Ikseon Choi

This paper describes the design, development, and implementation of a ubiquitous portfolio (u-portfolio) system aimed at enhancing clinical clerkship education at Inje University College of Medicine from 2016 to 2020. This developmental research employed involved a literature review of 69 papers on electronic portfolios (1990–2013), and as well as a series of focus group interviews and surveys with key stakeholders during the iterative design, evaluation, and revision process. The literature analysis revealed three main purposes of e-portfolios (learning, assessment, and showcase) and nine key elements for a multi-purpose e-portfolio (e.g., quality of student reflection, postgraduate continuous learning, and timely and frequent feedback). The system evolved from paper-based portfolios to address the standardization of students’ clerkship experiences across five teaching hospitals, incorporating competency-based education and enabling efficient data management to promote student learning, assessment, and feedback. Key challenges in transitioning from paper to electronic portfolios included infrastructure issues, user adaptation, and assessment standardization. The resulting u-portfolio system, which allowed the seamless integration of mobile devices, emphasized five core functions: enhanced real-time feedback, transparent evaluation with rubrics, improved reflection quality, real-time assessment and tracking, and mapping between learning and competency achievements. Initially implemented in the internal medicine clerkship in 2016, the system was gradually expanded to all core clerkships by 2018. The success of this system led to its adoption by 19 medical schools through a consortium organized by the Korea Association of Medical Colleges, with 31 schools now collaborating to enhance clerkships through the u-portfolio system.

Sarah E. Finch, Ellie S. Paek, Ikseon Choi, Jinho D. Choi. Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). 2025.

Recent research indicates the significant potential of artificial intelligence (AI) in enhancing teachers’ instructional practices in areas such as lesson planning, personalized teacher intervention and feedback, and performance assessment. To fully realize the potential of AI in teaching, it is crucial to understand how teachers innovatively apply and critically evaluate AI applications in their teaching practices. However, there is a research gap in investigating how teachers use various features of an AI-enabled system and their perceptions of AI integration in teaching to promote teachers’ effective AI integration practices. Employing an exploratory case study design, we investigated how six science teachers utilized an AI-enabled inquiry intelligent tutoring system (Inq-ITS) within their teaching and examined their perceptions of AI integration. Classroom observations and teacher interview data were collected. When using Inq-ITS functionalities, two teachers with a pedagogical orientation of teacher-guided scientific inquiry mainly engaged with its virtual tutor and teacher report summary features. Conversely, four teachers, practicing the pedagogical orientation of AI-guided scientific inquiry, relied on the AI system to guide student learning, interacting intensively with its features, particularly real-time teacher alerts and teacher inquiry practice support. Regardless of the differences in using Inq-ITS features, all teachers recognized the potential benefits of pedagogical change and encountered various challenges. This analysis also revealed that teachers exhibited distinct perceptions regarding the role of Inq-ITS integration in their teaching. Teachers who adopted a teacher-guided pedagogical orientation perceived the Inq-ITS as a supporting tool that enhanced traditional teaching methods. In contrast, those with an AI-guided pedagogical orientation viewed the Inq-ITS as akin to a teaching assistant and a pedagogical collaborator. The findings underscored the importance of enhancing teachers’ realization of the pedagogical affordance of AI in teaching through their use of AI functionalities. It is essential to consider teachers’ diverse perceptions of AI integration when promoting their integration of AI into teaching practices.

Clinical research coordinators (CRCs) play a key role in supporting the translational research enterprise, with responsibilities encompassing tasks related to the design, implementation, and evaluation of clinical research trials. While the literature explores CRC competencies, job satisfaction, and retention, little attention has been given to the role of the PI working with Human Resources (HR) in the CRC hiring and onboarding processes. We investigated the priorities, decision-making processes, and satisfaction levels of principal investigators (PIs) and hiring managers in CRC hiring. An online survey consisting of open-ended and fixed-choice questions to gather information on desired CRC qualifications and competencies, factors influencing hiring decisions, and overall satisfaction with selected candidates was administered. The survey utilized a Task/Competency Checklist developed from job descriptions and the literature. Respondents were asked to rank the importance of factors such as CRC skill set, years of experience, educational background, and budget constraints. Results indicated that the skill set of the applicant was the most frequently cited factor influencing the hiring decision, followed by years of experience. Education and budget constraints were of lesser importance. Most respondents reported a satisfaction rating of 50% or greater with their new hires, although some participants expressed challenges related to institutional training requirements, the performance of entry-level CRCs, and the qualifications of experienced candidates. The hiring cycle involves HR-PI collaboration for a clear job description, effective onboarding processes, and accessible professional development opportunities to enhance PI and employee satisfaction and CRC retention.