壹、 中文部份
方崇雄、黃敏蕙(2005)。成人網路學習行為對學習滿意度之影響。「第九屆全球華人計算機教育應用大會」發表之論文，美國夏威夷。
王文中、呂金燮、吳毓營、張郁雯，張淑慧(1999)。教育測驗與評量。臺北市：五南。
王如哲(2010)。解析「學生學習成效」。評鑑雙月刊，(27)，財團法人高等教育評鑑中心基金會，62-62。
余民寧(1997)。有意義的學習：概念構圖之研究。臺北市：商鼎。
林珊如、劉旨峰、袁賢銘(2001)。技術學院資訊相關科系學生的電腦病毒之迷思概念研究。資訊與教育，86，51-61。
林師模、陳苑欽 (2003)。多變量分析管理上的應用。臺北市：雙葉書廊。
林 華(1995)。認知型態與遊歷輔助工具種類對超媒體學習系統中使用者表現與態度之影響(未出版之碩士論文)。國立交通大學，新竹市。
林曉妮(1997)。電腦態度與電腦素養的影響因素探討—小學生的實地實驗研究(未出版之碩士論文)。國立中央大學，桃園市。
邱皓政 (2005)。量化研究法(一)：研究設計與資料處理。臺北市：雙葉書廊。
邱美虹(2000)。概念改變研究的省思與啓示。科學教育學刊，8(1)，1-34。邱貴發(1992)。電腦輔助教學成效探討。視聽教育雙月刊，33(5)，11-18。
姜善鑫(1998)。地理科迷思概念探討。「國民中學學生概念學習學術研討會」發表之論文，台灣大學教務處教育學程中心，109。
張芳全(2009)。家長教育程度與科學成就之關係 : 文化資本、補習時間與學習興趣為中介的分析，教育研究與發展期刊，5（4），39-76。張春興、林清山( 1981 )。教育心理學。臺北市：東華。
張春興(1998)。張氏心理學辭典。臺北市：東華。
程炳林、林清山(2001)。中學生自我調整學習量表的建構及其信、效度研究。中國測驗學會測驗年刊，48（1），1-41。黃萬益(1975)。國小學生學習適應問題之研究。新竹師專學報，146-182。
黃俊英(1991) 。行銷研究管理與技術(4 ed.)。臺北市：華泰。
黃俊英(1999) 。多變量分析(7 ed.)。臺北市：華泰書局。
黃國彥(2000)。實地實驗(Field Experiment)。教育大辭書，取自
http://terms.naer.edu.tw/detail/1313026/?index=17
教育部(2003)。國民小學九年一貫課程綱要重大議題。臺北市：教育部。教育部(2014)。十二年國民基本教育課程綱要總綱。臺北市：教育部。
梁雅琇、張義斌、鄭承昌(2006)。電腦病毒迷思概念。「2006台灣教育傳播暨科技學會」發表之論文。台北：台灣師範大學。
郭重吉(1988)。從認知觀點探討自然科學的學習。教育學院學報，13，351-379。
郭重吉(1989)。從認知觀點探討科學教育的理論與實際。臺北市：國科會科教處。
郭重吉(1998)。從認知的觀點探討自然科學的學習。教育學院學報，1，352-378。
陳啟明(1991)。發展紙筆測驗以探究高一學生對直流電路的迷思概念(未出版之碩士論文)。國立彰化師範大學，彰化市。
陳曉莉(2014)。美國紐約州去年資料外洩成本高達13.7億美元。取自http://www.ithome.com.tw/news/89437
黃寶鈿(1999)。從幾個學生錯誤概念的實例談理化科的教材教法。「國民中學學生概念學習學術研討會」發表之論文，台北市：國立台灣大學，51-59。
葉連祺(2003)。Bloom 認知領域教育目標分類修訂版之探討。教育研究月刊，105，94-106。
劉興郁(2006)。組織變革知覺、學習動機對學習成效之影響。工研院創新與科技管理研討會。謝安田(1989) )。企業研究方法論。臺北市：著者發行。
趨勢科技(2014)。TrendLabs 研究報告2015年暨未來預測。取自http://www.trendmicro.tw/cloud-content/tw/pdfs/security-intelligence/reports/2015_prediction_tw.pdf
貳、 英文部份
Alavi, M. (1994). Computer-Mediated Collaborative Learning: An Empirical Evaluation. MIS Quarterly, 18, 159-174.
