第五章、 結論與建議
第三節、 未來研究建議
在本研究中，由量化分析結果可知，4 種不同信號及回饋設計方式之數位學 習教材對於學習者之學習奈米科技之學習成效、自我效能皆無顯著差異，另外，
從前測與質化分析資料可知，部分學習者對於奈米科技之概念不甚熟悉與了解。
因此，未來在進行相關研究時，尤其是與數位學習相關之學習活動，必須加強事 前訓練的工作，讓學習者能夠有足夠之先備知識，使學習者對於數位學習課程之 內容能夠先有所了解，當透過數位學習工具進行課程時，較能夠掌握與課程內容 之相關知識，以免使學習者在數位課程進行時，花費太多心力於理解課程之基本 概念。
在數位學習教材設計的部分，必須配合課程內容及研究對象之程度，適當的 加入信號於教材中，將可達到提升學習成效的效果。在本研究中，由教材易用性 問卷之分析結果可知，具信號設計之數位學習教材雖然具有容易閱讀、介面設計 良好等優點，但在課程引導性與選單設計上仍需加強，因此，未來在設計數位學 習教材時，必須考量到課程的引導性與精進選單的設計，當學習者在進行自主學 習時，在不需經教學者的解說下，便能夠直接了解如何操作教材。透過數位學習 教材易用性問卷可知，本研究之數位學習教材中，具回饋設計的部分具有容易閱 讀、介面設計良好、容易引導學習、容易幫助理解與記憶等優點。然後，未來在 進行回饋設計時，可將詳盡回饋之設計方式加以改良，將原本之文字閱讀的部分 (如圖 5-1)，改成以圖像、重點式為主呈現的方式(如圖 5-2)，將有可能對學習者
94
有所幫助，較能夠學習者之注意力。未來，在設計相關之數位學習教材時，必須 配合學習者自身之學習能力設計相關內容，才能達到因材施教的目的。另外，在 數位學習環境中，國中學生或是一般青少年，對於動畫、圖像等呈現方式或是透 過遊戲學習之教學，較能夠產生共鳴，因此，未來在設計數位學習教材時，必須 兼顧趣味性及學習內容之專業性。
圖5-1 本研究之 EF 回饋設計
圖5-2 未來研究之 EF 回饋設計修改示意圖
在本研究進行之時，經研究觀察發現，由於研究對象為國中學生，部分國中 學生對於前、後測問卷之填寫，易抱持著較消極或輕忽的態度進行，有可能影響
95
到研究之統計結果。因此，未來，在做類似之研究時，若能夠直接將施測問卷的 部分加入數位學習教材中，使之成為數位學習課程之一部分，答題結束後才算完 成課程，將提升研究結果之可信度。由於本研究在施測進行之時間點，為寒假輔 導課期間，研究樣本所在之學校尚有部分學生為參與，同時，寒假期間，學生容 易花較少之心思於課程中，因此，未來若能夠選擇於學期中施測，或將研究對象 推廣至其他地區學校，將有可能會有不同的結果。另外，若能夠將施測期間拉長，
由二週的時間延長為數個月或一學期，對於學習者之自我調節能力或是自我效能，
將可能會有所改變。
96
參考文獻
英文部分Askew, S., & Caroline, L. (2000). Feedback for Learning. London: Routledge and Falmer.
Astleitner, H., & Winsner, C. (2004). An integrated model of multimedia learning and motivation. Journal of educational multimedia and hypermduia, 13(1), 3-21.
Atkinson, R. (2002). Optimizing learning from examples using animated pedagogical agents. Journal of Educational Psychology, 94(2), 416-427. doi:
citeulike-article-id:86378
Austin, K. A. (2009). Multimedia learning: Cognitive individual differences and display design techniques predict transfer learning with multimedia learning modules. Computers & Education, 53, 1339–1354. doi:
10.1016/j.compedu.2009.06.017
Baddeley, A. D. (1992). Working memory. Science, 255, 556-559.
Baddeley, A. D. (1999). Human memory. Boston: Allyn & Bacon.
Bagaria, H. G., Dean, M. R., Nichol, C. A., & Wong, M. S. (2011). Self-assembly and nanotechnology: Real-time, hands-on, and safe experiments for K-12 students.
