Supporting all learners in school-wide computational thinking: A cross-case qualitative analysis

Israel, Maya; Pearson, Jamie N.; Tapia, Tanya; Wherfel, Quentin M.; Reese, George C.

doi:10.1016/j.compedu.2014.11.022

Cited by 229 publications

(144 citation statements)

References 23 publications

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“…However, based on the findings of the current study, majority of the studies on CT in the literature concentrated on education and technology. Furthermore, study findings demonstrated that CT was mostly discussed based on computer technologies (Israel et al, 2015;Kim, Kim, & Kim, 2013;Pellas & Peroutseas, 2016). It was considered that this finding was due to the low level of perception of the significance of CT in other fields.…”

Section: Conclusion and Recommendations For Future Researchmentioning

confidence: 82%

“…Accordingly, it was observed that several topics such as programming instruction (Denner, Werner, Campe, & Ortiz, 2014;Pellas & Peroutseas, 2016), computer software (Haseski, İlic, & Tugtekin, 2017;Tahy, 2016;Weintrop, Holbert, Horn, & Wilensky, 2016) and robots (Berland & Wilensky, 2015;Bers, 2010;Kafai & Burke, 2013) were investigated with respect to CT. Furthermore, there are also studies in the literature on the integration of CT to educational contexts (Israel, Pearson, Tapia, Wherfel, & Reese, 2015;Olabe, Basogain, & Basogain, 2015) and the design of CT-oriented curricula (Bers, Flannery, Kazakoff & Sullivan, 2014;Manson & Olsen, 2010). Additionally, it was observed that different methodologies were used up to the experimental design from the literature review, and qualitative and quantitative data collection techniques were used on several sample groups (Denning, 2012;Farris & Sengupta, 2016;Pellas & Peroutseas, 2016).…”

Section: Introductionmentioning

confidence: 99%

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Publication Trends Over 10 Years of Computational Thinking Research

İliç¹,

Haseski²,

Tuğtekin³

2018

CONT ED TECHNOLOGY

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The current study aimed to review studies on computational thinking (CT) indexed in Web of Science (WOS) and ERIC databases. A thorough search in electronic databases revealed 96 studies on computational thinking which were published between 2006 and 2016. Studies were exposed to a quantitative content analysis through using an article control form developed by the researchers. Studies were summarized under several themes including the research purpose, design, methodology, sampling characteristics, data analysis, and main findings. The findings were reported using descriptive statistics to see the trends. It was observed that there was an increase in the number of CT studies in recent years, and these were mainly conducted in the field of computer sciences. In addition, CT studies were mostly published in journals in the field of Education and Instructional Technologies. Theoretical paradigm and literature review design were preferred more in previous studies. The most commonly used sampling method was the purposive sampling. It was also revealed that samples of previous CT studies were generally pre-college students. Written data collection tools and quantitative analysis were mostly used in reviewed papers. Findings mainly focused on CT skills. Based on current findings, recommendations and implications for further researches were provided.

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Section: Conclusion and Recommendations For Future Researchmentioning

confidence: 82%

Section: Introductionmentioning

confidence: 99%

Publication Trends Over 10 Years of Computational Thinking Research

İliç¹,

Haseski²,

Tuğtekin³

2018

CONT ED TECHNOLOGY

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“…Higher attaining pupils providing peer support to classmates may be an opportunity to address these issues. This is a particularly key focus as little previous research has focused on designing and delivering similar interventions for a diverse group of pupils, such as those found in a typical primary classroom (Israel et al 2015).…”

Section: Outcomes Of Preliminary Researchmentioning

confidence: 99%

Bridging Primary Programming and Mathematics: Some Findings of Design Research in England

Benton

Hoyles

Kalaš

et al. 2017

Digit Exp Math Educ

145

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In this paper we present the background, aims and methodology of the ScratchMaths (SM) project, which has designed curriculum materials and professional development (PD) to support mathematical learning through programming for pupils aged between 9 and 11 years. The project was framed by the particular context of computing in the English education system alongside the long history of research and development in programming and mathematics. In this paper, we present a Bframework for action^(diSessa and Cobb, Journal of the Learning Sciences, 13, 77-103, 2004) following design research that looked to develop an evidence-based curriculum intervention around carefully chosen mathematical and computational concepts. As a first step in teasing out factors for successful implementation and addressing any gap between our design intentions and teacher delivery, we focus on two key foundational concepts within the SM curriculum: the concept of algorithm and of 360°total turn. We found that our intervention as a whole enabled teachers with different backgrounds and Digit Exp Math Educ (2017) 3:115-138 DOI 10.1007/s40751-017-0028-x The research reported in this paper forms part of a larger project, the ScratchMaths project 2014-17 funded by the Educational Endowment Foundation. The project is being independently evaluated following a randomized control trial model involving over 100 primary schools across England. Department of Informatics Education, Comenius University, Bratislava, Slovakia levels of confidence to tailor the delivery of the SM in ways that can make these challenging concepts more accessible for both themselves and their pupils.

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“…Researchers have established strong connections between teacher efficacy and teacher behaviours that foster student achievement (Goddard, Hoy & Hoy, 2000;Guo et al, 2010;Ross, HogaboamGray, & Hannay, 2001). If teachers do not feel efficacious for teaching computational thinking, students may have negative experiences in learning the concept (Israel et al, 2015). In addition, there is no widespread agreement about strategies for teaching and assessing the level of computational thinking development in students (Brennan & Resnick, 2012).…”

Section: Introductionmentioning

confidence: 99%