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研究生: 吳皇慶
Wu Hunag-Ching
論文名稱: 地球科學動畫試題的發展與效能驗證
Development and validation of an animation-based test in the area of Earth Science
指導教授: 張俊彥
Chang, Chun-Yen
學位類別: 碩士
Master
系所名稱: 地球科學系
Department of Earth Sciences
論文出版年: 2006
畢業學年度: 94
語文別: 英文
論文頁數: 69
中文關鍵詞: 動畫電腦化測驗
英文關鍵詞: Animation, Computerized assessment
論文種類: 學術論文
相關次數: 點閱:193下載:23
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  • This study tries to develop an animation-based test (ABT) in the area of Earth science. The advantages of ABT includes: (1) To present more authentic situation in an animated testing environment; (2) To assess the learning outcomes with appropriate validity and reliability; (3) To be a more attractive way of testing. The content of the test focuses on four domains in Earth science including astronomy, meteorology, oceanography and geology. “Attitude toward Simulated Assessment Scale”(AAAS) was adapted in this study in order to explore examinees’ perceptions and attitudes toward ABT.
    This study has found that an animation-based test was more effective to trigger students’ positive attitude than was a graphic-based test. In addition, animation is found to influence students scores- especially for the low-order prior knowledge students. Therefore, it is suggested that the innovative forms of assessments, such as the ABT proposed in the current study, could not only indicate the importance to train cognitive skills to students, but also serve as an alternative and promising vehicle for implementing assessments in high school Earth sciences education.

    This study tries to develop an animation-based test (ABT) in the area of Earth science. The advantages of ABT includes: (1) To present more authentic situation in an animated testing environment; (2) To assess the learning outcomes with appropriate validity and reliability; (3) To be a more attractive way of testing. The content of the test focuses on four domains in Earth science including astronomy, meteorology, oceanography and geology. “Attitude toward Simulated Assessment Scale”(AAAS) was adapted in this study in order to explore examinees’ perceptions and attitudes toward ABT.
    This study has found that an animation-based test was more effective to trigger students’ positive attitude than was a graphic-based test. In addition, animation is found to influence students scores- especially for the low-order prior knowledge students. Therefore, it is suggested that the innovative forms of assessments, such as the ABT proposed in the current study, could not only indicate the importance to train cognitive skills to students, but also serve as an alternative and promising vehicle for implementing assessments in high school Earth sciences education.

    Chapter 1. Introduction 1-1. Background and motivation…………………………1 1-2. Purpose of the study…………………………………6 1-3. Research questions……………………………………6 1-4. Importance of the study…………………………… 7 1-5. Definition of Terms……………………………………8 Chapter 2. Literature Review 2-1. Animation utility…………………………………… 11 2-1-1. Psychological paradigm……………………… 12 2-1-2. Review of the empirical findings…………15 2-1-3 Recommendations: instructional roles of animation and conditions for use..................17 2-1-4 Issues beyond modality…………………………18 2-2. Individual differences…………………………...19 2-3. Issues about computerized test………………… 20 2-3-2. Attitude toward computerized test……….22 Chapter 3. Research Method 3-1. Test development……………………….……………..23 3-1-1. Content selecting….....................25 3-1-2. Animation design……………...............27 3-2. Item evaluation……..………………………………….29 3-2-1. Expert review of items…................30 3-2-2. Reliability……..........................30 3-3. Item analysis……………………………………...…….31 3-4. Participants………………….………………………...34 3-5. Design of the experiment…...................35 3-6. Measuring instrument……………………...........37 3-7. Data analysis………….........................38 Chapter 4. Result 4-1. Discriminating power testing…………………………40 4-2. Scores for animation-based test (ABT) and graphic-based test (GBT)………………….........................42 4-2-1. The group with students who have finished the curriculum (Group A)……………........................46 4-2-2. The group with students who are still in the progress of the curriculum (Group B).................48 4-2-3. Summary……………………………………….........50 4-3. Data of “Attitude toward Animation Assessment Scale” (AAAS)……………………..........................51 4-4. Interview……………………………………………………….......54 Chapter 5. Discussion and implication 5-1. Discussion……………………………………………………………….56 5-2. Quality of the animation-based test….……………57 5-3. Discussion about the attitude…………………………57 5-4. Discussion about the score for ABT………………….59 5-5. Implication……………………………….....………………61 5-6. Conclusion…………………………....………………………62 Reference

    Ainsworth, S., & VanLabeke, N. (2004). Multiple forms of dynamic representation. Learning and Instruction, 14(3), 241-255.

    Allessi S. M. & Trollip, S. R. (2001). Multimedia for Learning: Methods and Development (3rd Edition) Allyn & Bacon.

