DocumentCode
735176
Title
Drawing micro learning into MOOC: Using fragmented pieces of time to enable effective entire course learning experiences
Author
Sun, Geng ; Tingru Cui ; Jianming Yong ; Jun Shen ; Shiping Chen
Author_Institution
Sch. of Inf. Syst. & Technol., Univ. of Wollongong, Wollongong, NSW, Australia
fYear
2015
fDate
6-8 May 2015
Firstpage
308
Lastpage
313
Abstract
Recently the massive open online course (MOOC) is an emerging trend that attracts many educators´ and researchers´ attentions. Based on our pilot study focusing on the development and operation of MOOC in Australia, we found MOOC is featured with mastery learning and blended learning, but it suffers from low completion rates. Brining micro learning into MOOC can be a feasible solution to improve current MOOC delivery and learning experience. We design a system which aims to provide adaptive micro learning contents as well as learning path identifications customized for each individual learner. To investigate how micro learning can impact learning experience and knowledge acquisitions of learners participated in MOOC, we suggest a potential scheme including hypotheses to evaluate our proposed approach.
Keywords
computer aided instruction; educational courses; Australia; MOOC; course learning; drawing micro learning; learning path identifications; massive open online course; Australia; Data mining; Education; Lead; World Wide Web; Blended Learning; MOOC; Mastery Learning; Micro Learning; Resource Adaptation;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Supported Cooperative Work in Design (CSCWD), 2015 IEEE 19th International Conference on
Conference_Location
Calabria
Print_ISBN
978-1-4799-2001-3
Type
conf
DOI
10.1109/CSCWD.2015.7230977
Filename
7230977
Link To Document