Evaluating Digital Skill Acquisition in Technical Training: A Case Study of TechNova Workshops

Thesis Abstract

The rapid evolution of digital technologies underscores the critical need for effective technical training programs that enhance digital skills among learners engaged in vocational and technical education. Despite the increasing emphasis on digital literacy, there exists a significant gap in understanding the effectiveness of targeted training interventions, particularly within industry-specific settings such as TechNova Workshops, which serve as a pivotal platform for skills development in the manufacturing and IT sectors. This study aims to evaluate the extent of digital skill acquisition among participants of TechNova Workshops, with a focus on identifying factors that influence learning outcomes and assessing the alignment of training content with industry requirements. The study’s specific objectives are to determine the levels of digital skills prior to and after training, examine the relationship between training variables and skill acquisition, and propose strategies for optimizing training effectiveness. Adopting a mixed-methods research design, the study integrates quantitative and qualitative data collection approaches to provide a comprehensive analysis of digital skill development. The quantitative component employs a quasi-experimental pretest-posttest design, involving a sample of 200 workshop participants selected through stratified random sampling to ensure representation across different skill levels and industry backgrounds. Data collection instruments include standardized digital literacy assessments and structured questionnaires developed based on the European Digital Competence Framework (DigComp 2.1). Qualitative data are gathered through semi-structured interviews with 20 trainers and focus group discussions with 30 participants, facilitating in-depth insights into perceptions, challenges, and contextual factors affecting skill acquisition. Data analysis employs descriptive statistics to summarize demographic and baseline knowledge data, while inferential techniques such as paired sample t-tests evaluate the significance of improvements in digital skills post-training. Multiple regression analysis is utilized to identify predictors of skill gains, considering variables like training duration, availability of resources, and prior experience. Thematic analysis, guided by Braun and Clarke’s methodology, is applied to qualitative data to uncover recurring themes related to participant engagement, perceived training quality, and contextual barriers. Expected findings are anticipated to demonstrate significant improvements in digital literacy levels following participation in TechNova Workshops, with key factors such as training duration, trainer expertise, and access to practice tools significantly contributing to learning outcomes. The study also predicts that participants’ initial digital proficiency and motivation levels will moderate skill acquisition. These findings contribute to existing literature by providing empirical evidence on the efficacy of industry-specific training interventions in enhancing digital competencies, thereby filling identified gaps related to contextual and motivational factors influencing training success. The research’s main contribution lies in developing a contextual framework for optimizing digital training in technical and vocational education, supported by empirical data and grounded in Bandura’s Social Cognitive Theory and the Diffusion of Innovations Theory. The study concludes that targeted, contextually relevant digital training substantially elevates participants’ digital competencies, which can translate into improved employability and productivity within industry settings. Recommendations include the formulation of standardized training modules that align closely with industry needs, increased investment in trainer capacity development, and the integration of continuous assessment mechanisms to monitor skill progression. The study also advocates for expanding research to explore longitudinal impacts of digital training programs on career advancement and organizational performance, thereby contributing to policy formulation and curriculum development within technical education sectors.