The purpose of this study was to describe the creative thinking process of students' field-independent cognitive style in solving mathematical problems related to the circumference of a flat shape. ...The method used was descriptive qualitative. The subjects of this study were class VIII students who had a field-independent cognitive style based on the Group Embedded Figure Test (GEFT). Data were obtained through tests, documentation, observation, and interviews. Data analysis was carried out using four creative thinking processes developed by Graham Walla, namely preparation, incubation, illumination, and verification. The results indicated that students could understand the problem well, tend to be quiet to find solutions, could design solutions that would be done by choosing ideas to be solved by modifying the knowledge they already have and applying designed ideas to solve problems. Therefore, students seemed to understand mathematical operations related to the circumference of plat shapes.
Abstrak:
Tujuan penelitian ini adalah untuk menyajikan proses berpikir kreatif gaya kognitif field-Independent siswa dalam memecahkan masalah matematika berkaitan dengan keliling bangun datar. Metode yang digunakan adalah kualitatif deskriptif. Subjek penelitian ini merupakan siswa kelas VIII yang memiliki gaya kognitif field-independent berdasarkan hasil tes Group Embedded Figure Test (GEFT). Data diperoleh melalui tes, dokumentasi, observasi, dan wawancara. Analysis data dilakukan menggunakan empat proses berpikir kreatif yang dikembangkan Graham Walla, yaitu persiapan, inkubasi, iluminasi, dan verifikasi. Hasil penelitian menunjukkan bahwa Siswa dapat memahami masalah dengan baik, cenderung pendiam untuk mencari solusi, dapat merancang solusi yang akan dilakukan dengan memilih ide untuk diselesaikan dengan memodifikasi pengetahuan yang telah dimiliki, dan menerapkan ide yang dirancang untuk menyelesaikan masalah. Oleh karena itu, siswa tampak memahami operasi matematika yang berkaitan dengan keliling bangun datar.
Certain learners are less sensitive to learning environments and can always learn, while others are more sensitive to variations in learning environments and may fail to learn (Cronbach & Snow, ...1977). We refer to the former as high learners and the latter as low learners. One important goal of any learning environment is to bring students up to the same level of mastery. We showed that an intelligent tutoring system (ITS) teaching a domain-independent problem-solving strategy indeed closed the gap between high and low learners, not only in the domain where it was taught (probability) but also in a second domain where it was not taught (physics). The strategy includes two main components: one is solving problems via backward chaining (BC) from goals to givens, called the BC strategy, and the other is drawing students' attention to the characteristics of each individual domain principle, called the principle-emphasis skill. Evidence suggests that the low learners transferred the principle-emphasis skill to physics while the high learners seemingly already had such skill and thus mainly transferred the other skill, the BC strategy. Surprisingly, the low learners learned just as effectively as the high learners in physics. We concluded that the effective element of transfer seemed not to be the BC strategy, but the principle-emphasis skill.
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The central question of the article is already formulated in the title. The author advocates a minimal definition of intelligence: intelligence is independent problem solving. The level of ...intelligence depends on the complexity of the problems and the degree of independence in solving them (Klaus Mainzer). According to this definition, the author notes that intelligent machines already exist. These are AI systems that are capable of deep learning. In the paper, the author presents criticisms of the claim that AI is intelligent in the literal sense and not just in the metaphorical sense. These criticisms are based on objections that can be divided into two basic groups. Proponents of the first line of criticism cite mental abilities (such as phenomenal consciousness and awareness) and aliveness as essential attributes of intelligence, rejecting the notion of artificial life as nonsense. Inanimate and non-mental systems are merely adaptive, not intelligent systems. Representatives of the second group claim that the indispensable characteristics of intelligence are generality, intuition, common sense and abduction. The author analyses the aforementioned criticisms and concludes that their proponents have not given good reasons against the minimal definition.
One important goal of Intelligent Tutoring Systems (ITSs) is to bring students up to the same level of mastery. We showed that an ITS teaching a domain-independent problem-solving strategy indeed ...closed the gap between High and Low learners, not only in the domain where it was taught (probability) but also in a second domain where it was not taught (physics). The strategy includes two main components: one is solving problems via Backward-Chaining (BC) from goals to givens, named the BC-strategy, and the other is drawing students’ attention on the characteristics of each individual domain principle, named the principle-emphasis skill. Evidence suggests that the Low learners transferred the principle-emphasis skill to physics while the High learners seemingly already had such skill and thus mainly transferred the other skill, the BC-strategy. Surprisingly, the former learned just as effectively as the latter in physics. We concluded that the effective element of the taught strategy seemed not to be the BC-Strategy, but the principle-emphasis skill.
Used a 2 * 2 factorial design to determine the effect of cognitive style and teaching method on 3 different aspects of subject matter achievement factual content, conceptual-generalization content, ...and total content. Data from 80 undergraduates indicate that a teacher-structured-presentation method of instruction was significantly superior to an independent-problem-solving method of instruction on all 3 dependent measures. There was no significant difference between Ss with an analytic cognitive style and Ss with a nonanalytic cognitive style on any of the dependent measures nor was there a significant interaction between cognitive style and teaching method. (19 ref.)
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