problems and more inappropriate solutions following the negative emotion induction. Increases in self-reported negative emotions during the emotion induction mediated the relationship between BP features and reductions in social problem-solving performance. In addition, the high-BP group demonstrated trait deficits in social problem solving on the Social Problem-Solving Inventory-Revised. These findings suggest that future research must examine social problem solving under differing emotional conditions, and that clinical interventions to improve social problem solving among persons with BP features should focus on responses to emotional contexts.
NASA Astrophysics Data System (ADS)
La Cour, Brian R.; Ostrove, Corey I.
2017-01-01
This paper describes a novel approach to solving unstructured search problems using a classical, signal-based emulation of a quantum computer. The classical nature of the representation allows one to perform subspace projections in addition to the usual unitary gate operations. Although bandwidth requirements will limit the scale of problems that can be solved by this method, it can nevertheless provide a significant computational advantage for problems of limited size. In particular, we find that, for the same number of noisy oracle calls, the proposed subspace projection method provides a higher probability of success for finding a solution than does an single application of Grover's algorithm on the same device.
An Investigation of Secondary Teachers’ Understanding and Belief on Mathematical Problem Solving
NASA Astrophysics Data System (ADS)
Yuli Eko Siswono, Tatag; Wachidul Kohar, Ahmad; Kurniasari, Ika; Puji Astuti, Yuliani
2016-02-01
Weaknesses on problem solving of Indonesian students as reported by recent international surveys give rise to questions on how Indonesian teachers bring out idea of problem solving in mathematics lesson. An explorative study was undertaken to investigate how secondary teachers who teach mathematics at junior high school level understand and show belief toward mathematical problem solving. Participants were teachers from four cities in East Java province comprising 45 state teachers and 25 private teachers. Data was obtained through questionnaires and written test. The results of this study point out that the teachers understand pedagogical problem solving knowledge well as indicated by high score of observed teachers‘ responses showing understanding on problem solving as instruction as well as implementation of problem solving in teaching practice. However, they less understand on problem solving content knowledge such as problem solving strategies and meaning of problem itself. Regarding teacher's difficulties, teachers admitted to most frequently fail in (1) determining a precise mathematical model or strategies when carrying out problem solving steps which is supported by data of test result that revealed transformation error as the most frequently observed errors in teachers’ work and (2) choosing suitable real situation when designing context-based problem solving task. Meanwhile, analysis of teacher's beliefs on problem solving shows that teachers tend to view both mathematics and how students should learn mathematics as body static perspective, while they tend to believe to apply idea of problem solving as dynamic approach when teaching mathematics.
ERIC Educational Resources Information Center
Hayel Al-Srour, Nadia; Al-Ali, Safa M.; Al-Oweidi, Alia
2016-01-01
The present study aims to detect the impact of teacher training on creative writing and problem-solving using both Futuristic scenarios program to solve problems creatively, and creative problem solving. To achieve the objectives of the study, the sample was divided into two groups, the first consist of 20 teachers, and 23 teachers to second…
Teaching Real-World Applications of Business Statistics Using Communication to Scaffold Learning
ERIC Educational Resources Information Center
Green, Gareth P.; Jones, Stacey; Bean, John C.
2015-01-01
Our assessment research suggests that quantitative business courses that rely primarily on algorithmic problem solving may not produce the deep learning required for addressing real-world business problems. This article illustrates a strategy, supported by recent learning theory, for promoting deep learning by moving students gradually from…
Strategies of Successful Synthesis Solutions: Mapping, Mechanisms, and More
ERIC Educational Resources Information Center
Bodé, Nicholas E.; Flynn, Alison B.
2016-01-01
Organic synthesis problems require the solver to integrate knowledge and skills from many parts of their courses. Without a well-defined, systematic method for approaching them, even the strongest students can experience difficulties. Our research goal was to identify the most successful problem-solving strategies and develop associated teaching…
Positive Youth Development and Nutrition: Interdisciplinary Strategies to Enhance Student Outcomes
ERIC Educational Resources Information Center
Edwards, Oliver W.; Cheeley, Taylor
2016-01-01
Educational policies require the use of data and progress monitoring frameworks to guide instruction and intervention in schools. As a result, different problem-solving models such as multitiered systems of supports (MTSS) have emerged that use these frameworks to improve student outcomes. However, problem-focused models emphasize negative…
Teaching Molecular Phylogenetics through Investigating a Real-World Phylogenetic Problem
ERIC Educational Resources Information Center
Zhang, Xiaorong
2012-01-01
A phylogenetics exercise is incorporated into the "Introduction to biocomputing" course, a junior-level course at Savannah State University. This exercise is designed to help students learn important concepts and practical skills in molecular phylogenetics through solving a real-world problem. In this application, students are required to identify…
Dynamic Cognitive Tracing: Towards Unified Discovery of Student and Cognitive Models
ERIC Educational Resources Information Center
Gonzalez-Brenes, Jose P.; Mostow, Jack
2012-01-01
This work describes a unified approach to two problems previously addressed separately in Intelligent Tutoring Systems: (i) Cognitive Modeling, which factorizes problem solving steps into the latent set of skills required to perform them; and (ii) Student Modeling, which infers students' learning by observing student performance. The practical…
Path Planning For A Class Of Cutting Operations
NASA Astrophysics Data System (ADS)
Tavora, Jose
1989-03-01
Optimizing processing time in some contour-cutting operations requires solving the so-called no-load path problem. This problem is formulated and an approximate resolution method (based on heuristic search techniques) is described. Results for real-life instances (clothing layouts in the apparel industry) are presented and evaluated.
NASA Astrophysics Data System (ADS)
Palacio-Cayetano, Joycelin
"Problem-solving through reflective thinking should be both the method and valuable outcome of science instruction in America's schools" proclaimed John Dewey (Gabel, 1995). If the development of problem-solving is a primary goal of science education, more problem-solving opportunities must be an integral part of K-16 education. To examine the effective use of technology in developing and assessing problem-solving skills, a problem-solving authoring, learning, and assessment software, the UCLA IMMEX Program-Interactive Multimedia Exercises-was investigated. This study was a twenty-week quasi-experimental study that was implemented as a control-group time series design among 120 tenth grade students. Both the experimental group (n = 60) and the control group (n = 60) participated in a problem-based learning curriculum; however, the experimental group received regular intensive experiences with IMMEX problem-solving and the control group did not. Problem-solving pretest and posttest were administered to all students. The instruments used were a 35-item Processes of Biological Inquiry Test and an IMMEX problem-solving assessment test, True Roots. Students who participated in the IMMEX Program achieved significant (p <.05) gains in problem-solving skills on both problem-solving assessment instruments. This study provided evidence that IMMEX software is highly efficient in evaluating salient elements of problem-solving. Outputs of students' problem-solving strategies revealed that unsuccessful problem solvers primarily used the following four strategies: (1) no data search strategy, students simply guessed; (2) limited data search strategy leading to insufficient data and premature closing; (3) irrelevant data search strategy, students focus in areas bearing no substantive data; and (4) extensive data search strategy with inadequate integration and analysis. On the contrary, successful problem solvers used the following strategies; (1) focused search strategy coupled with the ability to fill in knowledge gaps by accessing the appropriate resources; (2) targeted search strategy coupled with high level of analytical and integration skills; and (3) focused search strategy coupled with superior discrimination, analytical, and integration skills. The strategies of students who were successful and unsuccessful solving IMMEX problems were consistent with those of expert and novice problem solvers identified in the literature on problem-solving.
From Walls to Windows: Using Barriers as Pathways to Insightful Solutions
ERIC Educational Resources Information Center
Walinga, Jennifer
2010-01-01
The purpose of this study was to explore and develop a conceptual model for how individuals unlock insight. The concept of insight--the "out of the box" or "aha!" solution to a problem--offers a framework for exploring and understanding how best to enhance problem solving skills due to the cognitive shift insight requires. Creative problem solving…
ERIC Educational Resources Information Center
Korpershoek, Hanke; Kuyper, Hans; van der Werf, Greetje
2015-01-01
Word problems are math- or science-related problems presented in the context of a story or real-life scenario. Literature suggests that, to solve these problems, advanced reading skills are required, in addition to content-related skills in, for example, mathematics. In the present study, we investigated the relation between students' reading…
ERIC Educational Resources Information Center
Burns, Nicholas R.; Lee, Michael D.; Vickers, Douglas
2006-01-01
Studies of human problem solving have traditionally used deterministic tasks that require the execution of a systematic series of steps to reach a rational and optimal solution. Most real-world problems, however, are characterized by uncertainty, the need to consider an enormous number of variables and possible courses of action at each stage in…
Solving multiconstraint assignment problems using learning automata.
Horn, Geir; Oommen, B John
2010-02-01
This paper considers the NP-hard problem of object assignment with respect to multiple constraints: assigning a set of elements (or objects) into mutually exclusive classes (or groups), where the elements which are "similar" to each other are hopefully located in the same class. The literature reports solutions in which the similarity constraint consists of a single index that is inappropriate for the type of multiconstraint problems considered here and where the constraints could simultaneously be contradictory. This feature, where we permit possibly contradictory constraints, distinguishes this paper from the state of the art. Indeed, we are aware of no learning automata (or other heuristic) solutions which solve this problem in its most general setting. Such a scenario is illustrated with the static mapping problem, which consists of distributing the processes of a parallel application onto a set of computing nodes. This is a classical and yet very important problem within the areas of parallel computing, grid computing, and cloud computing. We have developed four learning-automata (LA)-based algorithms to solve this problem: First, a fixed-structure stochastic automata algorithm is presented, where the processes try to form pairs to go onto the same node. This algorithm solves the problem, although it requires some centralized coordination. As it is desirable to avoid centralized control, we subsequently present three different variable-structure stochastic automata (VSSA) algorithms, which have superior partitioning properties in certain settings, although they forfeit some of the scalability features of the fixed-structure algorithm. All three VSSA algorithms model the processes as automata having first the hosting nodes as possible actions; second, the processes as possible actions; and, third, attempting to estimate the process communication digraph prior to probabilistically mapping the processes. This paper, which, we believe, comprehensively reports the pioneering LA solutions to this problem, unequivocally demonstrates that LA can play an important role in solving complex combinatorial and integer optimization problems.
Cuckoo search via Levy flights applied to uncapacitated facility location problem
NASA Astrophysics Data System (ADS)
Mesa, Armacheska; Castromayor, Kris; Garillos-Manliguez, Cinmayii; Calag, Vicente
2017-11-01
Facility location problem (FLP) is a mathematical way to optimally locate facilities within a set of candidates to satisfy the requirements of a given set of clients. This study addressed the uncapacitated FLP as it assures that the capacity of every selected facility is finite. Thus, even if the demand is not known, which often is the case, in reality, organizations may still be able to take strategic decisions such as locating the facilities. There are different approaches relevant to the uncapacitated FLP. Here, the cuckoo search via Lévy flight (CS-LF) was used to solve the problem. Though hybrid methods produce better results, this study employed CS-LF to determine first its potential in finding solutions for the problem, particularly when applied to a real-world problem. The method was applied to the data set obtained from a department store in Davao City, Philippines. Results showed that applying CS-LF yielded better facility locations compared to particle swarm optimization and other existing algorithms. Although these results showed that CS-LF is a promising method to solve this particular problem, further studies on other FLP are recommended to establish a strong foundation of the capability of CS-LF in solving FLP.
