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DAFTAR PUSTAKA

Akselaa, M. & Lundell, J. (2008). Computer-based molecular modeling: Finnish School teachers’ experiences and views. Chemistry Education Research and Practice, 9, (4), 301–308.

Ardac, D. & Akaygun, S. (2004). Effectiveness of multimedia-based instruction that emphasizes molecular representations on students’ understanding of chemical change. Journal of Research and Science Teaching. 41,(4),317–

337.

Arikunto, Suharsimi. (2001). Dasar-dasar Evaluasi Pendidikan (Edisi Revisi). Jakarta: Bumi Aksara.

Barke, H. D., Hazari A. & Yitbarek S. (2008). Misconception in Chemistry. Berlin: Springer.

Borg, W.R., et.al. (2003). Educational Research: An Introduction;(Seventh Ed.). Newyork: Longman, Inc

Brown. Theodore L., & Bursten B.E. (2009). Chemistry: The Central Science. (11th Ed.) Upper Saddle River, NJ: Pearson Prentice Hall

Chandrasegaran, Treagust & Mocerino. (2007). Enhancing students’ use of multiple levels of representations to describe and explain chemical reactions. School Science Review, 88, 325-330.

Chittleborough, G. D. & Treagust D.F. (2007). The modeling ability of non-major chemistry students and their understanding of the sub-microscopic level. Chemistry Education Research and Practice, 8:274-292.

Chiu, M.H & Wu, H.K. (2009). The roles of multimedia in the teaching and learning of the triplet relationship in chemistry. In: J.K. Gilbert & D. Treagust (Eds.). Multiple Representations in Chemical Education: Models and Modeling in Science Education. Dordrecht: Springer. pp. 251-283

Cheng, M. & Gilbert, J.K. (2009). Towards a better utilization of diagrams in research into the use of representative levels in chemical education. in: J.K. Gilbert & D. Treagust (Eds.). Multiple Representations in Chemical Education: Models and Modeling in Science Education. Dordrecht: Springer.pp. 55-73.

Dahar, Ratna W. (1996). Teori-teori Belajar. Jakarta: Erlangga.

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Dawley, Lisa. (2007). The Tools for Successful Online Teaching. London: Infoscl.

Davidowitz B. & Chittleborough, G. D. (2009). Linking the macroscopic and sub-microscopic levels : Diagram. In: J. Gilbert & D. Treagust (Eds.). Multiple Representation in Chemical Education: Models and Modeling in Science Education. Dordrecht: Springer. 169-191.

Devetak, Iztok, et al. (2004). Submicroscopic representations as a tool for evaluating students’ chemical conceptions. Acta Chim. Slov., 51, (4),

799:814.

Donovan,W. & Nakhleh, M. (2007). Student use of web-based tutorial materials and understanding chemistry concepts. Journal Comp. Math. and Sci.Tech.

26,(4), 291-327

Falvo, David. (2008). Animations and simulations for teaching and learning molecular chemistry. International Journal of Technology in Teaching and Learning,4(1), 68–77.

Farida, I. (2008). Kemampuan Mahasiswa Merepresentasikan Tingkat Makroskopik, Mikroskopik & Simbolik pada Topik Sintesis Amonia (Skala Lab). Prosiding Seminar Nasional Kimia & Pendidikan Kimia IV. Bandung : FPMIPA UPI

Farida, I., Liliasari, Widyantoro, D.H. & Sopandi, W. (2010). Representational competence’s profile of Pre-Service Chemistry Teachers in chemical problem solving. Proceeding The 4th International Seminar on Science Education. Bandung: SPs UPI

Finatri, Dian. (2007). Analisis konsepsi guru pada konsep larutan ditinjau dari representasi level mikroskopik. Tesis. Bandung:SPs UPI. Tidak diterbitkan. Garrison, D. R., & Vaughan, N. (2008). Blended Learning in Higher Education.

San Francisco: Jossey-Bass.

Gillani, Bijan B. (2003). Learning theories and the design of e-learning environments. Maryland: University Press of America.

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Education. Dordrecht: Springer.1-8

Gilbert, John K. (2005). Visualization: a metacognitive skill in science and science education. In Gilbert, J.K. (Ed.), Visualization in Science Education. Dordrecht: Springer.

