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請使用永久網址來引用或連結此文件:
http://ir.lib.ncu.edu.tw/handle/987654321/8563
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| 題名: | 以支援學習為目的之網路學習資料與學習歷程之知識分析與組織方法;A content organizing and student portfolio analysis methodology for supporting students in Web-based learning |
| 作者: | 王勤業;Chin-Yeh Wang |
| 貢獻者: | 資訊工程研究所 |
| 關鍵詞: | 網路學習系統;學習教材組織法;學習歷程分析;Portfolio analysis;Web-based learning system;Content Organization |
| 日期: | 2004-06-20 |
| 上傳時間: | 2009-09-22 11:30:25 (UTC+8) |
| 出版者: | 國立中央大學圖書館 |
| 摘要: | 因為網路的盛行，學生可以很長的時間使用網路，以前只能在傳統教室及家裡進行學習，要等到考試才知道結果，現在能以個人電腦，行動學習載具 來進行學習，可透過學習歷程評量知道結果，這也能促進學生合作學習，利用網路延伸同儕支援同儕競爭的機會，所以善用電腦網站分析紀錄的能力，將能幫助學生學習及小組合作學習。 為支援學生即時精確的學習資訊及資源，此研究利用網際網路學習平台架設個人及小組學習網站，分析學生學習歷程及作品集，透過學生閱讀時的註記發問，提供字典及參考案例支援學生學習，討論區文獻及同儕資源也用以支援學生學習；也透過分析學生的註記學習歷程，預測其閱讀學習成效，讓學生能了解自己的學習狀況，進而自我調整加強學習；此外，也建立小組學習網站，經由分析學生合作學習的學習歷程，自動化的決定小組成員小組功能性角色的扮演情形，並藉此預測小組合作學習成效，這將讓老師知道每個學生小組合作的參與情形，小組運作的細部狀態，能即時的介入小組合作適當的指示小組任務規劃及成員調整，小組成員也可藉此了解該如何促進彼此間的合作。此外也利用 行動學習載具「手機、個人數位助理」提供學生隨身的教材及資訊支援，為引導學生學習，利用概念構圖來掌握及輔導學生各觀念的學習，也利用手機提醒學生學習任務及其學習狀態與學習目標的差距，以維持學生學習動機；此外也藉由同儕專家的分析，藉由手機促進彼此間請益的機會與方便性。 分析及實驗結果顯示，有了透過註記發問的機制，學生的網路資源存取及討論區參與發問次數都有顯著增加，學生的閱讀學習成效75.5%能經由註記來進行預測；依據學生小組合作學習歷程來分析，能有90%的功能性角色能被成功的辨識，能藉此了解學生小組合作狀態及預測小組合作成效。關於行動學習載具支援的實驗，實驗對象也能較沒有行動學習支援但僅有網路學習支援的學生，在考試成績上有顯著差異；透過行動載具的資訊提醒，學生也能有較高的學習任務達成率；系統從同儕中建議的諮商對象，也有八成能順利的解答有問題學生的疑惑。 Because the widely use of computer and Internet, students can spend a lot time on World Wide Wed. In the past, students can learn only in classroom and reading at home. Only after test, teacher and students can know their learning performance. Nowadays, students can learn by Desk Top PC and mobile devices. Web portfolio assessments can let teacher and students know their learning performance early. Web learning environment can also facilitate group collaborative learning. Therefore, properly applying Web log analysis technique can effectively help student individual learning and collaborative learning. To support student precious and in time learning information and resources, this research describes how to construct a web system for student individual learning and collaborative learning based on web portfolio analyses. A reading mechanism on web learning system was designed for students annotating, querying, and consulting. Student’s annotation behavior was used to predict his learning performance. Students can therefore be aware of their learning performance in time and know how to reinforce their learning. Besides, a system for student collaborative learning was constructed and can identify functional role of group members automatically by group portfolio analysis. Furthermore, these characteristics were used to predict group learning performance. By these ways, teacher can know participation status of each student and can also know the detail of group collaboration. Teachers can intervene students’ group learning and instruct students learning properly according these analysis results. Group members can also know how to increase their collaborative learning performance. Besides, mobile learning devices, Cell Phone and PDA, were equipped to support students in learning. Concept Map technique was applied to record every student’s learning status about each concept and can as clue to induct students learning. Relevant recommendations were sending to students to maintain their motivation and intention. Cell phones were also used to facilitate consulting via mentor recommendation from classmates. Experiment and analysis results show that reading mechanism with annotate-query function can increase online resources access rate and participation times of discussion forum significantly. The precision of students learning performance predicted by annotation analyses can achieve 75.5%. In average, 90% functional roles can be predicted during students’ collaboration according group portfolio analyses. The result can help teacher know functional role playing status of each student and can forecast their collaborative learning performance. When using mobile devices to facilitate learning, objects can gain higher grades then contrasts in test. The mechanism can also increase the task accomplished rate. About mentor recommending mechanism, more then 80% questions of questioners can be solved successfully by recommended mentors. |
| 顯示於類別: | [資訊工程研究所] 博碩士論文
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