Computational Thinking Interventions in Higher Education

Jong, Imke de; Jeuring, Johan

doi:10.1145/3428029.3428055

Cited by 24 publications

(9 citation statements)

References 60 publications

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“…Furthermore, an updated search on 2022-02-02 in all three databases with the same procedure resulted in one more eligible review. In total, we included a total number of 11 reviews (Denning and Tedre, 2019;Lyon and Magana, 2020;Tang et al, 2020;Selby and Woollard, 2014;Ezeamuzie and Leung, 2022;Lu et al, 2022;de Araujo et al, 2016;Haseski and Ilic, 2019;Vinu Varghese and Renumol, 2021;Poulakis and Politis, 2021;de Jong and Jeuring, 2020) for analysis in this work.…”

Section: Screening and Eligibility Checkingmentioning

confidence: 99%

“…Regarding the method applied for studying assessed constructs, as presented in Table 5, by applying (a) Sullivan and Heffernan (2016)'s categories of first-order and second-order learning outcomes regarding the relationship between CT and other subject domains and (b) McMillan ( 2013)'s categories of cognitive constructs and non-cognitive dispositions and skills, Tang et al (2020) examined the relationship between the assessed constructs and the subject domain. For the remaining set of reviews, Cutumisu et al (2019) and Lu et al (2022) utilized an existing CT framework as reference to identify the assessed constructs, while the others clustered and synthesized similar constructs emerged in their investigation (de Araujo et al, 2016;Haseski and Ilic, 2019;Poulakis and Politis, 2021;de Jong and Jeuring, 2020;Taslibeyaz et al, 2020).…”

Section: Rq2a -Characteristics Of the Assessed Constructsmentioning

confidence: 99%

“…de Jong and Jeuring (2020) presented a list of academic disciplines, while the others presented either information about the coursework within a study program, or a categorization of the coursework / the study program. Though there are various schemes for the categorizing the academic domain or the coursework, the reviews mainly distinguished the academic background according to the relevance of the study program to CS, Science, Technology, Engineering and Technology (Tang et al, 2020;Ezeamuzie and Leung, 2022;de Jong and Jeuring, 2020;Taslibeyaz et al, 2020). Furthermore, all reviews revealed that most of the contributions on CT were within the scope of STEM disciplines, CS and Programming Education, with an increase in the number of studies regarding Non-STEM and non-CS majors and subjects in recent years.…”

Section: Rq2c -Characteristics Of the Assessment Contextmentioning

confidence: 99%

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A Systematic Umbrella Review on Computational Thinking Assessment in Higher Education

Zhang,

Aivaloglou,

Specht

2024

European Journal of STEM Education

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Computational Thinking (CT) is considered a core 21st century digital skill. The aspect of assessment is crucial and knowing what, who, when, how, and where to assess is important for assessment design. In this study, we conducted an umbrella review to gain insights regarding CT assessment in higher education. In total, we analyzed 11 reviews, focusing on: (1) bibliographical and methodological characteristics of the reviews; (2) aspects relevant of assessment design, including a) assessed constructs, b) applied assessment methodologies, and c) assessment contexts. Our findings suggest an increased attention on this topic. However, hardly any reviews reasoned the selection of their review methodology, and most of the reviews did not thoroughly examine existing reviews. Regarding assessment design aspects, most reviews did not confine their scope to higher education; however, findings on interventions and educational settings show commonalities. We identified 120 unique assessed constructs and around 10 types of assessment methods. Though a combined use of distinct assessment methods is suggested in reviews, guidelines for appropriate assessment design are yet to be constructed. Based on the findings, we argue that it is necessary to explore different combinations of assessment design in various contexts to construct assessment guidelines.

