Adaptive Assessment in Digital Learning Environments: An Expectancy-Value Theory Approach to Enhancing Learner Motivation

Abstract

Background/purpose: This study addresses the problem of demotivation generated by traditional assessment methods, which are often standardized, unengaging, and ill-suited to individual differences. In an increasingly digitized educational context, the primary objective is to assess the ability of an adaptive assessment system, developed on the Moodle platform, to stimulate learner motivation in accordance with the components of expectation-valence theory. Materials/methods: A mixed-methodology approach was adopted, combining quantitative data (academic results) with qualitative data (motivational questionnaire). The sample consisted of 72 senior students from a Moroccan public high school, randomly divided into two groups: an experimental group that underwent an adaptive online assessment, and a control group that received a traditional uniform assessment. The scenario integrated into Moodle included differentiated levels, immediate feedback, and progressive access conditions. Results: The results reveal a significant improvement in performance for the experimental group (average of 14.56/20 compared to 11.87/20). Qualitative data indicate a strengthening of perceptions of competence (expectancy), task usefulness (instrumentality), and assessment value (valence). The program was well received, with a satisfaction rate of 97.2%. Conclusion: Adaptive assessment appears to be an effective pedagogical lever for strengthening student motivation. The study proposes a transferable model that aligns LMS functionalities with the psychological determinants of motivation, in favor of a more inclusive and regulatory assessment of learning.