Journal of Chemical Education, 88, 609-614.
Bandura, A. (1977). Social Learning Theory. New York: General Learning Press.
Bandura, A. (1986). Social foundations of thought and action: A social cognitive
theory. Englewood Cliffs, NJ: Prentice-Hall.
Bandura, A. (1997). Self-efficacy: The exercise of control: New York: Freeman.
Bangert-Drowns, R. L., Kulik, C.-L. C., Kulik, J. A., & Morgan, M. (1991). The instructional effect of feedback in test-like events. Review of Educational
97
Research, 61(2), 213-238.
Barnard, L., Lan, W. Y., To, Y. M., Paton, V. O., & Lai, S.-L. (2009). Measuring self-regulation in online and blended learning environments. The Internet and
Higher Education, 12(1), 1-6. doi:
http://dx.doi.org/10.1016/j.iheduc.2008.10.005
Bernard, R. M., Abrami, C., Lou, Y., Borokhovski, E., Wade, A., Wozney, L., . . . Huang, B. (2004). How does distance education compare with classroom instruction? A meta-analysis of the empirical literature. Review of Educational
Research, 74(3), 379-439.
Bloom(1956).Taxonomy of educational objectives: Handbook I, The cognitive domain.
New York, Longmans: Green.
Burns, T. (2007). Using digital media to develop learner engagement. Paper presented at the 2007 iNet Online Conference: How do we meet the challenge of
inspiring learners.
Carless, D., Gordon, J., Ngar-Fun, L., & Associates. (2006). How Assessment
Supports Learning: Learning-Oriented Assessment in Action. Hong Kong:
Hong Kong University Press.
Carlson, C. R. (1979). Feedback for Learning. In O. Milton (ed.), On College
Teaching (pp. 125-152). San Francisco, CA: Jossey-Bass.
Chandler, P., & Sweller, J. (1991). Cognitive load theory and the format of instruction.
Cognition and Instruction, 8(4), 293-332.
Clariana, R. B. (1990). A comparison of answer until correct feedback and knowledge of correct response feedback under two conditions of contextualization.
Journal of Computer-Based Instruction, 17(4), 125-129.
Clark, J. M., & Paivio, A. (1991). Dual coding theory and education. Educational
98
Psychology Review, 3(3), 149-210.
Clark, R. E., & Feldon, D. F. (2005). Five comon but questionable principles of multimedia learning. In R. E. Mayer (Ed.), The cambridge handbook of
multimedia learning (pp. 97-115): New York: Cambridge University Press.
Colombo, B., & Antonietti, A. (2011). Self-regulated strategies and cognitive styles in multimedia learning. In G. Dettori & D. Persico (Eds.), Fostering
self-regulated learning through ICT (pp. 54-69). New York: Information
Science Reference.Cordero, E. D., Porter, S. H., Israel, T., & Brown, M. T. (2010). Math and science pursuits: a self-efficacy intervention comparison study. Journal of Career
Assessment, 18(4), 362-375. doi: doi:10.1177/1069072710374572
Dempsey, J. V., Driscoll, M. P., & Swindell, L. K. (1993). Text-based feedback. In J. V.
Dempsey & G. C. Sales (Eds.), Interactive instruction and feedback (pp.
21-54). Englewood Cliffs: NJ: Education Technology Publications.
Dempsey, J. V., & et al. (1993). Feedback, retention, discrimination error, and feedback study time. Journal of Research on Computing in Education, 25(3), 303-326.
Dempsey, J. V., & Wager, S. U. (1988). A taxonomy for the timing of feedback in computer-Based instruction. Educational Technology, 28(10), 20-25. doi:
citeulike-article-id:9651576
Dillon, A., & Jobst, J. (2005). Multimedia learning with hypermedia. In R. Mayer (Ed.), The Cambridge Handbook of Multimedia Learning (pp. 569-588).
Cambridge MA: Cambridge University Press.
Ebel, R. L., & Frisbie, D. A.(1991). Essentials of educational measurement, 5th ed.
Englewood Cliffs, NJ: Prentice-Hall.
99
Feynman, R. P. (1999). The pleasure of finding things out: The best short works of
Richard P. Feynman.
