The Korea University of Technology and Education's Online Lifelong Education Center announced that it held an awards ceremony for the '2026 Smart Vocational Training Platform (STEP) Learning Best Practices Contest' in Seoul's Dragon City on November 6.
This contest aimed to discover success stories of learners who achieved employment and improved work capabilities using STEP, as well as to share effective learning methods and experiences. STEP is an online vocational training platform that offers over 2,500 e-learning contents for free, covering new technology fields such as technology and engineering, AI+X, and humanities for all citizens, including current employees, job seekers, and those preparing for employment.
A total of 60 entries were submitted between August 24 and September 20, and after evaluation, eight entries were selected, including one grand prize, two excellence awards, and five encouragement awards. The grand prize, awarded by the Minister of Employment and Labor, went to learner Jeong Seon-woo, who transitioned from a high school graduate working in a small business to a national civil servant in the field of industrial safety.
Jeong began STEP learning to enhance his professional knowledge and practical skills after securing a job in a small company. From 2016 to 2024, he consistently took courses in various fields, including machinery, electricity, and industrial safety, earning 11 nationally recognized certifications. He later succeeded in re-employment in a central public enterprise's machinery sector and passed the national civil service exam for industrial safety after working in local government. He is currently active as an employment consultant and instructor, sharing his learning experiences with job seekers.
The excellence awards, presented by the President of Korea University of Technology and Education, were given to learners Kim Eun-ha and Han Young-beom. Kim, a professor at a vocational training institution in the beauty sector, applied what she learned from STEP to customer consultations, project presentations, and career-related education. Notably, she integrated generative AI question design and result modification techniques learned in the 'How to Use ChatGPT at Work' course into her classes. As a result, her students' competency achievement improved by 56.2 percentage points, and she expanded the improved teaching methods to other classes.
Han developed an AI analysis tool to assess the reliability of railway vehicles after taking AI-related courses such as 'Data Analysis? ChatGPT Can Help!' He distributed this tool on-site, improving the efficiency of analysis tasks that were previously concentrated on specific personnel, enabling field workers to perform these tasks and enhancing data-driven decision-making capabilities.
The encouragement awards were given to five learners: Yoo Kyung-hoon, Noh Jin-hyuk, Lee Gu, Kim Kwang-ho, and Na Young-jong. They presented cases linking their work with STEP learning in areas such as chemical process quality control, AI-based education, designing training courses using generative AI, solving construction site issues, and systematizing field knowledge related to equipment.
Han Yeon-hee, director of the Online Lifelong Education Center, stated, “The commonality among the diverse cases submitted this year is that STEP goes beyond simple knowledge transfer to present new perspectives on fieldwork and practical directions. We will continue to create better learning environments based on the diverse experiences and achievements of our learners.”
* This article has been translated by AI.
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