ERIC Educational Resources Information Center
Aljaberi, Nahil M.; Gheith, Eman
2016-01-01
This study aims to investigate the ability of pre-service class teacher at University of Petrain solving mathematical problems using Polya's Techniques, their level of problem solving skills in daily-life issues. The study also investigates the correlation between their ability to solve mathematical problems and their level of problem solving…
Solving lot-sizing problem with quantity discount and transportation cost
NASA Astrophysics Data System (ADS)
Lee, Amy H. I.; Kang, He-Yau; Lai, Chun-Mei
2013-04-01
Owing to today's increasingly competitive market and ever-changing manufacturing environment, the inventory problem is becoming more complicated to solve. The incorporation of heuristics methods has become a new trend to tackle the complex problem in the past decade. This article considers a lot-sizing problem, and the objective is to minimise total costs, where the costs include ordering, holding, purchase and transportation costs, under the requirement that no inventory shortage is allowed in the system. We first formulate the lot-sizing problem as a mixed integer programming (MIP) model. Next, an efficient genetic algorithm (GA) model is constructed for solving large-scale lot-sizing problems. An illustrative example with two cases in a touch panel manufacturer is used to illustrate the practicality of these models, and a sensitivity analysis is applied to understand the impact of the changes in parameters to the outcomes. The results demonstrate that both the MIP model and the GA model are effective and relatively accurate tools for determining the replenishment for touch panel manufacturing for multi-periods with quantity discount and batch transportation. The contributions of this article are to construct an MIP model to obtain an optimal solution when the problem is not too complicated itself and to present a GA model to find a near-optimal solution efficiently when the problem is complicated.
The Association between Motivation, Affect, and Self-regulated Learning When Solving Problems.
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.
Social factors predictive of social integration for adults with brain injury.
Batchos, Elisabeth; Easton, Amanda; Haak, Christopher; Ditchman, Nicole
2018-08-01
Individuals with acquired brain injury (ABI) may not only struggle with physical and cognitive impairments, but may also face challenges reintegrating into the community socially. Research has demonstrated that following ABI, individuals' social networks tend to dwindle, support may decline, and isolation increases. This study examined factors impacting social integration in a community-based sample of 102 individuals with ABI. Potential predictors included emotional support, instrumental support, problem solving confidence, and approach-avoidance style (AAS) of problem solving, while controlling for age, gender, education, and time since injury. Hierarchical regression was used to analyze whether these factors were predictive of social integration. The final model accounted for 33% of the variance in social integration outcomes. Results demonstrated that emotional support was initially a significant predictor; however, when controlling for emotional support the variance in social integration was better accounted for by social problem solving - specifically, AAS. A follow-up mediation analysis indicated that the relationship between social problem solving (specifically, AAS) and social integration was partially mediated by emotional support. This suggests that for individuals with ABI, a tendency to approach rather than avoid social problem solving issues is a significant predictor for social integration both directly and indirectly through its association with emotional social support. Implications for Rehabilitation Both instrumental and emotional social support should be assessed in patients with acquired brain injury (ABI), ensuring that emotional needs are met in addition to the more obvious instrumental needs. Barriers to problem solving for people with ABI may limit optimal social integration; thus, assessment and intervention aimed at increasing AAS are recommended. To enhance the social integration outcomes of people with brain injury, strength-based psychosocial rehabilitation should optimally balance an individual's abilities with areas requiring compensation, focusing on how to approach rather than avoid problems as well as strategies to cultivate emotional social support.
Higher-Order Compact Schemes for Numerical Simulation of Incompressible Flows
NASA Technical Reports Server (NTRS)
Wilson, Robert V.; Demuren, Ayodeji O.; Carpenter, Mark
1998-01-01
A higher order accurate numerical procedure has been developed for solving incompressible Navier-Stokes equations for 2D or 3D fluid flow problems. It is based on low-storage Runge-Kutta schemes for temporal discretization and fourth and sixth order compact finite-difference schemes for spatial discretization. The particular difficulty of satisfying the divergence-free velocity field required in incompressible fluid flow is resolved by solving a Poisson equation for pressure. It is demonstrated that for consistent global accuracy, it is necessary to employ the same order of accuracy in the discretization of the Poisson equation. Special care is also required to achieve the formal temporal accuracy of the Runge-Kutta schemes. The accuracy of the present procedure is demonstrated by application to several pertinent benchmark problems.
NASA Astrophysics Data System (ADS)
Demenev, A. G.
2018-02-01
The present work is devoted to analyze high-performance computing (HPC) infrastructure capabilities for aircraft engine aeroacoustics problems solving at Perm State University. We explore here the ability to develop new computational aeroacoustics methods/solvers for computer-aided engineering (CAE) systems to handle complicated industrial problems of engine noise prediction. Leading aircraft engine engineering company, including “UEC-Aviadvigatel” JSC (our industrial partners in Perm, Russia), require that methods/solvers to optimize geometry of aircraft engine for fan noise reduction. We analysed Perm State University HPC-hardware resources and software services to use efficiently. The performed results demonstrate that Perm State University HPC-infrastructure are mature enough to face out industrial-like problems of development CAE-system with HPC-method and CFD-solvers.
Duarte, Belmiro P.M.; Wong, Weng Kee; Atkinson, Anthony C.
2016-01-01
T-optimum designs for model discrimination are notoriously difficult to find because of the computational difficulty involved in solving an optimization problem that involves two layers of optimization. Only a handful of analytical T-optimal designs are available for the simplest problems; the rest in the literature are found using specialized numerical procedures for a specific problem. We propose a potentially more systematic and general way for finding T-optimal designs using a Semi-Infinite Programming (SIP) approach. The strategy requires that we first reformulate the original minimax or maximin optimization problem into an equivalent semi-infinite program and solve it using an exchange-based method where lower and upper bounds produced by solving the outer and the inner programs, are iterated to convergence. A global Nonlinear Programming (NLP) solver is used to handle the subproblems, thus finding the optimal design and the least favorable parametric configuration that minimizes the residual sum of squares from the alternative or test models. We also use a nonlinear program to check the global optimality of the SIP-generated design and automate the construction of globally optimal designs. The algorithm is successfully used to produce results that coincide with several T-optimal designs reported in the literature for various types of model discrimination problems with normally distributed errors. However, our method is more general, merely requiring that the parameters of the model be estimated by a numerical optimization. PMID:27330230
Duarte, Belmiro P M; Wong, Weng Kee; Atkinson, Anthony C
2015-03-01
T-optimum designs for model discrimination are notoriously difficult to find because of the computational difficulty involved in solving an optimization problem that involves two layers of optimization. Only a handful of analytical T-optimal designs are available for the simplest problems; the rest in the literature are found using specialized numerical procedures for a specific problem. We propose a potentially more systematic and general way for finding T-optimal designs using a Semi-Infinite Programming (SIP) approach. The strategy requires that we first reformulate the original minimax or maximin optimization problem into an equivalent semi-infinite program and solve it using an exchange-based method where lower and upper bounds produced by solving the outer and the inner programs, are iterated to convergence. A global Nonlinear Programming (NLP) solver is used to handle the subproblems, thus finding the optimal design and the least favorable parametric configuration that minimizes the residual sum of squares from the alternative or test models. We also use a nonlinear program to check the global optimality of the SIP-generated design and automate the construction of globally optimal designs. The algorithm is successfully used to produce results that coincide with several T-optimal designs reported in the literature for various types of model discrimination problems with normally distributed errors. However, our method is more general, merely requiring that the parameters of the model be estimated by a numerical optimization.
Extraction of a group-pair relation: problem-solving relation from web-board documents.
Pechsiri, Chaveevan; Piriyakul, Rapepun
2016-01-01
This paper aims to extract a group-pair relation as a Problem-Solving relation, for example a DiseaseSymptom-Treatment relation and a CarProblem-Repair relation, between two event-explanation groups, a problem-concept group as a symptom/CarProblem-concept group and a solving-concept group as a treatment-concept/repair concept group from hospital-web-board and car-repair-guru-web-board documents. The Problem-Solving relation (particularly Symptom-Treatment relation) including the graphical representation benefits non-professional persons by supporting knowledge of primarily solving problems. The research contains three problems: how to identify an EDU (an Elementary Discourse Unit, which is a simple sentence) with the event concept of either a problem or a solution; how to determine a problem-concept EDU boundary and a solving-concept EDU boundary as two event-explanation groups, and how to determine the Problem-Solving relation between these two event-explanation groups. Therefore, we apply word co-occurrence to identify a problem-concept EDU and a solving-concept EDU, and machine-learning techniques to solve a problem-concept EDU boundary and a solving-concept EDU boundary. We propose using k-mean and Naïve Bayes to determine the Problem-Solving relation between the two event-explanation groups involved with clustering features. In contrast to previous works, the proposed approach enables group-pair relation extraction with high accuracy.
On the parallel solution of parabolic equations
NASA Technical Reports Server (NTRS)
Gallopoulos, E.; Saad, Youcef
1989-01-01
Parallel algorithms for the solution of linear parabolic problems are proposed. The first of these methods is based on using polynomial approximation to the exponential. It does not require solving any linear systems and is highly parallelizable. The two other methods proposed are based on Pade and Chebyshev approximations to the matrix exponential. The parallelization of these methods is achieved by using partial fraction decomposition techniques to solve the resulting systems and thus offers the potential for increased time parallelism in time dependent problems. Experimental results from the Alliant FX/8 and the Cray Y-MP/832 vector multiprocessors are also presented.
Solving the Dark Matter Problem
Baltz, Ted
2018-05-11
Cosmological observations have firmly established that the majority of matter in the universe is of an unknown type, called 'dark matter'. A compelling hypothesis is that the dark matter consists of weakly interacting massive particles (WIMPs) in the mass range around 100 GeV. If the WIMP hypothesis is correct, such particles could be created and studied at accelerators. Furthermore they could be directly detected as the primary component of our galaxy. Solving the dark matter problem requires that the connection be made between the two. We describe some theoretical and experimental avenues that might lead to this connection.
Swarm Intelligence Optimization and Its Applications
NASA Astrophysics Data System (ADS)
Ding, Caichang; Lu, Lu; Liu, Yuanchao; Peng, Wenxiu
Swarm Intelligence is a computational and behavioral metaphor for solving distributed problems inspired from biological examples provided by social insects such as ants, termites, bees, and wasps and by swarm, herd, flock, and shoal phenomena in vertebrates such as fish shoals and bird flocks. An example of successful research direction in Swarm Intelligence is ant colony optimization (ACO), which focuses on combinatorial optimization problems. Ant algorithms can be viewed as multi-agent systems (ant colony), where agents (individual ants) solve required tasks through cooperation in the same way that ants create complex social behavior from the combined efforts of individuals.
