博碩士論文 103524601 詳細資訊




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姓名 戴 思萍(SISKA WATI DEWI PURBA)  查詢紙本館藏   畢業系所 網路學習科技研究所
論文名稱 探討高職學生使用“無所不在物理系統”時的學習行為及學習成效
(Investigation of Learning Behaviors and Learning Achievement of Vocational High School Students Using an Ubiquitous-Physics App)
檔案 [Endnote RIS 格式]    [Bibtex 格式]    至系統瀏覽論文 (2017-12-1以後開放)
摘要(中) 此研究的目標為探討高職學生在實驗中使用本系統(U-Physics)學習簡單單擺時,其學習行為與學習成就的關聯。U-Physics可以幫助實驗資料的蒐集以及實驗中對應圖案的繪製,因此,學生可以專注於圖形的解釋以及如何應用公式來解題。受試者為一年級以及二年級對於物理缺乏興趣的女性高職生,希望藉由在實驗中使用本系統來提升學生的學習動機,幫助他們在物理上的學習。學習行為包含提出假設、圖形解釋、公式應用、結論統整、成對比較以及概念理解。在前導實驗中我們選定一個班級,在正式實驗中則有兩個班級,在前導實驗中的結果顯示,圖形解釋以及公式應用的兩個行為間有顯著的正相關,這代表著圖形解釋的能力在科學學習的過程中扮演著很重要的角色,因此我們強烈建議物理老師使用圖形來提升學生於相關知識上的吸收與了解,而成對比較以及圖形解釋間則存在著負相關,可能的原因為大部分的高職生僅擁有有限的物理解題能力以及信心,以至於他們通常都是尋求老師或是高學習成就的同儕的幫助,此外,研究結果中也發現本系統能夠在三週的時間內提升學習者的學習成效。然而,在前導實驗中的結果顯示,學生的學習行為以及學習成效皆沒有顯著的關聯,可能的原因為前測以及後測的內容是基於學校的課程,並沒有任何問題是跟實驗有關的,例如:圖形的解釋以及公式的應用。因此我們根據前導實驗來執行我們的正式實驗,而在正式實驗中發現,學習行為(提出假設、圖形解釋、公式應用、結論統整以及概念理解)與學習成效間是有顯著正相關的(後測)。在進行更深入的探討後我們也發現,圖形的解釋以及概念的理解為兩個影響學習成效的重要因素。除此之外,學生也覺得本系統於操作上很容易,對於物理的學習也相當有幫助。因此,對於兩個實驗我們皆強烈的建議物理老師使用圖形來提升學生於相關知識上的吸收與了解,老師與研究者也應該設計相關的物理學習活動來提升系統中有支持的多重表徵能力,此外,行動裝置上較進階的功能,例如:加速度感測器、陀螺儀、光線感應以及GPS等等,對於物理學習上的應用也應該被考慮。
摘要(英) The aim of this study is to investigate relationship between learning behaviors and learning achievement on vocational students who use our developed system, Ubiquitous-Physics (U-Physics), to learn simple pendulum in the experiment. U-Physics can facilitate collecting experimental data and drawing the corresponding graphs during experiment, thereby students can focus on how to interpret graphs and solve problems through applying formula. Participants were first and second grade female vocational high school students who are less interested in physics, while hopefully by using, U-Physics in physical experiment can motivate their interests and help their learning in physics. Learning behaviors included hypothesis-making, interpreting graphs, applying formula, conclusion making, pair coherence and conceptual understanding. In pilot, we involved one class participant and two class participants for main study. Results of pilot study showed significant positive correlation between interpreting graphs and applying formula. This finding indicated that the ability to interpret graphs has an important role in scientific learning. Therefore, we strongly recommend that physics teachers use graphs to enrich students’ information content and understanding. In addition, negative correlation between pair coherence and interpreting graphs. It may be that most of the participants (vocational high school students) have limited skill or confidence in physics problem solving, so they often seek help from teachers or their high-achieving peers. In addition, the findings also indicated that U-Physics could enhance students’ learning achievement during a three-week time. However, pilot results showed that there were no significant correlations between learning behaviors and learning achievement. This might be due to the content of the pretest and posttest were designed based on the school curriculum and no questions related to the experiments, such as interpreting graphs and applying formula, were included. Therefore, we conducted the main study to follow up this pilot study. The findings of the main study were that positively significant correlations existed between learning behaviors (making hypothesis, interpreting graphs, applying formula, making conclusion, conceptual understanding) and learning achievement (posttest). After deep investigation, we found that interpreting graphs and conceptual understanding were the two most important factors to affect learning achievement. Additionally, students perceived that U-Physics was easy to use and useful for learning physics. Therefore, in both studies we strongly recommend that physics teachers use graphs to enrich students’ information content and understanding. Teachers and researchers also should design physics learning activities to improve students’ multiple representation skills supported by U-Physics and utilize advanced features of mobile devices such as acceleration sensors, gyroscope, light sensors and GPS for learning physics.
