PERC 2019 Abstract Detail Page
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| Abstract Title: | Instructional fingerprinting: network analysis of Framework for Interactive Learning in Lectures (FILL) data |
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| 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 |
| Co-Author(s) 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 |
