{"title":"Why I Do Not Talk About Computational Thinking in Journalism Classes: Sorry (Not Really Sorry)","authors":"Kayt Davies","doi":"10.1177/1326365x20970421","DOIUrl":null,"url":null,"abstract":"Paul Bradshaw nailed it a few years ago when he noted that despite calls as early as 2006 for newsrooms and their training grounds to change the way they think, ‘there is very little evidence of this being seriously addressed. Instead computational thinking is being taught earlier, to teenagers and younger children at school’ (Bradshaw, 2017, p. 1). This essay is a confession, a few excuses, but mainly an explanation why I, and other tertiary journalism educators like me, have not leapt at the opportunity to teach computational thinking and why you should not hate us for it. I remember trying to keep a poker face on, sitting around a table of respectable international colleagues, listening to one advocating passionately for teaching computational thinking to all journalism students. My inner monologue was howling, ‘OMG, No! Not more! My course is full to the brim and bursting’. I looked carefully at the faces around the table. Some were nodding. Others, like me, had tight brows and clenched jaws. We were in Paris at the World Journalism Education Congress in July 2019. The breakout group was the syndicate discussing the topic: ‘Teaching Data Journalism and Computational Skills’. Not a lot of love was shown in the discussion that followed for the idea of wheeling in a barrow-load of computational thinking. We broke it down and talked instead about quantitative literacy; we also talked about math aversion and my poker face dissolved. I am genuinely happy to talk to my students about their learnt number-phobia, experimental design and how to report statistics with confidence (Davies, 2019). Computational thinking felt like a bridge too far though, so I have been pondering why ever since.","PeriodicalId":43557,"journal":{"name":"Asia Pacific Media Educator","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1177/1326365x20970421","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Asia Pacific Media Educator","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1177/1326365x20970421","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"Social Sciences","Score":null,"Total":0}
引用次数: 0
Abstract
Paul Bradshaw nailed it a few years ago when he noted that despite calls as early as 2006 for newsrooms and their training grounds to change the way they think, ‘there is very little evidence of this being seriously addressed. Instead computational thinking is being taught earlier, to teenagers and younger children at school’ (Bradshaw, 2017, p. 1). This essay is a confession, a few excuses, but mainly an explanation why I, and other tertiary journalism educators like me, have not leapt at the opportunity to teach computational thinking and why you should not hate us for it. I remember trying to keep a poker face on, sitting around a table of respectable international colleagues, listening to one advocating passionately for teaching computational thinking to all journalism students. My inner monologue was howling, ‘OMG, No! Not more! My course is full to the brim and bursting’. I looked carefully at the faces around the table. Some were nodding. Others, like me, had tight brows and clenched jaws. We were in Paris at the World Journalism Education Congress in July 2019. The breakout group was the syndicate discussing the topic: ‘Teaching Data Journalism and Computational Skills’. Not a lot of love was shown in the discussion that followed for the idea of wheeling in a barrow-load of computational thinking. We broke it down and talked instead about quantitative literacy; we also talked about math aversion and my poker face dissolved. I am genuinely happy to talk to my students about their learnt number-phobia, experimental design and how to report statistics with confidence (Davies, 2019). Computational thinking felt like a bridge too far though, so I have been pondering why ever since.
期刊介绍:
Asia Pacific Media Educator is an international refereed journal published twice a year by SAGE Publications (New Delhi) in collaboration with the School of the Arts, English and Media, Faculty of Law, Humanities and the Arts, University of Wollongong in Australia. The journal follows international norms and procedures of blind peer reviewing by scholars representing a wide range of multi-disciplinary areas. APME focuses on generating discussions and dialogues among media educators, researchers and journalists. Content ranges from critical commentaries and essays to research reports and papers that contribute to journalism theory development and offer innovative ideas in improving the standard and currency of media reportage, teaching and training specific to the Asia Pacific region. Papers that integrate media theories with applications to professional practice, media training and journalism education are usually selected for peer review. APME also carries a Q&A section with book authors. APME takes conventional book reviews to a more creative level where reviewers directly engage with authors to understand the process that authors take in researching and writing the book, clarify their assumptions and pose critical questions.