博碩士論文 91542009 詳細資訊




以作者查詢圖書館館藏 以作者查詢臺灣博碩士 以作者查詢全國書目 勘誤回報 、線上人數:12 、訪客IP:3.133.107.11
姓名 陳志洪(Zhi-Hong Chen)  查詢紙本館藏   畢業系所 資訊工程學系
論文名稱 以動物同伴養成促進學生學習—模式設計和應用
(Motivating Students to Learn by Nurturing Animal Companions—Model Design and Applications)
相關論文
★ 一個適用於解題領域的模擬多重學習同伴之方法★ 亞卓市全民學校系統設計與初步使用成果
★ 網路學習資訊護照系統★ 全民學校之團隊教學與團隊學習設計
★ 電腦支援問答競爭學習遊戲設計之探索★ 亞卓期刊系統之設計與實作
★ 網路上目標設定環境的建置網路上目標設定環境的建置 以閱讀網站為例★ 亞卓合作觀察實驗站之研究
★ 使用 EduClick 當作遠端遙控互動評量系統★ 出題與同儕評題支援系統之設計及評估
★ 支援不同解題練習遊戲活動之雙人學習系統★ 亞卓市多重學習系統之黏合機制
★ 激發使用動機之網路個人學習平台★ 一個設計結構化網路學習社群之方法
★ 線上社群系統上可客製化機制之設計與實作★ 無線環境下支援高互動學習之通訊伺服器設計
檔案 [Endnote RIS 格式]    [Bibtex 格式]    [相關文章]   [文章引用]   [完整記錄]   [館藏目錄]   [檢視]  [下載]
  1. 本電子論文使用權限為同意立即開放。
  2. 已達開放權限電子全文僅授權使用者為學術研究之目的,進行個人非營利性質之檢索、閱讀、列印。
  3. 請遵守中華民國著作權法之相關規定,切勿任意重製、散佈、改作、轉貼、播送,以免觸法。

摘要(中) 本論文探討以寵物作為教育虛擬角色的設計和應用。基於人工智慧和多媒體技術的進步,傳統教育虛擬角色常將電腦模擬成智慧型家教(intelligent tutor),教導學習者,或程度相近的學習同伴(learning companion),與學習者一起互動。然而,不論是智慧型家教或學習同伴,大多採用系統主動策略(system-initiative strategy),電腦掌握主動權,追蹤學習者的認知狀態,並於適當時機介入。本論文則根據學習者主動策略(learner-initiative strategy),提出動物同伴(animal companion)概念,將電腦模擬成需要飼養和照顧的虛擬寵物,以期有助於學習者與虛擬角色的互動。
飼養寵物是人們生活上常見的普遍現象,尤其是孩童,對寵物似乎特別關愛。若分析孩童和寵物的關係,可發現兩點特徵:主動積極態度、情感依附(attachment)關係。這兩點特徵對學習而言,同樣相當重要。學習者應該被鼓勵採取主動積極的態度,專注於學習任務,並且不斷付出。基於這樣的設計理念,本研究實作了動物同伴系統:我的寵物(My-Pet)和我們的寵物(Our-Pet)系統,並應用於開放學習者模型(open learner model)和遊戲式學習(game-based learning)。
我的寵物(My-Pet)是學生所飼養的虛擬寵物,寵物會有不同的需求,為了滿足寵物的需求,學生必須參與學習活動,並通過所規定的評量活動而賺取金幣,學生即利用這些金幣飼養自己的寵物。我們的寵物(Our-Pet)則是小組所共同飼養的虛擬寵物,由小組內的每個成員一起負責飼養和照顧。
為了克服開放學習者模型的使用動機(usage motivation)和互動性(interactivity)兩項挑戰,My-Pet和Our-Pet扮演主動性鏡子(active mirror)的角色,並應用三項設計策略,以期在學生的動機、反思、和成員互動上,帶來更多助益。此外,My-Pet和Our-Pet基於鹽巴設計觀點(salt design perspective),採用鬆散結合架構,連結寵物養成遊戲和不同領域的學習活動,透過寵物訓練、競爭等遊戲要素,以悅趣化的學習方式,鼓勵學生不斷努力付出。
在開放學習者模型應用方面,本研究於一個三十一位國小五年級學生的班級中,進行初步的嘗試試驗,以收集學生對我的寵物和我們的寵物 (My-Pet-Our-Pet) 系統、開放學習者模型的反應和回饋。研究結果指出,學生對這樣的開放學習者模型設計,有許多情意面向的正面反應,尤其對My-Pet的關愛和照顧,更甚於Our-Pet。學生為了照顧好My-Pet,有高度的動機願意參與學習活動,並改善自己的學習狀況。
此外,針對遊戲式學習應用方面,本研究採用一個受試者間的實驗設計,以三班共六十八位國小五年級的學生為對象,操作不同版本的我的寵物(My-Pet)系統,進行實驗,用以檢驗數位教材、動物同伴、寵物競爭三者的效用。實驗結果顯示,有動物同伴和寵物競爭的版本,學生的使用動機較數位教材高,尤其是加入寵物競爭的版本,其學習品質(單位時間內的進步幅度)也顯著高於其他兩組。
摘要(英) This study investigates the design of virtual pets as educational virtual characters. In the research field of educational virtual characters, computers are traditionally simulated as intelligent tutors to provide personalized instruction, or as learning companions to provide peer-like interactions based on the technology of artificial intelligence and multimedia technologies. However, most of these systems emphasize the cognitive aspect rather than the affective aspect, and utilize “system-initiative strategy” to monitor the learners’ cognitive status for appropriate interventions. Instead, this study highlights the affective aspect prior to the cognitive aspect, and proposes the concept of animal companion based on the “learner-initiative strategy.” That is, computers are simulated as care-needed pets to motivate learners to learn through game-based learning models.
