Competency-based curriculum design for a Master of Information Science Program

Abstract

This study aimed to design a competency-based curriculum for a Master of Information Science program that addresses the evolving demands of the digital era, aligns with labor market expectations, and supports lifelong learning. Using a mixed-methods approach, the research incorporated document analysis, stakeholder interviews, curriculum drafting, and expert reviews. The curriculum was developed based on the competency-based education model and the backward design framework, ensuring alignment between expected professional competencies, program learning outcomes, and curriculum structure. Key findings identified a set of generic and specific competencies required of high-level information professionals, including expertise in digital transformation, data analytics, digital communication, and digital records management. Stakeholders emphasized the importance of theoretical knowledge, digital literacy, critical thinking, ethical behavior, and the ability to apply knowledge in practical settings. The curriculum structure comprises 36 credits, organized into modular learning units, including core, elective, and independent study components. It also allows for flexible pathways such as stackable credentials, non-degree options, and a graduate diploma track for learners not pursuing a thesis. The resulting curriculum promotes outcome-based learning, integrates lifelong learning principles, and offers a flexible, student-centered framework aligned with global standards such as those advocated by the iSchools Organization. This study contributes a practical model for aligning academic programs with labor market needs and national qualification frameworks. Recommendations for future research include piloting the curriculum, evaluating its impact on learner performance and employability, and developing systems for continuous curriculum updates in response to technological change. While the study provides a comprehensive design model, it is limited to the design phase and would benefit from empirical validation during implementation.