Thinging for Computational Thinking

Abstract

This paper examines conceptual models and their application to computational thinking. Computational thinking is a fundamental skill for everybody, not just for computer scientists. It has been promoted as skills that are as fundamental for all as numeracy and literacy. According to authorities in the field, the best way to characterize computational thinking is the way in which computer scientists think and the manner in which they reason how computer scientists think for the rest of us. Core concepts in computational thinking include such notions as algorithmic thinking, abstraction, decomposition, and generalization. This raises several issues and challenges that still need to be addressed, including the fundamental characteristics of computational thinking and its relationship with modeling patterns (e.g., object-oriented) that lead to programming/coding. Thinking pattern refers to recurring templates used by designers in thinking. In this paper, we propose a representation of thinking activity by adopting a thinking pattern called thinging that utilizes a diagrammatic technique called thinging machine (TM). We claim that thinging is a valuable process as a fundamental skill for everybody in computational thinking. The viability of such a proclamation is illustrated through examples and a case study.

Authors and Affiliations

Sabah Al Fedaghi, Ali Abdullah Alkhaldi

Keywords

Related Articles

Modeling of Quadrotor Roll Loop using Frequency Identification Method

Model estimation is an important step in quadrotor control design because model uncertainties can cause unstable behavior especially with non-robust control methods. In this paper, a modeling approach of a quadrotor prot...

Improving Energy Conservation in Wireless Sensor Network Using Energy Harvesting System

Wireless Sensor Networks assume an imperative part to monitor and gather information from complex geological ranges. Energy conservation plays a fundamental role in WSNs since such sensor networks are designed to be loca...

A new vehicle detection method 

This paper presents a new vehicle detection method from images acquired by cameras embedded in a moving vehicle. Given the sequence of images, the proposed algorithms should detect out all cars in realtime. Related to th...

A Secure Cloud-Based NFC Mobile Payment Protocol

Near Field Communication (NFC) is one the most recent technologies in the area of application development and service delivery via mobile phone. NFC enables the mobile phone to act as identification and a credit card for...

Fast Efficient Clustering Algorithm for Balanced Data

The Cluster analysis is a major technique for statistical analysis, machine learning, pattern recognition, data mining, image analysis and bioinformatics. K-means algorithm is one of the most important clustering algorit...

Download PDF file
  • EP ID EP468750
  • DOI 10.14569/IJACSA.2019.0100277
  • Views 114
  • Downloads 0

How To Cite

Sabah Al Fedaghi, Ali Abdullah Alkhaldi (2019). Thinging for Computational Thinking. International Journal of Advanced Computer Science & Applications, 10(2), 620-629. https://europub.co.uk/articles/-A-468750