Alavi, M., & Leidner, D. E. (2001). Research commentary: Technology-mediated learning—A call for greater depth and breadth of research. Information Systems Research, 12(1), 1-10.
Anderson, J. R. (1983). The architecture of cognition. Cambridge, MA: Harvard University Press.
Anderson, L. W., Krathwohl, D. R., Airasian, P. W., Cruikshank, K. A., Mayer R. E., Pintrich, P. R., Raths, J., & Wittrock, M. C. (2001). A taxonomy for learning, teaching, and Assessment: A revision of Blooms’ Educational Objectives. New York: Longman.
Arbaugh, J. B., Desai, A., Rau, B., & Sridhar, B. S. (2010). A review of research on online and blended learning in the management disciplines: 1994–2009. Organization Management Journal, 7 (1), 39–55.
Ausubel, D. P., Novak, J. D., & Hanesian, H. (1968). Educational psychology: A cognitive view.
Bastinos, A. Š., & Krisper, M. (2013). Multi-criteria decision making in ontologies. Information Sciences, 222, 593-610.
Berners-Lee, T., Hendler, J., & Lassila, O. (2001). The Semantic Web. Scientific American, 284 (5), 28-37.
Billingsley, P.A. (1982). Navigation through hierarchical menu structures: Does it help to have a map? Proceedings of the Human Factors Society, 26 thAnnual Meeting, 103-107.
Bloom, B. S., Engelahar, M. D., Frust, E. J., Hill, W. H. & Krathwohl, D. R. (1956). Taxonomy of Educational Objective, Handbook1:Cognitive Domain. N.Y. : David McKay.
Brook, A., Briggs, H., & Driver, R. (1984). Aspects of secondary students' understanding of the particulate nature of matter. Leeds: Centre for Studies in Science and Mathematics Education, University of Leeds.
Brown, D.E. (1993). Refocus core intuitions: a concretizing role for analogy in conceptual change. Journal of Research in Science Teaching, 30 (10), 1273-1290.
Browning, J. B. (2010). Open-source solutions in education: Theory and practice. Informing Science.
Burbules, N. C., & Lin, M. C. (1988). Response to contradiction: scientific reasoning during adolescence. Journal of educational psychology, 80, 67-75.
Carek, P. J., Geiger, W., Oelklaus, M. W., James, W., & Karty, A. M. (2013). Impact of reflective learning on physicians’ attitudes and care. Journal of Contemporary Medical Education, 1(3), 181-186.
Carey, S. (1986). Cognitive science and science education. American Psychologist, 41, 1123-1130.
Chang, S. H., Chen, M. L., Kuo, Y. K., & Shen, Y. C. (2011). A Simulation-Based LED Design Project in Photonics Instruction Based on Industry–University Collaboration. IEEE Transactions on Education, 54(4), 582-589.
Chen, C. H. & She, H.C. (2012). The impact of Recurrent On-line Synchronous Scientific Argumentation on Students’ Argumentation and Conceptual Change. Educational Technology & Society, 15(1), 197-210.
Cheng, Y. M. (2011). Antecedents and consequences of E-learning acceptance. Information Systems Journal, 21(3), 269–299.
Chi, M. T., & Giere, R. (1992). Conceptual change within and across ontological categories: Implications for learning and discovery in sciences. In R. Giere (Ed.), Cognitive models of science: Minnesota studies in the philosophy of science, 129-186.
Chi, M. T. H., Slotta, J. D., & deLeeuw, N. (1994). From things to processes: A theory of conceptual change for learning science concepts, Learning and Instruction, 4, 27-43.
Chinn, C. A., & Brewer, W. F. (1993). The role of anomalous data in knowledge acquisition: A theoretical framework and implications for science instruction. Review of educational research, 63(1), 1-49.
Cohen, F. (1984). Computer Viruses - Theory and Experiments, Computers & Security, 6(1), 22-35.
Compeau, D. R., & Higgins, C. A. (1995). Computer self-efficacy: Development of a measure and initial test. MIS quarterly, 189-211.Cordova, J. R., Sinatra, G. M., Jones, S. H., Taasoobshirazi, G., & Lombardi, D. (2014). Confidence in prior knowledge, self-efficacy, interest and prior knowledge: Influences on conceptual change. Contemporary Educational Psychology, 39(2), 164-174.
Dewey, J. (1963). Experience and education. New York: Collier Books.
Djellali Choukri.( 2014). A New Distributed Expert System to Ontology Evaluation, Computer Science, 37, 48-55.
