Showing papers on "Adaptive reasoning published in 2017"

Complex Problem Solving: What It Is and What It Is Not.

Abstract: Computer-simulated scenarios have been part of psychological research on problem solving for more than 40 years. The shift in emphasis from simple toy problems to complex, more real-life oriented problems has been accompanied by discussions about the best ways to assess the process of solving complex problems. Psychometric issues such as reliable assessments and addressing correlations with other instruments have been in the foreground of these discussions and have left the content validity of complex problem solving in the background. In this paper, we return the focus to content issues and address the important features that define complex problems.

A conceptual model of mathematical reasoning for school mathematics

Abstract: The development of students’ mathematical reasoning (MR) is a goal of several curricula and an essential element of the culture of the mathematics education research community. But what mathematical reasoning consists of is not always clear; it is generally assumed that everyone has a sense of what it is. Wanting to clarify the elements of MR, this research project aimed to qualify it from a theoretical perspective, with an elaboration that would not only indicate its ways of being thought about and espoused but also serve as a tool for reflection and thereby contribute to the further evolution of the cultures of the teaching and research communities in mathematics education. To achieve such an elaboration, a literature search based on anasynthesis (Legendre, 2005) was undertaken. From the analysis of the mathematics education research literature on MR and taking a commognitive perspective (Sfard, 2008), the synthesis that was carried out led to conceptualizing a model of mathematical reasoning. This model, which is herein described, is constituted of two main aspects: a structural aspect and a process aspect, both of which are needed to capture the central characteristics of MR.

Modeling visual problem solving as analogical reasoning.

Abstract: We present a computational model of visual problem solving, designed to solve problems from the Raven's Progressive Matrices intelligence test. The model builds on the claim that analogical reasoning lies at the heart of visual problem solving, and intelligence more broadly. Images are compared via structure mapping, aligning the common relational structure in 2 images to identify commonalities and differences. These commonalities or differences can themselves be reified and used as the input for future comparisons. When images fail to align, the model dynamically rerepresents them to facilitate the comparison. In our analysis, we find that the model matches adult human performance on the Standard Progressive Matrices test, and that problems which are difficult for the model are also difficult for people. Furthermore, we show that model operations involving abstraction and rerepresentation are particularly difficult for people, suggesting that these operations may be critical for performing visual problem solving, and reasoning more generally, at the highest level. (PsycINFO Database Record

Problem Solving Approach

Abstract: Problem is something that we can never get rid of, how much we try and howmany anticipatory actions we take Therefore, to deal with problems in our everyday life, every project implementation is to solve the problem as and when required In this article we will try and study about problems and the techniques and methods by which we can solve it or mitigate the situation Again it is worthy to mention as a prelude and also to conclude that problem solving is an individual skill and it therefore varies from person to person and from situation to situation and there exist no thumb rule to redress ay problem as a generalized rule By the end of this article, we will try and develop certain tools by which we may approach a problematic situation before redressing the problem

Adaptive control of bilateral teleoperation system with compensatory neural-fuzzy controllers

Abstract: This paper presents two adaptive neural-fuzzy controllers equipped with compensatory fuzzy control in order to adjust membership functions, and as well to optimize the adaptive reasoning by using a compensatory learning algorithm. To the first controller is applied compensatory neural-fuzzy inference (CNFI) and to the second compensatory adaptive neural fuzzy inference system (CANFIS). Each controller is incorporated into a two channel bilateral teleoperation architecture involving force-position scheme, which combines the position control of the slave system with force reflection on the master. An analysis of stability and transparency based on a passivity framework is carried out. The resulting controllers are implemented on a one degree of freedom teleoperation system actuated by DC motors. The experimental results obtained show a fairly high accuracy in terms of position and force tracking, under free space motion and hard contact motion, what highlights the effectiveness of the proposed controllers.

