Showing papers on "Adaptive reasoning published in 2018"

The effect of creative problem solving on students’ mathematical adaptive reasoning

Abstract: This research was conducted to analyse the effect of creative problem solving (CPS) learning model on the students' mathematical adaptive reasoning. The method used in this study was a quasi-experimental with randomized post-test only control group design. Samples were taken as many as two classes by cluster random sampling technique consisting of experimental class (CPS) as many as 40 students and control class (conventional) as many as 40 students. Based on the result of hypothesis testing with the t-test at the significance level of 5%, it was obtained that significance level of 0.0000 is less than α = 0.05. This shows that the students' mathematical adaptive reasoning skills who were taught by CPS model were higher than the students' mathematical adaptive reasoning skills of those who were taught by conventional model. The result of this research showed that the most prominent aspect of adaptive reasoning that could be developed through a CPS was inductive intuitive. Two aspects of adaptive reasoning, which were inductive intuitive and deductive intuitive, were mostly balanced. The different between inductive intuitive and deductive intuitive aspect was not too big. CPS model can develop student mathematical adaptive reasoning skills. CPS model can facilitate development of mathematical adaptive reasoning skills thoroughly.

Exploring students’ adaptive reasoning skills and van Hiele levels of geometric thinking: a case study in geometry

Abstract: This study aims to explore junior high school students' adaptive reasoning and the Van Hiele level of geometric thinking. The present study was a quasi-experiment with the non-equivalent control group design. The participants of the study were 34 seventh graders and 35 eighth graders in the experiment classes and 34 seventh graders and 34 eighth graders in the control classes. The students in the experiment classes learned geometry under the circumstances of a Knisley mathematical learning. The data were analyzed quantitatively by using inferential statistics. The results of data analysis show an improvement of adaptive reasoning skills both in the grade seven and grade eight. An improvement was also found for the Van Hiele level of geometric thinking. These results indicate the positive impact of Knisley learning model on students' adaptive reasoning skills and Van Hiele level of geometric thinking.

The analysis of adaptive reasoning ability reviewed from students’ confidence in ethnomathematic-based treffinger learning model

Abstract: The objective of this study was to examine whether ethnomathematics-based Treffinger learning model was good to improve students’ adaptive reasoning ability and to describe the adaptive reasoning ability based on students’ self-confidence level. The method of this study was Mixed Methods. While the population of this study was tenth grade science students of Wiradesa High School academic year 2017/2018. Again, the population was divided into 2 categories, they were the tenth grade of Science 2 was the experimental class and the tenth grade Science 1 was a control class. Eventually, the result showed that: (1) Ethnomathematics-based Treffinger learning model has good quality in improving students' adaptive reasoning ability since the planning and the implementation of learning process had good criteria, starting from teacher’s and student’s activities and the average of learning outcomes had reached the minimum score (KKM) and (2) the classification of adaptive reasoning ability was based on students' confidence level.

Making industrial robots smarter with adaptive reasoning and autonomous thinking for real-time tasks in dynamic environments: a case study

Abstract: In order to extend the abilities of current robots in industrial applications towards more autonomous and flexible manufacturing, this work presents an integrated system comprising real-time sensing, path-planning and control of industrial robots to provide them with adaptive reasoning, autonomous thinking and environment interaction under dynamic and challenging conditions. The developed system consists of an intelligent motion planner for a 6 degrees-of-freedom robotic manipulator, which performs pick-and-place tasks according to an optimized path computed in real-time while avoiding a moving obstacle in the workspace. This moving obstacle is tracked by a sensing strategy based on machine vision, working on the HSV space for color detection in order to deal with changing conditions including non-uniform background, lighting reflections and shadows projection. The proposed machine vision is implemented by an off-board scheme with two low-cost cameras, where the second camera is aimed at solving the problem of vision obstruction when the robot invades the field of view of the main sensor. Real-time performance of the overall system has been experimentally tested, using a KUKA KR90 R3100 robot.

Analisis penalaran adaptif dalam menyelesaikan soal polyhedron ditinjau dari gaya belajar dan gaya berpikir

Abstract: This descriptive qualitative research designed to investigate the ability of adaptive reasoning on students in major of polyhedron viewed from different teaching and learning styles in each student. The population of this study were 30 students of class VIII C Stella Matutina Junior High School Salatiga. Based on the population selected 13 from 30 students as sample of research by using purposive sampling technique that is student having different learning style and thinking style which will be used to observed different way of adaptive reasoning. Data collection techniques used interview and documentation methods consisting of learning style test, thinking style test, and written test about polyhedron. Data analysis techniques use classification guidelines for learning styles and thinking styles and rubrics assessment of adaptive reasoning. Based on the rubric it is found that students who have visual learning style and supported by abstract thinking style that is VAR / AA and VK / SA students get score 19, VAK / AA and VARK / AA got score 18, fulfilling the five indicators of adaptive reasoning and have reasoning ability an excellent adaptive in polyhedron compared to students with other type of learning and thinking styles.

Implementation of Problem Posing Learning on Conceptual Understanding and Adaptive Reasoning

Abstract: This research is based on the low level of students' mathematical skills in elementary schools, including conceptual understanding and adaptive reasoning. So it takes learning that emphasizes the conceptual understanding and adaptive reasoning is learning problem posing. This study uses Quasi Eksperimen. In the experimental group used problem posing learning with winger application, while in the control class used STAD learning assisted wingeom application. The results showed that learning posing problems with wingeom application support can improve conceptual understanding and thinking in adaptive reasoning in solving various mathematical problems, especially geometric math problems. Keywords—Problem posing; mathematical skills; geometry

Geometric skew image classification algorithm based on fusion adaptive reasoning

Abstract: The geometric skew model is widely used in image classification and image retrieval. In the traditional skew model, the geometric topology statistical method ignores the spatial information between geometric words and the classification object shape information, which leads to the distinguishing ability of image features. In this paper, we propose a geometric skew method with adaptive reasoning. Combined with significant region extraction and geometric topology, we not only can generate more representative geometric topologies but also can avoid complex background information and position change bands to a certain extent. First, the adaptive reasoning geometric skewness model is constructed on the obtained significant area by carrying out the significant region extraction of the training image. Second, in order to describe the characteristics of the image more accurately, it can resist the changing position and background information. The method uses the geometric topology strategy and the polygon segmentation method to integrate global information and local information. Through the simulation experiment and compared with the traditional skewness model and other models, the results show that the method proposed in this paper obtains higher intelligence image classification accuracy.

PRSPR: An Adaptive Framework for Massive RDF Stream Reasoning

Abstract: In this paper, we propose a plugin-based framework for massive RDF stream reasoning to support complicated tasks on RDF stream in an adaptive and flexible way Within this framework, the problem of RDF stream reasoning can be equivalently reduced to the combination problem of SPARQL querying and rule-based reasoning Take advantage of the plug-in method, we can apply various off-the-shelf SPARQL query engines and rule-based reasoners in a simple way Moreover, to efficiently support real-time reasoning on massive RDF stream, we develop a multi-threaded batch processing approach to manage resources and an adaptive reasoning plan for dynamically managing inference rules in the stream reasoning Finally, our experiments evaluate on dataset built on the benchmark LUBM and DBpedia The experimental results show that our framework is effective and efficient