Foley, E. T., & Hersam, M. C. (2006). Assessing the need for nanotechnology
education reform in the United States. Nanotechnology Law & Business, 3(4), 467-484.
Friedman, A., & Nasir, A. (2011). Nanotechnology and dermatology education in the United States: Data from a pilot survey. Journal of Drugs in Dermatology,
10(9), 1037-1041.
Gordijn, J., & Nijhof, W. J. (2002). Effects of complex feedback on computer-assisted modular instruction. Computers & Education, 39(2), 183-200. doi:
http://dx.doi.org/10.1016/S0360-1315(02)00025-8
Hahne, A. K., Benndorf, R., Frey, P., & Herzig, S. (2005). Attitude towards computer-based learning: Determinants as revealed by a controlled interventional study. Medical Education, 39(9), 935-943.
Hanna, G. S. (1976). Effects of total and partial feedback in multiple-choice testing upon learning. The Journal of Educational Research, 69(5), 202-205.
Hattie, J., & Timperley, H. (2007). The Power of Feedback. Review of Educational
Research, 77(1), 81-112.
Hegarty, M., & Kriz, S. (2007). Effects of knowledge and spatial ability on learning from animation. In R. Lowe & W. Schnotz (Eds.), Learning with Animation -
Research Implications for Design (pp. 3-29). New York: Cambridge
University Press
Hingant, B., & Albe, V. (2010). Nanosciences and nanotechnologies learning and teaching in secondary education: a review of literature. Studies in Science
Education, 46(2), 121-152.
100
Hoskins, S. L., & Van Hooff, J. C. (2005). Motivatio and ability: Which students use online learning and what influence does it have on their achievement? British
Journal of Educational Psychology, 36(2), 171-192.
Hwang, W., Wang, C., & Sharples, C. (2007). A study of multimedia annotation of Web-based materials. Computers & Education, 48, 680-692.
Jeung, H. J., Chandler, P., & Sweller, J. (1997). The role of visual indicators in dual sensory mode instruction. Educational Psychology, 17(3), 329-345. doi:
10.1080/0144341970170307
Jones, M. G., Andre, T., Kubasko, D., Bokinsky, A., Tretter, T., Negishi, A., . . . Superfine, R. (2004). Remote atomic force microscopy of microscopic organisms: Technological innovations for hands-on science with middle and high school students. Science Education, 88(1), 55-71. doi: 10.1002/sce.10112 Judge, T. A., Jackson, C. L., Shaw, J. C., Scott, B. A., & Rich, B. L. (2007).
Self-efficacy and work-related performance: The integral role of individual differences. Journal of applied psychology, 92(1), 107-127.
Keller, J. M. (1983). Motivational design of instruction. In C. M. Reigeluth (Ed.),
Instructional-design theories and models: An overview of their current status
(pp. 384-434). Hillsdale, NJ: Lawrence Erlbaum Associates.Ketelhut, D. J. (2007). The impact of student self-efficacy on scientific inquiry skills:
an exploratory investigation in River City, a multi-user virtual environment.
Journal of Science Education and Technology, 16, 99-111. doi:
10.1007/s10956-006-9038-y
Lee, C.-K., Wu, T.-T., Liu, P.-L., & Hsu, S. (2006). Establishing a K-12 nanotechnology program for teacher professional development. IEEE
Transactions on Education, 49(1), 141-146.
101
Lee, W. W., & Owens, D. L. (2006). Multimedia-based instructional design:
computer-based training, Web-Based Trainning, Distance Broadcast Training.
Low, R., & Jin, P. (2009). Motivation and multimedia learning. In R. Zheng (Ed.),
Cognitive Effects of Multimedia Learning (pp. 154-171): Hershey :
Information Science Reference, c2009.
Malone, T. W., & Lepper, M. R. (1987). Making learning fun. A taxonomy of intrinsic motivations for learning. Aptitude, learning, and instruction, 3, 223-253.
Malsch, I. (2008). Nano-education from a European perspective. Journal of Physics:
Conference Series, 100, 1-7.
Mandernach, B. J. (2005). Relative effectiveness of computer-based and human feedback for enhancing student learning. The Journal of Educators Online,
2(1), 1-17.
