Holistic Assessment of Computational Thinking for Undergraduate

Sondakh, Debby Erce; Osman, Kamisah; Zainudin, Suhaila

doi:10.1145/3369255.3369303

Cited by 5 publications

(4 citation statements)

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“…Sub-construct is construct categories among the candidate items that are defined to ensure the items' convergent validity. Further, the first version underwent a content validation process through experts' judgment in a three-round Fuzzy Delphi Study, as reported in [49]. As a result, the initial Hi-ACT comprising 155 items was ready for validity and reliability assessment.…”

Section: A Hi-act Initial Instrumentmentioning

confidence: 99%

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A Pilot Study of an Instrument to Assess Undergraduates’ Computational thinking Proficiency

Sondakh¹,

Osman²,

Zainudin³

2020

IJACSA

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The potentiality of computational thinking (CT) in problem solving has gained much attention in academic communities. This study aimed at developing and validating an instrument, called Hi-ACT, to assess CT ability of university undergraduates. The Hi-ACT evaluates both technical and soft skills applicable to CT based problem solving. This paper reports a pilot study conducted to test and refine the initial Hi-ACT. Survey method was employed through which questionnaire comprising of 155 items was piloted among 548 university undergraduates. Structural equation modeling with partial least squares was applied to examine the Hi-ACT's reliability and validity. Composite reliability was used to assess internal consistency reliability, while convergent validity was evaluated using based on items' outer loadings and constructs' average variance extracted. As a result, 41 items were excluded, and an instrument to assess CT ability comprising 114 items and ten constructs (abstraction, algorithmic thinking, decomposition, debugging, generalization, evaluation, problem solving, teamwork, communication, and spiritual intelligence) was developed. The reliability and validity of the Hi-ACT in its pilot form have been verified.

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Section: A Hi-act Initial Instrumentmentioning

confidence: 99%

“…This paper reports a pilot study that was conducted to assess and refine the initial Hi-ACT by examining its reliability and validity. This is an extended version of the work published in [20].…”

Section: Introductionmentioning

confidence: 99%

A Pilot Study of an Instrument to Assess Undergraduates’ Computational thinking Proficiency

Sondakh¹,

Osman²,

Zainudin³

2020

IJACSA

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“…Во многих работах, в которых вычислительное мышление рассматривается в контексте высшего образования, декларируемый набор навыков существенно шире. Так, в обзоре D. Sondakh [7] -наибольшая часть исследований проводилась в процессе изучения информатики и подготовки учителей (по 14 работ на каждый случай). Остальные дисциплины из самых разных областей -от математики и биологии до музыки и изобразительного искусства-были представлены одной-двумя работами;…”

Section: обзор работ по вычислительному мышлению студентов вузовunclassified

Computational thinking in the context of higher education: Analytical review

Khenner

2024

Obraz. nauka

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Introduction. Computational thinking is one of the categories that currently assess the quality of people’s preparedness for life, educational and professional activities in the modern world, saturated with information technologies and digital tools. Many issues related to university students’ computational thinking remain insufficiently studied as applied to general education.Aim. The present research aims to discuss the essence of the concept of “computational thinking” and, mainly, the composition of its structural elements, methods of their formation and assessment at the level of higher education; and to compare the requirements for university students’ computational thinking and digital competencies, which have similarities and differences.Methodology and research methods. The present review article has theoretical and applied aspects. Except for several fundamentally important works of general studies, which reveal the concept of “computational thinking”, the author analysed mainly review articles published in the past five years in order to identify and systematise modern solutions related to the purpose of the work.Results and scientific novelty. An analysis of the basic concepts associated with computational thinking showed that at the level of definitions, due to their certain abstractness, the computational thinking of university students does not have much specificity compared to the computational thinking of schoolchildren. This specificity is manifested at the level of the list of cognitive and non-cognitive skills associated with computational thinking, requirements for the level of their development and assessment methods. In computational thinking, cognitive skills include abstraction, decomposition, pattern recognition, algorithmisation, visualisation, logical thinking, communicative competence, the ability to present, structure and analyse data, and some others skills. Non-cognitive skills include self-confidence, communication skills, flexibility, and others.Methods for assessing the maturity of students’ computational thinking include the results of solving problems in block programming environments such as Scrath; knowledge/skill tests, self-assessment scales/surveys; tests on knowledge of the basics of computational thinking, interviews and observations; interviews, grades for assignments/courses, surveys/questionnaires, solving problems external to the class; the use of a special software environment, the use of criteria for assessing computational thinking and/or psychometric tools; assessments based on solving robotic problems or evaluating artifacts created during the game, and others.A comparison of computational thinking with digital competencies at the skill level leads to the conclusion that in computational thinking, skills represent a certain fixed set of meta-skills needed by a student regardless of solving specific problems (for example, abstraction skills). In digital competencies, skills are specified according to numerous types and are more specific.Practical significance. The results of this study can be used in the design of programmes for developing computational thinking and digital competencies of university students.