關鍵字(中) ★ 無所不在的物理
★ 假設決策
★ 解釋圖表
★ 公式運用
★ 結論決策
★ 概念理解
★ 多元表達
關鍵字(英) ★ Ubiquitous-Physics (U-Physics)
★ making hypothesis
★ interpreting graphs
★ applying formula
★ making conclusion
★ conceptual understanding
★ multiple representation
論文目次 中文摘要 i
Abstract ii
Acknowledgement iv
Contents v
List of Figures vii
List of Tables viii
List of Appendix ix
Chapter. 1 Introduction 1
1.1 Background and Motivation 1
1.2 Purpose 3
Chapter. 2 Literature Review 4
2. 1 Representation to facilitate scientific learning 4
2.2 Learning behaviors in scientific learning 6
2.3 Technology Acceptance Model 10
Chapter. 3 System Design and Implementation 13
3.1 Ubiquitous –Physics (U-Physics) 13
3.2 Implementation 15
Chapter. 4 Research Method 18
4.1 Research structure and research variables 18
4.2 Research flow and procedure 22
4.3 Research Subjects 26
4.4 Research tool 26
4.5 Experimental activities 28
4.6 Data collection and processing 30
Chapter. 5 Results and Analysis 32
5.1 Pilot study 32
5.1.1 Relationship among interpreting graphs, applying formula, and pair coherence 32
5.1.2 Relationship among pretest, posttest, and gain 35
5.1.3 Relationship between learning behaviors and learning achievement 35
5.2 Main study 36
5.2.1 Analysis of learning effect 36
5.2.2 Analysis of relationship between research variables and post-test 38
5.2.3 Students’ perception of U-Physics 41
Chapter. 6 Conclusions and Future Works 45
6.1 Conclusions 45
6.2 Future works 46
References 47
Appendix 51
參考文獻 Ainsworth, S. (1999). The functions of multiple representations. Computers & Education, 33(2), 131-152.
Beichner, R. J. (1994). Testing student interpretation of kinematics graphs.American journal of Physics, 62(8), 750-762.
Cai, J., & Hwang, S. (2002). Generalized and generative thinking in US and Chinese students’ mathematical problem solving and problem posing. The Journal of Mathematical Behavior, 21(4), 401-421.
Chambers, J. M. (1983). Graphical methods for data analysis.
Chung, J., & Tan, F. B. (2004). Antecedents of perceived playfulness: an exploratory study on user acceptance of general information-searching websites. Information & Management, 41(7), 869-881.
Dabbagh, N., & Kitsantas, A. (2012). Personal Learning Environments, social media, and self-regulated learning: A natural formula for connecting formal and informal learning. The Internet and higher education, 15(1), 3-8.
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS quarterly, 319-340.
De Jong, T. (2006). Scaffolds for scientific discovery learning. Handling complexity in learning environments: Theory and research, 107-128.
DeWindt-King, A., & Goldin, G. (2003). Children’s visual imagery: Aspects of cognitive representation in solving problems with fractions. Mediterranean Journal for Research in Mathematics Education, 2(1), 1-42.
Duschl, R. A., & Gitomer, D. H. (1991). Epistemological perspectives on conceptual change: Implications for educational practice. Journal of research in science teaching, 28(9), 839-858.
Dykstra, D. I., Boyle, C. F., & Monarch, I. A. (1992). Studying conceptual change in learning physics. Science Education, 76(6), 615-652.
Etkina, E., Murthy, S., & Zou, X. (2006). Using introductory labs to engage students in experimental design. American Journal of Physics, 74(11), 979-986.
Gagne, E. D., Yekovich, C. W., & Yekovich, F. R. (1993). The cognitive psychology of school learning: Allyn & Bacon.
Goldin, G. A. (1998). Representational systems, learning, and problem solving in mathematics. The Journal of Mathematical Behavior, 17(2), 137-165.
