2020 IRCET
International Symposium on Business and Social Sciences
January 7-9, 2020 in Seoul, South Korea
Keynote Speaker
Joseph Lau
Lecturer and Assistant Programme Leader (AD in Logistics and Supply Chain Management)
Title: Exploring sub-degree students growth mindset:The way forward to professionalism
Abstract:
The use of competition to foster student learning has been arisen progressively in higher education circumstances. In terms of Hong Kong sub-degree sector, a number of higher education institutions designed and organized various types of competition to encourage professionalism and develop teaching pedagogies. To some extent, competition considers as an incentive scheme that examines students’ comparative performance with peers. Students associate the competition results with the degree of perceived ability.
Specifically, students demonstrate their ability is higher than losers / others and attach their “self-worth” when they gain victory. Hence, top students are highly motivated to try hard so as to support good performance as disclosure of high ability. Some students may select to put lower efforts because they accept success is not promised at all times. When their substantial efforts are followed by low score or poor performance, they will describe themselves as incapable persons.
Dr. YoungranAn, Ph.D.
Assistant Professor KC University, Seoul Korea
Topic: Applying the Constructivism-based Flipped Learning
Abstract:
There have been many studies on the variables to predict learning outcome, most of which focused on academic self-efficacy and metacognitive strategies. In general, they have been concerned with e-learning or offline classroom environments, with a limited research on those variables in the flipped learning class.
Meanwhile, research into the flipped learning itself has been on the boil, in regard to the questions of the notion and implication that flipped learning presents and imparts. The research also centered around developing an instructional design model and verifying the effect of the flipped learning method on the basis of the application cases.