Investigating adaptive reasoning and strategic competence: Difference male and female

Abstract: The series of adaptive reasoning and strategic competencies represent the five components of mathematical proficiency to describe the students’ mathematics learning success. Gender contribute to the problem-solving process. This qualitative research approach investigated the adaptive reasoning and strategic competence aspects of a male student and a female student when they solved mathematical problem. They were in the eleventh grade of high school in Makassar. Both also had similar mathematics ability and were in the highest category. The researcher as the main instrument used secondary instrument to obtain the appropriate subject and to investigate the aspects of adaptive reasoning and strategic competence. Test of mathematical ability was used to locate the subjects with similar mathematical ability. The unstructured guideline interview was used to investigate aspects of adaptive reasoning and strategic competence when the subject completed the task of mathematical problem. The task of mathematical problem involves several concepts as the right solution, such as the circle concept, triangle concept, trigonometry concept, and Pythagoras concept. The results showed that male and female subjects differed in applying a strategy to understand, formulate and represent the problem situation. Furthermore, both also differed in explaining the strategy used and the relationship between concepts and problem situations.

Thinking Fast and Slow in Computer Problem Solving

Abstract: Research in spreadsheet management proved that the overuse of slow thinking, rather than fast thinking, is the primary source of erroneous end-user computing. However, we found that the reality is not that simple. To view end-user computing in its full complexity, we launched a project to investigate end-user education, training, support, activities, and computer problem solving. In this project we also set up the base and mathability-extended typology of computer problem solving approaches, where quantitative values are assigned to the different problem solving methods and activities. In this paper we present the results of our analyses of teaching materials collected in different languages from all over the world and our findings considering the different problem solving approaches, set in the frame of different thinking modes, the characteristics of expert teachers, and the meaning system model of teaching approaches. Based on our research, we argue that the proportions of fast and slow thinking and most importantly their manifestation are responsible for erroneous end-user activities. Applying the five-point mathability scale of computer problem solving, we recognized slow thinking activities on both tails and one fast thinking approach between them. The low mathability slow thinking activities, where surface navigation and language details are focused on, are widely accepted in end-user computing. The high mathability slow thinking problem solving activities, where the utilization of concept based approaches and schema construction take place, is hardly detectable in end-user activities. Instead of building up knowledge which requires slow thinking and then using the tools with fast thinking, end-users use up their slow thinking in aimless wandering in huge programs, making wrong decisions based on their untrained, clueless intuition, and distributing erroneous end-user documents. We also found that the dominance of low mathability slow thinking activities has its roots in the education system and through this we point out that we are in great need of expert teachers and institutions and their widely accepted approaches and methods.

Complex Adaptive Systems, Systems Thinking, and Agent-Based Modeling

Abstract: Systems thinking and complex adaptive systems theories share a number of components, namely emergence, self-organization, and hierarchies of interacting systems. We seek to integrate these schools of thought and discuss the similarities and differences of these two models, to introduce systems dynamics and agent-based modeling as methods for modeling complex systems, and how causal-loop diagrams can be used as a means to clarify the complex interactions among components (agents). We then apply a mixture of these different but similar techniques to a fly ecosystem modeling problem to demonstrate their effectiveness.

Reflective Plausible Reasoning in Solving Inequality Problem

Abstract: This study explored students' reflective plausible reasoning in solving inequality problem. This explorative study with the qualitative approach was conducted to seven subjects. Data are derived from the result of written answer, think aloud, and interview. The data from those subjects were analyzed using a constant comparative method so that it was obtained the same characteristics of reflective plausible reasoning. In this article, the authors described two subjects. The results of this study were the characteristics of students' reflective plausible reasoning shown by these behaviors: (1) students gave the argumentations based on intrinsic mathematical properties during solving inequality problem, (2) students experienced state of perplexity in problem solving process, (3) students realized that there was inaccuracy in the problem solving process which is indicated by feeling suspicious, doubtful, or curious, (4) students conducted inquiry to correct their error until they found the right solution, and (5) students experienced state of steadiness which is indicated by feeling sure and satisfied toward the truth of the result.