Hwang, G. J., Wu, P. H., Zhuang, Y. Y., & Huang, Y. M. (2013). Effects of the inquiry-based mobile learning model on the cognitive load and learning achievement of students. Interactive Learning Environments, 21(4), 338-354.
Hwang, W.-Y., Chen, N.-S., Dung, J.-J., & Yang, Y.-L. (2007). Multiple representation skills and creativity effects on mathematical problem solving using a multimedia whiteboard system. Educational Technology & Society, 10(2), 191-212.
Hwang, W.-Y., Chen, N.-S., & Hsu, R.-L. (2006). Development and evaluation of multimedia whiteboard system for improving mathematical problem solving. Computers & Education, 46(2), 105-121.
Hwang, W.-Y., Huang, Y.-M., Shadiev, R., Wu, S.-Y., & Chen, S.-L. (2014). Effects of using mobile devices on English listening diversity and speaking for EFL elementary students. Australasian Journal of Educational Technology, 30(5), 503-516.
Jimoyiannis, A., & Komis, V. (2001). Computer simulations in physics teaching and learning: a case study on students′ understanding of trajectory motion. Computers & education, 36(2), 183-204.
Johnson, S. (1998). What′s in a representation, why do we care, and what does it mean? Examining evidence from psychology. Automation in Construction, 8(1), 15-24.
Klahr, D., & Dunbar, K. (1988). Dual space search during scientific reasoning. Cognitive science, 12(1), 1-48.
Kintsch, W. (2014). The Representation of Meaning in Memory (PLE: Memory): Psychology Press.
Kohl, P. B., Rosengrant, D., & Finkelstein, N. D. (2007). Strongly and weakly directed approaches to teaching multiple representation use in physics. Physical Review Special Topics-Physics Education Research, 3(1), 010108.
Larkin‡, J. H., & Reif, F. (1979). Understanding and teaching problem‐solving in physics. European Journal of Science Education, 1(2), 191-203.
Lesh, R., Post, T., & Behr, M. (1987). Representations and translations among representations in mathematics learning and problem solving. Problems of representation in the teaching and learning of mathematics, 33-40.
Martin, M., Mullis, I., Foy, P., Olson, J., Erberber, E., Preuschoff, C., & Galia, J. (2008). TIMSS 2007 international science report: Findings from IEA’s mathematics and science study at the fourth and eighth grade. Chestnut Hill, MA: TIMSS & PIRLS International Study Center, Boston College.
Mayer, R. E. (1992). Thinking, problem solving, cognition: WH Freeman/Times Books/Henry Holt & Co.
McLeod, J. D., & Kaiser, K. (2004). Childhood emotional and behavioral problems and educational attainment. American Sociological Review, 69(5), 636-658.
McKenzie, D. L., & Padilla, M. J. (1986). The construction and validation of the test of graphing in science (TOGS). Journal of Research in Science Teaching, 23(7), 571-579.
Milrad, M. (2002). Using construction kits, modeling tools and system dynamics simulations to support collaborative discovery learning. Educational Technology & Society, 5(4), 76-87.
Mokros, J. R., & Tinker, R. F. (1987). The impact of microcomputer‐based labs on children′s ability to interpret graphs. Journal of research in science teaching, 24(4), 369-383.
Moon, J.-W., & Kim, Y.-G. (2001). Extending the TAM for a World-Wide-Web context. Information & Management, 38(4), 217-230.
Nakahara, T. (2008). Cultivating mathematical thinking through representation-utilizing the representational system. Paper presented at the APEC-TSUKUBA International Congress, Japan.
Posner, G. J., Strike, K. A., Hewson, P. W., & Gertzog, W. A. (1982). Accommodation of a scientific conception: Toward a theory of conceptual change. Science education, 66(2), 211-227.
Sherin, B. L. (2001). How students understand physics equations. Cognition and instruction, 19(4), 479-541.
Tarhini, A., Hone, K., & Liu, X. (2014). Measuring the moderating effect of gender and age on e-learning acceptance in england: A structural equation modeling approach for an extended technology acceptance model. Journal of Educational Computing Research, 51(2), 163-184. doi: http://dx.doi.org/10.2190/EC.51.2.b
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS quarterly, 425-478.
Zhang, J. (1997). The nature of external representations in problem solving. Cognitive science, 21(2), 179-217.
指導教授 黃武元(Wu-Yuin Hwang) 審核日期 2016-12-27
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