The purpose of this study was to explore ways to link and mutually recognize the accreditation for engineering education system and course-based qualifications system using learning outcome assessment. The realization of such a linkage plan can externally secure the effectiveness of accreditation for engineering education and strengthen the international competitiveness of engineering education, and internally, it can contribute to improving the employment rate and efficiency of academic operation by strengthening the competitiveness of students under the two systems. In order to achieve the research purpose, literature review on the national qualification system and accreditation for engineering education system was conducted and was analyzed cases for the advanced mechanical and information engineering major at H University in Sejong. H University's advanced mechanical and information engineering major satisfies the completion standards by dividing the curriculum into core competency, essential competency units, optional competency units, and non-NCS training courses to acquire qualifications as a mechanical design engineer. An evaluation plan was established and implemented according to the NCS learning module to evaluate the students' achievement level. A policy support plan was presented to minimize and establish the administrative burden of operating the two systems.

This study aims to present an empathic design method that can be utilized in engineering design classes. It is also a case study of an interdisciplinary design class that emphasizes empathy. Empathy helps us understand and think from the perspectives of different groups based on situations and contexts. Empathy is a new way of knowing and a skill. In recent years, social expectations for the roles and responsibilities of engineering professionals have increased, and it is important that we respond to them in education. This study shows the effectiveness of empathic design in connecting humans, society, and technology to define problems and design solutions. This study analyzed an empathy-based engineering design class at a university, and presented and analyzed the process and progress of empathic design, changes in students, and differences in solutions. First of all, we tracked how the problem definition and solution set at the beginning of the design process evolved through the empathic design process. It was a meaningful achievement to confirm that students can develop empathy through the course. Finally, the study suggests points to keep in mind when applying empathic design.

This study evaluated the performance of generative AI in solving mechanical engineering problems and its potential for improvement via error compensation. The research used questions from the civil servants competitive exam and the selection exam for secondary school level teachers to conduct experiments using Zero-shot(questions only) and Few-shot(questions and related contents) prompts. The study employed a controlled group pretest-posttest experimental design for the civil service exams and a single group post-test design for the secondary teacher exam. The results using Google's NotebookLM indicated that Zero-shot prompts yielded a correct answer rate of 60-75% on the civil servants exams, while Few-shot prompts yielded 88%-95%, a 25% and 24% rise for grade 7 and 9 exams, respectively. The Few-shot prompts significantly improved the accuracy, with a 40% increase in the secondary teacher exam. The study concludes that providing relevant materials through Few-shot prompts is crucial when using generative AI for engineering problem-solving. It also emphasizes the importance of verifying the reliability of the information provided and validating the AI's results. This highlights the necessity for accurate and trustworthy information when students or educators use generative AI for self-directed learning in engineering problem-solving.

This study has meta-analyzed 47 engineering education studies published in journals over the past 20 years to verify the effectiveness of engineering education programs. To this end, this study comprehensively analyzed the educational outcomes of engineering education programs conducted so far using the meta-analysis program CMA. As dependent variables for analysis, the effect size(ES) according to the cognitive domain, emotional domain, program types, and program execution periods was explored. As a result, the overall average effect size(ES) of the engineering education program was .715, indicating a medium-sized effect size corresponding to statistically significant to large levels. For the dependent variable, each effect size was shown to be the cognitive domain(ES=.495), the affective domain(ES=.275), the program types(ES=.463), and the execution periods(ES=.588). Meta-regression analysis showed that the optimal period of an engineering education program was most effective when conducted in a period of more than 12 weeks. These results imply that engineering education programs are effective in the learning development of engineering learners. Based on these research results, discussions and implications were presented. This study systematically analyzed the effects of engineering education programs conducted in Korea so far to secure specific and useful information on the effects of engineering education programs. Therefore, it contributed to providing empirical data necessary to deeply understand the learning effects through the implementation of engineering education programs. This study is meaningful in that it has laid the foundation for improving the educational quality of engineering education.