Poster #14 - When to Hold 'Em, When to Fold 'Em: A Markov Model of Task Perseverance

• In Event: 77.059 - MTCC Tuesday Poster Session 18
  In Poster Session: 77.059-1 - Exploring Motivational Constructs in Authentic Academic Settings

Abstract

An important but rarely studied aspect of writing as a process is deciding whether to stop or persevere. This study used learning analytics to automatically track 36,947 submissions as students write and revise machine-scored micro-themes in iterative writing with feedback. A discrete-time discrete-space Markov model fit the data well and predicted a general progression over time toward improved scores sometimes interrupted by unproductive revision cycles. Whether students stop or persevere was found to be a function of performance and three distinct types of stopping were examined: “quitting,” “satisficing” or “perfecting.” Results provide insights into how and when students stop and support for the self-regulated learing perspective.

Authors

• Edward Brent, University of Missouri

• Sounak Mizzou Chakraborty, University of Missouri - Columbia

• Morgan Mizzou Self, University of Missouri - Columbia

• Kandice Grossman, University of Missouri - Columbia