By Frederick W.B. Li, Ralf Klamma, Mart Laanpere, Jun Zhang, Baltasar Fernandez Manjon, Rynson W.H. Lau
This booklet constitutes the refereed lawsuits of the 14th overseas convention on Web-Based studying, ICWL 2015, held in Guangzhou, China, in Noavember 2015.
The 18 revised complete papers offered including 2 invited papers and seven brief papers have been rigorously reviewed and chosen from approximately seventy nine submissions. The papers are prepared in topical sections on collaborative and peer studying; e-lerning platform and tolls; layout, version, and framework of e-learning structures; clever tutoring and instruments; pedagogical matters; custom-made and adaptive studying; and net 2.0 and social studying environments.
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Additional resources for Advances in Web-Based Learning -- ICWL 2015: 14th International Conference, Guangzhou, China, November 5-8, 2015, Proceedings
We could thus look at the strength and weakness demon‐ strated by the students in the homework tasks and adjust our subsequent teaching focus to help students make better accomplishments. One problem that we observed in teaching this course was that some students did not want to take this course but felt that they were forced to take it because it is a compulsory course. As a result, they were not too motivated to learn despite our eﬀorts in designing this course with a lot of interesting content.
Students tended to give shorter comment on true/false and veriﬁcation criteria. • Students’ grading were less consistent on true/false and veriﬁcation criteria, perhaps due to “courteous grading”. • Undergraduate students tended to give more comments than graduate students. • Students tended to give more consistent grades for artifacts in a writing assignment than ones in a programming assignment. • More veriﬁcation criteria could potentially lower the peer-grading reliability. 36 Y. Song et al.
This paper reports on a pilot study that attempts to “close the circle” and analyze the quality of existing peer-assessment rubrics. We focused our efforts on ﬁnding what types of criteria and rubrics have more formative-feedback value and higher peer-grading reliability. Fig. 1. Rubric improvement cycle In the long-term, we hope to build a predictive model that can be used to predict the feedback validity, peer-grading reliability and overall quality of a peer-assessment rubric even before it is used by any students.