Integrating Data Analytics Training into Curricula at Small Colleges: A Practical Framework for Enhancing Student Skills

Abstract

Quantitative Data Analytics (QDA) is a critical skill for professionals across various natural science disciplines. However, college curricula, especially at small colleges, often lag behind the evolving workforce’s needs due to limited faculty resources. Despite abundant training materials, there is a noticeable gap in practical frameworks for effectively developing and implementing QDA training programs, particularly addressing existing curriculum gaps and resource constraints. This study presents a practical framework for developing introductory QDA training programs tailored for non-statistical majors at resource-constrained small colleges with various educational settings. Employing a design science strategy, we developed a modular co-curricular QDA Training Program (CQDATP), consisting of five training modules refined over three iterative phases. This flexible design integrates seamlessly with existing courses or can function as standalone workshops, bolstering students’ preparedness for advanced courses and research opportunities. Our program evaluation indicates that our approach significantly enhanced students’ QDA capabilities without necessitating extensive curriculum overhauls. By focusing on adaptability and resource efficiency, our framework holds the potential to benefit educators, curriculum developers, and administrators at small colleges, ensuring that graduates are well-prepared for data-driven industries, even when resources are limited.