Manlove, S., Lazonder, A., & Jong, T. (2007). Software scaffolds to promote regulation during scientific inquiry learning. Metacognition and Learning,
2(2-3), 141-155. doi: 10.1007/s11409-007-9012-y
Martin, M. O., Mullis, I. V. S., Foy, P., & Stanco, G. M. (2012). TIMSS 2011
International Results in Science. Chestnut Hill, MA, USA. Amsterdam, the
Netherlands: TIMSS & PIRLS International Study Center, Lynch School of Education, Boston College, & International Association for the Evaluation of Educational Achievement (IEA) IEA Secretariat.Mason, B. J., & Bruning, R. (2001). Providing feedback in computer-based instruction: What the Research Tells Us Retrieved Oct. 10, 2012, from http://dwb.unl.edu/Edit/MB/MasonBruning.html
Mautone, P., & Mayer, R. (2001). Signaling as a cognitive guide in multimedia learning. Journal of Educational Psychology, 93(2), 377-389. doi:
102
citeulike-article-id:86341
Mayer, R. E. (2001). Multimedia learning: Cambridge: University Press.
Mayer, R. E. (2005). Cognitive theory of multimedia learning. In R. E. Mayer (Ed.),
The Cambridge Handbook of Multimedia Learning (pp. 31-48). New York:
Cambridge University Press.
Mayer, R. E. (2008). Learning and instruction (2nd ed.). Upper Saddle River, NJ:
Person Merrill Prentice Hall.
Mayer, R. E., & Moreno, R. (1998). A split-attention effect in multimedia learning:
evidence for dual processing systems in working memory. Journal of
Educational Psychology, 90(2), 312-320.
Meluso, A., Zheng, M., Spires, H. A., & Lester, J. (2012). Enhancing 5th graders' science content knowledge and self-efficacy through game-based learning.
Computers & Education, 59, 497-504. doi:
doi:10.1016/j.compedu.2011.12.019
Moos, D. C. (2011). Self-regulated learning and externally generated feedback with hypermedia. Journal of Educational Computing Research, 44(3), 265-297.
Moreno, R. (2004). Decreasing cognitive load for novice students: Effects of explanatory versus corrective feedback in discovery-based multimedia.
Instructional Science, 32(1), 99-113. doi:
10.1023/B:TRUC.0000021811.66966.1d
Narciss, S., & Huth, K. (2006). Fostering achievement and motivation with bug-related tutoring feedback in a computer-based training for written subtraction. Learning and Instruction, 16(4), 310-322. doi:
10.1016/j.learninstruc.2006.07.003
Narciss, S., Proske, A., & Koerndle, H. (2007). Promoting self-regulated learning in
103
web-based learning environments. Computers in Human Behavior, 23(3), 1126-1144. doi: 10.1016/j.chb.2006.10.006
Naumann, J., Richter, T., Flender, J., Christmann, U., & Groeben, N. (2007).
Signaling in expository hypertexts compensates for deficits in reading skill
(Vol. 99). Washington, DC, ETATS-UNIS: American Psychological Association.Nicol, D. J., & Macfarlane-Dick, D. (2006). Formative assessment and self-regulated learning: A model and seven principles of good feedback practice. Studies in
Higher Education, 31(2), 199-218.
Nokelainen, P. (2006). An empirical assessment of pedagogical usability criteria for digital learning material with elementary school students. Educational
Technology & Society, 9(2), 178-197.
Nunnally, J. C. (1978). Psychometric Theory (2nd ed.). New York, NY: McGraw-Hill.
O'Connor, C., & Hayden, H. (2008). Contextualising nanotechnology in chemistry education. Chemistry Education Research and Practice, 9(35), 1-29.
Olakanmi, E. E., Blake, C., & Scanlon, E. (2011). The role of self-regulated learning in enhancing conceptual understanding of rate of chemical reactions. In G.
Dettori & D. Persico (Eds.), Fostering self-regulated learning through ICT (pp.
248-265). New York: Information Science Reference.
Paivio, A. (1986). Mental representations: A dual-coding approach. Oxford, England:
Oxford University Press.
Park, O.-C., & Gittelman, S. (1992). Selective use of animation and feedback in computer-based instruction. Educational Technology Research and
Development, 40(4), 27-38. doi: 10.1007/bf02296897
Pintrich, P. R., & Groot, E. V. D. (1990). Motivational and self-regulated learning
104
components of classroom academic performace. Journal of Educational
Psychology, 82(1), 33-40.
