Learning to program using immersive approaches: A case study learning SAS®, IBM Bluemix and Watson Analytics

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Self, Richard 2016. Learning to program using immersive approaches: A case study learning SAS®, IBM Bluemix and Watson Analytics. Verlag der Technischen Universität Graz. https://doi.org/10.3217/978-3-85125-472-3
AuthorsSelf, Richard
Abstract

Learning to program is an activity which needs the learner to develop a range of new skills. Traditionally, this has been achieved in Universities by a presenting a series of structured lectures and tutorials covering the syntax and grammar of the language. This approach often leads to disengagement by many of the weaker students. It is becoming clear that this may not be the most effective approach in the twenty first century as a result of the continuous development of software packages which leads to the need to continually revise the teaching materials. In addition, modern millennial students demand engaging modes of learning that al-so prepare them for employment. This paper evaluates an approach which pro-vides a directed, immersive learning approach that mirrors the real world of em-ployment, develops both the requisite technical skills together with the fundamen-tal soft skills necessary for employment and prepares the students for lifelong learning and development and maintenance of new skills and languages. It also provides an intensely engaging environment that allows students to demonstrate the wide range of technical and soft skills that are necessary for a successful ca-reer. This approach also leads to high levels of achievement from the students and reduces stress levels in the academics leading the courses. The approach should be applicable to most STEM subjects which require the use of specialist software packages.

KeywordsTechnical skills; Soft skills; Engaging learning
Year2016
JournalProceedings of the iLRN 2016 Santa Barbara
PublisherVerlag der Technischen Universität Graz
Digital Object Identifier (DOI)https://doi.org/10.3217/978-3-85125-472-3
Web address (URL)http://hdl.handle.net/10545/620927
hdl:10545/620927
ISBN9783319417684
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Publication dates28 Jun 2016
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Deposited21 Nov 2016, 12:33
SeriesSpringer CCIS
7899
ContributorsUniversity of Derby
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