The process of computational thinking typically includes four parts: decomposition, pattern recognition, abstraction and algorithmic thinking. Pattern recognition as part of computational thinking is the process of identifying patterns in a data set to categorize, process and resolve the information more ...
They solved problems using computational components, namely decomposition, pattern recognition, algorithm, abstraction, and debugging. Pattern recognition characteristics for solving the mathematics problem in computational thinking can be identified as follows: (1) understanding the problem by looking for ...
Sometimes we may also be interested in infrequent or rare patterns (i.e., patterns that occur rarely but are of critical importance, or negative patterns (i.e., patterns that reveal a negative correlation between items). ■ Based on the abstraction levels involved in a pattern: Patterns or ...
2022,Advanced Methods and Deep Learning in Computer Vision Chapter Visual Pattern Mining Abstract Visual patterns, i.e., high-order combinations of visual words, have provided a discriminative abstraction of the high-dimensional bag-of-words image representation. However, the existing visual pattern mi...
Timeless classic that must be read by all computer science majors. While some topics and the use of Scheme as the teaching language seems odd at first glance, the presentation of fundamental concepts such as abstraction, recursion, and modularity is so beautiful and insightful that you would neve...
The paper introduces the reader to the assurance case methodology and the 4 + 1 ethical principles, then presents their combination in the PRAISE argument pattern and describes this at a relatively high level of abstraction. It proceeds as follows. ...
This approach obviates the need for students to implement low level and often time-consuming agent behavior programming and yet, requires the use of abstraction, which is a key component of computational thinking. Initial data shows that students in the classroom can implement simulations faster ...
We present an approach facilitating exploration of long-term flow data by means of spatial and temporal abstraction. It involves a special way of data aggregation, which allows representing spatial situations by diagram maps instead of flow maps, thus reducing the intersections and occlusions ...
Data were collected through tests which were then analyzed based on indicators of computational thinking ability, namely problem decomposition, pattern recognition, algorithmic thinking, abstraction, and generalization. The results showed that students' computational thinking skills in solving number pattern ...
Task descriptions have certain “boilerplate” parameters, as described in the subsections below. Other kinds of task sequence models are used to highlight user workflow. These include state diagrams, which are a kind of hybrid abstraction between a flow model and a task-sequence model that ...