scholarly journals Cognitive psychology and problem solving in the physical sciences

2016 ◽  
pp. 21-25
Author(s):  
David Sands ◽  
Tina Overton
Keyword(s):  
Working Memory ◽  
Cognitive Psychology ◽  
Problem Solving ◽  
Mental Models ◽  
Cognitive Style ◽  
Field Dependence ◽  
Physical Sciences

This paper provides and introduction to the literature on cognitive psychology and problem solving in physical sciences. We consider the working memory and its three different components, two of which hold and record information and are controlled by an executive that controls attention. Working memory alone cannot explain problem solving ability and we review the influence of schemata, the construction of mental models, visual reasoning and the cognitive style of field dependence.

scholarly journals PENGARUH METODE PEMBELAJARAN PEMECAHAN MASALAH DAN GAYA KOGNITIF TERHADAP HASIL BELAJAR MATEMATIKA

Akademika ◽  
2018 ◽  
Vol 7 (01) ◽  
pp. 43-71
Author(s):  
Nurhayati Na ◽  
Khasanah Na
Keyword(s):  
Problem Solving ◽  
Cognitive Style ◽  
Learning Outcomes ◽  
Field Dependence ◽  
Teaching Method ◽  
Mathematics Learning ◽  
Cognitive Styles ◽  
Field Independence ◽  
Learning Problem ◽  
Expository Teaching

This study aimed to determine : ( 1 ) The difference in student learningoutcomes treated with problem-solving learning method is higher than student learningoutcomes treated with expository teaching methods , (2 ) interaction between learningmethod with cognitive style on learning outcomes of mathematics ; ( 3 ) the results of themathematical learning of students who have cognitive style field independence givenlearning problem-solving methods of treatment is higher than the expository method , (4 )the results of the mathematical learning of students who have cognitive style fielddependence given treatment expository teaching method is higher than the problemsolving methods . The hypothesis in this study were 1 ) There are differences in studentlearning outcomes treated with the methods of learning and problem solving expositoryteaching methods ; 2 ) There is an interaction between cognitive styles and teachingmethods on learning outcomes of mathematics ; 3 ) mathematics learning outcomes ofstudents who have cognitive style field independence given learning problem-solvingmethods of treatment is higher than the expository method ; 4 ) mathematics learningoutcomes of students who have cognitive style field dependence given treatmentexpository teaching method is higher than the methods of solving problems . The targetpopulation is the entire fourth grade students SDIT Al - Izzah Serang Banten whichtotaled 173 students . Samples were taken with a random sampling technique thatrandomly select each of the two ( 2 ) classes to be treated with the use of teachingmethods and classroom problem solving using learning methods usedekspositori.Instrumen untukmendapatkan data through student learning outcomesvariable ( Y ) using tests of cognitive learning outcomes , cognitive style variables usingtests of cognitive style Group embedded Figures test ( GEFT ) . The results showed that :First , the results of student learning using a problem -solving method of teaching ishigher than that using the expository method , value sig = 0.009 < α = 0.05 . Second ,there was an interaction between cognitive styles and learning methods , Value sig = 0.00< α = 0.05 , F value = 5.168 > F = 3.99 . Third , mathematics learning outcomes ofstudents who have cognitive style field independence given learning problem-solvingmethods of treatment is higher than the expository method , with the results Qhitung >Qtabel ( 4.55 > 2.95 ) . Mathematics learning outcomes of students who have thecognitive style of field dependence given treatment expository teaching method is higherthan the methods of solving problems , with the result Qhitung > Qtabel (3.03 > 2.95 )

scholarly journals Memoria di lavoro, chunks e Lexical Approach: alcune possibili convergenze

2021 ◽  
pp. 33-50
Author(s):  
Mario Cardona
Keyword(s):  
Working Memory ◽  
Cognitive Psychology ◽  
Problem Solving ◽  
Language Learning ◽  
Language Education ◽  
Phonological Loop ◽  
Anglo Saxon ◽  
Human System ◽  
Lexical Approach ◽  
Acquisition Processes

Working memory is one of the most investigated topics in cognitive psychology and neuropsychology since it plays a key role in the architecture of cognitive human system. Reasoning, problem solving, and learning would be not possible without the contribution of working memory. Working memory is deeply involved in linguistic processes and in essential activities such as reading. Recent scientific research, especially in Anglo-Saxon context, has begun to investigate the role played by working memory not only in learning L1, but also in the acquisition processes of L2. Nevertheless, the overview of Italian language education still presents a lack of adequate literature on the important implications of the activity of working memory both for the theories of language learning and the practices of language teaching. This paper has the goal to identify some possible convergences between the working memory processes – especially of phonological loop and phonological memory – and the theoretical-practical system of Lexical Approach proposed by Lewis (1993; 1997). In this latter, specific attention is paid to the structure and learning of lexical chunks which are, according to Lewis, a fundamental element of the nature of lexicon and especially of collocations.