Pintrich, P. R., Smith, D. A. F., Garcia, T., & McKeachie, W. J. (1991). A manual for
the use of the Motivated Strategies for Learning Questionnaire (MSLQ). Ann
Arbor, Michigan: The University of Michigan.Pridemore, D. R., & Klein, J. D. (1991). Control of feedback in computer-assisted instruction. Educational Technology Research and Development, 39(4), 27-32.
doi: 10.2307/30218350
Pridemore, D. R., & Klein, J. D. (1995). Control of practice and level of feedback in computer-based instruction. Contemporary Educational Psychology, 20(4), 444-450. doi: http://dx.doi.org/10.1006/ceps.1995.1030
Ramaprasad, A. (1983). On the definition of feedback. Behavioral Science, 28(1), 4-13.
Reed, S. K. (2006). Cognitive architectures for multimedia learning. Educational
Psychologist, 41(2), 87-98.
Rieber, L. (1996). Animation as feedback in a computer-based simulation:
Representation matters. Educational Technology Research and Development,
44(1), 5-22. doi: 10.1007/bf02300323
Salomon, G. (1984). Television is "easy" and print is "tough": The differential investment of mental effort in learning as a function of perceptions and attributions. Journal of Educational Psychology, 76, 647-658.
Schank, P., Wise, A., Stanford, T., & Rosenquist, A. (2009). Can high school students learn nanoscience? An evaluation of the viability and impact of the NanoSense curriculum. Menlo Park, CA: SRI International.
Schunk, D. H. (1995). Self-monitoring of skill acquisition through self-evaluation of
105
capabilities. Paper presented at the the meetion of the American Educational
Research Association, San Francisco, CA.Schunk, D. H., Pintrich, P. R., & Meece, J. L. (2010). Motivation in education (Third edition ed.). New Jersey, America: Person Prentice Hall.
Shute, V. J. (2008). Focus on formative feedback. Review of Educational Research,
78(1), 153-189. doi: 10.3102/0034654307313795
Stevens, S., Sutherland, L., & Krajcik, J. (2009). The "big ideas" of nanoscale science
and Engineering. Arlington, VA: National Science Teachers Association press.
Stevens, S. Y., Sutherland, L., Schank, P., & Krajcik, J. (2007). The big ideas of nanoscience., from http://hice.org/projects/nano/index.html
Sung, E., & Mayer, R. E. (2012). Affective impact of navigational and signaling aids to e-learning. Computers in Human Behavior, 28(2), 473-483. doi:
10.1016/j.chb.2011.10.019
Sweller, J. (1999). Instructional design in the technical areas. Camberwell, Australia:
ACER Press.
Tanes, Z., Arnold, K. E., King, A. S., & Remnet, M. A. (2011). Using Signals for appropriate feedback: Perceptions and practices. Computers & Education,
57(4), 2414-2422. doi: 10.1016/j.compedu.2011.05.016
Timmers, C., & Veldkamp, B. (2011). Attention paid to feedback provided by a computer-based assessment for learning on information literacy. Computers &
Education, 56(3), 923-930. doi: 10.1016/j.compedu.2010.11.007
Tseng, S.-C., & Tsai, C.-C. (2007). On-line peer assessment and the role of the peer feedback: A study of high school computer course. Computers & Education,
49(4), 1161-1174. doi: 10.1016/j.compedu.2006.01.007
Tunstall, P., & Gipps, C. (Sep., 1996). Teacher feedback to young children in
106
formative assessment: A Typology. British Educational Research Journal,
22(4), 389-404.
van der Kleij, F. M., Eggen, T. J. H. M., Timmers, C. F., & Veldkamp, B. P. (2012).
Effects of feedback in a computer-based assessment for learning. Computers
& Education, 58(1), 263-272. doi: 10.1016/j.compedu.2011.07.020
Wang, S.-L., & Wu, P.-Y. (2008). The role of feedback and self-efficacy on web-based learning: The social cognitive perspective. Computers & Education, 51(4), 1589-1598. doi: 10.1016/j.compedu.2008.03.004
Winne, P. H., & Hadwin, A. F. (1998). tudying self-regulated learning. In D. J. Hacker, J. Dunlosky & A. Graesser (Eds.), Metacognition in educational theory and
practice (pp. 277-304). Hillsdale, NJ: Erlbaum.
