Using a Mathematical Model of Motivation, Volition, and Performance to Examine Students’ E-Text Learning Experiences

Abstract

This empirical study used Keller’s (Technol Instr Cogn Learn 16:79–104, 2008b) motivation, volition, and performance (MVP) theory to develop and statistically evaluate a mathematical MVP model that can serve as a research and policy tool for evaluating students’ learning experiences in digital environments. Specifically, it explored undergraduate biology students’ learning and attitudes toward e-texts using a MVP mathematical model in two different e-text environments. A data set (N = 1334) that included student motivation and e-text information processing, frustration with using e-texts, and student ability variables was used to evaluate e-text satisfaction. A regression analysis of these variables revealed a significant model that explained 77% of the variation in student e-text satisfaction in both e-text learning environments. Student motivation and intrinsic cognitive load were positive predictors of student satisfaction, while extraneous cognitive load and student prior knowledge and background variables were negative predictors. Practical implications for e-text learning and generalizability of a mathematical MVP model are discussed.