Training and Development Practices in Higher Education: Challenges, Influencing Factors, and Employee Perceptions

Training and development play a crucial role in enhancing employee performance, organizational efficiency, and institutional competitiveness, particularly in higher education. This study examines the training and development practices within a university setting, focusing on employee perceptions, influencing factors, and challenges that affect training effectiveness. A descriptive survey design was employed, with data collected from academic, administrative, and finance staff using structured questionnaires. The findings reveal that while a significant proportion of employees are aware of and have participated in training programs, the frequency and systematic evaluation of these initiatives remain insufficient. Key factors influencing training effectiveness include university policies, financial resources, technological advancements, and strategic institutional objectives. The study identifies budget constraints as a major limitation, restricting the scope and accessibility of training programs. Additionally, the absence of structured needs assessments and limited opportunities for applying newly acquired skills hinder the overall impact of training initiatives. Despite the increasing use of digital learning tools, challenges such as digital literacy and resistance to technology adoption persist. The study underscores the need for universities to implement comprehensive needs assessments, allocate adequate financial resources, and establish systematic training evaluation mechanisms. Strengthening managerial support, leveraging technology enhanced learning, and aligning training with institutional goals are essential for optimizing employee development. This study contributes to the existing body of knowledge by providing empirical evidence on training challenges and offering policy recommendations to improve professional development in higher education. Future research should explore longitudinal studies on training effectiveness and the impact of artificial intelligence-driven learning models in academic institutions.