A steam inerting system for hydrogen disposal for the Vandenberg Shuttle
NASA Technical Reports Server (NTRS)
Belknap, Stuart B.
1988-01-01
A two-year feasibility and test program to solve the problem of unburned confined hydrogen at the Vandenberg Space Launch Complex Six (SLC-6) during Space Shuttle Main Engine (SSME) firings is discussed. A novel steam inerting design was selected for development. Available sound suppression water is superheated to flash to steam at the duct entrance. Testing, analysis, and design during 1987 showed that the steam inerting system (SIS) solves the problem and meets other flight-critical system requirements. The SIS design is complete and available for installation at SLC-6 to support shuttle or derivative vehicles.
Ratio Analysis: Where Investments Meet Mathematics.
ERIC Educational Resources Information Center
Barton, Susan D.; Woodbury, Denise
2002-01-01
Discusses ratio analysis by which investments may be evaluated. Requires the use of fundamental mathematics, problem solving, and a comparison of the mathematical results within the framework of industry. (Author/NB)
Azad, Gazi F.; Kim, Mina; Marcus, Steven C.; Mandell, David S.; Sheridan, Susan M.
2016-01-01
Effective parent-teacher communication involves problem-solving concerns about students. Few studies have examined problem solving interactions between parents and teachers of children with autism spectrum disorder (ASD), with a particular focus on identifying communication barriers and strategies for improving them. This study examined the problem-solving behaviors of parents and teachers of children with ASD. Participants included 18 teachers and 39 parents of children with ASD. Parent-teacher dyads were prompted to discuss and provide a solution for a problem that a student experienced at home and at school. Parents and teachers also reported on their problem-solving behaviors. Results showed that parents and teachers displayed limited use of the core elements of problem-solving. Teachers displayed more problem-solving behaviors than parents. Both groups reported engaging in more problem-solving behaviors than they were observed to display during their discussions. Our findings suggest that teacher and parent training programs should include collaborative approaches to problem-solving. PMID:28392604
Azad, Gazi F; Kim, Mina; Marcus, Steven C; Mandell, David S; Sheridan, Susan M
2016-12-01
Effective parent-teacher communication involves problem-solving concerns about students. Few studies have examined problem solving interactions between parents and teachers of children with autism spectrum disorder (ASD), with a particular focus on identifying communication barriers and strategies for improving them. This study examined the problem-solving behaviors of parents and teachers of children with ASD. Participants included 18 teachers and 39 parents of children with ASD. Parent-teacher dyads were prompted to discuss and provide a solution for a problem that a student experienced at home and at school. Parents and teachers also reported on their problem-solving behaviors. Results showed that parents and teachers displayed limited use of the core elements of problem-solving. Teachers displayed more problem-solving behaviors than parents. Both groups reported engaging in more problem-solving behaviors than they were observed to display during their discussions. Our findings suggest that teacher and parent training programs should include collaborative approaches to problem-solving.
NASA Astrophysics Data System (ADS)
Rr Chusnul, C.; Mardiyana, S., Dewi Retno
2017-12-01
Problem solving is the basis of mathematics learning. Problem solving teaches us to clarify an issue coherently in order to avoid misunderstanding information. Sometimes there may be mistakes in problem solving due to misunderstanding the issue, choosing a wrong concept or misapplied concept. The problem-solving test was carried out after students were given treatment on learning by using cooperative learning of TTW type. The purpose of this study was to elucidate student problem regarding to problem solving errors after learning by using cooperative learning of TTW type. Newman stages were used to identify problem solving errors in this study. The new research used a descriptive method to find out problem solving errors in students. The subject in this study were students of Vocational Senior High School (SMK) in 10th grade. Test and interview was conducted for data collection. Thus, the results of this study suggested problem solving errors in students after learning by using cooperative learning of TTW type for Newman stages.
Rejection Sensitivity and Depression: Indirect Effects Through Problem Solving.
Kraines, Morganne A; Wells, Tony T
2017-01-01
Rejection sensitivity (RS) and deficits in social problem solving are risk factors for depression. Despite their relationship to depression and the potential connection between them, no studies have examined RS and social problem solving together in the context of depression. As such, we examined RS, five facets of social problem solving, and symptoms of depression in a young adult sample. A total of 180 participants completed measures of RS, social problem solving, and depressive symptoms. We used bootstrapping to examine the indirect effect of RS on depressive symptoms through problem solving. RS was positively associated with depressive symptoms. A negative problem orientation, impulsive/careless style, and avoidance style of social problem solving were positively associated with depressive symptoms, and a positive problem orientation was negatively associated with depressive symptoms. RS demonstrated an indirect effect on depressive symptoms through two social problem-solving facets: the tendency to view problems as threats to one's well-being and an avoidance problem-solving style characterized by procrastination, passivity, or overdependence on others. These results are consistent with prior research that found a positive association between RS and depression symptoms, but this is the first study to implicate specific problem-solving deficits in the relationship between RS and depression. Our results suggest that depressive symptoms in high RS individuals may result from viewing problems as threats and taking an avoidant, rather than proactive, approach to dealing with problems. These findings may have implications for problem-solving interventions for rejection sensitive individuals.
The Cyclic Nature of Problem Solving: An Emergent Multidimensional Problem-Solving Framework
ERIC Educational Resources Information Center
Carlson, Marilyn P.; Bloom, Irene
2005-01-01
This paper describes the problem-solving behaviors of 12 mathematicians as they completed four mathematical tasks. The emergent problem-solving framework draws on the large body of research, as grounded by and modified in response to our close observations of these mathematicians. The resulting "Multidimensional Problem-Solving Framework" has four…
Mathematical Problem Solving: A Review of the Literature.
ERIC Educational Resources Information Center
Funkhouser, Charles
The major perspectives on problem solving of the twentieth century are reviewed--associationism, Gestalt psychology, and cognitive science. The results of the review on teaching problem solving and the uses of computers to teach problem solving are included. Four major issues related to the teaching of problem solving are discussed: (1)…
Teaching Problem Solving Skills to Elementary Age Students with Autism
ERIC Educational Resources Information Center
Cote, Debra L.; Jones, Vita L.; Barnett, Crystal; Pavelek, Karin; Nguyen, Hoang; Sparks, Shannon L.
2014-01-01
Students with disabilities need problem-solving skills to promote their success in solving the problems of daily life. The research into problem-solving instruction has been limited for students with autism. Using a problem-solving intervention and the Self Determined Learning Model of Instruction, three elementary age students with autism were…
Technology for return of planetary samples
NASA Technical Reports Server (NTRS)
1975-01-01
Technological requirements of a planetary return sample mission were studied. The state-of-the-art for problems unique to this class of missions was assessed and technological gaps were identified. The problem areas where significant advancement of the state-of-the-art is required are: life support for the exobiota during the return trip and within the Planetary Receiving Laboratory (PRL); biohazard assessment and control technology; and quarantine qualified handling and experimentation methods and equipment for studying the returned sample in the PRL. Concepts for solving these problems are discussed.
NASA Astrophysics Data System (ADS)
Sanan, P.; Schnepp, S. M.; May, D.; Schenk, O.
2014-12-01
Geophysical applications require efficient forward models for non-linear Stokes flow on high resolution spatio-temporal domains. The bottleneck in applying the forward model is solving the linearized, discretized Stokes problem which takes the form of a large, indefinite (saddle point) linear system. Due to the heterogeniety of the effective viscosity in the elliptic operator, devising effective preconditioners for saddle point problems has proven challenging and highly problem-dependent. Nevertheless, at least three approaches show promise for preconditioning these difficult systems in an algorithmically scalable way using multigrid and/or domain decomposition techniques. The first is to work with a hierarchy of coarser or smaller saddle point problems. The second is to use the Schur complement method to decouple and sequentially solve for the pressure and velocity. The third is to use the Schur decomposition to devise preconditioners for the full operator. These involve sub-solves resembling inexact versions of the sequential solve. The choice of approach and sub-methods depends crucially on the motivating physics, the discretization, and available computational resources. Here we examine the performance trade-offs for preconditioning strategies applied to idealized models of mantle convection and lithospheric dynamics, characterized by large viscosity gradients. Due to the arbitrary topological structure of the viscosity field in geodynamical simulations, we utilize low order, inf-sup stable mixed finite element spatial discretizations which are suitable when sharp viscosity variations occur in element interiors. Particular attention is paid to possibilities within the decoupled and approximate Schur complement factorization-based monolithic approaches to leverage recently-developed flexible, communication-avoiding, and communication-hiding Krylov subspace methods in combination with `heavy' smoothers, which require solutions of large per-node sub-problems, well-suited to solution on hybrid computational clusters. To manage the combinatorial explosion of solver options (which include hybridizations of all the approaches mentioned above), we leverage the modularity of the PETSc library.
Learning problem-solving skills in a distance education physics course
NASA Astrophysics Data System (ADS)
Rampho, G. J.; Ramorola, M. Z.
2017-10-01
In this paper we present the results of a study on the effectiveness of combinations of delivery modes of distance education in learning problem-solving skills in a distance education introductory physics course. A problem-solving instruction with the explicit teaching of a problem-solving strategy and worked-out examples were implemented in the course. The study used the ex post facto research design with stratified sampling to investigate the effect of the learning of a problem-solving strategy on the problem-solving performance. The number of problems attempted and the mean frequency of using a strategy in solving problems in the three course presentation modes were compared. The finding of the study indicated that combining the different course presentation modes had no statistically significant effect in the learning of problem-solving skills in the distance education course.
Hoover, Jerome D; Healy, Alice F
2017-12-01
The classic bat-and-ball problem is used widely to measure biased and correct reasoning in decision-making. University students overwhelmingly tend to provide the biased answer to this problem. To what extent might reasoners be led to modify their judgement, and, more specifically, is it possible to facilitate problem solution by prompting participants to consider the problem from an algebraic perspective? One hundred ninety-seven participants were recruited to investigate the effect of algebraic cueing as a debiasing strategy on variants of the bat-and-ball problem. Participants who were cued to consider the problem algebraically were significantly more likely to answer correctly relative to control participants. Most of this cueing effect was confined to a condition that required participants to solve isomorphic algebra equations corresponding to the structure of bat-and-ball question types. On a subsequent critical question with differing item and dollar amounts presented without a cue, participants were able to generalize the learned information to significantly reduce overall bias. Math anxiety was also found to be significantly related to bat-and-ball problem accuracy. These results suggest that, under specific conditions, algebraic reasoning is an effective debiasing strategy on bat-and-ball problem variants, and provide the first documented evidence for the influence of math anxiety on Cognitive Reflection Test performance.
