由於時代的轉變，過去的書信與E-mail，漸漸不常為人所使用，而取代之成為新寵的則是新型態的虛擬社群網路，透過社群網路可以達到即時更新資訊，即時訊息傳送，更可同時標記自己目前的所在地。而目前最受歡迎的社群網路系統則是Facebook，除了可以達到前所講的功能外，另還可以分享文章、圖片、影片與音樂等多媒體資訊。在網路上已有許多方式提供學習，例如數位教學、合作學習等。本篇論文目的著重在我們的學習方式可以透過朋友或網路上的朋友所分享的文章、圖片、影片等多媒體資訊來做為一個額外學習的教材。
本系統利用Facebook平台來連結教材推薦系統，此系統藉由使用者登入並授權後將會定時自動取得並蒐集使用者所發佈的多媒體資訊。接著，藉由對多媒體資訊做分類與難度的分級，並將之加入資料庫中，當使用者想透過這套系統來取得推薦資料時，只需要輸入主題及難度等級，系統則會透過蜜蜂演算法最佳化做推薦，推薦使用者可以透過哪些資料進行學習，此方法將有別一般的隨機取得方式，將會更有效率的給予使用者所需要的資料。最後在透過問卷來得到使用者對於這套系統使用的便利性與實用性，並在未來對此系統做出修正。

With the changes of the times, the virtual community network with a new type has become the new favorite instead of the past letters and E-mails which have been gradually infrequently used by people. Through the community network, real-time updates of information and immediate message delivery can be achieved, and even a user can mark his or her current location in the meantime. The most popular social networking site is currently Facebook which enables users to interact with each other, form groups, arrange activities, and also share multimedia data, such as articles, pictures, videos, and music. Many learning methods have been proposed for use online, such as digital teaching, cooperative learning, and so on. This thesis focuses on a learning approach in which people can use multimedia data such as articles, pictures, and videos, shared by friends or other network members, as additional learning materials.
The personalized learning material recommendation system presented in this work connects the Facebook platform with Facebook API, and both obtains and selects the multimedia content posted by other users regularly and automatically after the user logs into the system. The multimedia materials are classified and rated according to difficulty, and then data are stored in a specific database. When a user wants to get recommended information from the system, they enter the related topic and a difficulty rating, and then the system recommends suitable learning materials based on the artificial bee colony algorithm. This method can effectively and efficiently give users more personalized information that can better meet their learning needs. Finally, a questionnaire is applied to gather users' opinions of the system. In future work, the system will be further modified.

Anderson, J. C., & Gerbing, D. W. (1988). Structural equation modeling in practice: A review and recommended two-step approach. Psychological Bulletin, 103 (3), 411-423.
Ajzen, I., & Fishbein, M. (1980). Understanding attitudes and predicting social behavior. Englewood Cliffs, NJ: Prentice-Hall.
Amichai-Hamburger, Y., Wainapel, G., & Fox, S. (2002). On the Internet no one knows I’m an introvert: Extroversion, neuroticism, and Internet interaction. Cyberpsychology & Behavior, 5(2), 125–128.
Baddeley, A.D., & Hitch, G.J. (1974). Working memory. In G.A. Bower (ed.), Recent Advances inLearning and Motivation, Vol. 8 (pp. 47–89). New York: Academic Press.
Boer, J. d., Kommers P. A.M., Brock B. d. (2011). Using learning styles and viewing styles in streaming video. Computers & Education, 56(3), 727-735.
Chin, W. W. (1998a) . The partial least squares approach for structural equation modelling. In G. A. Marcoulides (Ed.), Modern methods for business research (pp. 295-336). Mahwah, New Jersey: Lawrence Erlbaum Associates.
Chin, W. W. (1998b). Issues and Opinion on Structural Equation Modeling. MIS Qyarterly, 22(1), 7-16.
Chin, W. W.,& Newsted, P. R. (1999). Structural equation modeling analysis with small samples using partial least squares. In R. Hoyle (Ed.), Statistical strategies for small sample research (pp. 307–341). California: Sage Publications.
Chiu, C.-F., & Lee, G. C. (2009). A video lecture and lab-based approach for learning of image processing concepts. Computers & Education, 52(2), 313-323.
Cox, M. D., & Myerscough, M. R. (2003). A flexible model of foraging by a honey bee colony: the effects of individual behaviour on foraging success. Journal of Theoretical Biology, 223(2), 179-197.
Davis, F. D. (1986). A technology acceptance model for empirically testing new end-user information systems: theory and results. Ph.D. dissertation, MIT Sloan School of management, Cambridge, MA.
Davis, F. D. , Bagozzi, R. P., & Warshaw, P. R. (1989). User acceptance of computer technology: A comparison of two theoretical model. Management Science, 35(8), 982-1003.
