An Item Response Theory Analysis of Algorithms and Programming Concepts in App Inventor Projects

Alves, Nathalia da Cruz; Wangenheim, Christiane Gresse von; Hauck, Jean Carlo Rossa; Borgatto, Adriano Ferreti

doi:10.5753/educomp.2021.14466

Cited by 3 publications

(8 citation statements)

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“…Table 3: CodeMaster rubric for assessing algorithms and programming based on the analysis of App Inventor projects (Alves et al, 2021). In general, most items were well estimated, with slope (a) parameter values above 1 (Table 3).…”

Section: Discussionmentioning

confidence: 99%

“…Figure 11: Frequency of the performance level score for each item (Alves et al, 2021). RBIE v.29 -2021 1392…”

Section: Difficult Itemsmentioning

confidence: 99%

“…Yet, so far, no research focusing on the analysis of the difficulty of concepts specifically concerning the block-based programming environment App Inventor considering also practical limitations, such as measurement errors, has been found. Therefore, aiming at understanding the difficulty related to different concepts, we performed an analysis of the 'demonstrated difficulty' in App Inventor projects as part of earlier research (Alves et al, 2021). We analyzed algorithms & programming items based on the CodeMaster rubric (Alves et al, 2020a;Gresse von Wangenheim et al, 2018) by extracting them automatically from the code of App Inventor projects and, adopting IRT, we obtained first results on the 'demonstrated difficulty' of the concepts application and their distribution among the App Inventor projects (Alves et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

“…Therefore, aiming at understanding the difficulty related to different concepts, we performed an analysis of the 'demonstrated difficulty' in App Inventor projects as part of earlier research (Alves et al, 2021). We analyzed algorithms & programming items based on the CodeMaster rubric (Alves et al, 2020a;Gresse von Wangenheim et al, 2018) by extracting them automatically from the code of App Inventor projects and, adopting IRT, we obtained first results on the 'demonstrated difficulty' of the concepts application and their distribution among the App Inventor projects (Alves et al, 2021). The objective of this article is to further detail this analysis and the interpretation of the results.…”

Section: Introductionmentioning

confidence: 99%

“…Figure8: Wright map of the algorithms and programming items in App Inventor projects(Alves et al, 2021).…”

mentioning

confidence: 99%

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A Detailed Item Response Theory Analysis of Algorithms and Programming Concepts in App Inventor Projects

Alves

Wangenheim

Hauck

et al. 2021

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Teaching computing in K-12 is often introduced focusing on algorithms and programming concepts using block-based programming environments, such as App Inventor. Yet, learning programming is a complex process and novices struggle with several difficulties. Thus, to be effective, instructional units need to be designed regarding not only the content but also its sequencing taking into consideration difficulties related to the concepts and the idiosyncrasies of programming environments. Such systematic sequencing can be based on large-scale project analyses by regarding the volition, incentive, and opportunity of students to apply the relevant program constructs as latent psychometric constructs using Item Response Theory to obtain quantitative ‘difficulty’ estimates for each concept. Therefore, this article presents the results of a large-scale data-driven analysis of the demonstrated use in practice of algorithms and programming concepts in App Inventor. Based on a dataset of more than 88,000 App Inventor projects assessed automatically with the CodeMaster rubric, we perform an analysis using Item Response Theory. The results demonstrate that the easiness of some concepts can be explained by their inherent characteristics, but also due to the characteristics of App Inventor as a programming environment. These results can help teachers, instructional and curriculum designers in the sequencing, scaffolding, and assessment design of programming education in K-12.

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Section: Discussionmentioning

confidence: 99%

“…Figure 11: Frequency of the performance level score for each item (Alves et al, 2021). RBIE v.29 -2021 1392…”

Section: Difficult Itemsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

“…Figure8: Wright map of the algorithms and programming items in App Inventor projects(Alves et al, 2021).…”

mentioning

confidence: 99%

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A Detailed Item Response Theory Analysis of Algorithms and Programming Concepts in App Inventor Projects

Alves

Wangenheim

Hauck

et al. 2021

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How Multidimensional is Computational Thinking Competency? A Bi-Factor Model of the Computational Thinking Challenge

Lai

Ellefson

2022

Journal of Educational Computing Research

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Computational thinking (CT) is an emerging and multifaceted competence important to the computing era. However, despite the growing consensus that CT is a competence domain, its theoretical and empirical account remain scarce in the current literature. To address this issue, rigorous psychometric evaluation procedures were adopted to investigate the structure of CT competency, as measured by Computational Thinking Challenge (Lai, 2021a), in a large sample of 1,130 British secondary school students ( M age = 14.14 years, SD age = 1.45). Based on model comparison from an exploratory multidimensional item response theory approach, the results supported the multidimensional operationalization of CT competency. A confirmatory bi-factor item response theory model further suggested CT competency is comprised of a general CT competency factor and two specific factors for programming and non-programming problem-solving. Despite the multidimensionality, the common variance is largely explained by a primary general factor of CT competency, thus the use of a single scale score is recommended. Psychometric evaluation from the bi-factor model indicated good psychometric properties of the assessment tool. Overall, the bi-factor model provides a useful approach to investigating CT competency and serves as a robust test validation tool.

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Review on the teaching of programming and computational thinking in the world

Belmar

2022

Front. Comput. Sci.

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Recent studies suggest that computational thinking, composed of the skills of abstraction, decomposition, algorithmization, debugging, and problem-solving, is the fundamental skill for scientific, technological, and economic development for the twenty-first century. However, this diagnosis that is unveiled in rich countries remains nebulous for poor countries. The problem is that education in computational thinking is fundamental for countries to insert themselves in the international arena in an advantageous way and thus achieve the welfare goals for the population of each country. The objective of this research was to make a bibliographic review that shows the state of the art in the teaching of computer programming and computational thinking in the 5 continents. In the review, the advances in the countries of Europe, North America, Oceania, and Asia were observed, whereas in Latin America and Africa, the advances are still basic in some countries and non-existent in others. This review is based on Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA). The main search terms were “Computational thinking” and “Teaching computer programming.” The search was performed in the ACM, Conference on Computational Thinking Education (Hong-Kong), Google Scholar, WOS, and SCOPUS databases, from October until December 2020, whose publication year was from 2016 onward. One of the main results found is that the teaching of computational thinking in England was implemented in schools in 2014; in Germany, it has been implemented since 2016 at a transversal level in universities; in South Korea, China, and Taiwan, it has been implemented since 2016. However, in Latin America and Africa governments, the subject is still not considered.

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An Item Response Theory Analysis of Algorithms and Programming Concepts in App Inventor Projects

Cited by 3 publications

References 37 publications

A Detailed Item Response Theory Analysis of Algorithms and Programming Concepts in App Inventor Projects

A Detailed Item Response Theory Analysis of Algorithms and Programming Concepts in App Inventor Projects

How Multidimensional is Computational Thinking Competency? A Bi-Factor Model of the Computational Thinking Challenge

Review on the teaching of programming and computational thinking in the world

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