Application of symbolic/numeric matrix solution techniques to the NASTRAN program
NASA Technical Reports Server (NTRS)
Buturla, E. M.; Burroughs, S. H.
1977-01-01
The matrix solving algorithm of any finite element algorithm is extremely important since solution of the matrix equations requires a large amount of elapse time due to null calculations and excessive input/output operations. An alternate method of solving the matrix equations is presented. A symbolic processing step followed by numeric solution yields the solution very rapidly and is especially useful for nonlinear problems.
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.
The Association between Motivation, Affect, and Self-regulated Learning When Solving Problems
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
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...
An experience sampling study of learning, affect, and the demands control support model.
Daniels, Kevin; Boocock, Grahame; Glover, Jane; Holland, Julie; Hartley, Ruth
2009-07-01
The demands control support model (R. A. Karasek & T. Theorell, 1990) indicates that job control and social support enable workers to engage in problem solving. In turn, problem solving is thought to influence learning and well-being (e.g., anxious affect, activated pleasant affect). Two samples (N = 78, N = 106) provided data up to 4 times per day for up to 5 working days. The extent to which job control was used for problem solving was assessed by measuring the extent to which participants changed aspects of their work activities to solve problems. The extent to which social support was used to solve problems was assessed by measuring the extent to which participants discussed problems to solve problems. Learning mediated the relationship between changing aspects of work activities to solve problems and activated pleasant affect. Learning also mediated the relationship between discussing problems to solve problems and activated pleasant affect. The findings indicated that how individuals use control and support to respond to problem-solving demands is associated with organizational and individual phenomena, such as learning and affective well-being.
ERIC Educational Resources Information Center
Kamis, Arnold; Khan, Beverly K.
2009-01-01
How do we model and improve technical problem solving, such as network subnetting? This paper reports an experimental study that tested several hypotheses derived from Kolb's experiential learning cycle and Huber's problem solving model. As subjects solved a network subnetting problem, they mapped their mental processes according to Huber's…
Young Children's Analogical Problem Solving: Gaining Insights from Video Displays
ERIC Educational Resources Information Center
Chen, Zhe; Siegler, Robert S.
2013-01-01
This study examined how toddlers gain insights from source video displays and use the insights to solve analogous problems. Two- to 2.5-year-olds viewed a source video illustrating a problem-solving strategy and then attempted to solve analogous problems. Older but not younger toddlers extracted the problem-solving strategy depicted in the video…
Investigating Problem-Solving Perseverance Using Lesson Study
ERIC Educational Resources Information Center
Bieda, Kristen N.; Huhn, Craig
2017-01-01
Problem solving has long been a focus of research and curriculum reform (Kilpatrick 1985; Lester 1994; NCTM 1989, 2000; CCSSI 2010). The importance of problem solving is not new, but the Common Core introduced the idea of making sense of problems and persevering in solving them (CCSSI 2010, p. 6) as an aspect of problem solving. Perseverance is…
NASA Technical Reports Server (NTRS)
Hopkins, Dale A.
1998-01-01
A key challenge in designing the new High Speed Civil Transport (HSCT) aircraft is determining a good match between the airframe and engine. Multidisciplinary design optimization can be used to solve the problem by adjusting parameters of both the engine and the airframe. Earlier, an example problem was presented of an HSCT aircraft with four mixed-flow turbofan engines and a baseline mission to carry 305 passengers 5000 nautical miles at a cruise speed of Mach 2.4. The problem was solved by coupling NASA Lewis Research Center's design optimization testbed (COMETBOARDS) with NASA Langley Research Center's Flight Optimization System (FLOPS). The computing time expended in solving the problem was substantial, and the instability of the FLOPS analyzer at certain design points caused difficulties. In an attempt to alleviate both of these limitations, we explored the use of two approximation concepts in the design optimization process. The two concepts, which are based on neural network and linear regression approximation, provide the reanalysis capability and design sensitivity analysis information required for the optimization process. The HSCT aircraft optimization problem was solved by using three alternate approaches; that is, the original FLOPS analyzer and two approximate (derived) analyzers. The approximate analyzers were calibrated and used in three different ranges of the design variables; narrow (interpolated), standard, and wide (extrapolated).
Problem-solving deficits in Iranian people with borderline personality disorder.
Akbari Dehaghi, Ashraf; Kaviani, Hossein; Tamanaeefar, Shima
2014-01-01
Interventions for people suffering from borderline personality disorder (BPD), such as dialectical behavior therapy, often include a problem-solving component. However, there is an absence of published studies examining the problem-solving abilities of this client group in Iran. The study compared inpatients and outpatients with BPD and a control group on problem-solving capabilities in an Iranian sample. It was hypothesized that patients with BPD would have more deficiencies in this area. Fifteen patients with BPD were compared to 15 healthy participants. Means-ends problem-solving task (MEPS) was used to measure problem-solving skills in both groups. BPD group reported less effective strategies in solving problems as opposed to the healthy group. Compared to the control group, participants with BPD provided empirical support for the use of problem-solving interventions with people suffering from BPD. The findings supported the idea that a problem-solving intervention can be efficiently applied either as a stand-alone therapy or in conjunction with other available psychotherapies to treat people with BPD.
Impulsivity as a mediator in the relationship between problem solving and suicidal ideation.
Gonzalez, Vivian M; Neander, Lucía L
2018-03-15
This study examined whether three facets of impulsivity previously shown to be associated with suicidal ideation and attempts (negative urgency, lack of premeditation, and lack of perseverance) help to account for the established association between problem solving deficits and suicidal ideation. Emerging adult college student drinkers with a history of at least passive suicidal ideation (N = 387) completed measures of problem solving, impulsivity, and suicidal ideation. A path analysis was conducted to examine the mediating role of impulsivity variables in the association between problem solving (rational problem solving, positive and negative problem orientation, and avoidance style) and suicidal ideation. Direct and indirect associations through impulsivity, particularly negative urgency, were found between problem solving and severity of suicidal ideation. Interventions aimed at teaching problem solving skills, as well as self-efficacy and optimism for solving life problems, may help to reduce impulsivity and suicidal ideation. © 2018 Wiley Periodicals, Inc.
Two dimensional finite element heat transfer models for softwood
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...
A Calculus Project that Really Makes Cents
ERIC Educational Resources Information Center
Green, Daniel L.
2006-01-01
This article describes a calculus project that exposes students to the concept of retirement annuities in both the saving and withdrawal phases, via revenue streams represented by integrals. Students use modeling skills to solve several related problems as the assumptions of the original problem are changed, and the project requires them to use a…
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.…
Addressing the problems of the twenty-first century will require new initiatives that complement traditional regulatory activities. Existing regulations, such as the Clean Air Act and Clean Water Act are important safety nets in the United States for protecting human health and t...
Multiply-Constrained Semantic Search in the Remote Associates Test
ERIC Educational Resources Information Center
Smith, Kevin A.; Huber, David E.; Vul, Edward
2013-01-01
Many important problems require consideration of multiple constraints, such as choosing a job based on salary, location, and responsibilities. We used the Remote Associates Test to study how people solve such multiply-constrained problems by asking participants to make guesses as they came to mind. We evaluated how people generated these guesses…
Diagramming Word Problems: A Strategic Approach for Instruction
ERIC Educational Resources Information Center
van Garderen, Delinda; Scheuermann, Amy M.
2015-01-01
While often recommended as a strategy to use in order to solve word problems, drawing a diagram is a complex process that requires a good depth of understanding. Many middle school students with learning disabilities (LD) often struggle to use diagrams in an effective and efficient manner. This article presents information for teaching middle…
Can History Succeed at School? Problems of Knowledge in the Australian History Curriculum
ERIC Educational Resources Information Center
Gilbert, Rob
2011-01-01
Successful curriculum development in any school subject requires a clear and established set of elements: agreed and widely appreciated goals; effective criteria for the selection of important knowledge content; and an explicit and well-integrated explanatory base for authentic problem-solving related to the subject goals. The article shows that…
NASA Technical Reports Server (NTRS)
Iida, H. T.
1966-01-01
Computational procedure reduces the numerical effort whenever the method of finite differences is used to solve ablation problems for which the surface recession is large relative to the initial slab thickness. The number of numerical operations required for a given maximum space mesh size is reduced.
Human factors involvement in bringing the power of AI to a heterogeneous user population
NASA Technical Reports Server (NTRS)
Czerwinski, Mary; Nguyen, Trung
1994-01-01
The Human Factors involvement in developing COMPAQ QuickSolve, an electronic problem-solving and information system for Compaq's line of networked printers, is described. Empowering customers with expert system technology so they could solve advanced networked printer problems on their own was a major goal in designing this system. This process would minimize customer down-time, reduce the number of phone calls to the Compaq Customer Support Center, improve customer satisfaction, and, most importantly, differentiate Compaq printers in the marketplace by providing the best, and most technologically advanced, customer support. This represents a re-engineering of Compaq's customer support strategy and implementation. In its first generation system, SMART, the objective was to provide expert knowledge to Compaq's help desk operation to more quickly and correctly answer customer questions and problems. QuickSolve is a second generation system in that customer support is put directly in the hands of the consumers. As a result, the design of QuickSolve presented a number of challenging issues. Because the produce would be used by a diverse and heterogeneous set of users, a significant amount of human factors research and analysis was required while designing and implementing the system. Research that shaped the organization and design of the expert system component as well.
Unterrainer, J M; Kaller, C P; Halsband, U; Rahm, B
2006-08-01
Playing chess requires problem-solving capacities in order to search through the chess problem space in an effective manner. Chess should thus require planning abilities for calculating many moves ahead. Therefore, we asked whether chess players are better problem solvers than non-chess players in a complex planning task. We compared planning performance between chess ( N=25) and non-chess players ( N=25) using a standard psychometric planning task, the Tower of London (ToL) test. We also assessed fluid intelligence (Raven Test), as well as verbal and visuospatial working memory. As expected, chess players showed better planning performance than non-chess players, an effect most strongly expressed in difficult problems. On the other hand, they showed longer planning and movement execution times, especially for incorrectly solved trials. No differences in fluid intelligence and verbal/visuospatial working memory were found between both groups. These findings indicate that better performance in chess players is associated with disproportionally longer solution times, although it remains to be investigated whether motivational or strategic differences account for this result.
Mr. Traore introduces team supervision. Case scenarios for training and group discussion.
1993-01-01
This supplement to "The Family Planning Manager" presents a case example and five case discussion questions to illustrate the concept of team supervision. In contrast to traditional supervision, where an emphasis is placed on inspection and the uncovering of deficiencies, team supervision uses a facilitative, advocacy-oriented approach. Problem-solving and decision-making responsibilities are assumed by the clinic staff, who identify and analyze problems in group meetings. Thus, the focus shifts from assessing individual performance to evaluating how well they meet clinic objectives as a team. In the team meetings, the visiting supervisor asks the team as a whole to analyze clinic problems and ensures that all staff members are aware of the significance of their contributions. The supervisor also clarifies the division of labor required for implementing solutions and performance standards. Staff are asked if they have concerns they would like communicated to the next organizational level. The supervisory report of the visit can serve as a guide for implementing the recommendations. This approach may require that supervisors and clinic managers receive training in problem solving, motivating staff, team building, and providing constructive feedback.
