Investigating Classroom Activities in English Conversation Lessons Based on Activity Coding and Data Visualization

  • Zilu LiangEmail author
  • Satoshi Nishimura
  • Takuichi Nishimura
  • Mario Alberto Chapa-Martell
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10838)


Reflective teaching has become dominant paradigm in second language teacher education, as critical reflection helps teachers achieve a better understanding of teaching and learning processes. Critical reflection begins from classroom investigation. Several methods such as questionnaire, lesson report, teaching journal and audio/video recordings are widely used for classroom investigation. However, these methods are either susceptible to memory bias or are hard to be continued on a day-to-day basis. In this study, we proposed an approach for effective classroom investigation in second language education using activity coding in combination with data visualization technology. The proposed method consists of three stages. In the first stage, a smartphone application was used to record the activities that happen in a class following a slightly modified experience sampling method. In the second stage, the activities were quantified using our proposed 2-level activity coding scheme, and each activity was assigned a colour code. In the third stage, a data visualization tool D3.js was used to create heat maps of the classroom activities. We applied the proposed method to investigating the classroom activities in five English conversation lessons given by native-speaking teachers. The visual feedback led to the answering of some key questions that critical reflection aims to address, including teachers’ time management, lesson structure, and the characteristics of teacher-student interaction. Based on the results obtained, we highlighted the potential of the proposed approach for involving different sectors in second language education and pointed out the directions for future research.


Second language education Data visualization D3.js Experience sampling method Reflective teaching 


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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Zilu Liang
    • 1
    Email author
  • Satoshi Nishimura
    • 2
  • Takuichi Nishimura
    • 2
  • Mario Alberto Chapa-Martell
    • 3
  1. 1.Faculty of EngineeringThe University of TokyoTokyoJapan
  2. 2.AI Research CentreNational Institute of Advanced Science and TechnologyTokyoJapan
  3. 3.CAC CorporationTokyoJapan

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