Gudimetla, P. & Iyers, R. Mahalinga (2006). The role for e-learning in engineering education: creating quality support structures to complement traditional learning. In Proceedings 17th Annual Conference of The Australasian Association for Engineering Education, Auckland, New Zealand.

Hake, Richard R. (2002). Assessment of student learning in introductory science courses. PKAL Roundtable on The Future: Assessment in The Service of Student Learning. Duke University. [Available online: www.physics.indiana.edu/~hake].

Harrison, A. G., & Treagust, D. F. (2002). The particulate nature of matter: challenges in understanding the submicroscopic world. In Gilbert, J.K et.al (Eds.), Chemical Education: Towards Research-Based Practice. Dordrecht: Kluwer Academic Publishers.

Herron, J. Dudley. (1977). Problems associated with concept analysis. Journal of Science Education,61(2),185 – 199.

Howard, Larry, Zsolt Remenyi, & Gabor Pap. (2006). Adaptive blended learning environments. 9th International Conference on Engineering Education : July 23 – 28.

Horton, William K., (2006). E-learning by Design. San Francisco: Pfeiffer Willey Imprint.

Hughes, J. M., Mitchell, P. A., and Ramson, W. S. (1995). Australian Concise Oxford Dictionary. Melbourne: Oxford University Press.

Kelly, R., & Jones, L. (2005). A qualitative study of how general chemistry students interpret features of molecular animations. Paper Presented at The NationalMeeting of The American Chemical Society, Washington, DC.

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Kozma, R. & Joel Russell. (2004). Multimedia learning of chemistry. In Richard Mayer (Ed.). Cambridge Handbook of Multimedia Learning . On-line version.

Linn, M. C., Davis, E. A. & Bell, P. (Eds.). (2004). Inquiry and technology. Internet Environments for Science Education. New Jersey: Lawrence Erlbaum Associates: 3 – 27

Leahy, W., & Sweller, J. (2004). Cognitive load and the imagination effect. Applied Cognitive Psychology . 18:7, 857-73.

Mammino L. (2008). Teaching chemistry with and without external representations in professional environments with limited resources. In : J.K Gilbert, Reiner & Nakhleh (Eds.). Visualization : Theory and Practice in Science Education. Dordrecht: Springer. pp. 155−185.

Mc Murry, John & Fay, Robert. (2006). Chemistry. Fourth Edition. NewYork : Prentice Hall.

Michalchik, V., Rosenquist, A., Kozma, R., Schank, P., & Kreikemeier, P. (2008). Representational resources for constructing shared understandings in the high school chemistry classroom. In : J.K Gilbert, Reiner & Nakhleh (Eds.). Visualization: Theory and Practice in Science Education. Models and modeling in science education . Dordrecht: Springer. 233-282.

Morgil, I., Yavuz, S., Oskay, Ö. & Seçil, A. (2005). Traditional and Computer-Assisted Learning In Teaching Acids and Bases. Chemistry Education Research andPractice, 6(1), 52-63

Oliver, Martin & Keith Trigwell. (2005). Can ‘blended learning’ be redeemed ?. E–Learning, 2, (1),17-26

Onder, Ismail & Geban, Omer. (2006). The effect conceptual change texts oriented instruction on students’ understanding of solubility equilibrium concept. H.U Journal of education. 30, 166-173.

Orgill, M. & Sutherland, A. (2008). Undergraduate chemistry students’ perceptions of and misconceptions about buffers & buffer problems. Chemistry Education Research and Practice,9:131–143.

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Pekdag , Bulent (2010). Alternative methods in learning chemistry: Learning with animation, simulation, video and multimedia. Journal of Turkish Science Education , 7, (6), 111-118

Rosengrant, D., Van Heuleven, A., & Etkina, E. (2006). Students’ use of multiple representations in problem solving. In P. Heron, L. McCullough & J. Marx, Physics Education Research Conference (AIP Conference Proceedings) Melville. New York : American Institute of Physics. pp. 49-52.

Savec, Vesca, F., et,al. (2006). In-service and pre-service teachers` opinion on the use of models in teaching chemistry. Acta Chim. Slov. 53:381–390.

