Significant potentials of big data in education and risks for academism:

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  • 教育ビッグデータの大きな可能性とアカデミズムに求められるもの
  • 教育ビッグデータの大きな可能性とアカデミズムに求められるもの : 情報工学と社会科学のさらなる連携の重要性
  • キョウイク ビッグデータ ノ オオキナ カノウセイ ト アカデミズム ニ モトメラレル モノ : ジョウホウ コウガク ト シャカイ カガク ノ サ ラ ナル レンケイ ノ ジュウヨウセイ
  • －情報工学と社会科学のさらなる連携の重要性－
  • Importance of further cooperation between computer science and social science

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Abstract

With the advancement of information and communication technologies，we can now collect a large and wide variety of data that was unimaginable in the past. However，when it comes to data relating to human behavior，an essential issue is that the availability of large data sets may not lead to meaningful findings. Without solving this issue，it is highly possible that big data research will make little progress. This paper addresses why big data research aiming to advance human behavioral prediction needs to transition from a quantitative to qualitative approach in the next stage. It will also introduce a new approach，“scheduling，” which helps to solve this issue in the field of education. Further，through an experiment applying this new methodology，individual learning processes are now visualized for the first time，by collecting and analyzing large and detailed longitudinal learning data (micro-big data) from individuals. We have high expectations for the future use of this data，as utilizing it to prepare feedback tailored to individual learners helps to fundamentally solve challenging issues such as declining academic abilities and motivation to learn，as well as the problem of absenteeism. The facts introduced in this paper powerfully illustrate that an enhanced quality (accuracy) of big data can lead to more strengths. Conversely，we believe that it would be a great loss to the social sciences if we failed to leverage this potentially powerful big data in the field of education.

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