• 沒有找到結果。

The work presented in this chapter provides a significant contribution to science learning involving the use of a web-based, multimedia, flash science learning program using an online e-learning environment.

Results show that students perceived their learning environment created during the use of this online flash science program is their science class as having high levels of students’ cohesiveness, task orientation, cooperation, equity, differentiation, and their teachers using more challenging questions. Students’ attitudes toward using computers and web usage are very favourable. Students were satisfied with the program and their cognitive outcomes increased dramatically after learning science this way, regardless of any types of learning preference or grade levels. In particular, students’ cognitive outcomes were also found to be higher when students perceived more student cohesiveness, investigation, equity, self-efficacy, and more teacher use of challenging questions.

These results are very encouraging and shed some light on how to successfully promote students’ science learning through the use of a web-based online physical science learning program.

References

Aggarwal, A. K., & Bento, R. (2000). Web-based education. In A.

Aggarwal (Ed.), Web-based learning and teaching technologies:

opportunities and challenges. London, UK. IDEA Group Publishing.

Beichner, L .B., Bernold, E. B., Dail, P., Felder, R, Gastineau, M. G., &

Risley, J. (1999). Case study of the physics component of an integrated curriculum. American Journal of Physics, 67, 16-24.

Bonk, C. J., & Cummings, J. A. (1998). A dozen recommendations for placing the student at the center of web-based learning. Educational Media International, 35 (2), 82-89.

Clement, J. (1994). Imagistic simulation and physical intuition in expert problem solving. In the Proceedings of the sixteenth Annual conference of the cognitive science society (pp. 146-156). Hillsdale, New Jersey: Lawrence Erlbaum,

De Jong, T. (1991). Leanring and instruction with computer simulations.

Education and Computing, 6, 217-229.

De Jong, T., & Van Joolingen, W. R. (1998). Scientific discovery learning with computer simulations of conceptual domains. Review of Educational Research, 68, 179-201.

Dunn, R., & Dunn, K (1990). Understanding the Dunn and Dunn learning styles model and the need for individual diagnosis and prescription. Reading, Writing, and Learning Disabilities, 6, 223-247.

Felder R., & Silverman, L. (1988). Learning and teaching styles in engineering education. Journal of Engineering Education, 78, 674-681.

Finke, R.A. (1989). Principles of mental imagery. Cambridge, MA: MIT Press.

Fraser, B. J. (1981). Test of Science-Related Attitudes handbook (TOSRA).

Melbourne, Australia: Australian Council for Educational Research.

Fraser, B. J. (1990). Individualised Classroom Environment Questionnaire: Handbook and test master set. Melbourne: The Australian Council for Educational Research.

Fraser, B.J. (1994). Research on classroom and school climate. In D.

Gabel (Ed.), Handbook of research on science teaching and learning (pp. 493-541). New York: Macmillan.

Fraser, B. J. (1998a). Science learning environments: Assessment, effects and determinants. In B.J. Fraser & K.G. Tobin (Eds.), The international handbook of science education (pp. 527-564).

Dordrecht, The Netherlands: Kluwer.

Fraser, B. J. (1998b). Classroom environment instruments: development, validity and applications. Learning Environments Research: An International Journal, 1, 7-33.

Fraser, B. J., McRobbie, C. J., & Fisher, D. L. (1996, April). Development, validation and use of personal and class forms of a new classroom environment instrument. Paper presented at the annual meeting of the American Educational Research Association, New York.

Fraser, B. J., & Walberg, H. J. (Eds.), (1991). Educational environments:

Evaluation, antecedents and consequences. Oxford, England:

Pergamon Press.

Goldberg, F. (1997). Constructing physics understanding in a computer-supported learning environment. AIP conf. Proc., 399, 903-911.

Gregory, J. R., & Stewart, M. F. (1997). Production of a multimedia CAL package in basic physics. Physics Education, 32 (5), 332-39.