Adaptive problem solving: Moving towards a new assessment domain in the second cycle of PIAAC

Abstract: The set of skills that is required to be a successful citizen in the 21st century is rapidly evolving. New technologies and social systems grow increasingly complex and require individuals to quickly and flexibly adapt to new and changing circumstances. This paper outlines the key features of the domain of adaptive problem solving that is proposed to be assessed in the 2nd cycle of the OECD Survey of Adult Skills (PIAAC) in addition to the domains of numeracy and literacy. Adaptive problem solving is considered to be a crucial 21st century skill that combines cognitive and meta-cognitive processes. The paper develops a definition of adaptive problem solving building on relevant work in cognitive psychology and cognitive science, introduces its covariates and preconditions, discusses relevant assessment principles, and provides insights on the relevance of adaptive problem solving for labour markets and social integration.

A multimodal LEGO®-based learning activity mixing musical notation and computer programming

Abstract: This paper discusses a multimodal learning activity based on LEGO® bricks where elements from the domains of music and informatics are mixed. Such an experience addresses children in preschool age and students of the primary schools in order to convey some basic aspects of computational thinking. The learning methodology is organized in two phases where construction blocks are employed as a physical tool and as a metaphor for music notation, respectively. The goal is to foster in young students abilities such as analysis and re-synthesis, problem solving, abstraction and adaptive reasoning. A web application to support this approach and to provide a prompt feedback to user action is under development, and its design principles and key characteristics will be presented.

The effect of problem posing and problem solving with realistic mathematics education approach to the conceptual understanding and adaptive reasoning

Abstract: One of the difficulties of students in learning mathematics is on the subject of geometry that requires students to understand abstract things. The aim of this research is to determine the effect of learning model Problem Posing and Problem Solving with Realistic Mathematics Education Approach to conceptual understanding and students’ adaptive reasoning in learning mathematics. This research uses a kind of quasi experimental research. The population of this research is all seventh grade students of Junior High School 1 Jaten, Indonesia. The sample was taken using stratified cluster random sampling technique. The test of the research hypothesis was analyzed by using t-test. The results of this study indicate that the model of Problem Posing learning with Realistic Mathematics Education Approach can improve students’ conceptual understanding significantly in mathematics learning. In addition tu, the results also showed that the model of Problem Solving learning with Realistic Mathematics Education Approach can improve students’ adaptive reasoning significantly in learning mathematics. Therefore, the model of Problem Posing and Problem Solving learning with Realistic Mathematics Education Approach is appropriately applied in mathematics learning especially on the subject of geometry so as to improve conceptual understanding and students’ adaptive reasoning. Furthermore, the impact can improve student achievement.

Probability or reasoning: Current thinking and realistic strategies for improved medical decisions

Abstract: A prescriptive model approach in decision making could help achieve better diagnostic accuracy in clinical practice through methods that are less reliant on probabilistic assessments. Various prescriptive measures aimed at regulating factors that influence heuristics and clinical reasoning could support clinical decision-making process. Clinicians could avoid time-consuming decision-making methods that require probabilistic calculations. Intuitively, they could rely on heuristics to obtain an accurate diagnosis in a given clinical setting. An extensive literature review of cognitive psychology and medical decision-making theory was performed to illustrate how heuristics could be effectively utilized in daily practice. Since physicians often rely on heuristics in realistic situations, probabilistic estimation might not be a useful tool in everyday clinical practice. Improvements in the descriptive model of decision making (heuristics) may allow for greater diagnostic accuracy.

How does anxiety influence fluid reasoning

Abstract: Does anxiety influence fluid reasoning, either negatively or positively? The purpose of this article was to review much of the relevant current literature to answer this question. An individual's ability to employ fluid reasoning to solve novel problems must include the context of the circumstances, the individual's unique set of cognitive resources, one's ability to utilize previously acquired knowledge from similar situations, and to create a solution in a quick and effective manner. Working memory and creativity are cognitive skill sets that influence the efficiency and effectiveness of novel problem solving, while anxiety can be a crippling factor for some. This article aims to discuss the role of each of these factors the implementation of novel problem solving with a special emphasis on the role of development during adolescence.

