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題名 Enhancement of digital reading performance by using a novel web-based collaborative reading annotation system with two quality annotation filtering mechanisms
作者 陳志銘
Jan, Jiun-Chi;Chen, Chih-Ming;Huang, Po-Han
貢獻者 圖檔所
關鍵詞 Cooperative/collaborative learning; Human–computer interface; Interactive learning environments; Teaching/learning strategies
日期 2015-09
上傳時間 3-Feb-2016 10:14:47 (UTC+8)
摘要 Collaboratively annotating digital texts allows learners to add valued information, share ideas, and create knowledge. However, excessive annotations and poor-quality annotations in a digital text may cause information overload and divert attention from the main content. The increased cognitive load ultimately reduces the effectiveness of collaborative annotations in promoting reading comprehension. Thus, this work develops a web-based collaborative reading annotation system (WCRAS-TQAFM) with two quality annotation filtering mechanisms—high-grade and master annotation filters—to promote the reading performance of learners. Ninety-seven students from three classes of a senior high school in Taiwan were invited to participate in an 80-min reading activity in which individual readers use WCRAS with or without annotation filters. Analytical results indicate that digital reading performance is significantly better in readers who use the high-grade annotation filter compared to those who read all annotations. Moreover, the high-grade annotation filter can enhance the reading comprehension of learners in all considered question types (i.e., recall, main idea, inference, and application). Also, the Cohen’s kappa statistics was used for assessing whether the annotation selected by the high-grade annotation filter is in agreement with the annotations selected by a domain expert. The statistic results indicate that the proposed high-grade annotation filter is valid to some degree. Finally, neither of the proposed quality annotation filtering approaches significantly reduces cognitive load.
關聯 International Journal of Human-Computer Studies,86,81-93
資料類型 article
DOI http://dx.doi.org/10.1016/j.ijhcs.2015.09.006
dc.contributor 圖檔所
dc.creator (作者) 陳志銘zh_TW
dc.creator (作者) Jan, Jiun-Chi;Chen, Chih-Ming;Huang, Po-Han
dc.date (日期) 2015-09
dc.date.accessioned 3-Feb-2016 10:14:47 (UTC+8)-
dc.date.available 3-Feb-2016 10:14:47 (UTC+8)-
dc.date.issued (上傳時間) 3-Feb-2016 10:14:47 (UTC+8)-
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/81079-
dc.description.abstract (摘要) Collaboratively annotating digital texts allows learners to add valued information, share ideas, and create knowledge. However, excessive annotations and poor-quality annotations in a digital text may cause information overload and divert attention from the main content. The increased cognitive load ultimately reduces the effectiveness of collaborative annotations in promoting reading comprehension. Thus, this work develops a web-based collaborative reading annotation system (WCRAS-TQAFM) with two quality annotation filtering mechanisms—high-grade and master annotation filters—to promote the reading performance of learners. Ninety-seven students from three classes of a senior high school in Taiwan were invited to participate in an 80-min reading activity in which individual readers use WCRAS with or without annotation filters. Analytical results indicate that digital reading performance is significantly better in readers who use the high-grade annotation filter compared to those who read all annotations. Moreover, the high-grade annotation filter can enhance the reading comprehension of learners in all considered question types (i.e., recall, main idea, inference, and application). Also, the Cohen’s kappa statistics was used for assessing whether the annotation selected by the high-grade annotation filter is in agreement with the annotations selected by a domain expert. The statistic results indicate that the proposed high-grade annotation filter is valid to some degree. Finally, neither of the proposed quality annotation filtering approaches significantly reduces cognitive load.
dc.format.extent 1592290 bytes-
dc.format.mimetype application/pdf-
dc.relation (關聯) International Journal of Human-Computer Studies,86,81-93
dc.subject (關鍵詞) Cooperative/collaborative learning; Human–computer interface; Interactive learning environments; Teaching/learning strategies
dc.title (題名) Enhancement of digital reading performance by using a novel web-based collaborative reading annotation system with two quality annotation filtering mechanisms
dc.type (資料類型) article
dc.identifier.doi (DOI) 10.1016/j.ijhcs.2015.09.006
dc.doi.uri (DOI) http://dx.doi.org/10.1016/j.ijhcs.2015.09.006