Driver, R. (1989).Students’ conceptions and the learning of science, International Journal of Science Education, 11, 481-490.
Duffy, T. M., Lowyck, J., & Jonassen, D. H., (1993). Designing environment for constructive learning. Heidelberg: Spring-Verlag.
Duit, R., & Treagust, D. F. (2003). Conceptual change: A powerful framework for improving science teaching and learning. International Journal of Science Education, 25, 671–688.
Dunteman, G. H. (1994). Principal component analysis. In M. S. Lewis-Beck (Eds.), Factor analysis and related techniques, 157-245.
Ebel, R., & Frisbie, D. (1991). Essentials of Educational Measurement. Prentice-Hall, Englewood Cliffs.
Erozel, G., Cicekli, N. K., & Cicekli, I. (2008). Natural language querying for video databases. Information Sciences, 178(12), 2534-2552.
Fan, J., Gao, Y., & Luo, H. (2008). Integrating concept ontology and multitask learning to achieve more effective classifier training for multilevel image annotation. IEEE Transactions on Image Processing, 17(3), 407-426.
Gider, F., Likar, B., Kern, T., & Miklavcic, D. (2012). Implementation of a multidisciplinary professional skills course at an electrical engineering school. IEEE Transactions on Education, 55(3), 332-340.
George, C. Y. (2013). Accelerated approach to primary school English education in China: Three case studies. In Self-directed Learning Oriented Assessments in the Asia-Pacific, 335-357.
Goetz, J. P., & LeCompte, M. D. (1984). Ethnography and qualitative design in educational research, 19, Orlando, FL: Academic Press.
Gotoda, N., Sakurai, Y., Matsuura, K., Nakagawa, K., & Miyaji, C. (2013). A Server-Based System Supporting Motor Learning through Real-Time and Reflective Learning Activities. In Human-Computer Interaction. Applications and Services, 84-93.
Gruber, T. R. (1993). A translation approach to portable ontology specifications. Knowledge Acquisition, 5(2), 199–220.
Gruber, T. R. (1995). Toward principles for the design of ontologies used for knowledge sharing. International Journal of Human and Computer studies, 43(5), 907–928.
Gruber, T. R. (2000). The Pragmatics of Ontology as Language, Contract, and Content. Third Annual Bio-Ontologies Meeting (Bio-Ontologies 2000), San Diego, CA.
Guarino, N. (1997). Understanding, building and using ontologies. International Journal of Human-Computer Studies, 46(2), 293-310.
Güne, M. H., Güne, O., & Hoplan, M. (2011). The using of computer for elimination of misconceptions about photosynthesis. Procedia-Social and Behavioral Sciences, 15, 1130-1134.
Gupta, M., & Gramopadhye, K. (1995). An evaluation of different navigational tools in using hypertext. Computers and Industrial Engineering, 29, 437-41.
Hartley, R. (2010). The evolution and redefining of ‘CAL’: a reflection on the interplay of theory and practice. Journal of Computer Assisted Learning, 26(1), 4–17.
Hazman, M., El-Beltagy, S. R., & Rafea, A. (2011). Survey of Ontology Learning Approaches. International Journal of Computer Applications, 22, 0975 – 8887.
Head, J. (1986). Research into Alternative Frameworks: promise and problems. Research in Science & Technological Education, 4(2), 203-211.
Hendler, J. (2001). Agents and the Semantic Web. IEEE Intelligent System, 16(2), 30-37.
Hidi, S., & Renninger, K. A. (2006). The four-phase model of interest development, Educational Psychologist, 41(2), 111-127.
Hobson, S. M., Trundle, K. C., & Sackes, M. (2010).Using a planetarium software program to promote conceptual change with young children. Journal of Science Education and Technology, 19(2), 165–176.
Huang, T. H., Liu, Y. C., & Chang, H. C. (2012). Learning achievement in solving word-based mathematical questions through a computer-assisted learning system. Educational Technology & Society, 15(1), 248-259.
Kara, S., Alan, Ö., Sabuncu, O., Akpınar, S., Cicekli, N. K., & Alpaslan, F. N. (2012). An ontology-based retrieval system using semantic indexing. Information Systems, 37(4), 294-305.
Kelly, R. M., Phelps, A. J., & Sanger, M. J. (2004). The effects of a computer animation on students’ conceptual understanding of a can-crushing demonstration at the macroscopic, microscopic, and symbolic levels. The Chemical Educator, 9(3), 184–189.