Pet-keeping is a pervasive culture in the human’s life. People, particularly children, seem to have natural attachment to their pets. Analyzing the keeper-to-pets relationship, we could find two apparent characteristics: responsible attitude and attachment relationship. These two characteristics are also crucial to learning. Learners should be encouraged to be responsible for their learning, and make efforts constantly for long period of time. Therefore, based on such rationales, an animal companion system, My-Pet-Our-Pet, is implemented to explore the design and applications: open learner model and game-based learning.
In terms of open learner model, to overcome the two challenges of usage motivation and interactivity, animal companions are portrayed as open learner models to benefit children’s learning in motivation, reflection, and member interactions. Furthermore, in terms of game-based learning, a loosely-coupling structure invented by a salt design perspective is proposed. Learning activities are incorporated with game activities with the loosely-coupling way. Contrast to the sugar perspective, the salt perspective means that learning requires constant efforts and sweat. Several game elements, such as pet-nurturing, pet-training, and pet-competition, are embedded in to the learning model. The rationale of such design is to make learning more enjoyable and to encourage students’ effort-making learning behaviors.
A trial study was conducted in a 31 fifth-grade pupil classroom for collecting feedbacks and comments on My-Pet-Our-Pet system. A student keeps her own individual animal companion, called My-Pet, which holds the open learner model of the student, and each team has a team animal companion, called Our-Pet, which owns their open group learner model. The results revealed that pupils gave positive affective comments on the portrait of animal companions as open learner model, and were willing to participate in learning activities for taking good care of My-Pet. Nevertheless, the driving force of Our-Pet is not as successful as that of My-Pet.
In addition, a between-subjects experiment was conducted among three fifth-grade classes (totally 68 pupils) to examine the effect of three key components in the My-Pet system: digital content, pet-nurturing, and pet-competition. Therefore, three different versions of My-Pet systems were used by three groups. The result showed that the presence of My-Pet is helpful to the pupils’ perception of enjoyable experience. In addition, the complete version (containing digital content, pet-nurturing, and pet-competition) has a better learning quality. That is, the group got more improved score during a shorter period of time.
