Development of a Modularized Undergraduate Data Science and Big Data Curricular Using No-Code Software Development Tools

Over the last decade, Data Science has emerged as one of the most important subjects that has had a major impact on industry. This is due to the continual development of scientific methods, algorithms, processes, and computational tools that help to extract knowledge from raw data efficiently and co...

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Veröffentlicht in:	IEEE access Jg. 12; S. 100939 - 100956
Hauptverfasser:	Mafukidze, Harry D., Nechibvute, Action, Yahya, Abid, Badruddin, Irfan Anjum, Kamangar, Sarfaraz, Hussien, Mohamed
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	IEEE 2024
Schlagworte:	Computer languages Curriculum Curriculum development Data mining Data models Data science Education no-code tools Programming profession visual programming languages Visualization
ISSN:	2169-3536, 2169-3536
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Abstract	Over the last decade, Data Science has emerged as one of the most important subjects that has had a major impact on industry. This is due to the continual development of scientific methods, algorithms, processes, and computational tools that help to extract knowledge from raw data efficiently and cost-effectively, compared with early-generation tools. Professional data scientists create code that processes, analyses and extracts actionable insights from high volumes of data. This process requires a deep understanding of mathematical principles, statistics, business knowledge, and computer science. But most importantly, the data science development chain requires knowledge of a high-level programming tool and its dependencies. This is a major problem in some aspects due to the steep learning curve. In this paper, we describe and present a modularized Data Science curriculum for undergraduate learners that relies on no-code software development tools as programming aids for non-computer science majors. No-code development tools have been added to the traditional teaching pedagogy to improve students' motivation and conceptual understanding of coding despite their limited programming skills. The study aims to assess the impacts of visual programming languages on the performance of non-computer science majors on programming problems. The study's sample consists of 50 fourth-year students from the Faculty of Science and Technology at the Midlands State University. A post-survey questionnaire and assessment items were administered to the control and experimental groups. Results show that the students drawn from the experimental group benefited from the use of a visual programming language. These results offer evidence-based recommendations for incorporating high-performance no-code software development tools in the formal curriculum to aid teaching and learning data science programming for students of diverse academic backgrounds.
AbstractList	Over the last decade, Data Science has emerged as one of the most important subjects that has had a major impact on industry. This is due to the continual development of scientific methods, algorithms, processes, and computational tools that help to extract knowledge from raw data efficiently and cost-effectively, compared with early-generation tools. Professional data scientists create code that processes, analyses and extracts actionable insights from high volumes of data. This process requires a deep understanding of mathematical principles, statistics, business knowledge, and computer science. But most importantly, the data science development chain requires knowledge of a high-level programming tool and its dependencies. This is a major problem in some aspects due to the steep learning curve. In this paper, we describe and present a modularized Data Science curriculum for undergraduate learners that relies on no-code software development tools as programming aids for non-computer science majors. No-code development tools have been added to the traditional teaching pedagogy to improve students’ motivation and conceptual understanding of coding despite their limited programming skills. The study aims to assess the impacts of visual programming languages on the performance of non-computer science majors on programming problems. The study’s sample consists of 50 fourth-year students from the Faculty of Science and Technology at the Midlands State University. A post-survey questionnaire and assessment items were administered to the control and experimental groups. Results show that the students drawn from the experimental group benefited from the use of a visual programming language. These results offer evidence-based recommendations for incorporating high-performance no-code software development tools in the formal curriculum to aid teaching and learning data science programming for students of diverse academic backgrounds.
Author	Badruddin, Irfan Anjum Hussien, Mohamed Yahya, Abid Nechibvute, Action Mafukidze, Harry D. Kamangar, Sarfaraz
Author_xml	– sequence: 1 givenname: Harry D. orcidid: 0000-0001-8534-6139 surname: Mafukidze fullname: Mafukidze, Harry D. email: mafukidzehd@staff.msu.ac.zw organization: Department of Applied Physics and Telecommunications, Midlands State University, Gweru, Zimbabwe – sequence: 2 givenname: Action surname: Nechibvute fullname: Nechibvute, Action organization: Department of Applied Physics and Telecommunications, Midlands State University, Gweru, Zimbabwe – sequence: 3 givenname: Abid orcidid: 0000-0003-3741-8315 surname: Yahya fullname: Yahya, Abid organization: Department of Electrical, Computer and Telecommunications Engineering, Botswana International University of Science and Technology, Palapye, Botswana – sequence: 4 givenname: Irfan Anjum surname: Badruddin fullname: Badruddin, Irfan Anjum organization: Department of Mechanical Engineering, College of Engineering, King Khalid University, Abha, Saudi Arabia – sequence: 5 givenname: Sarfaraz orcidid: 0000-0001-7838-1884 surname: Kamangar fullname: Kamangar, Sarfaraz organization: Department of Mechanical Engineering, College of Engineering, King Khalid University, Abha, Saudi Arabia – sequence: 6 givenname: Mohamed surname: Hussien fullname: Hussien, Mohamed organization: Department of Chemistry, Faculty of Science, King Khalid University, Abha, Saudi Arabia
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SubjectTerms	Computer languages Curriculum Curriculum development Data mining Data models Data science Education no-code tools Programming profession visual programming languages Visualization
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Title	Development of a Modularized Undergraduate Data Science and Big Data Curricular Using No-Code Software Development Tools
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