Technological Ecology Theory: A TVET Lecturer Development Model for Understanding Human Development in Technological Environments

Abstract

The Technical and Vocational Education and Training (TVET) artificial intelligence field is becoming increasingly sophisticated and complex. Consequently, a deeper analysis was required of lecturer development in the face of the evolving technological environment. The emphasis on the specific characteristics of an individual does not consider the larger ecological and structural drivers of technological adoption. The report introduces Technological Ecology Theory (TET), an ecological model developed through a qualitative study exploring the relationship between Mechanical Engineering lecturers and AI. TET integrates the Ecological Systems Theory (EST), the Technological Pedagogical Content Knowledge (TPACK) framework, and the structural realities of TVET institutions. This integration provides a comprehensive ecological perspective on how lecturers adapt to AI within Technical and Vocational Education and Training (TVET) institutions, where challenges such as industry misalignment constrain effective AI integration and necessitate a contextualised model. The model portrays the lecturer training process in an ecological manner, which is shaped by organisational structures, environments surrounding teaching/learning, resource allocation, and job-specific experience. Furthermore, the study highlights the importance of recognising multilevel influences on lecturer development, including institutional policies, community engagement, and technological infrastructure. By adopting TET, stakeholders in TVET can better design curriculum, training programmes, and support systems that address both individual competencies and the broader system dynamics impacting AI adoption. Ultimately, this ecological approach offers a framework to enhance the responsiveness and effectiveness of lecturer development, facilitating improved integration of AI technologies in teaching and learning.