Primary school pre-service teachers’ solutions to pattern problem-solving tasks based on three components of creativity

Education stakeholders and researchers in South Africa have emphasised the need to enhance teachers’ creativity through problem-solving tasks. Teachers’ creativity entails using new ideas of creative devices to solve problems, implement solutions, and make learning more effective. In the research reported on here, Guilford’s theory was used to explore primary school pre-service teachers’ solutions to pattern problem-solving tasks based on 3 components of creativity. The data for this research were produced from primary school pre-service teachers’ written responses to the pattern problem-solving tasks, and an extract from participants’ semi-structured interviews. The research involved a qualitative design using convenient purposive sampling to sample 62 pre-service teachers enrolled for a primary mathematics module at a selected higher education institution. Participants’ responses to the written tasks were analysed using content analysis, while the semi-structured interviews were analysed thematically. The result shows that 35 participants were able to draw patterns and express patterns in nth form, while 27 failed to do so. The most common method used to draw a new pattern was counting in 2s and 4s. Furthermore, the result shows that half of the pre-service teachers who participated in the study were not capable of producing varied solutions to pattern tasks. An indication that they did not have the creative potential to prepare learners even after they had been exposed to advanced mathematics content as part of their training process. We recommend that pre service teacher education programmes should include academic activities that could help pre-service teachers enhance creativity through tasks with divergent thinking.

Exploring the Prospective Mathematics Teachers Computational Thinking in Solving Pattern Geometry Problem

This research aims to describe the characteristic of mathematics prospective teacher's computational thinking (CT) in solving the geometric pattern problem. The subject consists of 65 preservice mathematics teachers in Universitas in Madiun. The instrument was used in this research are geometric pattern problem tests and interview guidelines. The result shows that are three types of mathematics prospective teachers in solving the problem. First, CT substantial, i.e. prospective mathematics teachers use the conceptual knowledge who collaborated with procedural knowledge exactly. They use mathematics iteration to find the pattern and express them to the general form easily. Second, CT Nominal, i.e. prospective mathematics teachers, use manual ways to solve the pattern problem. They count using numeric, not symbolic, of solving the pattern formed. They can understand the design but can't express it to the mathematics model. Third, CT procedural, i.e. mathematics prospective teacher using the procedural knowledge only, not an expert in concept, and following the steps who teaches from experience before. The recommendation for future research is to develop the research to find the other characters in other mathematics subjects, in other students, to develop the learning models who can embody CT.

Pola Pendidikan Rasulullah Shallallahu ‘Alaihi Wasallam Sebagai Pendidik Ideal

This article discusses the pattern of education of the Prophet sallallaahu 'alaihi wasallam which is the foundation of education, especially Islamic education. The success of education applied by the Prophet Muhammad SAW, both in Makkah Al-Mukarramah approximately 13 (thirteen) years, and in Madinah Al-Munawwarah approximately 10 (ten) years, because of what he conveyed, he has applied first in all aspects of his life and his life. The education or teaching of the Prophet sallallaahu 'alaihi wasallam uses educational patterns, such as: Dialogue Pattern, Repetition Pattern, Praga Giving Pattern, Experiment Pattern, Problem Solving Pattern, Discussion Pattern, Joy Giving Pattern, and Sanction Giving Pattern.

On the subjects of property rights and the ownership pattern problem by the example of the legislation in Russia and foreign countries

The paper examines the scientific views and ideas development regarding the range of ownership right subjects, starting from the Roman law times and ending with modern civil legislation codifications. Considerations are expressed regarding the possibility of recognizing the people as a whole as a subject of the ownership rights. The concept of ownership patterns existing in the legislation of Russia and a number of other countries in the post-Soviet space is analysed.

A novel algorithm for searching frequent gradual patterns from an ordered data set

Mining frequent simultaneous attribute co-variations in numerical databases is also called frequent gradual pattern problem. Few efficient algorithms for automatically extracting such patterns have been reported in the literature. Their main difference resides in the variation semantics used. However in applications with temporal order relations, those algorithms fail to generate correct frequent gradual patterns as they do not take this temporal constraint into account in the mining process. In this paper, we propose an approach for extracting frequent gradual patterns for which the ordering of supporting objects matches the temporal order. This approach considerably reduces the number of gradual patterns within an ordered data set. The experimental results show the benefits of our approach.

The Phantom Pattern Problem

Pattern recognition prowess served our ancestors well. However, today we are confronted by a deluge of data that are far more abstract, complicated, and difficult to interpret than were annual seasons and the sounds of predators. The number of possible patterns that can be identified relative to the number that are genuinely useful has grown exponentially—which means that the chances that a discovered pattern is useful is rapidly approaching zero. Coincidental streaks, clusters, and correlations are the norm—not the exception. Our challenge is to overcome our inherited inclination to think that all patterns are meaningful.Computer algorithms can easily identify an essentially unlimited number of phantom patterns and relationships that vanish when confronted with fresh data. The paradox of big data is that the more data we ransack for patterns, the more likely it is that what we find will be worthless. Our challenge is to overcome our inherited inclination to think that all patterns are meaningful.