Student work on computers is creating bigger data sets (homework, tests, essays, online forums), as are videotapes of classroom lessons. By combining computers, statistics, mathematics, and linguistics to analyze these big data (analytics), we can better understand our students’ strengths and weaknesses to inform our teaching. Illustrative cases include analytics of students’: (a) tests for easy vs. hard questions, poorly designed questions, bias (e.g., gender), and easily guessed answers; (b) essays for content and creativity; (c) online discussions for unproductive sequences to alert teachers; and (d) classroom activities for attention and engagement. Parallel to big data analytics, I also show how a teacher can do simple, informative analyses of small data (e.g., students in one class). Copyright © 2018 Learning and Teaching @EdUHK Festival.
|Publication status||Published - May 2018|
|Event||Learning and Teaching @EdUHK Festival 2018: Teaching Excellence in the Big Data Era - The Education University of Hong Kong, Hong Kong|
Duration: 01 Feb 2018 → 31 May 2018
|Seminar||Learning and Teaching @EdUHK Festival 2018: Teaching Excellence in the Big Data Era|
|Period||01/02/18 → 31/05/18|