1984-07-01
piecewise constant energy dependence. This is a seven-dimensional problem with time dependence, three spatial and two angular or directional variables and...in extending the computer implementation of the method to time and energy dependent problems, and to solving and validating this technique on a...problems they have severe limitations. The Monte Carlo method, usually requires the use of many hours of expensive computer time , and for deep
NASA Astrophysics Data System (ADS)
Traversa, Fabio L.; Di Ventra, Massimiliano
2017-02-01
We introduce a class of digital machines, we name Digital Memcomputing Machines, (DMMs) able to solve a wide range of problems including Non-deterministic Polynomial (NP) ones with polynomial resources (in time, space, and energy). An abstract DMM with this power must satisfy a set of compatible mathematical constraints underlying its practical realization. We prove this by making a connection with the dynamical systems theory. This leads us to a set of physical constraints for poly-resource resolvability. Once the mathematical requirements have been assessed, we propose a practical scheme to solve the above class of problems based on the novel concept of self-organizing logic gates and circuits (SOLCs). These are logic gates and circuits able to accept input signals from any terminal, without distinction between conventional input and output terminals. They can solve boolean problems by self-organizing into their solution. They can be fabricated either with circuit elements with memory (such as memristors) and/or standard MOS technology. Using tools of functional analysis, we prove mathematically the following constraints for the poly-resource resolvability: (i) SOLCs possess a global attractor; (ii) their only equilibrium points are the solutions of the problems to solve; (iii) the system converges exponentially fast to the solutions; (iv) the equilibrium convergence rate scales at most polynomially with input size. We finally provide arguments that periodic orbits and strange attractors cannot coexist with equilibria. As examples, we show how to solve the prime factorization and the search version of the NP-complete subset-sum problem. Since DMMs map integers into integers, they are robust against noise and hence scalable. We finally discuss the implications of the DMM realization through SOLCs to the NP = P question related to constraints of poly-resources resolvability.
Improving mathematical problem solving skills through visual media
NASA Astrophysics Data System (ADS)
Widodo, S. A.; Darhim; Ikhwanudin, T.
2018-01-01
The purpose of this article was to find out the enhancement of students’ mathematical problem solving by using visual learning media. The ability to solve mathematical problems is the ability possessed by students to solve problems encountered, one of the problem-solving model of Polya. This preliminary study was not to make a model, but it only took a conceptual approach by comparing the various literature of problem-solving skills by linking visual learning media. The results of the study indicated that the use of learning media had not been appropriated so that the ability to solve mathematical problems was not optimal. The inappropriateness of media use was due to the instructional media that was not adapted to the characteristics of the learners. Suggestions that can be given is the need to develop visual media to increase the ability to solve problems.
In search of the 'Aha!' experience: Elucidating the emotionality of insight problem-solving.
Shen, Wangbing; Yuan, Yuan; Liu, Chang; Luo, Jing
2016-05-01
Although the experience of insight has long been noted, the essence of the 'Aha!' experience, reflecting a sudden change in the brain that accompanies an insight solution, remains largely unknown. This work aimed to uncover the mystery of the 'Aha!' experience through three studies. In Study 1, participants were required to solve a set of verbal insight problems and then subjectively report their affective experience when solving the problem. The participants were found to have experienced many types of emotions, with happiness the most frequently reported one. Multidimensional scaling was employed in Study 2 to simplify the dimensions of these reported emotions. The results showed that these different types of emotions could be clearly placed in two-dimensional space and that components constituting the 'Aha!' experience mainly reflected positive emotion and approached cognition. To validate previous findings, in Study 3, participants were asked to select the most appropriate emotional item describing their feelings at the time the problem was solved. The results of this study replicated the multidimensional construct consisting of approached cognition and positive affect. These three studies provide the first direct evidence of the essence of the 'Aha!' The potential significance of the findings was discussed. © 2015 The British Psychological Society.
Search and Coherence-Building in Intuition and Insight Problem Solving.
Öllinger, Michael; von Müller, Albrecht
2017-01-01
Coherence-building is a key concept for a better understanding of the underlying mechanisms of intuition and insight problem solving. There are several accounts that address certain aspects of coherence-building. However, there is still no proper framework defining the general principles of coherence-building. We propose a four-stage model of coherence-building. The first stage starts with spreading activation restricted by constraints. This dynamic is a well-defined rule based process. The second stage is characterized by detecting a coherent state. We adopted a fluency account assuming that the ease of information processing indicates the realization of a coherent state. The third stage is designated to evaluate the result of the coherence-building process and assess whether the given problem is solved or not. If the coherent state does not fit the requirements of the task, the process re-enters at stage 1. These three stages characterize intuition. For insight problem solving a fourth stage is necessary, which restructures the given representation after repeated failure, so that a new search space results. The new search space enables new coherent states. We provide a review of the most important findings, outline our model, present a large number of examples, deduce potential new paradigms and measures that might help to decipher the underlying cognitive processes.
Search and Coherence-Building in Intuition and Insight Problem Solving
Öllinger, Michael; von Müller, Albrecht
2017-01-01
Coherence-building is a key concept for a better understanding of the underlying mechanisms of intuition and insight problem solving. There are several accounts that address certain aspects of coherence-building. However, there is still no proper framework defining the general principles of coherence-building. We propose a four-stage model of coherence-building. The first stage starts with spreading activation restricted by constraints. This dynamic is a well-defined rule based process. The second stage is characterized by detecting a coherent state. We adopted a fluency account assuming that the ease of information processing indicates the realization of a coherent state. The third stage is designated to evaluate the result of the coherence-building process and assess whether the given problem is solved or not. If the coherent state does not fit the requirements of the task, the process re-enters at stage 1. These three stages characterize intuition. For insight problem solving a fourth stage is necessary, which restructures the given representation after repeated failure, so that a new search space results. The new search space enables new coherent states. We provide a review of the most important findings, outline our model, present a large number of examples, deduce potential new paradigms and measures that might help to decipher the underlying cognitive processes. PMID:28611702
A 2D forward and inverse code for streaming potential problems
NASA Astrophysics Data System (ADS)
Soueid Ahmed, A.; Jardani, A.; Revil, A.
2013-12-01
The self-potential method corresponds to the passive measurement of the electrical field in response to the occurrence of natural sources of current in the ground. One of these sources corresponds to the streaming current associated with the flow of the groundwater. We can therefore apply the self- potential method to recover non-intrusively some information regarding the groundwater flow. We first solve the forward problem starting with the solution of the groundwater flow problem, then computing the source current density, and finally solving a Poisson equation for the electrical potential. We use the finite-element method to solve the relevant partial differential equations. In order to reduce the number of (petrophysical) model parameters required to solve the forward problem, we introduced an effective charge density tensor of the pore water, which can be determined directly from the permeability tensor for neutral pore waters. The second aspect of our work concerns the inversion of the self-potential data using Tikhonov regularization with smoothness and weighting depth constraints. This approach accounts for the distribution of the electrical resistivity, which can be independently and approximately determined from electrical resistivity tomography. A numerical code, SP2DINV, has been implemented in Matlab to perform both the forward and inverse modeling. Three synthetic case studies are discussed.
ERIC Educational Resources Information Center
Limin, Chen; Van Dooren, Wim; Verschaffel, Lieven
2013-01-01
The goal of the present study is to investigate the relationship between pupils' problem posing and problem solving abilities, their beliefs about problem posing and problem solving, and their general mathematics abilities, in a Chinese context. Five instruments, i.e., a problem posing test, a problem solving test, a problem posing questionnaire,…
ERIC Educational Resources Information Center
Higgins, Karen M.
This study investigated the effects of Oregon's Lane County "Problem Solving in Mathematics" (PSM) materials on middle-school students' attitudes, beliefs, and abilities in problem solving and mathematics. The instructional approach advocated in PSM includes: the direct teaching of five problem-solving skills, weekly challenge problems,…
Parallel satellite orbital situational problems solver for space missions design and control
NASA Astrophysics Data System (ADS)
Atanassov, Atanas Marinov
2016-11-01
Solving different scientific problems for space applications demands implementation of observations, measurements or realization of active experiments during time intervals in which specific geometric and physical conditions are fulfilled. The solving of situational problems for determination of these time intervals when the satellite instruments work optimally is a very important part of all activities on every stage of preparation and realization of space missions. The elaboration of universal, flexible and robust approach for situation analysis, which is easily portable toward new satellite missions, is significant for reduction of missions' preparation times and costs. Every situation problem could be based on one or more situation conditions. Simultaneously solving different kinds of situation problems based on different number and types of situational conditions, each one of them satisfied on different segments of satellite orbit requires irregular calculations. Three formal approaches are presented. First one is related to situation problems description that allows achieving flexibility in situation problem assembling and presentation in computer memory. The second formal approach is connected with developing of situation problem solver organized as processor that executes specific code for every particular situational condition. The third formal approach is related to solver parallelization utilizing threads and dynamic scheduling based on "pool of threads" abstraction and ensures a good load balance. The developed situation problems solver is intended for incorporation in the frames of multi-physics multi-satellite space mission's design and simulation tools.
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.
Linear homotopy solution of nonlinear systems of equations in geodesy
NASA Astrophysics Data System (ADS)
Paláncz, Béla; Awange, Joseph L.; Zaletnyik, Piroska; Lewis, Robert H.
2010-01-01
A fundamental task in geodesy is solving systems of equations. Many geodetic problems are represented as systems of multivariate polynomials. A common problem in solving such systems is improper initial starting values for iterative methods, leading to convergence to solutions with no physical meaning, or to convergence that requires global methods. Though symbolic methods such as Groebner bases or resultants have been shown to be very efficient, i.e., providing solutions for determined systems such as 3-point problem of 3D affine transformation, the symbolic algebra can be very time consuming, even with special Computer Algebra Systems (CAS). This study proposes the Linear Homotopy method that can be implemented easily in high-level computer languages like C++ and Fortran that are faster than CAS by at least two orders of magnitude. Using Mathematica, the power of Homotopy is demonstrated in solving three nonlinear geodetic problems: resection, GPS positioning, and affine transformation. The method enlarging the domain of convergence is found to be efficient, less sensitive to rounding of numbers, and has lower complexity compared to other local methods like Newton-Raphson.
Three Modes of Hydrogeophysical Investigation: Puzzles, Mysteries, and Conundrums
NASA Astrophysics Data System (ADS)
Ferre, P. A.
