Motivational and emotional orientation, engagement, and achievement in mathematics. A case study with one sixth-grade classroom working with an electronic textbook on fractions

Abstract

Interactive and adaptive scaffolds implemented in electronic mathematics textbooks bear high potential for supporting students individually in learning mathematics. In this paper, we argue that emotional and behavioral engagement may account for the effectiveness of such digital curriculum resources. Following the general model for determinants and course of motivated action, we investigated the relationship between students’ domain-specific motivational and emotional orientations (person)—while working with an e-textbook on fractions (situation), their emotional and behavioral engagement while learning (action), and their achievement after tuition (outcome). We conducted a case-study with N = 27 students from one 6th-grade classroom, asking about the relationship between students’ motivational and emotional orientations and their emotional and behavioral engagement, and whether emotional and behavioral engagement are unique predictors of students’ cognitive learning outcomes while working with an e-textbook. For that, we designed a four-week-intervention on fractions using an e-textbook on iPads. Utilizing self-reports and process data referring to students’ interactions with the e-textbook we aimed to describe if and how students make use of the learning opportunities offered. Despite being taught in the same classroom, results indicated large variance in students’ motivational and emotional orientations before the intervention, as well as their emotional and behavioral engagement during the intervention. We found substantial correlations between motivational and emotional orientations (i.e., anxiety, self-concept, and enjoyment) and emotional engagement (i.e., intrinsic motivation, competence and autonomy support, situational interest, and perceived demand)—with positive orientations being associated with positive emotional engagement, as expected. Although the correlations between orientations and behavioral engagement (i.e., task, exercise, and hint count, problem solving time, and feedback time) also showed the expected directions, effect sizes were smaller than for emotional engagement. Generalized linear mixed models revealed that emotional engagement predicted cognitive learning outcomes uniquely, while for behavioral engagement the interaction with prior knowledge was the significant predictor. Taken together, they accounted for a proportion variance change of 44 % in addition to prior knowledge. We conclude that when designing digital learning environments, promoting engagement—in particular in students who share less-promising prerequisites—should be considered a key feature.