Kirtman, L. (2009). Online versus in-class courses: An examination of differences in learning outcomes. Issues in Teacher Education, 18(2), 103-116.
Kozma, R., Chin, E., Russell, J., & Marx, N. (2000). The roles of representations and tools in the chemistry laboratory and their implications for chemistry learning. The Journal of the Learning Sciences, 9(2), 105–143.
Kroeker, K. L. (2010). Engineering the Web’s third decade. Communications of the ACM, 53(3), 16–18.
Leasure, A. R., Davis, L., & Thievon, S. L. (2000). Comparison of student outcomes and preferences in a traditional vs. World Wide Web based baccalaureate nursing research course. Journal of Nursing Education, 39(4), 149–154.
Lee, C.Q., & She, H.C. (2010). Facilitating Students' Conceptual Change and Scientific Reasoning Involving the Unit of Combustion. Research in Science Education, 40(4), 479-504.
Leger, P. M., Charland, P., Feldstein, H. D., Robert, J., Babin, G., & Lyle, D. (2011). Business simulation training in information technology education: guidelines for new approaches in IT training. Journal of Information Technology Education, 10(1), 39–53.
Leidner, D., & Jarvenpaa, S. (1995). The use of information technology to enhance management school education: At heoretical view. MIS Quarterly, 19(3), 265-291 .
Leidner, D. E., & Jarvenpaa, S. L. (1995). The use of information technology to enhance management school education: A theoretical view. MIS quarterly, 265-291.
Lenci, A. (2001). Building an Ontology for the Lexicon: Semantic Types and Word Meaning, In Ontology-Based Interpretation of Noun Phrases: Proceedings of the First International OntoQuery Workshop, University of Southern Denmark, 103-120.
Liao, Y.W., & She, H.C. (2009). Enhancing Eight Grade Students’ Scientific Conceptual Change and Scientific Reasoning through a Web-based Learning Program. Educational Technology & Society, 12(4), 228-240.
Liao, Y.W. & She, H.C. (2009). Enhancing Eight Grade Students’ Scientific Conceptual Change and Scientific Reasoning through a Web-based Learning Program. Educational Technology & Society, 12(4), 228-240.
Liu, S. H., Liao, H. L., & Pratt, J. A. (2009). Impact of media richness and flow on e-learning technology acceptance. Computers and Education, 52(3), 599–607.
Lyons, N., Halton, C., & Freidus, H. (2013). Reflective inquiry as transformative self-study for professional education and learning. Studying Teacher Education, 9(2), 163–174.
MacDermott, S. (2013). Using a blog as a tool for reflective learning in nurse education. In EDULEARN13 proceedings, 1431–1434.
Mariana, G., & Hewson, A. B. (1985). The role of intelligence environment in the origin of conceptions: An explanatory study. In L.H. T. West, & A. L. Pines, (Eds.),Cognitive structure and conceptual change. Orlando, FL: Academic Press.
McCormick, R. (2004). Issues of Learning and Knowledge in Technology Education, International Journal of Technology and Design Education, 14(1), 21-44.
Merrick, K. E. (2010). An empirical evaluation of puzzle-based learning as an interest approach for teaching introductory computer science. IEEE Transactions on Education, 53(4), 677-680.
Miller, G. A. (1968). The magical numer seven, plus or minus two: Some limits on our capacity for processing information. Psychological Review, 63, 81-97.
Moreno, A., Isern, D., & Fuentes, A. C. L. (2013). Ontology-based information extraction of regulatory networks from scientific articles with case studies for escherichia coli. Expert Systems with Applications, 40(8), 3266-3281.
Natalya, F. N., & Deborah, L. M. (2001). Ontology development 101: a guide to creating your first ontology. Stantford Medical Informatics Technical Report, SMI-2001-0880.
Novak, J. D., & Gowin, D. B. (1984). Concept mapping for meaningful learning. In Learning how to learn, 15-54. NY: Cambridge University Press.
Özmen, H., Demircioğlu, H., & Demircioğlu, G. (2009). The effects of conceptual change texts accompanied with animations on overcoming 11th grade students’ alternative conceptions of chemical bonding. Computers & Education, 52(3), 681-695.
Özmen, H. (2011). Effect of animation enhanced conceptual change texts on 6th grade students’ understanding of the particulate nature of matter and transformation during phase changes. Computers & Education, 57(1), 1114-1126.
