Reflections on algorithmic thinking for video analysis: sorting out complex human activities

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Abstract

Algorithmic thinking approaches utilize a number of steps to break down the issues surrounding a given problem. It involves a problem being analyzed and specified to then identify basic actions to the given problem that can be used to construct an algorithm. This means that algorithmic thinking is a very structured way of thinking and analyzing things. In this article, I will discuss how those principles could be used in teaching video ethnography, how to think analytically in a field that is inherently qualitative and descriptive in nature. Utilizing examples from a video ethnography course, it is explained how students examine video data that was collected as part of their inquiries about the nature of scientific practices. The process of using an algorithmic structured analysis in their examinations allowed the students to identify the materiality of scientific activities. The process also allowed for the identification of rules, explained through the use of ethnomethodologically inspired methods. The students examined visual and non-verbal aspects. Through this process, the students were able to identify basic actions and examine the relationship between tools, rules, practices and people. It’s argued that repurposing the concept of algorithmic thinking for the analysis of complex events can prove to be useful for teaching, since a structured analytical approach permits for organized and critical examinations of human practices.
Original languageEnglish
JournalKnowledge Cultures
Volume6
Issue number1
Pages (from-to)97-111
Number of pages15
ISSN2327-5731
DOIs
Publication statusPublished - 2018

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Keywords

  • video ethnography
  • algorithmic thinking
  • basic actions

Cite this

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Reflections on algorithmic thinking for video analysis : sorting out complex human activities. / Otrel-Cass, Kathrin.

In: Knowledge Cultures, Vol. 6, No. 1, 2018, p. 97-111.

Research output: Contribution to journalJournal articleResearchpeer-review

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