關鍵字(中) ★ 虛擬角色
★ 開放性學生模型
★ 學習同伴
關鍵字(英) ★ virtual character
★ open learner model
★ learning companion
論文目次 1. INTRODUCTION 1
1.1 Research on educational virtual characters 1
1.2 Initiative strategy 4
1.3 Motivation 5
1.4 Objective 6
1.5 Organization 7
2. RELATED WORK 8
2.1 Educational virtual character 8
2.2 Open learner model 12
2.3 Implications on pet-keeping 14
2.4 Game-based environment design 16
3. DESIGN OF ANIMAL COMPANIONS 21
3.1 Design rationales 21
3.1.1 Deepening emotional relationship 21
3.1.2 Making learning experience enjoyable 22
3.1.3 Shaping positive belief in learning effort 23
3.2 Animal companion design 25
3.2.1 Meeting two challenges of open learner model 26
3.2.2 Representation of open learner model 27
3.2.3 Representation of open group learner model 29
3.3 Learning model design 31
3.3.1 Pet nurturing mode 31
3.3.2 Individual learning mode 33
3.3.3 Group discussion mode 34
3.3.4 Game competition mode 35
3.4 Applied strategies 37
3.4.1 Learning by care-taking strategy 37
3.4.2 Multiple perspective strategy 39
3.4.3 Game competition strategy 41
4. IMPLEMENTATION: MY-PET-OUR-PET 43
4.1 Implemented versions 43
4.1.1 My-Pet system 43
4.1.2 My-Pet-Our-Pet system 44
4.1.3 My-Pet-Her-Friends system 45
4.1.4 Training My-Pet system 46
4.2 System architecture 48
5. PILOT STUDY 50
5.1 Participants 50
5.2 Procedure 51
5.3 Measurement 51
5.4 Results 52
5.4.1 Cognitive results 52
5.4.2 Affective feedbacks 53
5.5 Discussion 58
6. EXPERIMENT 61
6.1 Participants 61
6.2 Procedure 61
6.3 Measurement 62
6.4 Results 63
6.4.1 Achievement test 63
6.4.2 Motivational scale 65
6.4.3 Time spent on tasks 67
6.5 Discussion 67
7. DISCUSSION AND FUTURE WORK 69
7.1 Discussion 69
7.2 Future work 71
參考文獻 Aïmeur, E., Dufort, H., Leibu, D., and Frasson, C. (1997). Some justifications for the learning by disturbing strategy. In Proceedings of the Eighth World Conference on Artificial Intelligence in Education, 119-126. IOS Press.
Anderson, J. R., Corbett, A. T., Koedinger, K. R., & Pelletier, R. (1995). Cognitive tutors: Lessons learned. The Journal of the Learning Sciences, 4 (2) 167-207.
Amory, A. (2007). Game object model version 2: a theoretical framework for educational game development. Educational Technology Research and Development, 55(1), 51-77.
Bandai (1996). Tamagotchi keychain toy. Website URL: http://www.bandai.com
Barnard, Y. F. & Sandberg, J. A. C. (1996). Self-Explanations, do we get them from our students?, Proceedings of European Conference on AI in Education, Lisbon, 115-121.
Baylor, A. L., Shen, E., & Huang, X. (2003). Which Pedagogical Agent do Learners Choose? The Effects of Gender and Ethnicity. Proceedings of ELearn (World Conference on ELearning in Corporate,Government, Healthcare, & Higher Education). Phoenix, Nov., 2003.
Baylor, A. L., Shen, E., & Warren, D. (2004). Supporting learners with math anxiety: The impact of pedagogical agent emotional and motivational support. Workshop on Social and Emotional Intelligence in Learning Environments, International Conference on Intelligent Tutoring Systems, Maceió, Brazil.
Beck, A. & Katcher, A. (1996). Between pets and people. West Lafayette, IN: Purdue University Press.
Bickmore, T. (2003). Relational Agents: Effecting Change Through Human-Computer Relationships, Ph.D. Thesis, MIT Program in Media Arts and Science.
Bickmore, T. & Picard, R. W. (2004). Establishing and Maintaining Long-Term Human-Computer Relationships, Trans. on Computer-Human Interaction, 12(2), 293-327.
Biswas, G., Leelawong, K., Schwartz, D. & Vye, N. (2005). Learning by Teaching: A New Agent Paradigm for Educational Software. Applied Artificial Intelligence, 19, 363-392.
Biswas, G., Katzlberger, T., Brandford, J. Schwartz, X., & TAG-V. (2001). Extending intelligent learning environments with teachable agents to enhance learning. Artificial Intelligence in Education, J.D. Moore et al. (Eds.) IOS Press, 389–397.
