Abstract

The principles of computer skills have been included in primary and secondary educated since the early 2000s, and the reform of curricula is related to the development of IT. Therefore, curricula should reflect the latest technological trends and needs of society. The development of a curriculum involves the subjective judgment of a few experts or professors to extract knowledge from several similar documents. More objective extraction needs to be based on standardized terminology, and professional terminology can help build content frames for organizing curricula. The purpose of this study is to develop a smart system for extracting terms from the body of computer science (CS) knowledge and organizing knowledge areas. The extracted terms are composed of semantically similar knowledge areas, using the word2vec model. We analyzed a higher-education CS standards document and compiled a dictionary of technical terms with a hierarchical clustering structure. Based on the developed terminology dictionary, a specialized system is proposed to enhance the efficiency and objectivity of terminology extraction. The analysis of high school education courses in India and Israel using the technical term extraction system found that (1) technical terms for Software Development Fundamentals were extracted at a high rate in entry-level courses, (2) in advanced courses, the ratio of technical terms in the areas of Architecture and Organization, Programming Languages, and Software Engineering areas was high, and (3) electives that deal with advanced content had a high percentage of technical terms related to information systems.

Highlights

  • The development of IT, including virtual reality, block chain using P2P networking, and intelligent ones based on learning algorithms, smartly solves transportation problems, environmental problems, and inefficiencies in facilities [1,2,3,4]

  • The hybrid method generally has better performance than the existing rule- and statistical-based methods, there is a disadvantage in terminology extraction, as its accuracy degrades when it is not supported by a corpus [16]

  • A curriculum is structured according to values that are important to each country in view of the sociocultural context

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Summary

Introduction

The development of IT, including virtual reality, block chain using P2P networking, and intelligent ones based on learning algorithms, smartly solves transportation problems, environmental problems, and inefficiencies in facilities [1,2,3,4]. The composition of any curriculum reflects knowledge selectively based on contents that experts in a given field think are necessary. It is necessary to reflect the global trend in elementary and middle school education for CS, as it is a special field that rapidly drives forward technological change and society. For this reason, such education should be based on an objective flow, such as frame and knowledge extraction for curriculum development and curriculum analysis for each country. This study focused on the extraction of terms and the composition of knowledge domains, which are content elements that help build a curriculum that reflects the standards of CS education and global trends.

Terminology Extraction
Word2vec
Terminology Extraction System
Construction of a Terminology Dictionary
Development of the Terminology Extraction System
System Application and Evaluation
Knowledge Area Composition Using Word2vec
Curriculum Development
Design and Implementation of Algorithms
Conclusions

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