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  • 學位論文

基於學生滑鼠行為之適性學習網站

An adaptive learning web based on student's mouse behavior

指導教授 : 劉寶鈞 劉晨鐘
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摘要


網際網路的盛行,使得許多教材和課程都以Web來呈現,學生可以進行多樣化的Web based learning activities,然而學生在瀏覽網路教材時,由於WWW由一堆網頁靠著彼此錯綜複雜的超鏈結(hyperlinks)做連結,所以學生很容易會有迷失於超空間中(lost in hyperspace),以及不易獲得整體資訊的概觀等問題發生。 為了要解決迷失的問題,教學網站就必須要有相當大的彈性,也就是能夠提供適性化(adaptive)的網路教材。現有的adaptive web多以web log作為取得使用者網頁瀏覽access pattern的方式,透過分析web log給予使用者適當的建議。從web log中並無法探知使用者在個別網頁的觀注區域。本研究利用滑鼠軌跡以非侵入式的方式偵測學習者的觀注區域,並嘗試在adaptive learning web上,將學生的動機狀態作為adaptation的考量因素,提供適當的學習輔助。本研究所採用的Longest Common Sequence演算法可以有效的偵測使用者的觀注區域,最後我們也探討了滑鼠行為與學習狀態的關係,以作為學習網站提供學習輔助的依據。

並列摘要


Web-based courses are numerous and allow students to perform various learning activities in a virtual classroom. With the model of user interests during browsing web pages, teachers and learning systems can provide instantaneous learning supports based on users’ interests. The awareness of users’ interests also provides feedback to restructure the content of web-based learning curricula. However, to analyze users’ interests on individual pages requires the tracking student gaze movement. Requiring users to equip gaze movement detection devices is not feasible. In addition, web usage mining techniques can not inspect users’ reading behavior on individual web pages since web logs contains only the page request history of users. This research investigates the feasibility of mouse movement analysis for detecting student interests by investigating the mechanism to track student mouse movement, identifying the mouse movement patterns that can indicate student interests, and devising the methodologies detecting these identified patterns. Teachers and learning website designers can utilize the detected patterns for restructuring web-based curricula and providing instantaneous on-line learning supports. This research proposes also investigate the application of the human-computer interface on adaptive web for learning, and the dynamic instructional re-organization based on student interests.

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