Role of perceived self-efficacy in automated project allocation: Measuring university students’ perceptions of justice in interdisciplinary project-based learning (original) (raw)

Computers in Human Behavior, 2022

Abstract

Universities have implemented digital-technology-assisted automated project-allocation solutions to solve perceived injustices raised by students during manual project allocation for project-based learning (PBL). However, perceived injustices still occur. Grounded in social cognitive theory and organizational justice theory, this mixed-method case study explored the proposition that self-efficacy predicts perceived justice. First, we developed and evaluated an integrated scale that assessed self-efficacy and perceived justice by incorporating the educational context into PBL project allocation. Second, we tested three hypotheses regarding the relationship between self-efficacy and the dimensions of perceived justice, using structural equation modelling. Third, we conducted focus group interviews and qualitative analysis to explain the quantitative findings. The questionnaire was administered to two undergraduate cohorts (N1 = 226, N2 = 537) in an interdisciplinary PBL course at an international university. Perceived self-efficacy, procedural justice, distributive justice, and learning equity were the most relevant factors for perceived justice in PBL project allocation. Moreover, students' self-efficacy significantly predicted perceived justice, confirming human agency's critical role in automated project-allocation decision-making. Three themes were extracted to explain underlying mechanisms. This study provides a context-specific justice measurement tool and a conceptual model highlighting the importance of student self-efficacy for perceived justice in sustainable PBL in higher education.

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