The Impact of Digitally Enhanced Training Programs on Building Employees' Future Skills, with Learning Motivation as a Mediating Variable

Abstract

The rapid advancement of digital technologies has brought about a profound transformation in the field of employee training and development, highlighting the importance of digitally enhanced training programs in preparing employees to meet future organizational challenges. This study aimed to examine the impact of digitally enhanced training programs on the development of employees’ future skills, with learning motivation serving as a mediating variable. Drawing on a conceptual framework grounded in Self-Determination Theory (SDT) and the Technology Acceptance Model (TAM), the study investigated how digital training interventions influence skill acquisition and the role of intrinsic and extrinsic learning motivation in this process.

A quantitative research methodology was employed through the distribution of a questionnaire to trainees at Naif Arab University for Security Sciences. Data analysis included descriptive statistics, reliability and validity tests, multicollinearity assessment, Kolmogorov–Smirnov tests, and regression analyses to evaluate the relationships and effects among the study variables. The findings indicated that digitally enhanced training programs significantly improve employees’ future skills and that learning motivation partially mediates this relationship. These results suggest that organizations seeking to enhance workforce resilience and adaptability should invest in digital training solutions, actively engage employees in digitally enhanced training programs, and strengthen both intrinsic and extrinsic learning motivation. The study also offers directions for future research.

Country : Saudi Arabia

1 Dr. Naif bin Sulaiman Al-Mutlaq

  1. Executive Director of Consulting Studies and Services at Naif Arab University for Security Sciences (NAUSS), Saudi Arabia

IRJIET, Volume 10, Issue 3, March 2026 pp. 42-57

doi.org/10.47001/IRJIET/2026.103008

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