2011-12-01
In an article in the New Yorker in 2007, Malcolm Gladwell discussed the distinction that national security expert Gregory Treverton has made between puzzles and mysteries. Specifically, puzzles are problems that we understand and that will eventually be solved when we amass enough information. (Think crossword puzzles.) Mysteries are problems for which we have the necessary information, but it is often overwhelmed by irrelevant or misleading input. To solve a mystery, we require improved analysis. (Think find-a-word.) Gladwell goes on to explain that, in the national security realm, the Cold War was a puzzle while the current national security condition is a mystery. I will discuss the past, current, and future trajectories of hydrogeophysics in terms of puzzles and mysteries. I will also add a third class of problem: conundrums - those for which we lack sufficient information about their structure to know how to solve them. A conundrum is a mystery with an unexpected twist. I hope to make the case that the future growth of hydrogeophysics lies in our ability to address this more challenging and more interesting class of problem.
NASA Astrophysics Data System (ADS)
Roussel, Marc R.
1999-10-01
One of the traditional obstacles to learning quantum mechanics is the relatively high level of mathematical proficiency required to solve even routine problems. Modern computer algebra systems are now sufficiently reliable that they can be used as mathematical assistants to alleviate this difficulty. In the quantum mechanics course at the University of Lethbridge, the traditional three lecture hours per week have been replaced by two lecture hours and a one-hour computer-aided problem solving session using a computer algebra system (Maple). While this somewhat reduces the number of topics that can be tackled during the term, students have a better opportunity to familiarize themselves with the underlying theory with this course design. Maple is also available to students during examinations. The use of a computer algebra system expands the class of feasible problems during a time-limited exercise such as a midterm or final examination. A modern computer algebra system is a complex piece of software, so some time needs to be devoted to teaching the students its proper use. However, the advantages to the teaching of quantum mechanics appear to outweigh the disadvantages.
Student’s scheme in solving mathematics problems
NASA Astrophysics Data System (ADS)
Setyaningsih, Nining; Juniati, Dwi; Suwarsono
2018-03-01
The purpose of this study was to investigate students’ scheme in solving mathematics problems. Scheme are data structures for representing the concepts stored in memory. In this study, we used it in solving mathematics problems, especially ratio and proportion topics. Scheme is related to problem solving that assumes that a system is developed in the human mind by acquiring a structure in which problem solving procedures are integrated with some concepts. The data were collected by interview and students’ written works. The results of this study revealed are students’ scheme in solving the problem of ratio and proportion as follows: (1) the content scheme, where students can describe the selected components of the problem according to their prior knowledge, (2) the formal scheme, where students can explain in construct a mental model based on components that have been selected from the problem and can use existing schemes to build planning steps, create something that will be used to solve problems and (3) the language scheme, where students can identify terms, or symbols of the components of the problem.Therefore, by using the different strategies to solve the problems, the students’ scheme in solving the ratio and proportion problems will also differ.
A vigorous approach to customer service.
Pollock, E K
1993-01-01
PPG Industries, Inc. is the world's largest supplier of automotive original coatings. Its business-to-business customers require individualized service based on specific requirements. The company has solidified these relationships by establishing satellite supply facilities, applying the quality process to problem solving, and providing a variety of outlets for customer feedback.
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.
Testing foreign language impact on engineering students' scientific problem-solving performance
NASA Astrophysics Data System (ADS)
Tatzl, Dietmar; Messnarz, Bernd
2013-12-01
This article investigates the influence of English as the examination language on the solution of physics and science problems by non-native speakers in tertiary engineering education. For that purpose, a statistically significant total number of 96 students in four year groups from freshman to senior level participated in a testing experiment in the Degree Programme of Aviation at the FH JOANNEUM University of Applied Sciences, Graz, Austria. Half of each test group were given a set of 12 physics problems described in German, the other half received the same set of problems described in English. It was the goal to test linguistic reading comprehension necessary for scientific problem solving instead of physics knowledge as such. The results imply that written undergraduate English-medium engineering tests and examinations may not require additional examination time or language-specific aids for students who have reached university-entrance proficiency in English as a foreign language.
Beam wavefront and farfield control for ICF laser driver
NASA Astrophysics Data System (ADS)
Dai, Wanjun; Deng, Wu; Zhang, Xin; Jiang, Xuejun; Zhang, Kun; Zhou, Wei; Zhao, Junpu; Hu, Dongxia
2010-10-01
Five main problems of beam wavefront and farfield control in ICF laser driver are synthetically discussed, including control requirements, beam propagation principle, distortions source control, system design and adjustment optimization, active wavefront correction technology. We demonstrate that beam can be propagated well and the divergence angle of the TIL pulses can be improved to less than 60μrad with solving these problems, which meets the requirements of TIL. The results can provide theoretical and experimental support for wavefront and farfield control designing requirements of the next large scale ICF driver.
Some variance reduction methods for numerical stochastic homogenization
Blanc, X.; Le Bris, C.; Legoll, F.
2016-01-01
We give an overview of a series of recent studies devoted to variance reduction techniques for numerical stochastic homogenization. Numerical homogenization requires that a set of problems is solved at the microscale, the so-called corrector problems. In a random environment, these problems are stochastic and therefore need to be repeatedly solved, for several configurations of the medium considered. An empirical average over all configurations is then performed using the Monte Carlo approach, so as to approximate the effective coefficients necessary to determine the macroscopic behaviour. Variance severely affects the accuracy and the cost of such computations. Variance reduction approaches, borrowed from other contexts in the engineering sciences, can be useful. Some of these variance reduction techniques are presented, studied and tested here. PMID:27002065
Inflationary dynamics for matrix eigenvalue problems
Heller, Eric J.; Kaplan, Lev; Pollmann, Frank
2008-01-01
Many fields of science and engineering require finding eigenvalues and eigenvectors of large matrices. The solutions can represent oscillatory modes of a bridge, a violin, the disposition of electrons around an atom or molecule, the acoustic modes of a concert hall, or hundreds of other physical quantities. Often only the few eigenpairs with the lowest or highest frequency (extremal solutions) are needed. Methods that have been developed over the past 60 years to solve such problems include the Lanczos algorithm, Jacobi–Davidson techniques, and the conjugate gradient method. Here, we present a way to solve the extremal eigenvalue/eigenvector problem, turning it into a nonlinear classical mechanical system with a modified Lagrangian constraint. The constraint induces exponential inflationary growth of the desired extremal solutions. PMID:18511564
Reference manual for the POISSON/SUPERFISH Group of Codes
DOE Office of Scientific and Technical Information (OSTI.GOV)
Not Available
1987-01-01
The POISSON/SUPERFISH Group codes were set up to solve two separate problems: the design of magnets and the design of rf cavities in a two-dimensional geometry. The first stage of either problem is to describe the layout of the magnet or cavity in a way that can be used as input to solve the generalized Poisson equation for magnets or the Helmholtz equations for cavities. The computer codes require that the problems be discretized by replacing the differentials (dx,dy) by finite differences ({delta}X,{delta}Y). Instead of defining the function everywhere in a plane, the function is defined only at a finitemore » number of points on a mesh in the plane.« less
ERIC Educational Resources Information Center
Scherer, Ronny; Tiemann, Rudiger
2012-01-01
The ability to solve complex scientific problems is regarded as one of the key competencies in science education. Until now, research on problem solving focused on the relationship between analytical and complex problem solving, but rarely took into account the structure of problem-solving processes and metacognitive aspects. This paper,…
ERIC Educational Resources Information Center
Gustafsson, Peter; Jonsson, Gunnar; Enghag, Margareta
2015-01-01
The problem-solving process is investigated for five groups of students when solving context-rich problems in an introductory physics course included in an engineering programme. Through transcripts of their conversation, the paths in the problem-solving process have been traced and related to a general problem-solving model. All groups exhibit…
Klein, Daniel N.; Leon, Andrew C.; Li, Chunshan; D’Zurilla, Thomas J.; Black, Sarah R.; Vivian, Dina; Dowling, Frank; Arnow, Bruce A.; Manber, Rachel; Markowitz, John C.; Kocsis, James H.
2011-01-01
Objective Depression is associated with poor social problem-solving, and psychotherapies that focus on problem-solving skills are efficacious in treating depression. We examined the associations between treatment, social problem solving, and depression in a randomized clinical trial testing the efficacy of psychotherapy augmentation for chronically depressed patients who failed to fully respond to an initial trial of pharmacotherapy (Kocsis et al., 2009). Method Participants with chronic depression (n = 491) received Cognitive Behavioral Analysis System of Psychotherapy (CBASP), which emphasizes interpersonal problem-solving, plus medication; Brief Supportive Psychotherapy (BSP) plus medication; or medication alone for 12 weeks. Results CBASP plus pharmacotherapy was associated with significantly greater improvement in social problem solving than BSP plus pharmacotherapy, and a trend for greater improvement in problem solving than pharmacotherapy alone. In addition, change in social problem solving predicted subsequent change in depressive symptoms over time. However, the magnitude of the associations between changes in social problem solving and subsequent depressive symptoms did not differ across treatment conditions. Conclusions It does not appear that improved social problem solving is a mechanism that uniquely distinguishes CBASP from other treatment approaches. PMID:21500885
Implementing thinking aloud pair and Pólya problem solving strategies in fractions
NASA Astrophysics Data System (ADS)
Simpol, N. S. H.; Shahrill, M.; Li, H.-C.; Prahmana, R. C. I.
2017-12-01
This study implemented two pedagogical strategies, the Thinking Aloud Pair Problem Solving and Pólya’s Problem Solving, to support students’ learning of fractions. The participants were 51 students (ages 11-13) from two Year 7 classes in a government secondary school in Brunei Darussalam. A mixed method design was employed in the present study, with data collected from the pre- and post-tests, problem solving behaviour questionnaire and interviews. The study aimed to explore if there were differences in the students’ problem solving behaviour before and after the implementation of the problem solving strategies. Results from the Wilcoxon Signed Rank Test revealed a significant difference in the test results regarding student problem solving behaviour, z = -3.68, p = .000, with a higher mean score for the post-test (M = 95.5, SD = 13.8) than for the pre-test (M = 88.9, SD = 15.2). This implied that there was improvement in the students’ problem solving performance from the pre-test to the post-test. Results from the questionnaire showed that more than half of the students increased scores in all four stages of the Pólya’s problem solving strategy, which provided further evidence of the students’ improvement in problem solving.
Evaluation of the eigenvalue method in the solution of transient heat conduction problems
NASA Astrophysics Data System (ADS)
Landry, D. W.
1985-01-01
The eigenvalue method is evaluated to determine the advantages and disadvantages of the method as compared to fully explicit, fully implicit, and Crank-Nicolson methods. Time comparisons and accuracy comparisons are made in an effort to rank the eigenvalue method in relation to the comparison schemes. The eigenvalue method is used to solve the parabolic heat equation in multidimensions with transient temperatures. Extensions into three dimensions are made to determine the method's feasibility in handling large geometry problems requiring great numbers of internal mesh points. The eigenvalue method proves to be slightly better in accuracy than the comparison routines because of an exact treatment, as opposed to a numerical approximation, of the time derivative in the heat equation. It has the potential of being a very powerful routine in solving long transient type problems. The method is not well suited to finely meshed grid arrays or large regions because of the time and memory requirements necessary for calculating large sets of eigenvalues and eigenvectors.
