Annotation Recommendation for Online Reading Activities
| Autor: | Fathi Essalmi, Maiga Chang, Miao Han Chang, Rita Kuo, Hsu Yang Kung, Vivekanandan Kumar |
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| Rok vydání: | 2018 |
| Předmět: |
E-text
Aside Computer science media_common.quotation_subject Online learning 05 social sciences 02 engineering and technology World Wide Web Annotation Resource (project management) 020204 information systems Reading (process) Similarity (psychology) ComputingMilieux_COMPUTERSANDEDUCATION 0202 electrical engineering electronic engineering information engineering 0509 other social sciences 050904 information & library sciences Cluster analysis media_common |
| Zdroj: | Challenges and Solutions in Smart Learning ISBN: 9789811087424 |
| DOI: | 10.1007/978-981-10-8743-1_19 |
| Popis: | Both classroom and online learning ask students doing reading activities. The mature and widely used e-readers allow students reading and making annotation on the screen with their computer, tablet, or even smartphone. Annotations will be a very important resource aside from the notes for students while preparing for exams. However, sometimes students might think something is not important or relevant or just simply overlook while making annotations on the materials. Such annotations might lead to lose marks later when they are writing exams. The research team has developed an online annotation system that allows teachers to create online reading activities for their students and review students’ annotations on the e-text. Moreover, with the help of a bioinspired innovative clustering method GRACE (General Rapid Annotation Clustering Enhancement), students will be offered annotation recommendations based on the similarity their annotations have from other students on the same text. In such case, students may reconsider the content they chose to ignore or overlooked earlier and make their annotations more complete and better for exam preparation later. |
| Databáze: | OpenAIRE |
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