    Bakx, A.W.E.A. & Sijtsma, K. (2002). Development and evaluation of a students-centered multimedia self-assessment instrument for social-communicative competence. Instructional Science, 30, 335-359

    Bell, B. & Cowie, B. (2001). The characteristics of formative assessment in science education. Science Education, 85, 536-553

    Bloom, B., Englehart, M. Furst, E., Hill, W., & Krathwohl, D. (1956). Taxonomy of educational objectives: The classification of educational goals. Handbook I: Cognitive domain. New York, Toronto: Longmans, Green.

    Bodemer, D., Ploetzner, R., Feuerlein, I. & Spada, H. (2004). The active integration of information during learning with dynamic and interactive visualisations. Learning and Instruction, 14, 325-341.

    Brooke, S. & Peter C. (2004). The development of the attitude towards computerized assessment scale. Journal of educational computing research, 31, 407-422

    Bugbee, A. C. & Bernt, F. M. (1990). Testing by Computer Findings in Six Years of Use 1982-1988. Journal of Research on Computing in Education, 23, 87-100.
    Carney, R. N. & Levin, J. R. (2002) Pictorial Illustrations Still Improve Student’s Learning from Text. Educational Psychology Review, 14, 5-26.

    Chang, C. Y. (2002). Does Computer-Assisted Instruction + Problem Solving = Improved Science Outcomes? A Pioneer Study. The Journal of Educational Research, 95, 143-150.

    Chang, C. Y. (2003). Teaching earth sciences: Should we implement teacher-directed or student-controlled CAI in the secondary classroom? International Journal of Science Education, 25, 427-438.

    Chang, C. Y. (2005). Taiwanese Science and Life Technology Curriculum Standards and Earth Systems Education. International Journal of Science Education , 27, 625-638.

    Chang, C. Y., & Tsai, C. C. (2005). The interplay between different forms of CAI and students’ preferences of learning environment in the secondary science class. Science Education, 89, 707-724.

    Chatterji, M. (2003). Designing and using tools for educational assessment. Boston, MA : Allyn and Bacon.

    Cohen, J. (1988). Statistical Power Analysis for the Behavioral Sciences 2nd edition. Hillsdale, NJ: Lawrence Erlbaum.

    Ebel, R. L. & Frisbie, D. A. (1991). Essentials of Educational Measurement (5th ed).
    Englewood, NJ: Prentice Hall.

    Fraenkel, J. R. & Wallen, N. E. (1993). How to design and evaluate research in education. New York : McGraw-Hill, 2nd ed.
    Goldberg, A. L. (2000). Test-level, item-level, and experiential differences on computerized and paper-and-pencil versions of a practice Graduate Record Exam (GRE). Unpublished doctoral dissertation, Boston College.

    Hagmann, S., Mayer, R. E. & Nenninger, P. (1998). Using structural theory to make a word-processing manual more understandable. Learning and instruction, 8, 19-35

    Hedl, J. J., O’Neil, H. F., & Hansen, D. N. (1973). Affective reactions toward computerbased intelligence testing. Journal of Consulting and Clinical Psychology, 40(2), 217-222.

    Hsu, Y. S. & Thomas, R. A. (2002). The impacts of a web-aided instructional simulation on science learning. International Journal of Science Education, 24 (9), 955-980.

    Hsu, Y. S., Cheng, Y. J. & Chiou, G. F., (2003). Internet uses in the school : A case study of the Internet adoption in a senior high school. Innovations in Education and Teaching International, 40 , 356-368.

    Issenberg, S.B., McGaghie, W.C., Hart, I.R.,Mayer, J.M., Felner, J.M., Petrusa, E.R.,Waugh, R.A., Brown, D.D., Safford, R.S., Gessner, I.H., Gordon, D.L. & Ewy, G.A. (1999). Simulation technology for health care professional skills training and assessment. Journal of the American Medical Association, 282, 861–867.
    Jih, H. J. & Reeves, T. C. (1992). Mental Models: A Research Focus on Interactive Learning Systems. Educational Technology Research and Development, 40(3). 39-53.
    Jonassen, D. H., & Henning, P. (1999) Mental models: knowledge in the head and knowledge in the world. Educational Technology, 39, 37-42.

    Just, M. A., & Carpenter, P. A. (1992). A capacity theory of comprehension: Individual differences in working memory. Psychological Review, 98, 122–149.

    Kobrin, J. L. (2000). An Investigation of the Cognitive Equivalence of Computerized
    and Paper-and-Pencil Reading Comprehension Test Items. Paper presented at the Annual Meeting of the American Educational Research Association, New Orleans, LA
    Lepper, M.R., Keavney, M., & Drake, M. (1996). Intrinsic motivation and extrinsic rewards: A commentary on Cameron and Pierce's Meta-analysis. Review of Educational Research, 66, 5-32.
    Lowe, R. K. (2003). Animation and learning: selective processing of information in dynamic graphics. Learning and Instruction, 13, 157-176.