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“…Multiple definitions and operationalizations have been proposed making it difficult to design and assess teaching materials aimed at developing CT [11]- [16]. This lack of consensus has obstructed the development and assessment of teaching approaches to support students' development of CT [17], [18]. However, most common approaches include framing CT in terms of abstraction, automation, and decomposition [17].…”

Section: Introduction and Theoretical Frameworkmentioning

confidence: 99%

Promoting Computational Thinking in Integrated Engineering Design and Physics Labs

Lopez-Parra,

Chatta Subramaniam,

Morphew

2023 ASEE Annual Conference &Amp; Exposition Proceedings

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Computational thinking has widely been recognized as a crucial skill for engineers engaged in problem-solving. Multidisciplinary learning environments such as integrated STEM courses are powerful spaces where computational thinking skills can be cultivated. However, it is not clear the best ways to integrate computational thinking instruction or how students develop computational thinking in those spaces. Thus, we wonder: To what extent does engaging students in integrated engineering design and physics labs impact their development of computational thinking? We have incorporated engineering design within a traditional introductory calculusbased physics lab to promote students' conceptual understanding of physics while fostering scientific inquiry, mathematical modeling, engineering design, and computational thinking. Using a generic qualitative research approach, we explored the development of computational thinking for six teams when completing an engineering design challenge to propose an algorithm to remotely control an autonomous guided vehicle throughout a warehouse. Across five consecutive lab sessions, teams represented their algorithms using a flowchart, completing four iterations of their initial flowchart. 24 flowcharts were open coded for evidence of four computational thinking facets: decomposition, abstraction, algorithms, and debugging. Our results suggest that students' initial flowcharts focused on decomposing the problem and abstracting aspects that teams initially found to be more relevant. After each iteration, teams refined their flowcharts using pattern recognition, algorithm design, efficiency, and debugging. The teams would benefit from having more feedback about their understanding of the problem, the relevant physics concepts, and the logic and efficiency of the flowcharts. materials, resources and tools familiar to students, developing a prototype that may be a product or a process, generating multiple solutions, and engaging in teamwork. Integration of CT. CT tasks consisted of working with Jupyter Notebooks hosted by GoogleColab and creating flowcharts to document their algorithms. Apart from being free for anyone with a Google account, these Notebooks combine executable code and rich text in a single document. These are particularly useful for running Python codes, typing equations in Latex, uploading images and CSV files, performing data analysis, creating, and sharing files without having to download or install anything. Students were not expected to have prior programming experience, as the focus of the CT tasks were on applying physics concepts to edit and modify existing code relevant to the physical concept of the lab. Carefully designed scaffolds were provided for the students to facilitate learning elements of programming in the context of the laboratory experiment.Integration of scientific inquiry. The physics tasks consisted of hands-on activities using PASCO equipment and PASCO Capstone software, which are aligned with the three principles defined by course textbook (i.e.,...

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Holistic Assessment of Computational Thinking for Undergraduate

Cited by 5 publications

References 10 publications

A Pilot Study of an Instrument to Assess Undergraduates’ Computational thinking Proficiency

A Pilot Study of an Instrument to Assess Undergraduates’ Computational thinking Proficiency

Computational thinking in the context of higher education: Analytical review

Promoting Computational Thinking in Integrated Engineering Design and Physics Labs

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