scholarly journals MATHEMATICAL REASONING ABILITIES OF STUDENTS IN TERMS OF FIELD DEPENDENCE (FD) COGNITIVE STYLE IN PROBLEM-SOLVING

2021 ◽  
Vol 1 (1) ◽  
pp. 1-5
Author(s):  
Zaini Zaini
Keyword(s):  
Problem Solving ◽  
Cognitive Style ◽  
Field Dependence ◽  
Test Problem ◽  
Mathematical Reasoning ◽  
Research Data ◽  
Basic Knowledge ◽  
Reasoning Abilities ◽  
Long Time

Every individual has different abilities in translating problems because it is influenced by basic knowledge, experience, and cognitive. The cognitive types of FD were identical slower than others. This study describes the mathematical reasoning of students with cognitive type of  FD in problem solving. The research data needed is the GEFT test, problem-solving tests, and interviews involving twostudents in level IV . All data were analyzed inductively. The results showed that students with the cognitive type of FD needed a long time to create  connection to the problem thinking and they needed direction as a stimulus to stimulate their thinking. Lecturers can use realistic examples in the  environment around them to make connections in their thinking.

The Prediction of Problem-Solving Assessed Via Microworlds

2016 ◽  
Vol 32 (4) ◽  
pp. 298-306 ◽  
Author(s):  
Samuel Greiff ◽  
Katarina Krkovic ◽  
Jarkko Hautamäki
Keyword(s):  
Working Memory ◽  
Problem Solving ◽  
Complex Problem ◽  
Two Dimensions ◽  
Assessment Instruments ◽  
Complex Problem Solving ◽  
Visual Spatial ◽  
Rule Knowledge ◽  
Rule Application ◽  
Fluid Reasoning

Abstract. In this study, we explored the network of relations between fluid reasoning, working memory, and the two dimensions of complex problem solving, rule knowledge and rule application. In doing so, we replicated the recent study by Bühner, Kröner, and Ziegler (2008) and the structural relations investigated therein [ Bühner, Kröner, & Ziegler, (2008) . Working memory, visual-spatial intelligence and their relationship to problem-solving. Intelligence, 36, 672–680]. However, in the present study, we used different assessment instruments by employing assessments of figural, numerical, and verbal fluid reasoning, an assessment of numerical working memory, and a complex problem solving assessment using the MicroDYN approach. In a sample of N = 2,029 Finnish sixth-grade students of which 328 students took the numerical working memory assessment, the findings diverged substantially from the results reported by Bühner et al. Importantly, in the present study, fluid reasoning was the main source of variation for rule knowledge and rule application, and working memory contributed only a little added value. Albeit generally in line with previously conducted research on the relation between complex problem solving and other cognitive abilities, these findings directly contrast the results of Bühner et al. (2008) who reported that only working memory was a source of variation in complex problem solving, whereas fluid reasoning was not. Explanations for the different patterns of results are sought, and implications for the use of assessment instruments and for research on interindividual differences in complex problem solving are discussed.

scholarly journals Working Memory, Fluid Reasoning, and Complex Problem Solving: Different Results Explained by the Brunswik Symmetry

2021 ◽  
Vol 9 (1) ◽  
pp. 5
Author(s):  
André Kretzschmar ◽  
Stephan Nebe
Keyword(s):  
Working Memory ◽  
Problem Solving ◽  
Cognitive Abilities ◽  
Latent Variables ◽  
Complex Problem ◽  
Equation Modeling ◽  
Complex Problem Solving ◽  
Symmetry Principle ◽  
Fluid Reasoning ◽  
The Impact

In order to investigate the nature of complex problem solving (CPS) within the nomological network of cognitive abilities, few studies have simultantiously considered working memory and intelligence, and results are inconsistent. The Brunswik symmetry principle was recently discussed as a possible explanation for the inconsistent findings because the operationalizations differed greatly between the studies. Following this assumption, 16 different combinations of operationalizations of working memory and fluid reasoning were examined in the present study (N = 152). Based on structural equation modeling with single-indicator latent variables (i.e., corrected for measurement error), it was found that working memory incrementally explained CPS variance above and beyond fluid reasoning in only 2 of 16 conditions. However, according to the Brunswik symmetry principle, both conditions can be interpreted as an asymmetrical (unfair) comparison, in which working memory was artificially favored over fluid reasoning. We conclude that there is little evidence that working memory plays a unique role in solving complex problems independent of fluid reasoning. Furthermore, the impact of the Brunswik symmetry principle was clearly demonstrated as the explained variance in CPS varied between 4 and 31%, depending on which operationalizations of working memory and fluid reasoning were considered. We argue that future studies investigating the interplay of cognitive abilities will benefit if the Brunswik principle is taken into account.

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