Utility-Value Score: A Case Study in System Generalization for Writing Analytics

  • Beata Beigman Klebanov Educational Testing Service
  • Stacy Priniski University of Wisconsin–Madison
  • Jill Burstein Educational Testing Service
  • Binod Gyawali Educational Testing Service
  • Judith Harackiewicz University of Wisconsin–Madison
  • Dustin Thoman San Diego State University
Keywords: automated writing evaluation, data variability, first-year STEM, model evaluation, model generalization, STEM motivation. student writing, utility value, writing analytics

Abstract

Collection and analysis of students’ writing samples on a large scale is a part of the research agenda of the emerging writing analytics community that promises to deliver an unprecedented insight into characteristics of student writing. Yet with a large scale often comes variability of contexts in which the samples were produced—different institutions, different purposes of writing, different author demographics, to name just a few possible dimensions of variation. What are the implications of such variation for the ability of automated methods to create indices/features based on the writing samples that would be valid and meaningful? This paper presents a case study in system generalization. Building on a system developed to assess the expression of utility value (a social-psychology-based construct) in essays written by first-year biology students at one postsecondary institution, we vary data parameters and observe system performance. From the point of view of social psychology, all these variants represent the same underlying construct (i.e., utility value), and it is thus very tempting to think that an automatically produced utility-value score could provide a meaningful analytic, consistently, on a large collection of essays. However, findings from this research show that there are challenges: Some variations are easier to deal with than others, and some components of the automated system generalize better than others. The findings are then discussed both in the context of the case study and more generally.

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Published
2018-12-09