A preliminary study on the learning assessment in massive open online courses

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Abstract

Massive Open Online Course (MOOC) is a new online education form. MOOC aims to provide the advance systematic educations to the public and share the access to the best high educations to Internet users. Although the MOOC platform contained many video lessons of high-quality courses from famous universities around the world, the assessment of students’ learning, including testing methods, grading methods and feedback to student, was unsatisfactory according to XuetangX, an xMOOC websites leading by Tsinghua University in China. Setting effective and satisfactory assessment methods to test and grade students’ learning performance in MOOC has significant values for all stakeholders including instructors, students and the MOOC platform. An interview study was conducted to understanding the current situation of assessments and the opinions towards different types of assessment methods from both instructors and students. We interviewed five teachers, eight course assistants of different categories of MOOCs in XuetangX, and six students from different MOOC platforms. Some conclusions and suggestions about the assessment on students’ learning performance in different categories of MOOCs were drawn in the study. The findings in the study can be referred as guidelines for instructors to design great assessment methods in different MOOCs.

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APA

Yuan, Q., Gao, Q., & Chen, Y. (2017). A preliminary study on the learning assessment in massive open online courses. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10281, pp. 592–602). Springer Verlag. https://doi.org/10.1007/978-3-319-57931-3_47

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