Facebook. (2011). Statistics of Facebook. Retrieved October17, 2011, from http://www.facebook.com/press/info.php?statistics
Fornell, C. R., & Bokkstein, F. L. (1982). Two structural equation models: LISREL and PLS applied to consumer exit-voice theory. Journal of Market Research, 19(4), 440-453.
Hair, J. F., Black, W. C., Babin B. J., Anderson, R. E., & Tatham, R. L. (2006). Multivariate Data Analysis (6th ed.). Upper Saddle River, NJ: Pearson Education.
Hamburger, Y. A., & Ben-Artzi, E. (2000). The relationship between extraversion and neuroticism and the different uses of the Internet. Computers in Human Behavior, 16(4), 441–449.
Huang, T.-C., Huang, Y.-M., & Cheng, S.-C. (2008). Automatic and interactive e-Learning auxiliary material generation utilizing particle swarm optimization. Expert Systems with Applications, 35(4), 2113-2122.
Huang, T.-C., Huang, Y.-M., & Yu, F.-Y. (2011). Cooperative weblog learning in higher education: Its facilitating effects on social interaction, time lag, and cognitive load. Educational Technology & Society, 14(1), 95-106.
Huang, Y.-M., Chen, J.-N., Kuo, Y.-H., & Jeng, Y.-L. (2008). An intelligent human-expert forum system based on fuzzy information retrieval technique. Expert Systems with Applications, 34(1), 446-458.
Huang, Y.-M., Chiu, P.-S., Liu, T.-C., & Chen, T.-S. (2011). The design and implementation of a meaningful learning-based evaluation method for ubiquitous learning. Computers & Education, 57(4), 2291-2302.
Huang, Y.-M., Huang, Y.-M., Huang, S.-H., & Lin, Y.-T. (2012). A ubiquitous English vocabulary learning system: Evidence of active/passive attitudes vs. usefulness/ease-of-use. Computers & Education, 58(1), 273-282.
Huang, Y.-M., Kuo, Y.-H., Lin, Y.-T., & Cheng, S.-C. (2008). Toward interactive mobile synchronous learning environment with context-awareness service. Computers & Education, 51(3), 1205-1226.
Huang, Y.-M., & Liu, C.-H. (2009). Applying adaptive swarm intelligence technology with structuration in web-based collaborative learning. Computers & Education, 52(4), 789-799.
Huang, Y.-M., Lin, Y.-T., & Cheng, S.-C. (2009). An adaptive testing system for supporting versatile educational assessment. Computers & Education, 52(1), 53-67.

Huang, Y.-M., Lin, Y.-T., & Cheng, S.-C. (2010). Effectiveness of a Mobile Plant Learning System in a science curriculum in Taiwanese elementary education. Computers & Education, 54(1), 47-58.
Huang, Y.-M., & Wu, T.-T. (2011). A systematic approach for learner group composition utilizing u-learning portfolio. Educational Technology & Society, 14(3), 102-117.
Kabilan, M. K., Ahmad, N., & Abidin, M. J. Z. (2010). Facebook: An online environment for learning of English in institutions of higher education?, The Internet and Higher Education, 13(4), 179-187.
Karaboga, D. (2005). An idea based on honey bee swarm for numerical optimization. Techn. Rep. TR06, Erciyes Univ. Press, Erciyes.
Karaboga, D., & Akay, B. (2009). A comparative study of artificial bee colony algorithm. Applied Mathematics and Computation, 214(1), 108-132.
Karaboga, D., & Basturk, B. (2007). A powerful and efficient algorithm for numerical function optimization: artificial bee colony (ABC) algorithm. J. of Global Optimization, 39(3), 459-471.
Karaboga, D., & Basturk, B. (2008). On the performance of artificial bee colony (ABC) algorithm. Applied Soft Computing, 8(1), 687-697.
Karaboga, N. (2009). A new design method based on artificial bee colony algorithm for digital IIR filters. Journal of the Franklin Institute, 346(4), 328-348.
Lampe, C., Ellison, N., & Steinfield, C. (2006). A Face(book) in the crowd: Social searching vs. social browsing. Proceedings of the 2006 20th Anniversary Conference on Computer Supported Cooperative Work (pp. 167–170). New York: ACM Press.
Lampe, C., Ellison, N., & Steinfield, C. (2007). A familiar Face(book): Profile elements as signals in an online social network. Proceedings of the SIGCH Conference on Human Factors in Computing Systems (pp. 435-444). New York: ACM Press.
Laurillard, D. (1988). Multimedia and the learner’s experience of narrative. Computers & Education, 31(2), 229–242.
