Please use this identifier to cite or link to this item:
https://ah.lib.nccu.edu.tw/handle/140.119/110946
題名: | Two tales of time: Uncovering the significance of sequential patterns among contribution types in knowledge-building discourse | 作者: | 洪煌堯 Chen, Bodong;Resendes, Monica;Chai, Ching Sing;Hong, Huang-Yao |
貢獻者: | 教育系 | 關鍵詞: | Temporality; learning analytics; Lag-sequential Analysis; Frequent Sequence Mining; knowledge building | 日期: | Jan-2017 | 上傳時間: | 12-Jul-2017 | 摘要: | As collaborative learning is actualized through evolving dialogues, temporality inevitably matters for the analysis of collaborative learning. This study attempts to uncover sequential patterns that distinguish “productive” threads of knowledge-building discourse. A database of Grade 1–6 knowledge-building discourse was first coded for the posts’ contribution types and discussion threads’ productivity. Two distinctive temporal analysis techniques – Lag-sequential Analysis (LsA) and Frequent Sequence Mining (FSM) – were subsequently applied to detecting sequential patterns among contribution types that distinguish productive threads. The findings of LsA indicated that threads that were characterized by mere opinion-giving did not achieve much progress, while threads having more transitions among questioning, obtaining information, working with information, and theorizing were more productive. FSM further uncovered from productive threads distinguishing frequent sequences involving sustained theorizing, integrated use of evidence, and problematization of proposed theories. Based on the significance of studying temporality in collaborative learning revealed in the study, we advocate for more analytics tapping into temporality of learning. | 關聯: | Interactive Learning Environments, 25(2), 162-175 | 資料類型: | article | DOI: | http://dx.doi.org/10.1080/10494820.2016.1276081 |
Appears in Collections: | 期刊論文 |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
162-175.pdf | 635.23 kB | Adobe PDF2 | View/Open |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.