Mixed Methods for the Assessment and Incorporation of Computational Thinking in K-12 and Higher Education

Weese, Joshua Levi

doi:10.1145/2960310.2960347

Cited by 16 publications

(8 citation statements)

References 5 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“… Algo.Rhythm [65]  Alice [7,16,29,60,73,82,109,115,116,117,118,119]  Ardublock [120]  Arduino [13,42,65,66]  Bebras [121,122]  Binary toy [123]  BingBee [124]  Blockly [63,71,125,126,127,128]  Bunny Bright [123]  CargoBot [129]  CHERP [15,24,103,104,130]  Code Bits [131]  CTArcade [132]  CTSiM [27,133,134,135]  CyberPLAYce [66]  DigitMile [136]  Dragon Architect [126]  Drawing Machine Model [37]  Entry [137]  Escape Machine [138,139]  Game ...…”

Section: Other Toolsmentioning

confidence: 99%

Computational Thinking in Secondary Education: Where does it fit? A systematic literary review

Lockwood

Mooney

2018

IJCSES

113

View full text Add to dashboard Cite

Computational Thinking (CT) has been described as an essential skill which everyone should learn and can therefore include in their skill set. Seymour Papert [1] is credited as concretising Computational Thinking in 1980 but since Wing [2] popularised the term in 2006 and brought it to the international community's attention, more and more research has been conducted on CT in education. The aim of this systematic literary review is to give educators and education researchers an overview of what work has been carried out in the domain, as well as potential gaps and opportunities that still exist.

show abstract

Section: Other Toolsmentioning

confidence: 99%

Computational Thinking in Secondary Education: Where does it fit? A systematic literary review

Lockwood

Mooney

2018

IJCSES

113

View full text Add to dashboard Cite

show abstract

“…Talking about the reconnection of CT and problem solving, there is some confusion between these two concepts, as one is considered identical or overlapping with the other [31]. This has something to do with STEM that explicitly solves real-world problems.…”

Section: Stem and Ct Relationshipmentioning

confidence: 99%

STEM: Its Potential in Developing Students' Computational Thinking

Pratama,

Widjajanti

2024

KSS

View full text Add to dashboard Cite

Computational thinking skills are a person’s ability to solve problems with several passed processes. The process is recognizing patterns, decomposing patterns, compiling algorithms, making models, and doing abstractions. This ability is essential for students to master understanding aspects of computational problems. It also helps students evaluate the suitability of computational techniques to solve the problem. In addition, this computational thinking ability can also help students understand the limitations and strengths of computing techniques, apply or adapt computing tools/techniques to new uses, recognize opportunities to use computing in new ways, and apply computational strategies. The STEM approach, is learning that integrates science, technology, engineering, and mathematics to develop creativity in solving problems. The transformation of the educational process in the current era that requires a high level of technology makes STEM one of the keys to progress and innovation in developing human competence. Based on a study of more than 30 articles and research results related to the effect of STEM on student learning outcomes, we can conclude that learning using STEM has the potential to develop students’ computational thinking skills. This article discusses how, theoretically, we can acquire computational thinking skills through education with a STEM approach. Keywords: STEM, developing students’, computational thingking

show abstract

“…Measuring attitude related to CT is required because there does not yet exist any widely adopted standardized assessments (Haseski et al, 2018;Sondakh et al, 2020a;Weese, 2016). As a result, it's unsurprising that CT evaluation continues to be a significant weakness in this sector.…”

Section: Literature Reviewmentioning

confidence: 99%

Rasch Analysis for Disposition Levels of Computational Thinking Instrument Among Secondary School Students

Osman

Sovey

Matore

2022

EURASIA J Math Sci Tech Ed

View full text Add to dashboard Cite

Computational thinking is a strategy of thinking to tackle complex problems. There is a paucity of conceptualization and instruments that cogitate on computational thinking disposition and attitudes. This study reacts to these constraints by establishing an instrument to test computational thinking related dispositions and attitudes. The computational thinking disposition Instrument is an indicator of student's disposition towards computational thinking in daily life. The objective of this study is to investigate the psychometric features using Rasch model. Data of 535 form four computer science students in Malaysia were obtained. Instrument consists of 55 core measures in three domains: cognitive, affective and conative. The Rasch analysis indicated good psychometric features of the instrument. In these three domains no items showed disordered thresholds and the reliability was good. As a result, the Rasch analysis provides basis for cautious optimism permitting more detailed and finer level investigation of the instrument.

show abstract

Mixed Methods for the Assessment and Incorporation of Computational Thinking in K-12 and Higher Education

Cited by 16 publications

References 5 publications

Computational Thinking in Secondary Education: Where does it fit? A systematic literary review

Computational Thinking in Secondary Education: Where does it fit? A systematic literary review

STEM: Its Potential in Developing Students' Computational Thinking

Rasch Analysis for Disposition Levels of Computational Thinking Instrument Among Secondary School Students

Contact Info

Product

Resources

About