An Heuristic Framework for Non-Conscious Reasoning

Abstract: Human non-conscious reasoning is one of the most successful procedures evolved for the purposes of solving everyday problems in an efficient way. This is why the field of artificial intelligence should analyze, formalize and emulate the multiple ways of non-conscious reasoning with the purpose of applying them in human problem solving tasks, like medical diagnostics and treatments, educational diagnostics and intervention, organizational and political decision making, artificial intelligence knowledge based systems and neurocomputers, automatic control systems and similar devices for aiding people in the problem-solving process. In this paper, a heuristic framework for those non-conscious ways of reasoning is presented based on neurocognitive representations, heuristics, and fuzzy sets.

Building from In Vivo Research to the Future of Research on Relational Thinking and Learning

Abstract: This concluding commentary takes the perspective of research on practicing scientists and engineers to consider what open areas and future directions on relational thinking and learning should be considered beyond the impressive research presented in the special issue. Areas for more work include (a) a need to examine educational applications of relational thinking in divergent reasoning, rather than primarily in convergent reasoning; (b) considerations of when to not focus on relational reasoning in learning; (c) more research on the distributed nature of relational reasoning across students in a class, and to embedded physical, social, and historical contexts; (d) treatment of the hot components of relational reasoning including motivational and emotional processes; and (e) more attention to how relational reasoning is changed by the details of modalities rather than treating all contents as abstract symbols.

Adaptive Reasoning Algorithm with Automated Test Cases Generation and Test Algebra in Saas System

Abstract: A new integrated testing framework is proposed to use adaptive reasoning algorithm with automated test cases generation (ARP) and test algebra (TA) for increasing SaaS testing efficiency in faulty combination identification and elimination. The ARP algorithm has been evaluated by both simulation and real experimentation using a MTA SaaS sample running on GAE (Google App Engine). Both the simulation and experiment show that the ARP algorithm can identify those faulty combinations rapidly and TA can eliminate a large number of faults from candidate test set with a small number of seeded faults.

Management of Multimodal User Interaction in Companion -Systems

Abstract: While interacting, human beings continuously adapt their way of communication to their surroundings and their communication partner. Although present context-aware ubiquitous systems gather a lot of information to maximize their functionality, they predominantly offer rather static ways to communicate. In order to fulfill the user’s communication needs and demands, ubiquitous sensors’ varied information could be used to dynamically adapt the user interface. Considering such an adaptive user interface management as a major and relevant component for a Companion-Technology, we also have to cope with emotional and dispositional user input as a source of implicit user requests and demands. In this chapter we demonstrate how multimodal fusion based on evidential reasoning and probabilistic fission with adaptive reasoning can act together to form a highly adaptive and model-driven interactive system component for multimodal interaction. The presented interaction management (IM) can handle uncertain or ambiguous data throughout the complete interaction cycle with a user. In addition, we present the IM’s architecture and its model-driven concept. Finally, we discuss its role within the framework of the other constituents of a Companion-Technology.

Problem solving ability in probability theory through problem solving based learning

Abstract: The aims of this study are to determine level of problem solving ability after being given problem solving based learning and to determine the effect of problem solving based learning to problem solving ability in probability theory. The method used is quasi experimental, with pre-experimental design and one shot case study design. The population are the students of fifth semester in IKIP PGRI Pontianak and it consists of 3 classes. Sample just consists of a class, which obtained through cluster random sampling technique. Instrument used is problem solving ability test. Data is analyzed using descriptive statistics and inferential statistics. The study show that the problem solving based learning doesn’t give good effect to problem solving ability, but it has average score is 67 or good level. Beside of that, the study also show that students have ability of understanding the problem with the average score is 75 or high level, ability of devising the plan with the average score is 66 or high level, ability of carrying out the plan with the average score is 50 or middle level, and the average score is 19 or very low level for ability of looking back.

