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Abstract Title: Instructional fingerprinting: network analysis of Framework for Interactive Learning in Lectures (FILL) data
Abstract: Classroom observation protocols capture instructional practices and moves in order to better understand active learning and connect these instructional practices to student outcomes. One observational protocol, developed at University of Edinburgh, is the Framework for Interactive Learning in Lectures (FILL). FILL focuses on instructor actions during active learning lectures and includes six codes for lecture activity. The data generated from the FILL is a set of time-stamped which can be transformed into a network representing transitions from instructional activity to another. These networks allow us to generate an 'instructional fingerprint.' We use generalized exponential random graph models (GERGMs) to identify the fingerprint of an instructor and to search for the characteristic fingerprint of various instructional practices. We present results that illustrate the network analysis of FILL data and propose further elaborations of how the method could be extended as part of an overall instructional evaluation protocol.
Abstract Type: Contributed Poster Presentation
Session Time: Poster Session II
Poster Number: B86

Author/Organizer Information

Primary Contact: Eric Brewe
Drexel University
3141 Chestnut St.
Disque Hall #816
Philadelphia, PA 19104-2816
Phone: 2158952779
and Co-Presenter(s)
Ross Galloway, University of Edinburgh
Judy Hardy, University of Edinburgh
Anna Wood, University of Edinburgh
Craig Young, University of Edinburgh
Emma Elley, University of Edinburgh