@article{Braun2022Compu-58616,
  year={2022},
  doi={10.3389/feduc.2022.937048},
  title={Computational literacy in science education : A systematic review},
  volume={7},
  journal={Frontiers in Education},
  author={Braun, Daniel and Huwer, Johannes},
  note={Article Number: 937048}
}

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    <dc:creator>Braun, Daniel</dc:creator>
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    <dcterms:title>Computational literacy in science education : A systematic review</dcterms:title>
    <dcterms:abstract xml:lang="eng">Computational literacy is one of the 21st century skills–students must therefore acquire the appropriate competencies in computer science to meet the demands of 21st century society. To achieve this, teachers must be adequately trained. Furthermore, this also means that introductory computer science education concepts must also be integrated into the training of (pre- service) science teachers and anchored in the curriculum. This is particularly important because many scientific professions or research can no longer be done without basic computer knowledge and computational literacy. The central approach to educating future teachers is the university course of study. This paper aims to systematically provide an insight into which scientifically relevant publications address this issue. The essential criterion in this review is the restriction on science education or more general science, technology, engineering, and mathematics (STEM) education in schools or universities. Equally important is the specification that computational literacy (informatics competencies, information literacy, computer literacy, or computational thinking) are purposefully taught or trained. Only publications in the Web of Science database were included for quality assurance. This paper investigates to what extent scientifically valid research or knowledge is available at this junction, i.e., computational literacy in science education. Thereby, we distinguish between different approaches, such as effect studies on individual aspects, isolated practical contributions with a pronounced trial-and-error character, or systematic or model-based considerations in quantitative and qualitative studies. The results show common aspects, prominent trends, and promising approaches. However, possibly existing (subject-) didactic concerns should be considered in more detail and the dual perspective role of the students as future teachers. In addition to learning basic computer skills, the ability to teach them is also essential so that the scientific education of the students can benefit from them to the required extent.</dcterms:abstract>
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    <dc:contributor>Huwer, Johannes</dc:contributor>
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