Assessment of the Research on Problem Solving and Insight

Abstract: This literature review explores the extent of research on problem solving and insight, as well as the roles of conscious and unconscious processes. This paper looks at the research on the structure of how insight develops and in general the problem solving process. Next, the type of problems are examined as to which type of problem solving task work best using either conscious or unconscious processes. Then, this paper covers research on probabilistic reasoning as this may be an unconscious process and the role of memory and sleep may have in problem solving and insight. To conclude, there are areas that still need further research but there is strong evidence of an integral role of unconsciousness processes in problem solving.

Adaptive Fault Detection In Multi-tenancy Saas Systems

Abstract: This chapter discusses combinatorial testing in multi-tenancy Software-as-a-Service (SaaS) system. SaaS often uses multi-tenancy architecture (MTA) where tenant developers compose their applications online using the components stored in the SaaS database. Tenant applications need to be tested, and combinatorial testing can be used. While numerous combinatorial testing techniques are available, most of them produce static sequence of test configurations and their goal is often to provide sufficient coverage such as 2-way interaction coverage. But the goal of SaaS testing is to identify those compositions that are faulty for tenant applications. In this chapter, it proposes an adaptive test configuration generation algorithm called adaptive reasoning (AR) that can rapidly identify those faulty combinations so that those faulty combinations cannot be selected by tenant developers for composition. Whenever a new component is submitted to the SaaS database, the AR algorithm can be applied so that any faulty interactions with new components can be identified to continue to support future tenant applications.

Toward Adaptive Rough Sets

Abstract: In this paper we take an attempt to depart from the closed way of presenting information table characterizing a vague concept with respect to a closed sample of objects, a fixed set of attributes, and a static time point. The aim is rather to have an interactive information system which is open to incorporate new information based on the interactions of an agent with the physical reality. This in turn prepares the ground for the notion of adaptive information system which incorporates the possibility of adapting decision strategies based on the history of making decisions over a period of time through interactions of an agent with the physical reality.

From play to problem solving to Common Core: The development of fluid reasoning.

Abstract: How and when does fluid reasoning develop and what does it look like at different ages, from a neurodevelopmental and functional perspective? The goal of this article is to discuss the development of fluid reasoning from a practical perspective of our children's lives: from play to problem solving to Common Core Curriculum. A review of relevant and current literature supports a connection between movement, including movement through free play, and the development of novel problem solving. As our children grow and develop, motor routines can become cognitive routines and can be evidenced not only in games, such as chess, but also in the acquisition and demonstration of academic skills. Finally, this article describes the connection between novel problem solving and the demands of the Common Core Curriculum.

Analisis adaptive reasoning proficiency mahasiswa melalui implementasi teori conditioning-reinforcement-scaffolding (CRS) pada mata kuliah analisis real

Abstract: The research approach used in this research is the quantitative approach. The quantitative study is done through experimental research method by giving treatment through CRS theory implementation in Real Analysis lecture. Provision of treatment directed to improve student’s adaptive reasoning proficiency. The research design used was quasi-experimental with the design form of matching-only pretest-posttest control group design. Population in this research is all student of semester IV of academic year 2016/2017 Program of the Mathematics Education University of Singaperbangsa Karawang who contract Real Course of Analysis, and a sample of this research involves two groups of students selected using purposive sampling technique with matching the subject. Matching the subject is done by pairing individuals based on certain criteria. These criteria are determined based on placement test results before pretesting. This is done in an effort to obtain an equivalent group. The result of the research concludes that 1) The improvement of the adaptive reasoning proficiency of students who get the learning through the implementation of CRS theory does not reach 70% of ideal criteria expected. 2) Increased adaptive reasoning proficiency of students who get learning through the implementation of CRS theory is higher than students who get learning through the implementation of constructivism theory. 3) There is an adaptive difference in reasoning proficiency of students who get learning through the implementation of CRS theory based on achievement of adaptive indicators of reasoning proficiency. 4) There is no interaction between learning factor with achievement factor of adaptive reasoning proficiency toward student’s adaptive reasoning proficiency in real analysis course.

