From learning to teaching analytics: using the data collected in class to increase visible participation

ID: 53037 Type: Full Paper: Practice Based
  1. Emmanuel Zilberberg, ESCP Europe / CREF (Paris XII), France
  2. Cristina Davino, University of Naples Federico II, Department of Economics and Statistics –, Italy

Tuesday, June 26 11:15-11:45 AM Location: Vondelpark View on map

Presider: Kurt Ackermann, Hokusei Gakuen University Junior College, Japan

Abstract: Synchronous Interactions Systems Mediated by Individual Computers (SISMIC, aka Audience response systems) collect numerous textual responses in classes, making participation visible and perhaps also encouraging it. They promote formative evaluation by providing on-the-fly analytics that are primarily teaching analytics rather than learning analytics. Teachers can use them for immediate remediation during and after the class to improve instructional design for subsequent cohorts. The collection of as many teaching analytics as possible is therefore very beneficial. Although empirical evidence is lacking, the literature asserts that anonymity is appreciated by students and encourages visible participation. The aim of this paper is to study if students’ identification modalities impact visible participation. The analysis is based on a case study and the paper proposes to support a descriptive analysis with a quantile regression analysis. Participation is tested with three experimental units, each of which has been randomly assigned one of the following student identification methods: a patronymic identifier (control group), a uniform but individual identifier (student X), which is not traceable, and a unit with a self-determined identifier.

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