Computational thinking and online learning: A systematic literature review

This paper introduces research concerned with investigating how Computational Thinking and online learning can be successfully married to help empower secondary teachers to teach this subject. To aid this research, a systematic literature review was undertaken to investigate what is currently known in the academic literature on where Computational Thinking and online learning intersect. This paper presents the findings of this systematic literature review. It outlines the methodology used and presents the current data available in the literature on how Computational Thinking is taught online. Using a systematic process eight hundred articles were initially identified and then subsequently narrowed down to forty papers. These papers were analysed to answer the following two questions: 1. What are the current pedagogical approaches to teaching Computational Thinking online? 2. What were the categories of online learning observed in the teaching of Computational Thinking? Our findings show that a wide range of pedagogical approaches are used to teach Computational Thinking online, with the constructivist theory of learning being the most popular. The tools used to teach Computational Thinking were also varied, video game design, playing video games, competitions, and unplugged activities, to name a few. A significant finding was the dependency between the tool used and the definition of the term Computational Thinking. Computational Thinking lacks consensus on a definition, and thus the definition stated in the literature changed depending on the tool. By considering a significant body of research up to the present, our findings contribute to teachers, researchers and policy makers understanding of how computational thinking may be taught online at second level

Bringing Computational Thinking to Nonengineering Students through a Capstone Course

Although the concept of computational thinking has flourished, little research has explored how to integrate various elements of computational thinking into an undergraduate classroom setting. Clarifying core concepts of computational thinking and providing empirical cases that apply computational thinking practices into a real-world educational setting is crucial to the success of software engineering education. In this article, we describe the development of a curriculum for a social innovation capstone course, using core concepts and elements of computational thinking. The course was designed for undergraduate students of a liberal arts college at a university in Korea. Students were asked to define a social problem and introduced to the core concepts and processes of computational thinking aided by Arduino and Raspberry Pi programming environments. After building a business model, they implemented a working prototype for their proposed solution. We document class project outcomes and student feedback to demonstrate the effectiveness of the approach

Bringing Computational Thinking to Nonengineering Students through a Capstone Course

Although the concept of computational thinking has flourished, little research has explored how to integrate various elements of computational thinking into an undergraduate classroom setting. Clarifying core concepts of computational thinking and providing empirical cases that apply computational thinking practices into a real-world educational setting is crucial to the success of software engineering education. In this article, we describe the development of a curriculum for a social innovation capstone course, using core concepts and elements of computational thinking. The course was designed for undergraduate students of a liberal arts college at a university in Korea. Students were asked to define a social problem and introduced to the core concepts and processes of computational thinking aided by Arduino and Raspberry Pi programming environments. After building a business model, they implemented a working prototype for their proposed solution. We document class project outcomes and student feedback to demonstrate the effectiveness of the approach

Computational Thinking Self-Efficacy in High School Latin Language Learning

Research suggests that computational thinking is a necessary skill exercised in STEM courses, non-STEM fields, and in everyday life. However, very little research has investigated the potential transfer of computational thinking self-efficacy available through classical Latin courses. This causal comparative study contrasted the computational thinking self-efficacy of computer science students with no exposure to Latin to computer science students with exposure to Latin at a Memphis all-boy high school. The independent variables were Latin language learning experience, i.e., up to 6 years total of Latin language learning (n = 33), versus 0 years of Latin language learning experience (n = 20). Additional data on the number of years enrolled in other foreign languages was collected. The dependent variable was mean scores of items found on a computational thinking and problem solving self-efficacy scale. This instrument uses a Likert scale to measure students self-efficacy in nine computational thinking components including algorithmic thinking; abstraction; problem decomposition; data collection, representation, and analysis; parallelization; control flow; incremental and iterative; testing and debugging; and questioning. Conducting this research addressed the question of whether the computational thinking skills present in Latin can transfer to a students computational thinking self-efficacy which may affect STEM/computer science course achievement. To test the null hypothesis that having a Latin language learning yields no significant influence on computer science students self-efficacy in computational thinking and problem solving, a multivariate analysis of variance (MANOVA) test was utilized for this causal-comparative study. To test the null hypotheses that having a Latin language learning yields no significant influence on computer science students abstraction, problem decomposition, data, parallelization, control flow, incremental and iterative, testing and debugging, and questioning skills self-efficacy, a separate ANOVA test were run for each computational thinking skill component.The data did not meet of the necessary assumptions for a MANOVA test. The sample size for the non-Latin group was a concern at n = 20. The means from the descriptive statistics show that the non-Latin group outscored the Latin group in most of the computational thinking skills. Pillais trace statistic from the MANOVA test showed no statistical significance in the computational thinking and problem solving scale. The individual results from the ANOVA tests showed no statistical significance for any of the nine subscales

Programmering som verktøy for å lære computational thinking - En kvalitativ studie av elevers resonnement i problemløsning med programmering som verktøy.

