Increasing Student Self-Efficacy in Computational Thinking via STEM Outreach Programs

Feldhausen, Russell; Weese, Joshua Levi; Bean, Nathan

doi:10.1145/3159450.3159593

Cited by 45 publications

(30 citation statements)

References 9 publications

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“…Prior programming experience is an important variable for CPSE (Mazman & Altun, 2013;Kittur, 2020). Effect of programming experience on self-efficacy was revealed, after four weeks of STEM-supported training (Feldhausen, Weese, & Bean, 2018) or for a period of algorithm and coding training (Mıhçı-Türker & Pala, 2020;Okal, Yıldırım, & Timur, 2020). Considering the situation that people think that computer programming is complex and difficult (Yükseltürk & Altıok, 2017), it is an expected result that students who did not take IT&S course before and therefore did never perform computer-programming performance would have lower CPSE perceptions.…”

Section: Discussion Of Findingsmentioning

confidence: 99%

Computational Thinking Skills, Programming Self-Efficacies and Programming Attitudes of the Students

Günbatar

2020

IJCSES

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The purpose of this research is to examine Computer Programming Attitude (CPA), Computer Programming Self-Efficacy (CPSE) and Computational Thinking (CT) skills of middle school students who took the Information Technologies & Software (IT&S) courses and those who did not, and make various analyses according to the relationships between these variables. As a result of the analysis, it was found that CPA and CPSE variables are significant predictors for CT skills, both students who took IT&S course and those who did not take have moderate CPSE, but students who took IT&S course have a statistically significantly higher CPSE. In addition, it was observed that both those who took IT&S course and those who did not have moderate CPA and did not differ statistically, and students who took IT&S course had a high level of CT, while those who did not take the course were moderate and statistically different. It was also found that students who took IT&S courses made cumulative progress in terms of CPSE, CPA and CT variables compared to those who did not. The obtained results are discussed within the framework of middle school IT & S course curriculum held in Turkey in 2018.

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Section: Discussion Of Findingsmentioning

confidence: 99%

Computational Thinking Skills, Programming Self-Efficacies and Programming Attitudes of the Students

Günbatar

2020

IJCSES

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“…In general most outreach programmes focus on students attending a college campus for hands-on practical workshops in different aspects of CS [13,14,16,21]. Typically workshops use interactive problems to engage students with mostly online tools.…”

Section: Outreach Methodologiesmentioning

confidence: 99%

“…A significant number of the programmes surveyed the students before and after [9,13,27]. The results were generally positive, with students feeling they were more aware of what CS involved and more confident to attempt programming and other CS related activities.…”

Section: Outreach Researchmentioning

confidence: 99%

Developing an Inclusive K-12 Outreach Model

Nolan

Faherty

Quille

et al. 2020

Proceedings of the 2020 ACM Conference on Innovation and Technology in Computer Science Education

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This paper outlines the longitudinal development of a K-12 outreach model, to promote Computer Science in Ireland. Over a three-year period, it has been piloted to just under 9700 K-12 students from almost every county in Ireland. The model consists of a two-hour camp that introduces students to a range of Computer Science topics: addressing computing perceptions, introduction to coding and exploration of computational thinking. The model incorporates on-site school delivery and is available at no cost to any interested school across Ireland. The pilot study so far collected over 3400 surveys (pre-and post-outreach delivery). Schools from all over Ireland self-selected to participate, including male only, female only and mixed schools. The no-cost nature of the model meant schools deemed "disadvantaged", to private fee-paying schools participated. Initial findings are very positive, including the balance of male and female participants, where in the 2017-18 academic year it was 56:44 and in 2019-20 (to date), it is 35:65 respectively. Once the model is validated and tweaked (based on survey data), the model will be published (open access) for other institutions to implement the model locally. In addition, the authors intend to link schools (that the team have worked with over the three years) with local institutions, thus developing a sustainable ecosystem for the program to continue. This paper describes the model structure and outlines early findings. CCS CONCEPTS • Social and professional topics → Computer science education.

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“…The quantitative research instrument was a questionnaire consisting of study demographics, questions on the level of knowledge, and self-confidence in computational thinking skills. The questionnaire formulated in this study refers to the questionnaire administered by the previous expert (Feldhausen, Weese, & Bean, 2018;Korkmaz, Çakir, & Özden, 2017;Yadav et al, 2014;Yağcı, 2019). Meanwhile, the qualitative research instruments refer to the questionnaire administered by Bower (2017).…”

Section: Methodsmentioning

confidence: 99%

Knowledge Level and Self-Confidence on The Computational Thinking Skills Among Science Teacher Candidates

Rahayu

Osman

2019

JIPFAlBiruni

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The trending topic in today's education is computational thinking skills which are used to help to solve complicated problems easier. This study aims to identify the level of knowledge and self-confidence of science teacher candidates (physics and biology) on computational thinking skills. The survey research design was used through a mixed-method approach by combining quantitative and qualitative approaches. The quantitative study involved 1016 randomly selected groups of science teachers whilein the qualitative study, eight science teachers were chosen based on the scores obtained from the quantitative study. The questionnaire was used as a quantitative data collecting technique to analyze descriptive statistics. Then, an interview was used as the qualitative data collecting technique and was analyzed through theme creation. The findings show that science teacher candidates have a high level of knowledge and self-confidence. The implication of this study is very important for teacher candidates because computational thinking can help to facilitate problems solving in everyday life. Teacher candidates need to be given knowledge and understanding of computational thinking skills, to have readiness and self-confidence in facing the challenges of the learning in the 21st-century

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Increasing Student Self-Efficacy in Computational Thinking via STEM Outreach Programs

Cited by 45 publications

References 9 publications

Computational Thinking Skills, Programming Self-Efficacies and Programming Attitudes of the Students

Computational Thinking Skills, Programming Self-Efficacies and Programming Attitudes of the Students

Developing an Inclusive K-12 Outreach Model

Knowledge Level and Self-Confidence on The Computational Thinking Skills Among Science Teacher Candidates

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