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Section: Screening and Eligibility Checkingmentioning

confidence: 99%

Section: Rq2a -Characteristics Of the Assessed Constructsmentioning

confidence: 99%

Section: Rq2c -Characteristics Of the Assessment Contextmentioning

confidence: 99%

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A Systematic Umbrella Review on Computational Thinking Assessment in Higher Education

Zhang,

Aivaloglou,

Specht

2024

European Journal of STEM Education

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“…A study on CT assessment and coding for elementary school children was conducted by (Fang et al, 2022;Li et al, 2021;de Ruiter & Bers, 2021;Lai & Ellefson, 2022) carried out research on the CT competency structure using psychometric assessment and measurement. An overview study was done by (De Jong & Jeuring, 2020) to see CT interventions in the context of higher education. CT studies and computer programming are not emphasised for vocational students in Malaysia.…”

Section: Introductionmentioning

confidence: 99%

Coding and Computational Thinking Learning for Vocational Students: Issues and Challenges

Mohd Rosli,

Mohd Matore

2023

IJARBSS

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Coding is the act of writing code, whereas programming is the act of developing functional software or computer programs. A set of instructions or a set of rules expressed in a specific programming language are referred to as "computer code" in computer programming. Students pursuing certificates in vocational studies are now starting to learn about programming. At the lower secondary level, these students received preparation in computational thinking (CT). This concept paper identifies three primary problems with coding and computational thinking among vocational students: (i) CT's inadequate educational foundation; (ii) lack of interest in programming, and (iii) absence of measurement of CT literacy level in programming for vocational students. The uniqueness of this concept paper is in its ability to elaborate on coding challenges in programming and computational thinking abilities. The results of this study imply that screening should be done before bringing on new pupils. Attention should be taken to this article so that novice learners are better equipped to continue learning in a motivated way because they get the fundamentals of coding in programming. The aim of this research is to contribute to a better understanding of the problems and difficulties in teaching computational thinking and programming skills. Vocational colleges and Lead Trainers may engage collaboratively to create this proposed solution with the aim to provide interventions for students who are still novice to programming.

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“…Students have traditionally encountered difficulties and misconceptions on the concepts learned [22]. Along with the learning of programming, researchers and educators in higher education aim to improve student computational thinking (CT) skills using appropriate interventions [23] and approaches using games for teaching and learning, CT principles, and concepts [24].…”

Section: Introductionmentioning

confidence: 99%

A Guided Scratch Visual Execution Environment to Introduce Programming Concepts to CS1 Students

et al. 2021

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First-year computer science (CS1) university students traditionally have difficulties understanding how to program. This paper describes research introducing CS1 students to programming concepts using a Scratch programming language guided visual execution environment (VEE). The concepts addressed are those from an introductory programming course (sequences, variables, operators, conditionals, loops, and events and parallelism). The VEE guides novice students through programming concepts, explaining and guiding interactive exercises executed in Scratch by using metaphors and serious games. The objective of this study is, firstly, to investigate if a cohort of 124 CS1 students, from three distinct groups, studying at the same university, are able to improve their programming skills guided by the VEE. Secondly, is the improvement different for various programming concepts? All the CS1 students were taught the module by the same tutor in four 2-h sessions (8 h), and a qualitative research approach was adopted. The results show students significantly improved their programming knowledge, and this improvement is significant for all the programming concepts, although greater for certain concepts such as operators, conditionals, and loops than others. It also shows that students lacked initial knowledge of events and parallelism, though most had used Scratch during their high school years. The sequence concept was the most popular concept known to them. A collateral finding in this study is how the students’ previous knowledge and learning gaps affected grades they required to access and begin study at the university level.

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Computational Thinking Interventions in Higher Education

Cited by 24 publications

References 60 publications

A Systematic Umbrella Review on Computational Thinking Assessment in Higher Education

A Systematic Umbrella Review on Computational Thinking Assessment in Higher Education

Coding and Computational Thinking Learning for Vocational Students: Issues and Challenges

A Guided Scratch Visual Execution Environment to Introduce Programming Concepts to CS1 Students

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