Samfunnets stadige endringer er katalysert av teknologiens utvikling og fremskritt. Samfunnet digitaliseres ytterligere og digitale verktøy er blitt en stor del av menneskets hverdag. Dette har endret kompetansebehovet for fremtiden. For å dekke morgendagens kompetansebehov og holde tritt med samfunnets digitale og teknologiske utvikling har Utdanningsdirektoratet (2020) gjennom kunnskapsløftet 2020 implementert programmering i matematikkfaget. I lys av dette samt egen erfaring og motivasjon er følgende problemstilling utformet: Ved hvilke kjennetegn av computational thinking resonnerer elever kreativt i problemløsning med tekstbasert programmering som verktøy? Problemstillingen har blitt belyst gjennom en kvalitativ tilnærming med deltakende observasjon som metode. Studiens datamaterialet består av notater og lyd- og skjermopptak av elevers problemløsning med programmering som verktøy. Datamaterialet er analysert ved hjelp av et sammensatt rammeverk bestående av Lithner (2006) rammeverk for analysering av imitativ og kreativ resonnement og Shute et al. (2017) sitt rammeverk for computational thinking. Analysen viser at Shute et al. (2017) sine komponenter av computational thinking er til stede i elevers resonnement i problemløsning med programmering som verktøy. Komponentene som ble observert flest ganger var algoritmer, feilsøking og dekomposisjon. Videre viser analysen at resonnementene tilknyttet komponentene var både kreative og imitative. Studiens resultater antyder at computational thinking gjennom programmering kan bidra til å øke elevers matematiske kreativitet, og ha en positiv effekt på elevers matematiske kunnskap. Det ble også avdekket et behov for å øke elevenes feilsøkingsevner i programmering

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

Computational Thinking (CT) has been described as an essential skill which everyone should learn and can therefore include in their skill set. Seymour Papert is credited as concretising Computational Thinking in 1980 but since Wing 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. Overall it was found in this review that, although there is a lot of work currently being done around the world in many different educational contexts, the work relating to CT is still in its infancy. Along with the need to create an agreed-upon definition of CT lots of countries are still in the process of, or have not yet started, introducing CT into curriculums in all levels of education. It was also found that Computer Science/Computing, which could be the most obvious place to teach CT, has yet to become a mainstream subject in some countries, although this is improving. Of encouragement to educators is the wealth of tools and resources being developed to help teach CT as well as more and more work relating to curriculum development. For those teachers looking to incorporate CT into their schools or classes then there are bountiful options which include programming, hands-on exercises and more. The need for more detailed lesson plans and curriculum structure however, is something that could be of benefit to teachers

Desenvolvimento de um modelo de avaliação de criatividade no ensino da computação na educação básica

TCC(graduação) - Universidade Federal de Santa Catarina. Centro Tecnológico. Sistemas de Informação.O século XXI requer novas habilidades que são cada vez mais valorizadas para um desenvolvimento pessoal e no mercado de trabalho, conhecidas como habilidades do século XXI. Faz parte dessas habilidades a criatividade, que aborda as dimensões de fluência, flexibilidade, originalidade e elaboração. Portanto, a importância do incentivo da criatividade na Educação Básica é cada vez mais concreta. Uma das formas de incentivar o desenvolvimento dessa habilidade é a inserção do ensino da computação já na escola. Assim, no contexto educacional faz parte a avaliação dessa habilidade relacionada com a computação. Atualmente já existem vários modelos de avaliação de criatividade, abordando dimensões diferentes, evidenciando uma falta de consenso em como avaliar. Partindo dessa premissa, foi desenvolvido o modelo de avaliação SCORE a fim de avaliar criatividade no ensino da computação na Educação Básica, visto que não existem modelos específicos para este meio. O instrumento decompõe a criatividade em oito fatores: “personalidade criatividade e curiosidade”, “amplia habilidades e conhecimentos”, “conexão”, “ousadia”, “originalidade”, “fluência”, “flexibilidade” e “elaboração”. Os resultados da avaliação, com base em uma amostra de 76 estudantes da Educação Básica, indicam uma excelente confiabilidade interna (alfa de Cronbach = 0,961). A análise da validade do modelo também apresentou ótimos resultados. Por meio da análise fatorial exploratória foram observados apenas três itens com carga fatorial abaixo do ponto de corte, sugerindo a exclusão desses itens. A análise da amostra total (n = 197), com respostas do ensino superior, confirma os resultados obtidos na análise utilizando somente os dados da Educação Básica. Dessa forma, espera-se obter um modelo capaz de avaliar a criatividade com o ensino da computação e aumentar o interesse em introduzi-lo em mais escolas da Educação Básica no Brasil

The machine in the ghost: an educational design research study that explores the teaching of computational thinking to Irish second-level students

Computational Thinking is a problem-solving process that draws on concepts fundamental to Computer Science. These concepts can support problem-solving across many disciplines. The Digital Strategy for Schools (2015-2020) describes the Irish Government's intention to give every student in compulsory education the opportunity to learn Computational Thinking. This research is an Educational Design Research study underpinned by a pragmatic approach and concerned with Computational Thinking. It aims to answer the following question: what are the characteristics of a practical, engaging, effective, high quality, and low threshold course for both the learning and teaching of Computational Thinking to Irish post-primary teachers and students? This study also aims to validate whether unplugged activities can be successfully used to teach Computational Thinking. This research study had three phases: preliminary analysis, prototype, and semi- summative. It was conducted in six schools with eleven teachers, four content experts, and over four hundred and forty six students. Data was gathered using various means: interviews, focus groups, teacher diaries, students' questionnaires, and students' artefacts. The analytic approach was mixed; it involved content and thematic analysis as well as descriptive statistics. This study found that the following characteristics: activities, demonstration, application, pre-activation, transparency, theory, exemplification, and reflection (ADAPTTER) gave rise to a practical, engaging, effective, high quality, and low threshold Computational Thinking course. This study validated the use of unplugged activities as a pedagogy for teaching Computational Thinking