Wittrock, M. C. (1989). Generative processes of comprehension. Educational
Psychologist, 24, 345-376.
Zheng, R., Mcalack, M., Wilmes, B., Kohler-Evans, P., & Williamson, J. (2009).
Effects of multimedia on cognitive load, self-efficacy, and multiple rule-based problem solving. British Journal of Educational Technology, 40(5), 790-803.
doi: 10.1111/j.1467-8535.2008.00859.x
Zimmerman, B. J. (1986). Development of self-regulated learning: Which are the key subprocesses? Contemporary Educational Psychology, 16, 307-313.
Zimmerman, B. J. (1989). A social-cognitive view of self-regulated learning. Journal
of Educational Psychology, 81, 329-339.
Zimmerman, B. J. (1994). Dimensions of academic self-regulation: A conceptual framework for education. In D. H. Schunk & B. J. Zimmerman (Eds.),
Self-regulation of of learning and performance: Issues and educational
applications (pp. 3-21). Hillsdale, NJ: Erlbaum.
107
Zimmerman, B. J. (1995). Self-efficacy and educational development. In A. Bandura (Ed.), Self-efficacy in changing societies (pp. 202-231). New York: Cambridge University Press.
Zimmerman, B. J. (2000). Attaining self-regulation: A social cognitive perspective. In M. Boekaerts, P. R. Pintrich & M. Zeidner (Eds.), Metacognition in
educational theory and practice. San Diego, CA: Academic Press.
Zimmerman, B. J. (2000). Self-Efficacy: An Essential Motive to Learn.
Contemporary Educational Psychology, 25, 82-91.
Zimmerman, B. J., & Risemberg, R. (1997). Self-regulatory dimensions of academic learning and motivation. In G. D. Phye (Ed.), Handbook of academic learning:
Construction of knowledge (pp. 105-125). San Diego, CA: Academic Press.
中文部分
王宗坤（2001）。從「自然與生活科技」領域課程的目標談科普教育的作法。
研 習資訊
，18（1），79-85。王美芬（2000）。國小教師面對九年一貫「自然與生活科技」領域新課程因應策 略。
國教新知
，46（3），31-36。吳政忠（2004）。往下紮根的奈米教育，
台北市雜誌商業同業工會－電子報
。 吳茂昆（2002 ）。美好的未來不是夢-簡介奈米國家型科技計畫。科技發展政策
報導
，SR9109。吳雪櫻（2011）。
信號提示與分段呈現融入多媒體教材對七年級學生氣壓概念學 習之影響
。未出版之碩士論文，佛光大學學習與數位科技學系。李世光、林宜靜、吳政忠、黃圓婷、蔡雅雯（2003）。奈米科技人才培育計畫之 推動規劃與展望：從k-12 奈米人才培育試行計劃談起。
物理雙月刊
，25（3），435-461。
108
李世忠、趙倩筠（2007）。步驟性教材製作軟體於e-learning 應用軟體學習之探討。
教育資料與圖書館學
，45（2），233-248。李立彬、曾世綺（2010）。多媒體中的提示信號與反思之使用對學習物理概念的 影響。
教學科技與媒體
，93，2-16。李哲迪（2009）。臺灣國中學生在 timss 及 pisa 的科學學習成果表現及其啟示。
研習資訊
，26（2），73-88。李麗娟（2010）。
運用電子歷程檔案於國小資訊課程對學生學習成效及自我調整 之研究
。未出版，國立臺北教育大學理學院教育傳播與科技研究所，臺北 市。奈米科技教育學院（2009。上網日期：2012，Dec. 10。檢自：
http://nano.narl.org.tw/index.aspx
林桂櫻（2005）。
科技議題融入國小自然生活科技領域教學模式之研究 - 以奈米應 用為例
。未出版之，國立花蓮師範學院國小科學教育研究所，花蓮縣。林煥祥、劉聖忠、林素微、李暉（2008）。
臺灣參加 PISA 2006 成果報告
：行政林煥祥、劉聖忠、林素微、李暉（2008）。