Bloom, B. S. (1984). The 2 Sigma Problem: the search for methods of group instruction as effective as one-to-one tutoring. Educational Researcher, 13, 4–16.
Brophy, S., Biswas, G., Katzlberger, T., Bransford, J., & Schwartz, D. (2000). Teachable agents: Combining insights from learning theory and computer science. International Conference on AI in Education, Le Mans, France.
Bull, S., Greer, J., McCalla, G., Kettel, L. & Bowes, J. (2001). User Modelling in I-Help: What, Why, When and How, in M. Bauer, P.J. Gmytrasiewicz & J. Vassileva (eds), User Modeling 2001: 8th International Conference, Springer-Verlag, Berlin Heidelberg, 117-126.
Bull, S. & Nghiem, T. (2002). Helping Learners to Understand Themselves with a Learner Model Open to Students, Peers and Instructors, in P. Brna & V. Dimitrova (eds), Proceedings of Workshop on Individual and Group Modelling Methods that Help Learners Understand Themselves, International Conference on Intelligent Tutoring Systems 2002, 5-13.
Bull, S. & Pain, H. (1995). 'Did I say what I think I said, and do you agree with me?': Inspecting and Questioning the Student Model, in J. Greer (ed), Proceedings of World Conference on Artificial Intelligence in Education, Association for the Advancement of Computing in Education (AACE), Charlottesville, VA, 1995, 501-508.
Bull, S. (2004). Supporting Learning with Open Learner Models, Proceedings of 4th Hellenic Conference with International Participation: Information and Communication Technologies in Education, Athens, Greece. Keynote.
Bull, S. & McKay, M. (2004). An Open Learner Model for Children and Teachers: Inspecting Knowledge Level of Individuals and Peers, in J.C. Lester, R.M. Vicari & F. Paraguacu (eds), Intelligent Tutoring Systems: 7th International Conference, Springer-Verlag, Berlin Heidelberg, 646-655.
Bull, S. & Kay, J. (2007). Student Models that Invite the Learner In: The SMILI Open Learner Modelling Framework, International Journal of Artificial Intelligence in Education 17(2), 89-120.
Bull, S., & McEvoy, A. (2003). An Intelligent Learning Environment with an Open Learner Model for the Desktop PC and Pocket PC. In U. Hoppe, F. Verdejo & J. Kay (Eds.) Artificial Intelligence in Education: Shaping the Future of Learning through Intelligent Technologies (pp. 389-391). Amsterdam: IOS Press.
Bull, S. & Kay, J. (2005). A Framework for Designing and Analysing Open Learner Modelling, Proceedings of Workshop on Learner Modelling for Reflection, International Conference on Artificial Intelligence in Education 2005, 81-90.
Burton, R. R. & Brown, J. S. (1976). A tutoring and student modeling paradigm for gaming environment. In Colman, R., & Lorton, P. Jr. (Eds), Computer Science and Education, ACM SIGCSE Bulletin, 8(1), 236-246.
Chan, T. W. & Baskin, B. (1988). "Studying With the Prince" the Computer as A Learning Companion. Proceedings of International Conference on Intelligent Tutoring, ITS88, Montreal, Canada, 194-200.
Chan, T. W. & Baskin, B. (1990). Learning Companion Systems. In C. Frasson & G. Gauthier (Eds.), Intelligent Tutoring Systems. New Jersey:Ablex, 6-33
Chan, T.W., Chung, Y.L., Ho, R.G., Hou, W.J. & Lin, G.L. (1992). Distributed learning companion systems - WEST revisited. The 2nd International Conference of Intelligent Tutoring Systems, C. Frasson, G. Gauthier & G. McCalla (Eds.). Lecture Notes in Computer Science, 608, Springer-Verlag, 643-650.
Chan, T. W. (1996). Learning Companion Systems, Social Learning Systems, and the Global Social Learning Club. International Journal of Artificial Intelligence in Education, 7(2), 125-159.
Chan, T. W., & Chou, C. Y. (1997). Exploring the Design of Computer Supports for Reciprocal Tutoring. International Journal ofArtificial Intelligence in Education, 8, 1–29.
