Theme-based Invited Speakers

Chengjiu YIN

Kobe University, Japan

e-Books reading log based Learning Analytics

In recent years, Learning Analytics has become an important issue in the ﬁeld of computer technology. Learning Analytics is a central concern of educational institutions, as its value becomes increasingly visible (Chen, Yin, Isaias, Psotka, 2020). Different roles can get different benefits from Learning Analytics. In Japan, e-books are continually being introduced to educational institutions, and many researchers focus on doing Learning Analytics through e-books reading logs data. By using e-book systems, we can collect students’ learning behaviour logs, which recorded such behaviours as “open learning content,” “turning to the next page,” “returning to a previous page,” “adding a bookmark,” “adding a marker,” “writing a memo,” and so on.

The talk begins by reviewing the previous researches about learning analytics in the last 10 years. I then present two case studies, which are about analysing the e-book reading logs. I will introduce the data collection procedures and how the learning strategies were identified with these two case studies. The first is “Identifying Learning Strategies Using Clustering” (Yin et al., 2018). In order to identify learning strategies from the learning logs, we visualized the learning log in time series, and grouped the students into clusters based on their learning of some meaningful measurements. An important finding emerged from the analyses: The backtrack learning strategy was found to have merit as it can help students save time when studying. The second is “Examining Learning Strategies Using Sequential Analysis” (Yin et al., 2017). In order to explore the learning strategies students adopted when reading academic papers. Progressive sequential analysis was used to infer the learning strategies of students when they were reading the academic papers. The analysis results identified many significant sequences that occurred while reading the digital textbooks. We then carried out interviews to ask the participants why they took such actions.There are also some interesting findings.

Ting-Chia Hsu

National Taiwan Normal University

Mobile-Assisted Language Learning Studies

Dr. Ting-Chia HSU is currently a Distinguished Professor in the Department of Technology Application and Human Resource Development in National Taiwan Normal University. She is the Chair of The Special Interest Group (SIG) on Technology Enhanced Language Learning (TELL) in the computer education division in the Ministry of Science and Technology, Taiwan at present. She was also the chair of the TELL SIG in the Asia-Pacific Society for Computers in Education from 2018 to 2019. She is an associate editor of a SSCI journal named Frontiers in Psychology-Educational Psychology.She has published more than thirty SSCI journal paper and received multiple academic awards such as the Special Outstanding Talent Award, the Ta-You Wu Memorial Award rewarded by the Ministry of Science and Technology, and the winner of the Early Career Researcher Award 2018 in the Asia-Pacific Society for Computers in Education, and Academic Excellence Award in National Taiwan Normal University. Her research interests include computer education and educational technology. Dr. Hsu was awarded a government scholarship by Ministry of Education for project research abroad from August to October in 2011 (i.e., A visiting scholar in National Institute of Education in Singapore). She was granted a project research abroad by Ministry of Science and Technology from August 2019 to January 2020 (i.e., A visiting faculty in Massachusetts Institute of Technology, USA).

From 2007, she has developed and evaluated some mobile-assisted language learning systems. The results found that the foreign language listening comprehension of the students using partial hidden captions was similar to the listening comprehension of the students using full captions. The hidden words avoid the students inputting information through reading text from eyes. The perception processing of ears becomes important so as to adapt the students to the features of reduced forms, assimilation, elision, and so on. On the contrary, unfamiliar vocabulary which was shown in the video captions so as to be read by the eyes of the students would assist students to recognizing the vocabulary they heard and prevent the students from confusing the vocabulary they heard with other words having similar pronunciation. Finally, she conducted an experiment to compare the effects of the identical caption-filtering and personalized caption-filtering on system usability, perceived satisfaction, enjoyment, and learning motivations. In conclusion, those studies attempted toimplement personalized mobile-assisted languagelearning systems by providing adaptively support or learning materials.

Emma Mercier

University of Illinois at Urbana Champaign

A micro-ecological approach to the design and implementation of CSCL in Classrooms

Designing and implementing CSCL for classrooms requires that we consider the interplay between multiple classroom features (teams, tasks, technology and teachers) and consider learning as it occurs across levels (individual, group, whole class). In this talk I will be draw on a multi-year design-based implementation research project, focused on supporting collaborative learning in large introductory engineering courses, to illustrate how these features and levels can be addressed.