dc.description.abstract | The study aimed at examining the employers agents views on the employability skills of Makerere University graduates. Using the phenomenological research design, data was collected from eight departmental heads and deans on individual endowments (creativity, problem solving), social skills (communication, teamwork) and job inevitable skills (computer knowledge, ability to transfer acquired knowledge) claimed by Makerere University graduates and are exhibited at work in Kampala International University and Islamic University in Uganda. Findings show employers agents place a great value on the graduates' illustrated unique endowment abilities, such as creativity and problem-solving skills. Employer’s agents of Makerere University graduates also show that they demonstrated strong social competencies in their jobs, especially in the areas of communication and teamwork. The employers agents lastly express that Makerere University graduates have excellent knowledge transfer skills, which are crucial for their chosen job positions. They are also able to use computer software and technologies effectively. In conclusion, the study worked towards developing more effective and inclusive skill requirements during work processes that value a wide range of employability skills that contribute to modern industrial production. The underlying structures of consciousness that shape employer agents views were revealed. The employers agents identified their biases and limitations. However, employers agents may prioritize certain skills over others based on their experiences, beliefs, and biases, leading to undervaluing of soft skills like communication and teamwork or certain academic backgrounds. The study recommends that universities prioritize the cultivation and development of creativity, problem-solving, communication, teamwork, computer knowledge and ability to transfer the acquired knowledge. The study suggests additional employability skills studies be conducted in other contexts using systematic mixed methods approach. | en_US |