Sheppard, Keith. (2006). High school students’ understanding of titrations and related acid-base phenomena. Chemistry Education Research and Practice,7,(1), 32-45

Silberberg, M. (2009). Chemistry: The molecular nature of matter and change, 5th, New York : McGraw-Hill

Singh, Harvey. (2003). Building effective blended learning programs. Issue of Educational Technology, 43. (6):51-54.

Snelson, Chareen. (2005). Designing dynamic online lessons with multimedia representations. The Journal of Educator Online. 2, (1), 1-12

Sopandi, W. & Murniati. (2007). Microscopic level misconceptions on topic acid base, salt, buffer, and hydrolysis: a case study at a state Senior High School, Prosiding Seminar Internasional I. Bandung: SPS UPI.

Stocker, Vincent Lee (2010). Science Teaching With Moodle 2.0. Brimingham : Packt Pub. Ltd (Tersedia online : www.packtpub.com).

Subarkah, Cucu Zenab. (2008). Analisis kemampuan intertekstualitas mahasiswa pada topik Fermentasi Karbohidrat. Prosiding Seminar Nasional Kimia & Pendidikan Kimia IV. Bandung: Jurusan Pendidikan Kimia FPMIPA UPI. Sudria, Ida Bagus Nyoman (2007). Peningkatan kualitas konsepsi mahasiswa

tentang konsep dasar kimia melalui optimalisasi pengaitan kajian aspek makroskopis, mikroskopis, & simbolik pada perkuliahan Kimia Dasar. Prosiding Seminar Internasional I. SPS UPI Bandung.

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using learner & information characteristics in the design of powerful learning environments. Applied Cognitive. Psychology. 20, 353–357.

Talib, Othman, Robert Matthews & Margaret Secombe. (2005). Constructivist animations for conceptual change: An effective instructional strategy in understanding complex, abstract and dynamic science concepts. Malaysian Online Journal of Instructional Technology (MOJIT). 2,(3),78-87.

Taber, K. S. (2003). The atom in the chemistry curriculum: fundamental concept, teaching model or epistemological obstacle? Foundations of Chemistry, 5,

43-84.

Taber, K. S. (2009). Learning at the symbolic level. In: Gilbert, J.K & D. Treagust (Eds.). Multiple Representation in Chemical Education: Models & Modeling in Science Education . Dordrecht: Springer. pp. 75-105

Tasker, Roy & Rebecca Dalton. (2006). Research into practice: visualization of the molecular world using animations. Chemistry Education Research and Practice,7, 141-159.

Treagust, David F., Chittleborough & Mamiala (2003). The role of submicroscopic and symbolic representations in chemical explanations. International Journal of Science Education, 25, (11): 1353– 1368

Treagust, David F. (2008). The role of multiple representations in learning science: enhancing students’ conceptual understanding and motivation. In Yew-Jin & Aik-Ling (Eds.). Science Education at The Nexus of Theory & Practice. Rotterdam - Taipei: Sense Publishers. pp:7-23

Treagust, David F. & Chandrasegaran, (2009). The efficacy of an alternative instructional programme designed to enhance secondary students’ competence in the triplet relationship. In: Gilbert, J.K & D. Treagust (Eds.). Multiple Representation in Chemical Education: Models & Modeling in Science Education . Dordrecht: Springer. pp:151-164

Venkataraman, Bhawani. (2009). Visualization and interactivity in the teaching of chemistry to science and non-science students. Chemistry Education Research and Practice,10: 62–69.

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Education,11,(1),87-107.

Wu, H-K. & Shah, P. (2004). Exploring Visuospatial Thinking in Chemistry Learning. Science Education, 88, 465-92

Weerawardhana, Anula, Brian Ferry & Christine Brown (2006). Use of visualization software to support understanding of chemical equilibrium: the importance of appropriate teaching strategies. Proceedings of The 23rd Annual Ascilite Conference: The University of Sydney

Yeung, A., Schmid, S. & Tasker, R. (2008). Can one version of online learning materials benefit all students ?. Symposium Presentation : Universe Science Proceedings Visualization.

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