Park, J. Y., & Son, J. B. (2011). Expression and connection: the integration of the reflective learning process and the writing process into social network sites. Journal of Online Learning and Teaching, 7(1), 170–178.
Pfundt, F., & Duit, R. (1991). Bibliography: Students’ alternative frameworks and science education. (3re ed.). Keil, West Germany:IPN.
Piccoli, G., Ahmad, R., & Ives B. (2001). Web-based virtual learning environment: Are search framework and a preliminary assessment of effectiveness in basic IT skill training. MIS Quarterly, 25(4), 401-426.
Poslad, S., & Kesorn, K. (2014). A Multi-Modal Incompleteness Ontology model (MMIO) to enhance information fusion for image retrieval. Information Fusion, 20, 225-241.
Posner, G. J., Strike, K. A., Hewson, P. W., & Gertzog, W. A. (1982). Accommodation of as scientific conception: toward a theory of conceptual. Science Education, 66(2), 211-277.
Potting, M., Sniekers, M., Lamers, C., & Reverda, N. (2010). Legitimizing social work: the practice of reflective professionals. Journal of Social Intervention: Theory and Practice, 19(3), 6–20.
Pradhan, M., & Dev, P. (1993). Conceptual change and computer-assisted instruction. In Proceedings of the seventeenth annual symposium on computer applications in medical care, Washington DC, 786–790.
Sornkhatha, P., & Srisawasdi, N. (2013). Supporting Conceptual Development in Newton's Laws of Motion Using an Interactive Computer-simulated Laboratory Environment. Procedia-Social and Behavioral Sciences, 93, 2010-2014.
Riaño, D., Real, F., LóPez-Vallverdú, J. A., Campana, F., Ercolani, S., Mecocci, P., ... & Caltagirone, C. (2012). An ontology-based personalization of health-care knowledge to support clinical decisions for chronically ill patients. Journal of biomedical informatics, 45(3), 429-446.
Rue, J., Font, A., & Cebrian, G. (2013). Towards high-quality reflective learning amongst law undergraduate students: analysing students’ reflective journals during a problem based learning course. Quality in Higher Education, 19(2), 191–209.
Sackes, M., & Trundle, K. C. (2010). The role of metaconceptual awareness in the change and the durability of conceptual understandings. In Paper presented at the annual meeting of the National Association of Research in Science Teaching, Philadelphia, PA, March , 20–24.
Salcedo, C. S. (2010). Comparative Analysis Of Learning Outcomes In Face-To-Face Foreign Language Classes Vs. Language Lab And Online. Journal of College Teaching & Learning, 7(2), 43-54.
Sandoval, W. A., & Reiser, B. (2004). Explanation-Driven Inquiry: Integrating Conceptual and Epistemic Scaffolds for Scientific Inquiry. Science Education, 88(3), 345-372.
Scagnoli, N. I., Buki, L. P., & Johnson, S. D. (2009). The influence of online teaching on face-to-face teaching practices. Journal of Asynchronous Learning Networks, 13(2), 115-128.
Shannon, C. E. (1948). A Mathematical Theory of Communication, The Bell System Technical Journal, 27, 379–423, 623–656.
She, H. C. (2002). Concepts of a higher hierarchical level require more dual situated learning events for conceptual change: a study of air pressure and buoyancy. International journal of science education, 24(9), 981-996.
She, H. C. (2003). DSLM Instructional Approach to Conceptual Change Involving Thermal Expansion. Research in Science and Technological Education, 21(1), 43-54.
She, H. C. (2004a). Fostering Radical Conceptual Change through Dual-Situated Learning Model. Journal of Research in Science Teaching, 41(2), 142-164.
She, H. C. (2004b). Facilitating changes in ninth grade students’ understanding of dissolution and diffusion through DSLM instruction. Research in science education, 34, 503-525.
She, H. C. (2005). Enhancing eighth grade students' learning of buoyancy: The interaction of teachers' instructional approach and students' learning preference styles. International Journal of Science and Mathematics Education, 3(4), 609-624.
She, H. C., & Fisher, D. (2003). Web-based e-learning environment in Taiwan: The impact of the online science flash program on students’ learning. Technology-rich learning environments: A future perspective, 343-368.
She, H.C., & Lee, C.Q. (2008). SCCR Digital Learning System for Scientific Conceptual change and Scientific Reasoning. Computers & Education, 51(2), 724-742.