Chang, S. B., Deng, Y. C., Cheng, H. N.H., Liao, H. C., Yu, F. Y., & Chan, T. W. (2007). Implementation and Evaluation of EduBingo for Arithmetic Drill. The First IEEE International Workshop on Digital Game and Intelligent Toy Enhanced Learning (pp.99-103). Los Alamitos, CA: IEEE Computer Society.
Chen, Z. H., Deng, Y. C., Chou, C. Y., & Chan, T. W. (2005a). Motivating Learners by Nurturing Animal Companions: My-Pet and Our-Pet, Proceedings of 12th International Conference on Artificial Intelligence in Education, Amsterdam, Netherlands, 136-143.
Chen, Z. H., Deng, Y. C., Chou, C. Y., & Chan, T. W. (2005b). Animal companions as motivators for teammates helping each other learn, Proceedings of 5th International Conference on Computer Supported Collaborative Learning, Taipei, Taiwan, 43-47.
Chen, Z. H., Chou, C. Y., Deng, Y. C., & Chan, T. W. (2007). Active Open Learner Models as Animal Companions: Motivating Children to Learn through Interacting with My-Pet and Our-Pet. International Journal of Artificial Intelligence in Education, 17(2), 145-167.
Chen, Z. H., Liao, C. C. Y., & Chan, T. W. (2007). My-Pet-and-Her-Friends: identifying educational roles of animal companions in game-based learning environment. The first IEEE international workshop on digital game and intelligent toy enhanced learning (DiGiTEL 2007), JhongLi, Taiwan.
Cheng, H. N. H., Deng, Y. C., Chang, S. B., & Chan, T. W. (2007). EduBingo: Design of Multi-level Challenges of a Digital Classroom Game. The First IEEE International Workshop on Digital Game and Intelligent Toy Enhanced Learning (pp.11-18). Los Alamitos, CA: IEEE Computer Society.
Chou, C. Y., Chan, T. W. & Lin, C. J. (2003). Redefining the Learning Companion: the Past, Present, and Future of Educational Agents. Computers and Education, 40, 255-269.
Corbett, A. T. & Bhatnagar, A. (1997). Student Modeling in the ACT Programming Tutor: Adjusting a Procedural Learning Model with Declarative Knowledge, User Modeling: Proceedings of 6th International Conference, Springer Wien New York, 243-254.
Crawford, C. (1982). The art of computer game design. Berkeley, CA: Osborne/McGraw-Hill.
Csikszentmihalyi, M. (1975). Beyond boredom and anxiety. San Francisco: Jossey-Bass.
Csikszentmihalyi, M. (1990). Flow: The psychology of optimal experience. New York: Harper & Row.
de Vicente, A., & Pain, H. (1999). Motivation self-report in ITS. Proceedings of the Ninth World Conference on Artificial Intelligence in Education, 648–650.
de Vicente, A., & Pain, H. (2002). Informing the detection of the students' motivational state: an empirical study. Proceedings of the Sixth International Conference on Intelligent Tutoring Systems, 933-943.
del Soldato, T. and du Boulay, B. (1995). Implementation of motivational tactics in tutoring systems. Journal of Artificial Intelligence in Education, 6(4):337–378.
Davis, J. M., K. Leelawong, K. Belynne, R. Bodenheimer, G. Biswas, N. Vye and J. Bransford (2003). Intelligent User Interface Design for Teachable Agent Systems. International Conference on Intelligent User Interfaces, Miami, Florida (pp. 22-33). The Association for Computing Machinery.
Dempsey, J. V., Rasmussen, K., Haynes, L. L., & Casey, M. S. (1997). An Exploratory Study of Forty Computer Games (COE Technical Report No. 97-2): University of South Alabama.
Dickey, M. (2007). Game design and learning: a conjectural analysis of how massively multiple online role-playing games (MMOROGs) foster intrinsic motivation. Educational Technology & Society, 55, 253-273.
Dillenbourg, P., & Self, J. (1992). People power: a human–computer collaborative learning system. C. Frasson, G. Gauthier, & G. McCalla (Eds.). The 2nd International Conference of Intelligent Tutoring Systems, Lecture Notes in Computer Science, 608, Springer-Verlag, 651–660.