Hermann, N. (1988). The creative brain. Lake Lure, NC: Brain Books.

Jinks, J. L., & Morgan, V. (1999). Children's perceived academic self-efficacy: An inventory scale. Clearing House, 72, 224-230.

Kosslyn, S. M. (1994). Image and brain: The resolution of the imagery debate. Cambridge, MA: MIT Press,

Lumsdaine, E., & Lumsdaine, M. (1995). Creative problem solving. New York, NY: McGraw-Hill, Inc.

Maor, D., & Fraser, B. J. (1996). Use of classroom environment perceptions in evaluating inquiry-based computer assisted learning.

International Journal of Science Education, 18, 401-421.

Maccoby, E. E. (1990). The role of gender identity and gender constancy in sex-differentiated development. New Directions for Child Development, 47, 5-20.

Monaghan, J. M., & Clement, J. (2000). Algorithms, visualization, and mental models: high school students’ interaction with a relative motion simulation. Journal of Science Education and Technology, 9(4), 311-325.

Newhouse, C. P. (2001). Development and use of an instrument for computer-supported learning environments. Learning Environment Research: An International Journal, 4, 115-138.

Okebukola, P. A. (1986). The influence of preferred learning styles on cooperative learning in science. Science Education, 70 (5), 509-17.

Owens, L., & Barnes, J. (1982). The relationships between cooperative, competitive, and individualized learning preferences and students' perceptions of classroom learning atmosphere. American Educational Research Journal, 19 (2) 182-200.

Oyama, T., & Ichikawa, S. (1990). Some experimental studies on imagery in Japan. Journal of Mental Imagery, 14, 185-195.

Packer. J., & Bain, J. D. (1978). Cognitive style and teacher-student compatibility . Journal of Educational Psychology, 70, 864-871 Renninger, K. A., Snyder, S. S., (1983). Effects of cognitive style on

perceived satisfaction and performance among students and teachers. Journal of Educational Psychology,75 (5), 668-676.

Riding, R. J., & Douglas, G. (1993). The effect of cognitive style and mode of presentation on learning performance. British Journal of Education Psychology, 63, 297-307.

Rieber, L. P. (1991). Animation, incidental learning, and continuing motivation. Journal of Educational Psychology, 83, 318-328.

She, H.C., & Fisher, D. (2000). The development of a questionnaire to describe science teacher communication behavior in Taiwan and Australia. Science Education, 84(6), 706-26.

She, H. C., & Fisher, D. (2002). Teacher communication behavior and Its association with students' cognitive and attitudinal outcomes in science in Taiwan. Journal of Research in Science Teaching, 39(1), 63-78.

Steinberg, R. (2000). Computers in teaching science: to stimulate or not to stimulate. American Journal of Physics, 68(7), 37-s41.

Sternberg, R. (1997). Thinking styles. New York: Cambridge University press.

Tao, P. K., & Gunstone, R.F. (1999). The process of conceptual change in force and motion during computer-supported physics instruction.

Journal of Research in Science Teaching, 36 (7), 859-82.

Teh, G., & Fraser, B.J. (1994). An evaluation of computer-assisted learning in terms of achievement, attitudes and classroom environment. Evaluation and Research in Education, 8, 401-421.

Tetiwat, O., & Igbaria, M. (2000). Opportunities in web-based teaching:

The future of education. In A. Aggarwal (Ed.) Web-based learning and teaching technologies: opportunities and challenges. London, UK: IDEA Group Publishing.

Trindade, J., Fiolhais, C., & Almeida, L. (2002). Science learning in

virtual environments: a descriptive study. British Journal of Educational Technology, 33 (4), 471-488.

Wiles, J. & Bondi, J. (1993). The essential middle school (Second Edition). New York, NY: Macmillan Publishing, Co.

Wubbels, T., & Levy, J. (Eds.). (1993). Do you know what you look like?

Interpersonal relationships in education. London, England:

Falmer Press.

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