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Journal Cover Themes in Science and Technology Education
  [2 followers]  Follow
    
  This is an Open Access Journal Open Access journal
   ISSN (Print) 1792-8788 - ISSN (Online) 1792-8788
   Published by University of Ioannina Homepage  [1 journal]
  • Editorial: Special issue on “Big Data in Education”

    • Authors: Renato P. dos Santos
      Pages: 81 - 83
      PubDate: 2016-02-26
      Issue No: Vol. 8, No. 2 (2016)
       
  • Big Data science education: A case study of a project-focused introductory
           course

    • Authors: Jeffrey Saltz, Robert Heckman
      Pages: 85 - 94
      Abstract: This paper reports on a case study of a project-focused introduction to big data science course. The pedagogy of the course leveraged boundary theory, where students were positioned to be at the boundary between a client’s desire to understand their data and the academic class. The results of the case study demonstrate that using live clients within a team-based, project-focused course provides a useful platform in which to teach an introduction to data science course to graduate students across a range of backgrounds. While more work needs to be done to compare different possible pedagogies for teaching an introduction to data science course, the results of this study indicate that one successful approach is a project-focused class that puts students at the boundary between the academic context of the course and solving a real-world problem for their client.
      PubDate: 2016-02-26
      Issue No: Vol. 8, No. 2 (2016)
       
  • The relationship between Big Data and Mathematical Modeling: A discussion
           in a mathematical education scenario

    • Authors: Rodrigo Dalla Vecchia
      Pages: 95 - 103
      Abstract: This study discusses aspects of the association between Mathematical Modeling (MM) and Big Data in the scope of mathematical education. We present an example of an activity to discuss two ontological factors that involve MM. The first is linked to the modeling stages. The second involves the idea of pedagogical objectives. The main findings indicate that Big Data may contribute new ways of working with MM in the classroom, helping develop pedagogical objectives associated with the ability to deal with and interpret digital media.
      PubDate: 2016-02-26
      Issue No: Vol. 8, No. 2 (2016)
       
  • Big Data with small cases: A method for discovering students centered
           contexts for Physics courses

    • Pages: 105 - 114
      Abstract: This article proposes a methodology that could assist teachers in understanding their students’ primary needs or interests to decide on the kind of examples or contexts to be used in the classroom. The methodology was tested on 100 volunteers from university (N=50) and high school (N=50) in Ankara, Turkey. The participants were asked to write down the first word they thought of when they were presented with a single letter from the Turkish alphabet, which contains 29 letters. Then all the collected words (29x100=2900) were analyzed with the online word cloud creator, Wordle. According to results, the most cited words from the high-school classes were similar to each other, while the data from university participants showed more diversity. The most chosen word by the participants may give some clues in relation to the context that the teacher can utilize in planning a course. This study shows how to use a big-data-visualization-tool-based methodology to analyze the data gleaned from the participants’ life-long experiences.
      PubDate: 2016-02-26
      Issue No: Vol. 8, No. 2 (2016)
       
  • Big Data: Philosophy, emergence, crowdledge, and science education

    • Authors: Renato P. dos Santos
      Pages: 115 - 127
      Abstract: Big Data already passed out of hype, is now a field that deserves serious academic investigation, and natural scientists should also become familiar with Analytics. On the other hand, there is little empirical evidence that any science taught in school is helping people to lead happier, more prosperous, or more politically well-informed lives. In this work, we seek support in the Philosophy and Constructionism literatures to discuss the realm of the concepts of Big Data and its philosophy, the notions of ‘emergence’ and crowdledge, and how we see learning-with-Big-Data as a promising new way to learn Science.
      PubDate: 2016-02-26
      Issue No: Vol. 8, No. 2 (2016)
       
 
 
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