Leijen, Ä., Lam I., Wildschut L., Simons P. R.-J., & Admiraal W. (2009). Streaming video to enhance students’ reflection in dance education. Computers & Education, 52(1), 169-176.
Levie, W.H., & Lentz, R. (1982). Effects of text illustrations: A review of research. EducationalCommunication and Technology Journal, 30(4), 195-232.
Lin, Y. C., Lin, Y. T., & Huang, Y. M. (2011). Development of a diagnostic system using a testing-based approach for strengthening student prior knowledge. Computers & Education, 57(2), 1557-1570.
Lin, Y.-T., Huang, Y.-M., & Cheng, S.-C. (2010). An automatic group composition system for composing collaborative learning groups using enhanced particle swarm optimization. Computers & Education, 55(4), 1483-1493.
Liu, I-F., Chen, M. C., Sun, Y. S., Wible, D., & Kuo, C.-H. (2010). Extending the TAM model to explore the factors that affect Intention to Use an Online Learning Community. Computers & Education, 54(2), 600-610.
Mason, R. (2006). Learning technologies for adult continuing education. Studies in Continuing Education, 28(2), 121-133.
Mayer, R.E., & Anderson, R.B. (1991). Animations need narrations: An experimental test of adual-coding hypothesis. Journal of Educational Psychology, 83(4), 484-490.
Mayer, R. E. (1993). Illustrations that instruct. In R. Glaser (Ed.), Advances in instructional psychology (Vol. 4, pp. 254-284). Hillsdale, NJ: Lawrence Erlbaum Associates.
Mayer, R. E., & Moreno, R. (2003). Nine Ways to Reduce Cognitive Load in MultimediaLearning. Educational Psychologist, 38(1), 43-52.
Mazman, S. G., & Usluel, Y. K. (2010). Modeling educational usage of Facebook. Computers & Education, 55(2), 444-453.
Milgram, S. (1967). The Small World Problem. Psychology Today, 2(1), 60-67.
Najjar, L. J. (1996). Multimedia Information and Learning. Journal of Educational Multimedia and Hypermedia, 5(2), 129-150.
Nie, N. H., & Erbring, L. (2000). Internet and Society: A Preliminary Report. Palo Alto, CA: Stanford Institute for the Quantitative Study of Society Press.
Nosko, A., Wood, E.,& Molema, S. (2010). All about me: Disclosure in online social networking profiles: The case of FACEBOOK. Computers in Human Behavior, 26(3), 406-418.
Nunnally, J. C. (1978). Psychometic theory(2nd ed.). New York: McGraw-Hill.
Paivio, A. (1971), Imagery and verbal processes, New York: Holt, Rinehart & Winston.
Pempek, T. A., Yermolayeva, Y. A., & Calvert S. L. (2009). College students' social networking experiences on Facebook. Journal of Applied Developmental Psychology, 30(3), 227– 238.
Pham, D. T., Castellani, M., & Fahmy, A. A. (2008, 13-16 July 2008). Learning the inverse kinematics of a robot manipulator using the Bees Algorithm. Paper presented at the Industrial Informatics, 2008. INDIN 2008. 6th IEEE International Conference.
Rau, P.-L. P., Gao, Q., & Ding, Y. (2008). Relationship between the level of intimacy and lurking in online social network services. Computers in Human Behavior, 24(6), 2757-2770.
Ringle, C. M., Wende, S.,& Will, A. (2005). SmartPLS-Version 2.0. Germany: University at Hamburg. Retrieved February 20, 2008, from http://www.smartpls.de.
Rosaen, C. L., Degnan, C., VanStratt, T., & Zietlow, K. (2004). Designing a virtual K-12 classroom literacy tour: Learning together as teachers explore “best practice.” In J. Brophy (Ed.), Advances in research on teaching, volume 10: Using video in teacher education (pp. 169-199). New York: Elsevier Science.
Sherin, M. G., & Han, S. Y. (2004). Teacher learning in the context of a video club. Teaching and Teacher Education, 20(2), 163-183.
Wachter, R. M., Gupta, J. N. D., & Quaddus, M. A. (2000). It takes a village: Virtual communties in support of education. International Journal of information Management, 20(6), 473-489
Wang, K. T., Huang, Y.-M., Jeng, Y.-L., & Wang, T.-I. (2008). A blog-based dynamic learning map. Computers & Education, 51(1), 262-278.
Wold, H.(1982). Systems Under Indirect Observation Using PLS. In: C. Fornell(Ed.), A Second Generation of Multivariate Analysis, Vol. 1: Methods (pp. 325-347). New York: Praeger.
Yang, F.-Y., & Tsai, C.-C. (2008). Investigating university student preferences and beliefs about learning in the web-based context. Computers & Education, 50(4), 1284–1303.