She, H.C., & Liao, Y.W. (2010). Bridging Scientific Reasoning and Conceptual Change through Adaptive Web-based Learning. Journal of Research in Science Teaching, 47(1), 91–119.
Shuell, T. (1986 ). Cognitive conceptions of learning. Review of Educational Research, 54(4), 411-436 .
Snow, R. E. (1980). Aptitude, learner control, and adaptive instruction. Educational Psychologist, 15(3), 151-158.
Solskinnsbakk, G., & Gulla, J. A. (2010). Combining ontological profiles with context in information retrieval. Data & Knowledge Engineering, 69(3), 251-260.
Srisawasdi, N., Kerdcharoen, T., & Suits, J. P. (2008). Turning scientific laboratory research into innovative instructional material for science education: Case studies from practical experience. The International Journal of Learning, 15(5), 201-210.
Stipek, D., Feiler, R., Daniels, D., & Milburn, S. (1995). Effects of different instructional approaches on young children's achievement and motivation. Child development, 66(1), 209-223.
Tang, H. Y., She, H. C., & Lee, Y. M. (2005a). The impact of DSLM instruction on middle school students’ conceptual change involving mitosis and Meiosis. In National Association for Research in Science Teaching 2005 World Conference, Dallas, Texas. April.
Tang, H. Y., She, H. C., & Lee, Y. M. (2005b). Promoting middle school students’ conceptual change involving mitosis and meiosis with a DSLM instructional approach. In National Association for Research in Science Teaching 2005 World Conference, Dallas, Texas. April.
Termtachatipongsa, P. (2014). Instructional Context, Motivational Beliefs, Attitude and Strategies in Teaching Genetics for Conceptual Change.Social and Behavioral Sciences, 116, 2023-2029.
Ting, C. Y., Sam, Y. C., & Wong, C. O. (2013). Model of conceptual change for INQPRO: A Bayesian Network approach. Computers & Education, 65, 77-91.
Treagust, D. F., & Duit, R. (2008). Conceptual change: a discussion of theoretical, methodological and practical challenges for science education. Cultural Studies of Science Education, 3, 297–328.
Trundle, K. C., & Bell, R. L. (2010). Use of computer simulation to promote conceptual change: a quasi-experimental study. Computers and Education, 54, 1078–1088.
Trundle, K. C., Atwood, R. K., & Christopher, J. E. (2007). A longitudinal study of conceptual change: pre-service elementary teachers’ conceptions of moon phases. Journal of Research in Science Teaching, 44(2), 303–326.
Tytler, R. (1998). The nature of students’ informal science conceptions. International Journal of Science Education, 20(8), 901-927.
Vamvakoussi, X., & Vosniadou, S. (2010). How many decimals are there between two fractions? Aspects of secondary school students' understanding of rational numbers and their notation. Cognition and Instruction, 28(2), 181-209.
Vosniadou, S. (1994). Capturing and modeling the process of conceptual change. Learning and Instruction, 4(1), 45–69.
Vosniadou, S. (2007). The conceptual change approach and its reframing. Reframing the conceptual change approach in learning and instruction, 1–15.
Vosniadou, S., & Brewer, W. F. (1987). Theories of knowledge restructuring in development. Review of educational research, 57(1), 51-67.
Vroom, V. (1964), Work and Motivation. New York: John Wiley & Sons.
Wandersee, J. H., Mintzes, J. J., & Novak, J. D. (1994). Research on alternative conceptions in science. Handbook of research on science teaching and learning, 177, 210.
Wang, A. Y., & Newlin, M. H. (2000). Characteristics of students who enroll and succeed in psychology web-based classes. Journal of Educational Psychology, 92(1), 137–143.
Webster, J., & Hackley, P. (1997). Teaching Effectiveness inTechnology-Mediated Distance Learning. Academy of Management Journal, 40(6), 1282-1310.
William, S., & Austin, T. (1999). Ontologies. IEEE Intelligent System and their Applications, 18-19.
Yalcin, M., & Celikler, D. (2011). The effect of computer-assisted applications in the teaching of “Matter and Heat”. Journal of Educational Research, 11(42), 273–293.
Yeh, K. H., & She, H. C. (2010). On-line synchronous scientific argumentation learning: Nurturing students' argumentation ability and conceptual change in science context. Computers & Education, 55(2), 586-602.
Yi, M. Y., & Davis, F. D. (2003). Developing and validating an observational learning model of computer software training and skill acquisition. Information Systems Research, 14(2), 146-169.