Dimitrova, V. (2003). StyLE-OLM: Interactive Open Learner Modelling, International Journal of Artificial Intelligence in Education 13(1), 35-78.
Dweck (2000). Self-theories:Their Role in Motivation, Personality, and Development, Essays in Social Psychology. Philadelphia, PA: Psychology Press.
Elliott, C., Rickel, J., & Lester, J. (1999). Lifelike Pedagogical Agents and Affective Computing: An Exploratory Synthesis. Artificial Intelligence Today, 1999, 195-211.
Ertmer, P. A., & Newby, T. J. (1996). The Expert Learner: Strategic, Self-Regulated, and Reflective. Instructional Science, 24:1-24.
Gee, J. P. (2003). What video games have to teach us about learning and literacy. New York: Palgrave/Macmillan.
Grand, S., Cliff, D., & Malhotra, A. (1997). Creatures: Artificial Life Autonomous Software Agents for Home Entertainment. In Proceedings of the First Intl. Conference on Autonomous Agents, Minneapolis, ACM Press, 22-29.
Gulz, A. (2004). Benefits of Virtual Characters in Computer Based Learning Environments: Claims and Evidence. International Journal of Artificial Intelligence in Education, 14, 313-334.
Gulz, A. (2005). Social enrichment by virtual characters – differential benefits. Journal of Computer Assisted Learning 21(6), 405-418.
Greer, J., McCalla, G., Collins, J., Kumar, V., Meagher, P. & Vassileva, J. (1998). Supporting Peer Help and Collaboration in Distributed Workplace Environments, International Journal of AI and Education. 9, 159-177,
Greer, J., McCalla, G., Vassileva, J., Deters, R., Bull, S. & Kettel, L. (2001). Lessons Learned in Deploying a Multi-Agent Learning Support System: The I-Help Experience, in J.D. Moore, C.L. Redfield & W. L. Johnson (eds), Proceedings of International Conference on Artificial Intelligence in Education, IOS Press, Amsterdam, 410-421.
Graesser, A. C., Ventura, M., Jackson, G. T., Mueller, J., Hu, X., & Person, N. (2003). The impact of conversational navigational guides on the learning, use, and perceptions of users of a web site. Proceedings of the AAAI Spring Symposium 2003 on Agent-mediated Knowledge Management. AAAI Press.
Goodman, B., Soller, A., Linton, F., & Gaimari, R. (1998). Teaching tactics and dialog in AutoTutor. International Journal of Artificial Intelligence in Education, 12, 257-279.
Höök, K., Persson, P., & Sjölinder, M. (2000). Evaluating users' experience of a character-enhanced information space. AI communications: the European Journal on Artificial Intelligence 13, 3, 195-212.
Hietala, P., & Niemirepo, T. (1998). The Competence of Learning Companion Agents. International Journal of Artificial Intelligence in Education, 9, 178-192.
Johnson, W. L., Rickel, J. W. and Lester, J. C. (2000). Animated pedagogical agents: face-to-face interaction in interactive learning environments, International Journal of Artificial Intelligence in Education, 11, 47-78.
Kay, J. (1995). The UM Toolkit for Cooperative User Modelling. User Modelling and User Adapted Interaction 4, 149-196.
Kay, J, (1997) Invited keynote address, Learner know thyself: student models to give learner control and responsibility Halim, Z, T Ottomann, Z Razak, (eds). ICCE'97 International Conference on Computers in Education, 17-24.
Keller, J. M. (1987a). Strategies for stimulating the motivation to learn. Performance & Instruction, 26 (8), 1-7.
Keller, J. M. (1987b). Development and use of the ARCS Model of instructional design. Journal of Instructional Development, 10 (3), 2-10.
Leelawong, K., Davis, J., Vye, N., Biswas, G., Schwartz, D., Belynne, T., Katzlberger, T., & Bransford, J. (2002). The effects of feedback in supporting learning by teaching in a teachable agent environment. In P. Bell, R. Stevens, & T. Satwicz (Eds.), Keeping Learning Complex: The Proceedings of the Fifth International Conference of the Learning Sciences (ICLS) (pp. 245-252). Mahwah, NJ: Erlbaum.