NASA Astrophysics Data System (ADS)
Umbarkar, A. J.; Balande, U. T.; Seth, P. D.
2017-06-01
The field of nature inspired computing and optimization techniques have evolved to solve difficult optimization problems in diverse fields of engineering, science and technology. The firefly attraction process is mimicked in the algorithm for solving optimization problems. In Firefly Algorithm (FA) sorting of fireflies is done by using sorting algorithm. The original FA is proposed with bubble sort for ranking the fireflies. In this paper, the quick sort replaces bubble sort to decrease the time complexity of FA. The dataset used is unconstrained benchmark functions from CEC 2005 [22]. The comparison of FA using bubble sort and FA using quick sort is performed with respect to best, worst, mean, standard deviation, number of comparisons and execution time. The experimental result shows that FA using quick sort requires less number of comparisons but requires more execution time. The increased number of fireflies helps to converge into optimal solution whereas by varying dimension for algorithm performed better at a lower dimension than higher dimension.
Flood inundation extent mapping based on block compressed tracing
NASA Astrophysics Data System (ADS)
Shen, Dingtao; Rui, Yikang; Wang, Jiechen; Zhang, Yu; Cheng, Liang
2015-07-01
Flood inundation extent, depth, and duration are important factors affecting flood hazard evaluation. At present, flood inundation analysis is based mainly on a seeded region-growing algorithm, which is an inefficient process because it requires excessive recursive computations and it is incapable of processing massive datasets. To address this problem, we propose a block compressed tracing algorithm for mapping the flood inundation extent, which reads the DEM data in blocks before transferring them to raster compression storage. This allows a smaller computer memory to process a larger amount of data, which solves the problem of the regular seeded region-growing algorithm. In addition, the use of a raster boundary tracing technique allows the algorithm to avoid the time-consuming computations required by the seeded region-growing. Finally, we conduct a comparative evaluation in the Chin-sha River basin, results show that the proposed method solves the problem of flood inundation extent mapping based on massive DEM datasets with higher computational efficiency than the original method, which makes it suitable for practical applications.
Requirements Analysis and Modeling with Problem Frames and SysML: A Case Study
NASA Astrophysics Data System (ADS)
Colombo, Pietro; Khendek, Ferhat; Lavazza, Luigi
Requirements analysis based on Problem Frames is getting an increasing attention in the academic community and has the potential to become of relevant interest also for industry. However the approach lacks an adequate notational support and methodological guidelines, and case studies that demonstrate its applicability to problems of realistic complexity are still rare. These weaknesses may hinder its adoption. This paper aims at contributing towards the elimination of these weaknesses. We report on an experience in analyzing and specifying the requirements of a controller for traffic lights of an intersection using Problem Frames in combination with SysML. The analysis was performed by decomposing the problem, addressing the identified sub-problems, and recomposing them while solving the identified interferences. The experience allowed us to identify certain guidelines for decomposition and re-composition patterns.
NASA Technical Reports Server (NTRS)
Tucker, W. B.; Hooper, H. L.
1963-01-01
This report presents two fundamental properties of lunar trajectories and makes use of these properties to solve various lunar landing site problems. Not only are various problems treated and solved but the properties and methods are established for use in the solution of other problems. This report presents an analysis of lunar landing site problems utilizing the direct mission mode as well as the orbital mission mode. A particular landing site is then specified and different flight profiles are analyzed for getting an exploration vehicle to that landing site. Rendezvous compatible lunar orbits for various stay-times at the landing site are treated. Launch opportunities are discussed for establishing rendezvous compatible lunar orbits without powered plane changes. Then, the minimum required plane changes for rendezvous in the lunar orbit are discussed for launching from earth on any day. On days that afford rendezvous compatible opportunities, there are no powered plane change requirements in the operations from launch at AMR through the rendezvous in lunar orbit, after the stay at the lunar site.
Jiang, Weili; Shang, Siyuan; Su, Yanjie
2015-01-01
People may experience an “aha” moment, when suddenly realizing a solution of a puzzling problem. This experience is called insight problem solving. Several findings suggest that catecholamine-related genes may contribute to insight problem solving, among which the catechol-O-methyltransferase (COMT) gene is the most promising candidate. The current study examined 753 healthy individuals to determine the associations between 7 candidate single nucleotide polymorphisms on the COMT gene and insight problem-solving performance, while considering gender differences. The results showed that individuals carrying A allele of rs4680 or T allele of rs4633 scored significantly higher on insight problem-solving tasks, and the COMT gene rs5993883 combined with gender interacted with correct solutions of insight problems, specifically showing that this gene only influenced insight problem-solving performance in males. This study presents the first investigation of the genetic impact on insight problem solving and provides evidence that highlights the role that the COMT gene plays in insight problem solving. PMID:26528222
Jiang, Weili; Shang, Siyuan; Su, Yanjie
2015-01-01
People may experience an "aha" moment, when suddenly realizing a solution of a puzzling problem. This experience is called insight problem solving. Several findings suggest that catecholamine-related genes may contribute to insight problem solving, among which the catechol-O-methyltransferase (COMT) gene is the most promising candidate. The current study examined 753 healthy individuals to determine the associations between 7 candidate single nucleotide polymorphisms on the COMT gene and insight problem-solving performance, while considering gender differences. The results showed that individuals carrying A allele of rs4680 or T allele of rs4633 scored significantly higher on insight problem-solving tasks, and the COMT gene rs5993883 combined with gender interacted with correct solutions of insight problems, specifically showing that this gene only influenced insight problem-solving performance in males. This study presents the first investigation of the genetic impact on insight problem solving and provides evidence that highlights the role that the COMT gene plays in insight problem solving.
NASA Astrophysics Data System (ADS)
Kase, Sue E.; Vanni, Michelle; Caylor, Justine; Hoye, Jeff
2017-05-01
The Human-Assisted Machine Information Exploitation (HAMIE) investigation utilizes large-scale online data collection for developing models of information-based problem solving (IBPS) behavior in a simulated time-critical operational environment. These types of environments are characteristic of intelligence workflow processes conducted during human-geo-political unrest situations when the ability to make the best decision at the right time ensures strategic overmatch. The project takes a systems approach to Human Information Interaction (HII) by harnessing the expertise of crowds to model the interaction of the information consumer and the information required to solve a problem at different levels of system restrictiveness and decisional guidance. The design variables derived from Decision Support Systems (DSS) research represent the experimental conditions in this online single-player against-the-clock game where the player, acting in the role of an intelligence analyst, is tasked with a Commander's Critical Information Requirement (CCIR) in an information overload scenario. The player performs a sequence of three information processing tasks (annotation, relation identification, and link diagram formation) with the assistance of `HAMIE the robot' who offers varying levels of information understanding dependent on question complexity. We provide preliminary results from a pilot study conducted with Amazon Mechanical Turk (AMT) participants on the Volunteer Science scientific research platform.
Universal Skills and Competencies for Geoscientists
NASA Astrophysics Data System (ADS)
Mosher, S.
2015-12-01
Geoscience students worldwide face a changing future workforce, but all geoscience work has universal cross-cutting skills and competencies that are critical for success. A recent Geoscience Employers Workshop, and employers' input on the "Future of Undergraduate Geoscience Education" survey, identified three major areas. Geoscience work requires spatial and temporal (3D & 4D) thinking, understanding that the Earth is a system of interacting parts and processes, and geoscience reasoning and synthesis. Thus, students need to be able to solve problems in the context of an open and dynamic system, recognizing that most geoscience problems have no clear, unambiguous answers. Students must learn to manage uncertainty, work by analogy and inference, and make predations with limited data. Being able to visualize and solve problems in 3D, incorporate the element of time, and understand scale is critical. Additionally students must learn how to tackle problems using real data, including understand the problems' context, identify appropriate questions to ask, and determine how to proceed. Geoscience work requires integration of quantitative, technical, and computational skills and the ability to be intellectually flexible in applying skills to new situations. Students need experience using high-level math and computational methods to solve geoscience problems, including probability and statistics to understand risk. Increasingly important is the ability to use "Big Data", GIS, visualization and modeling tools. Employers also agree a strong field component in geoscience education is important. Success as a geoscientist also requires non-technical skills. Because most work environments involve working on projects with a diverse team, students need experience with project management in team settings, including goal setting, conflict resolution, time management and being both leader and follower. Written and verbal scientific communication, as well as public speaking and listening skills, are important. Success also depends on interpersonal skills and professionalism, including business acumen, risk management, ethical conduct, and leadership. A global perspective is increasingly important, including cultural literacy and understanding societal relevance.
Understanding Undergraduates’ Problem-Solving Processes †
Nehm, Ross H.
2010-01-01
Fostering effective problem-solving skills is one of the most longstanding and widely agreed upon goals of biology education. Nevertheless, undergraduate biology educators have yet to leverage many major findings about problem-solving processes from the educational and cognitive science research literatures. This article highlights key facets of problem-solving processes and introduces methodologies that may be used to reveal how undergraduate students perceive and represent biological problems. Overall, successful problem-solving entails a keen sensitivity to problem contexts, disciplined internal representation or modeling of the problem, and the principled management and deployment of cognitive resources. Context recognition tasks, problem representation practice, and cognitive resource management receive remarkably little emphasis in the biology curriculum, despite their central roles in problem-solving success. PMID:23653710
Thinking Process of Naive Problem Solvers to Solve Mathematical Problems
ERIC Educational Resources Information Center
Mairing, Jackson Pasini
2017-01-01
Solving problems is not only a goal of mathematical learning. Students acquire ways of thinking, habits of persistence and curiosity, and confidence in unfamiliar situations by learning to solve problems. In fact, there were students who had difficulty in solving problems. The students were naive problem solvers. This research aimed to describe…
Teaching Problem Solving without Modeling through "Thinking Aloud Pair Problem Solving."
ERIC Educational Resources Information Center
Pestel, Beverly C.
1993-01-01
Reviews research relevant to the problem of unsatisfactory student problem-solving abilities and suggests a teaching strategy that addresses the issue. Author explains how she uses teaching aloud problem solving (TAPS) in college chemistry and presents evaluation data. Among the findings are that the TAPS class got fewer problems completely right,…
Transdisciplinary translational science and the case of preterm birth
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.
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.