    Lowe, R. (2004). Interrogation of a dynamic visualization during learning. Learning and Instruction, 14, 257–274.

    Malone, T. W., & Lepper, M. R. (1987). Making learning fun: A taxonomy of intrinsic motivations for learning. Aptitude, learning and instruction: III. Conative and affective process analysis (pp. 223-253)
    Mayer, R. E. (1992). Thinking, problem solving, cognition (2nd ed.). New York: W. H. Freeman.
    Mayer, R. E. (1997). Multimedia Learning: Are we asking the right questions? Educational Psychologist, 32, 1-19

    Mayer, R. E., Moreno, R., Boire. (2002). Aids to computer-based multimedia learning. Learning and Instruction, 12, 107-119

    Mayer, R. E. & Moreno, R., Boire. (2002). Animation as an aid to multimedia learning. Educational Psychology Review, 14, No.1.

    McGuire, L. (2005). Assessment using new technology. Innovations in Education and Teaching International, 42, 265-276.

    Meijer, R.R. & Nering, M.L. (1999). Computerized adaptive testing: overview and
    introduction. Applied Psychological Measurement, 23, 187-194.

    Morrell, D. (1992). The effects of computer assisted instruction on student achievement in high school biology. School Science and Mathematics, 92, 177–181.

    Ogilvie, R. W., Trusk, T. C., & Blue, A. V. (1999). Student’s attitudes towards computer testing in a basic science course. Medical Education, 33, 828-831.

    Olugbemiro, J. (1991). Computers and the learning of biological concepts, attitudes and achievement of Nigerian students. Science Education, 75, 701–706.

    Park, O. C. & Hopkins R. (1993). Instructional conditions for using dynamic visual displays: a review. Instructional Science, 21, 427-449

    Powers, D. E., & O’Neill, K. (1993). Inexperienced and anxious computer users: Coping with a computer-administered test of academic skills. Educational Assessment, 1, 153-173.

    Powers, D.E. (2001). Test Anxiety and Test Performance: Comparing Paper-Based and Computer-Adaptive Versions of the Graduate Record Examinations (GRE) General Test. Journal of Educational Computing Research, 24, 249-273.

    Reimann, P. (2003). Multimedia learning: beyond modality. Learning and Instruction, 13, 245-252.

    Rieber, L. P. (1990). Using computer animated graphics in science instruction with children. Journal of Educational Psychology, 82, 135-140

    Robert L. L. & Norman E. G., (2000). Measurement and assessment in teaching. Upper Saddle River, N.J. : Merrill

    Roever, C. (2001). Web-based language testing. Language Learning and Technology, 5, 84-94.

    Salomon, G., Perry, M., & Globerson, T. (1991). Partners in cognition: extending human intelligence with intelligent technologies. Educational Researcher, 20, 2–9.

    Schnotz, W. (2002). Towards an Integrated View of Learning From Text and Displays. Educational Psychology Review, 14, 101-120.

    Smith, B. & Caputi, P. (2004). The development of the attitude towards the computerized assessment scale. Journal of educational computing research, 31, 407-422.

    Spector, J. M., Christensen, D. L.,& Sioutine, A. V., et al. (2001). Models and simulations for learning in complex domains: using causal loop diagrams for assessment and evaluation. Computers in Human Behavior, 17, 517-545.

    Tarbuck, E. J.,& Lutgens, F. K. (2003). Earth Science, Upper Saddle River, N.J.

    Taylor, C., Jamieson, J., Eignor, D., & Kirsch, I. (1998). The Relationship Between
    Computer Familiarity and Performance on Computer-Based TOEFL Test Tasks.
    Educational Testing Service: Research Reports. Report 61 (RR-98-8).

    Tonidandel, S., Quinones, M. A., & Adams, A. A. (2002). Computer-adaptive testing: The impact of test characteristics on perceived performance and test takers’ reactions. Journal of Applied Psychology, 87(2), 320-332.

    Tsai, M. J. & Tsai, C. C. (2003). Student computer achievement, attitude and anxiety: the role of learning strategies. Journal of Educational Computing Research, 28(1), 47-61.

    Vispoel, W.P. (2000). Computerized Versus Paper-and-Pencil Assessment of Self-
    Concept: Score Comparability and Respondent Preference. Measurement and
    Evaluation in Counseling and Development, 33, 130-143.

    Wainwright, C. L. (1989). The effectiveness of a computer-assisted instruction package in high school chemistry. Journal of Research in Science Teaching, 26, 275–290

    Winn, W., Stahr, F., & Sarason, C. (2006). Learning Oceanography from a Computer Simulation Compared with Direct Experience at Sea. Journal of Research in Science Teaching, 43, 25–42.

    Wu, M. L. (1998). 電腦態度的意義及其量表內涵的探究。資訊與教育,65,48-55

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