Lepper, M., & Malone, T. (1987). Intrinsic motivation and instructional effectiveness in computer-based education. In R. Snow & M. Farr (Eds.), Aptitude, learning, and instruction (Vol. 3, pp. 255-286). Hillsdale, NJ: Erlbaum.
Lester, J., Converse, S., Kahler, S, Barlow, S., Stone, B., & Bhoga, R. (1997). The Persona Effect: Affective Impact of Animated Pedagogical Agents. In Proceedings of CHI 97, Atlanta.
Lester, J.C., Towns, S.G. and Fitzgerald, P.J. (1999). Achieving affective impact: visual emotive communication in lifelike pedagogical agents, 10, 278-291.
Levinson, B. M. (1969). Pet-oriented child psychotherapy. Springfield, Ill: Charles C. Thomas.
Malone, T. W. (1981). Toward a theory of intrinsically motivating instruction. Cognitive Science, 5(4), 333-369.
Malone, T. W., & Lepper, M. R. (1987). Making learning fun: A taxonomy of intrinsic motivations for learning. In R. E. Snow & M. J. Farr (Eds.), Aptitude, learning, and instruction, Ⅲ: Conative and affective process analysis. Hillsdale, NJ: Lawrence Erlbaum Associates, 223-225.
Manske, M., & Conati, C. (2005) Modeling Learning in Educational Games. Proceedings of the International Conference on Artificial Intelligence in Education, 411-418.
Melson, G. F. (2001). Why the wild things are: Animals in the lives of children. Cambridge, MA: Harvard University Press.
Mitrovic, A. & Martin, B. (2002). Evaluating the Effects of Open Student Models on Learning, in P. De Bra, P. Brusilovsky & R. Conejo (eds), Adaptive Hypermedia and Adaptive Web-Based Systems, Proceedings of Second International Conference, Springer-Verlag, Berlin Heidelberg, 296-305.
Mitrovic, A., & Martin, B. (2007). Evaluating the effect of open student models on self-assessment. International Journal of Artificial Intelligence in Education, 17(2): 121-144, 2007.
Myers, O. E. (1998). Children and animals. Boulder, CO: Westview Press.
Norman, D. A. (1993). Things That Make Us Smart: Defending Human Attributes in the Age of the Machine. New York: Addison-Wesley Publishing.
Nichols, D. (1994). Issues in designing learning by teaching systems. In Proceedings ofthe East-West International Conference on Computer Technologies in Education (EW-ED’94), 176–181.
Pesce, M. (2000). The playful world: how technology is transforming our imagination. New York: Random House.
Picard, R. W. (1997). Affective Computing, MIT Press, Cambridge.
Prensky, M. (2001). Digital game-based learning. NY: McGraw-Hill.
PF. Magic / Mindscape (1995). Dogz and Catz: Your Virtual Petz, Babyz. Website URLs: http://www.petz.com and http://www.babyz.net
Ransome, P (2005) Work, Consumption and Culture: Affluence and Social Change in the Twenty First Century, London: Sage.
Reeves, B., & Nass, C. (1996). The Media Equation: How People Treat Computers, Television and New Media Like Real People and Places. New York: CSLI.
Rieber, L. P. (1996). Seriously considering play: Designing interactive learning environments based on the blending of microworld, simulations, and games. Educational Technology Research and Development, 44(2), 43-58.
Ryokai, K., Vaucelle, C., & Cassell, J. (2003). Virtual peers as partners in storytelling and literacy learning. Journal of Computer Assisted Learning, 19, 195-208.
Slavin, R. E. (1990) Cooperative learning: Theory, research, and practice. Englewood Cliffs, NJ: Prentice-Hall.
Schunk, D. H., & Zimmerman, B. J. (1998). Self-Regulated Learning: From Teaching to Self-Reflective Practice. New York: Guilford Press.
Self, J. A. (1974). Student models in computer-aided instruction. International Journal ofMan–Machine Studies, 6, 261-276.
Self, J. A. (1988). Bypassing the intractable problem of student modeling. Proceedings of Intelligent Tutoring Systems, 88, Montreal, Canada.