NASA Astrophysics Data System (ADS)
Castagnoli, Giuseppe
2018-03-01
The usual representation of quantum algorithms, limited to the process of solving the problem, is physically incomplete. We complete it in three steps: (i) extending the representation to the process of setting the problem, (ii) relativizing the extended representation to the problem solver to whom the problem setting must be concealed, and (iii) symmetrizing the relativized representation for time reversal to represent the reversibility of the underlying physical process. The third steps projects the input state of the representation, where the problem solver is completely ignorant of the setting and thus the solution of the problem, on one where she knows half solution (half of the information specifying it when the solution is an unstructured bit string). Completing the physical representation shows that the number of computation steps (oracle queries) required to solve any oracle problem in an optimal quantum way should be that of a classical algorithm endowed with the advanced knowledge of half solution.
ERIC Educational Resources Information Center
Diehl, Brian E.
1997-01-01
Describes the Electric Car Challenge during which students applied methods of construction to build lightweight, strong vehicles that were powered by electricity. The activity required problem solving, sheet metal work, electricity, design, and construction skills. (JOW)
Personality, problem solving, and adolescent substance use.
Jaffee, William B; D'Zurilla, Thomas J
2009-03-01
The major aim of this study was to examine the role of social problem solving in the relationship between personality and substance use in adolescents. Although a number of studies have identified a relationship between personality and substance use, the precise mechanism by which this occurs is not clear. We hypothesized that problem-solving skills could be one such mechanism. More specifically, we sought to determine whether problem solving mediates, moderates, or both mediates and moderates the relationship between different personality traits and substance use. Three hundred and seven adolescents were administered the Substance Use Profile Scale, the Social Problem-Solving Inventory-Revised, and the Personality Experiences Inventory to assess personality, social problem-solving ability, and substance use, respectively. Results showed that the dimension of rational problem solving (i.e., effective problem-solving skills) significantly mediated the relationship between hopelessness and lifetime alcohol and marijuana use. The theoretical and clinical implications of these results were discussed.
Implementing a Loosely Coupled Fluid Structure Interaction Finite Element Model in PHASTA
NASA Astrophysics Data System (ADS)
Pope, David
Fluid Structure Interaction problems are an important multi-physics phenomenon in the design of aerospace vehicles and other engineering applications. A variety of computational fluid dynamics solvers capable of resolving the fluid dynamics exist. PHASTA is one such computational fluid dynamics solver. Enhancing the capability of PHASTA to resolve Fluid-Structure Interaction first requires implementing a structural dynamics solver. The implementation also requires a correction of the mesh used to solve the fluid equations to account for the deformation of the structure. This results in mesh motion and causes the need for an Arbitrary Lagrangian-Eulerian modification to the fluid dynamics equations currently implemented in PHASTA. With the implementation of both structural dynamics physics, mesh correction, and the Arbitrary Lagrangian-Eulerian modification of the fluid dynamics equations, PHASTA is made capable of solving Fluid-Structure Interaction problems.
From Novice to Expert: Problem Solving in ICD-10-PCS Procedural Coding
Rousse, Justin Thomas
2013-01-01
The benefits of converting to ICD-10-CM/PCS have been well documented in recent years. One of the greatest challenges in the conversion, however, is how to train the workforce in the code sets. The International Classification of Diseases, Tenth Revision, Procedure Coding System (ICD-10-PCS) has been described as a language requiring higher-level reasoning skills because of the system's increased granularity. Training and problem-solving strategies required for correct procedural coding are unclear. The objective of this article is to propose that the acquisition of rule-based logic will need to be augmented with self-evaluative and critical thinking. Awareness of how this process works is helpful for established coders as well as for a new generation of coders who will master the complexities of the system. PMID:23861674
Social problem-solving in Chinese baccalaureate nursing students.
Fang, Jinbo; Luo, Ying; Li, Yanhua; Huang, Wenxia
2016-11-01
To describe social problem solving in Chinese baccalaureate nursing students. A descriptive cross-sectional study was conducted with a cluster sample of 681 Chinese baccalaureate nursing students. The Chinese version of the Social Problem-Solving scale was used. Descriptive analyses, independent t-test and one-way analysis of variance were applied to analyze the data. The final year nursing students presented the highest scores of positive social problem-solving skills. Students with experiences of self-directed and problem-based learning presented significantly higher scores in Positive Problem Orientation subscale. The group with Critical thinking training experience, however, displayed higher negative problem solving scores compared with nonexperience group. Social problem solving abilities varied based upon teaching-learning strategies. Self-directed and problem-based learning may be recommended as effective way to improve social problem-solving ability. © 2016 Chinese Cochrane Center, West China Hospital of Sichuan University and John Wiley & Sons Australia, Ltd.
Problem Solving and Chemical Equilibrium: Successful versus Unsuccessful Performance.
ERIC Educational Resources Information Center
Camacho, Moises; Good, Ron
1989-01-01
Describes the problem-solving behaviors of experts and novices engaged in solving seven chemical equilibrium problems. Lists 27 behavioral tendencies of successful and unsuccessful problem solvers. Discusses several implications for a problem solving theory, think-aloud techniques, adequacy of the chemistry domain, and chemistry instruction.…
Role of autobiographical memory in social problem solving and depression.
Goddard, L; Dritschel, B; Burton, A
1996-11-01
Depressed patients frequently exhibit deficiencies in social problem solving (SPS). A possible cause of this deficit is an impairment in patients' ability to retrieve specific autobiographical memories. A clinically depressed group and a hospital control group performed the Means-End Problem-Solving (MEPS; J. J. Platt & G. Spivack, 1975a) task, during which they were required to attend to the memories retrieved during solution generation. Memories were categorized according to whether they were specific, categoric, or extended and whether the valence of the memories was positive or negative. Results support the general hypothesis that SPS skill is a function of autobiographical memory retrieval as measured by a cuing task and by the types of memories retrieved during the MEPS. However, the dysfunctional nature of categoric memories in SPS, rather than the importance of specific memories, was highlighted in the depressed group. Valence proved to be an unimportant variable in SPS ability. The cyclical links among autobiographical memory retrieval, SPS skills, and depression are discussed.
NASA Astrophysics Data System (ADS)
Ushijima, T.; Yeh, W.
2013-12-01
An optimal experimental design algorithm is developed to select locations for a network of observation wells that provides the maximum information about unknown hydraulic conductivity in a confined, anisotropic aquifer. The design employs a maximal information criterion that chooses, among competing designs, the design that maximizes the sum of squared sensitivities while conforming to specified design constraints. Because that the formulated problem is non-convex and contains integer variables (necessitating a combinatorial search), for a realistically-scaled model, the problem may be difficult, if not impossible, to solve through traditional mathematical programming techniques. Genetic Algorithms (GAs) are designed to search out the global optimum; however because a GA requires a large number of calls to a groundwater model, the formulated optimization problem may still be infeasible to solve. To overcome this, Proper Orthogonal Decomposition (POD) is applied to the groundwater model to reduce its dimension. The information matrix in the full model space can then be searched without solving the full model.
An approach to quantum-computational hydrologic inverse analysis
O'Malley, Daniel
2018-05-02
Making predictions about flow and transport in an aquifer requires knowledge of the heterogeneous properties of the aquifer such as permeability. Computational methods for inverse analysis are commonly used to infer these properties from quantities that are more readily observable such as hydraulic head. We present a method for computational inverse analysis that utilizes a type of quantum computer called a quantum annealer. While quantum computing is in an early stage compared to classical computing, we demonstrate that it is sufficiently developed that it can be used to solve certain subsurface flow problems. We utilize a D-Wave 2X quantum annealermore » to solve 1D and 2D hydrologic inverse problems that, while small by modern standards, are similar in size and sometimes larger than hydrologic inverse problems that were solved with early classical computers. Our results and the rapid progress being made with quantum computing hardware indicate that the era of quantum-computational hydrology may not be too far in the future.« less
An approach to quantum-computational hydrologic inverse analysis.
O'Malley, Daniel
2018-05-02
Making predictions about flow and transport in an aquifer requires knowledge of the heterogeneous properties of the aquifer such as permeability. Computational methods for inverse analysis are commonly used to infer these properties from quantities that are more readily observable such as hydraulic head. We present a method for computational inverse analysis that utilizes a type of quantum computer called a quantum annealer. While quantum computing is in an early stage compared to classical computing, we demonstrate that it is sufficiently developed that it can be used to solve certain subsurface flow problems. We utilize a D-Wave 2X quantum annealer to solve 1D and 2D hydrologic inverse problems that, while small by modern standards, are similar in size and sometimes larger than hydrologic inverse problems that were solved with early classical computers. Our results and the rapid progress being made with quantum computing hardware indicate that the era of quantum-computational hydrology may not be too far in the future.
NASA Technical Reports Server (NTRS)
Hudlicka, Eva; Corker, Kevin
1988-01-01
In this paper, a problem-solving system which uses a multilevel causal model of its domain is described. The system functions in the role of a pilot's assistant in the domain of commercial air transport emergencies. The model represents causal relationships among the aircraft subsystems, the effectors (engines, control surfaces), the forces that act on an aircraft in flight (thrust, lift), and the aircraft's flight profile (speed, altitude, etc.). The causal relationships are represented at three levels of abstraction: Boolean, qualitative, and quantitative, and reasoning about causes and effects can take place at each of these levels. Since processing at each level has different characteristics with respect to speed, the type of data required, and the specificity of the results, the problem-solving system can adapt to a wide variety of situations. The system is currently being implemented in the KEE(TM) development environment on a Symbolics Lisp machine.
An approach to quantum-computational hydrologic inverse analysis
DOE Office of Scientific and Technical Information (OSTI.GOV)
O'Malley, Daniel
Making predictions about flow and transport in an aquifer requires knowledge of the heterogeneous properties of the aquifer such as permeability. Computational methods for inverse analysis are commonly used to infer these properties from quantities that are more readily observable such as hydraulic head. We present a method for computational inverse analysis that utilizes a type of quantum computer called a quantum annealer. While quantum computing is in an early stage compared to classical computing, we demonstrate that it is sufficiently developed that it can be used to solve certain subsurface flow problems. We utilize a D-Wave 2X quantum annealermore » to solve 1D and 2D hydrologic inverse problems that, while small by modern standards, are similar in size and sometimes larger than hydrologic inverse problems that were solved with early classical computers. Our results and the rapid progress being made with quantum computing hardware indicate that the era of quantum-computational hydrology may not be too far in the future.« less
Worry and problem-solving skills and beliefs in primary school children.
Parkinson, Monika; Creswell, Cathy
2011-03-01
To examine the association between worry and problem-solving skills and beliefs (confidence and perceived control) in primary school children. Children (8-11 years) were screened using the Penn State Worry Questionnaire for Children. High (N= 27) and low (N= 30) scorers completed measures of anxiety, problem-solving skills (generating alternative solutions to problems, planfulness, and effectiveness of solutions) and problem-solving beliefs (confidence and perceived control). High and low worry groups differed significantly on measures of anxiety and problem-solving beliefs (confidence and control) but not on problem-solving skills. Consistent with findings with adults, worry in children was associated with cognitive distortions, not skills deficits. Interventions for worried children may benefit from a focus on increasing positive problem-solving beliefs. ©2010 The British Psychological Society.
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.