Facilitating Problem Solving and Critical Thinking Using a Comprehensive Pedagogical Approach

Abstract: v There were notable differences in the significant trends for Total Problem Solving (posi9ve linear trend with higher final scores than ini9al) and Cri$cal (quadra9c with higher ini9al scores than final) scores v Overall improvements in Problem-­‐Solving but not Cri$cal Thinking v Low scores on select components (ex: Implica$ons and Consequences) are ripe areas for further targeted solu9ons. v May need more than one semester to make a significant difference in Cri$cal Thinking abili9es v Students at the senior level may s9ll be developing cri9cal thinking and problem-­‐solving skills

SynAdapt: Automated Synthesis of Adaptive Agents

Abstract: Distributed autonomous multi-agent reasoning and classification systems have been thought of to be the basis of intelligence and have wide applications in the space of operational intelligence in closing the loop between sensing, analytics, and actions. This paper targets multi-agent systems that employ rulebased logics (i.e., rules that determine the output/response of an agent depending on the range of the input values) with pre-defined rules to accurately perceive the environment, and provide associated reactions. Such rule-based systems do not perform well in scenarios, where human generated rules cannot adapt to dynamic variations in the data distribution arising due to dynamic changes in the environment, especially if data dimensionality is very high. Examples of such scenarios exist wherever the sensed data arrives from the physical world - such as weather data, physical sensor data, human behaviour controlled data, etc. Clearly, to meet the adaptivity requirements of such scenarios we require the agents to possess adaptive reasoning capability such that they can adapt the underlying rules with respect to the changing environment. Developing such adaptive agents requires the developer to additionally possess considerable expertise of state-of-the-art machine learning techniques, apart from possessing knowledge of the agent's target domain. To address the above issues, we automate the process of development and deployment of adaptive agents. We present the fundamental design concepts behind the development of SynAdapt: a new adaptive meta-learning based multi-agent synthesis framework, that automates the synthesis of adaptive multi-agent systems from high-level user specifications. SynAdapt provides the following key features: a) Automated synthesis and deployment of adaptive agents from high-level user specification, b) Agents synthesised by SynAdapt can select a learning strategy that is particularly suited for given user specifications and input dataset, and c) Agents synthesised by SynAdapt can leverage adaptive ensemble learning techniques to deal with concept drift.

The Influence of Learning Activeness and Adaptive Reasoning on Students' Strategic Competence with Metaphorical Thinking Learning Approach

Abstract: This research aims to describe and examine the influence of learning activeness and adaptive reasoning on strategic competence of learning Intelligent Control System (ICS) course with metaphorical thinking learning approach. The type of research was a survey study. The population of this research included all students of the semester VI of Mechatronics Engineering Education. The sample in the study were the class F students in the academic year of 2013 who were taking course of Intelligent Control System. Data collection techniques used observation, test, and question. Research instruments included a sheet of observation, Likert-scale questions form, and strategic competence tests of ICS. Data analysis techniques to answer the problem formulation used correlation and regression analysis. The results of the result are (1) there is a positive influence of adaptive reasoning on strategic competence of learning ICS for R = 0.5806 or 58.1%, (2) there is a significant and positive influence of metaphorical thinking learning on strategic competence of learning ICS for R = 0.3769 or 37.7%, (3) there is a positive and significant influence of adaptive reasoning and learning of metaphorical thinking together on strategic competence of learning ICS with F 45.202 significant with the model of equation y =-45.18 + 1.07 0.87 x 1 + X 2. Keywords—adaptive reasoning; Intelligent Control System; metaphorical thinking; strategic competence;