이현우 교수

Introduction 112 Making Meaning in Generative Learning 112 Generative Learning Foundations 112 Interrelationship of the Components of Generative Learning 113 Applied Research 114 Synthesis from the Learning Process Perspective 114 Synthesis from a Learning Outcomes Perspective 114 Recall 115 Comprehension 115 Higher Order Thinking 115 Self-Regulation Skill 121 Summary 121 Implications for Further Research 122 Motivation, Learner, and Knowledge Creation Processes 122 Instructor-Provided or Learne

We tackle biomedical image segmentation in the scenario of only a few labeled brain MR images. This is an important and challenging task in medical applications, where manual annotations are time-consuming. Current multi-atlas based segmentation methods use image registration to warp segments from labeled images onto a new scan. In a different paradigm, supervised learning-based segmentation strategies have gained popularity. These method consistently use relatively large sets of labeled trainin

As the technology-enriched learning environments and theoretical constructs involved in instructional design become more sophisticated and complex, a need arises for equally sophisticated analytic methods to research these environments, theories, and models. Thus, this paper illustrates a comprehensive approach for analyzing data arising from experimental studies using structural equation modeling (SEM) procedures that can formulate and test theories regarding how interventions affect observed o

Abstract This study investigates the establishment and benefits of the comprehensive admissions type recently introduced into Korean universities. We analyse undergraduate students' academic achievement and career readiness across three different admissions types in a medium‐sized university: rolling, comprehensive and regular. First, a series of mixed ANOVAs examined longitudinal changes for academic achievement and a set of ANOVAs found differences for academic achievement, within each semeste