Self, J. A. (1999). The defining characteristics of intelligent tutoring systems research: ITSs care, precisely. International Journal of Artificial Intelligence in Education, 10(3-4), 350-364.
Sony Electronics (1999). Aibo robot dog. Website URL: http://www.world.sony.com/ robot/get/meet.html
Stern, A. (2002). Creating Emotional Relationships With Virtual Characters. Chapter in Emotions in Humans and Artifacts, In R. Trappl, P. Petta, and S.Payr (Eds.), MIT Press.
Tanimoto, S. (2005). Dimensions of transparency in open learner models. Workshop on Learner Modelling for Reflection, to Support Learner Control, Metacognition and Improved Communication between Teachers and Learners, 12th International Conference on Artificial Intelligence in Education, Amsterdam, the Netherlands.
Tholander, J., Karlgren, K., Rutz, F., Johannesson, P., & Ramberg, R. (1999). Design and Evaluation of an Apprenticeship Setting for Learning object-Oriented Modelling. 7th International Conference on Computers in Education, Chiba, Japan.
Tiger Electronics (1998). Furby toy. Website URL: http://www.furby.com
Trappl, R., Petta, P., and Payr, S., eds. (2001). Emotions in Humans and Artifacts. MIT Press.
Vassileva, J., Greer, J., & McCalla, G. (1999). Openness and disclosure in multi-agent learner models. In R. Morales, H. Pain, S. Bull and J. Kay (eds), Proceedings of the Workshop on Open, Interactive, and Other Overt Approaches to Learner Modelling, held in conjunction with AIED 99, Lemans, France.
Vassileva, J., Deters, R., McCalla, G. Greer, J., Bull, S. & Kettel, L. (2001). Deploying I-Help: Some Software Engineering and Social Lessons, in J. Vassileva (ed), Proceedings of Workshop on Multi-Agent Based Learning Environments, International Conference on Artificial Intelligence in Education 2001.
Vygotsky, L.S. (1978). Mind in society: The development of higher psychological processes. Cambridge, MA: Harvard University Press.
Van Labeke, N., Brna, P. and Morales, R. (2007). Opening up the Interpretation Process in an Open Learner Model. 17(3), 305-338.
Weiner, B. Niernberg, R., & Goldstein, M. (1976). Social learning (locus of control) versus attributional (causal stability) interpretations of expectancy of success. Journal of Personality, 44, 52–68.
Weiner, B. (1985). An attributional theory of achievement motivation and emotion. Psychological Review, 92(4), 548-573.
Weiner, B. (1992). Attributional theories of human motivation. In B. Weiner (Ed.), Human motivation: Metaphors, theories, and research. Newbury Park, CA: Sage.
Wenger, E. (1987). Artificial Intelligence and Tutoring Systems. Los Altos, CA: Morgan Kaufmann.
Webster, N. C. (1998), Tamagotchi, Advertising Age, 69(26), 43.
Weber, G. & Brusilovsky, P. (2001). ELM-ART: An Adaptive Versatile System for Web-Based Instruction, International Journal of Artificial Intelligence in Education 12(4), 351-384.
Wu, W., Cheng, H. N.H., Chiang, M. C., Deng, Y. C., Chou, C. Y., Tsai, C. C., & Chan, T. W. (2007). AnswerMatching: A Competitive Learning Game with Uneven Chance Tactic. The First IEEE International Workshop on Digital Game and Intelligent Toy Enhanced Learning (pp.89-96). Los Alamitos, CA: IEEE Computer Society.
Zapata-Rivera, J. D. & Greer, J. E. (2002). Exploring Various Guidance Mechanisms to Support Interaction with Inspectable Learner Models, Intelligent Tutoring Systems: 6th In-ternational Conference, Springer-Verlag, Berlin, Heidelberg, 442-452.
指導教授 陳德懷(Tak-Wai Chan) 審核日期 2008-7-21
推文 facebook   plurk   twitter   funp   google   live   udn   HD   myshare   reddit   netvibes   friend   youpush   delicious   baidu   
網路書籤 Google bookmarks   del.icio.us   hemidemi   myshare   

若有論文相關問題,請聯絡國立中央大學圖書館推廣服務組 TEL:(03)422-7151轉57407,或E-mail聯絡  - 隱私權政策聲明