政大機構典藏-National Chengchi University Institutional Repository(NCCUR):Item 140.119/124824
English  |  正體中文  |  简体中文  |  Post-Print筆數 : 27 |  Items with full text/Total items : 113451/144438 (79%)
Visitors : 51274053      Online Users : 873
RC Version 6.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.
Scope Tips:
  • please add "double quotation mark" for query phrases to get precise results
  • please goto advance search for comprehansive author search
  • Adv. Search
    HomeLoginUploadHelpAboutAdminister Goto mobile version
    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/124824


    Title: 發展「即時觀點比較系統」促進討論歷程中學習者的學習成效
    Developing Instant Perspective Comparison System to Facilitate Learning Performance of Learners in Discussion Process
    Authors: 曹瀚文
    Tsao, Han-Wen
    Contributors: 陳志銘
    Chen, Chih-Ming
    曹瀚文
    Tsao, Han-Wen
    Keywords: 線上討論
    觀點比較機制
    自我網絡分析
    資料視覺化
    自然語言
    學習行為歷程
    社會性科學議題
    電腦中介溝通能力
    科技接受度
    online discussion
    perspective comparison mechanism
    ego-network analysis
    data visualization
    natural language
    learning behavior process
    socio-scientific issues
    computer-mediated communication ability
    technology acceptance
    Date: 2019
    Issue Date: 2019-08-07 16:26:11 (UTC+8)
    Abstract: 線上討論為數位學習常見的學習活動,過程中可以透過與他人互動交流,獲取更多知識和不同意見想法,提升學習者對於學習議題的認知與批判思考能力。其中,社會性科學議題(Socio-Scientific Issues, SSI)更是討論活動中常見的主題之一,這類議題牽涉層面廣泛、內容複雜且無標準答案,在SSI的討論過程中,學習者的意見發想扮演著相當重要的角色,是影響討論成效的關鍵要素。因此,本研究設計「即時觀點比較系統(Instant Perspective Comparison System, 以下簡稱IPCS)」,希望透過視覺化觀點比較的方式來呈現雙方在意見想法上的異同,以促進討論過程中學習者思考的深度與廣度,提升線上討論學習成效。

    本研究採用準實驗研究,隨機選取台北市某高中二年級兩班共63名學生為研究對象,進行「核能發電」主題之線上討論。其中一班36名學生被隨機分派為採用IPCS輔助線上討論的實驗組,另一班27名學生則被隨機分派為僅使用一般線上討論的控制組,以探討兩組學習者在學習表現與科技接受度上是否具有顯著差異。此外,也以先備知識、電腦中介溝通(Computer-Mediated Communication, CMC)能力作為背景變項,探討不同背景變項之兩組學習者,在學習表現以及科技接受度上是否具有顯著差異。此外,也透過滯後序列分析(Lag Sequential Analysis, LSA)探討實驗組學習者之有效學習行為模式。

    研究結果發現,相較於使用一般傳統線上討論區,採用IPCS輔助線上討論對於促進學習者的整體學習表現、分項多觀點具有顯著的助益。IPCS亦能提升低CMC能力學習者的學習表現,並且提升其討論內容的複雜度,使其對於討論議題有更深入地理解與認識。而在科技接受度上兩組並沒有達到統計上的顯著差異,皆呈現普遍高的科技接受度,但是實驗組學習者科技接受度平均分數高於控制組學習者,表示學習者對IPCS抱持較正面、滿意態度。此外,從訪談質性資料與學習歷程行為分析的結果來看,多元度計算和觀點異同比較等功能對於促進討論內容理解具有益處,學習者若將能將思考著重在相同議題的切入點差異上,或是瀏覽貼文資訊後能多檢視自己的討論內容,則IPCS將能有效地促進學習者進行線上討論時的學習表現。

    最後基於研究結果,本研究提出IPCS教學建議和Moodle討論區改善建議,以及未來可以繼續進一步探討的研究方向。整體而言,本研究將討論區學習、自然語言處理、社會網絡與資料視覺化等技術進行結合,發展IPCS,提供一個科技輔助線上討論之創新有效學習工具,對於促進數位學習之線上討論具有貢獻。
    Online discussion, the common learning activity in e-learning, allows acquiring more knowledge and different opinions and ideas through interaction and exchange with others in the process to promote leaners’ cognition of learning issues and critical thinking ability. Socio-scientific issues (SSI) are a commonly discussed issue in the activity. Such issues involve in broad dimensions, show complicated contents, and have no standard answers. In the SSI discussion process, learners’ opinions and ideas play critical roles and are the critical factors in the discussion effectiveness. Accordingly, “Instant Perspective Comparison System (IPCS)” is designed in this study, expecting to present the differences in the opinions and ideas of both parties through visualization perspective comparison in order to facilitate the depth and width of learners’ thinking in the discussion process and promote the learning effectiveness of online discussion.

    With quasi-experimental study, 63 students of two G11 classes in a senior high school in Taipei City are randomly selected for the online discussion about “nuclear power generation”. 36 students of a class are randomly assigned as the experimental group with IPCS assisted online discussion, and 27 students of another class are randomly assigned as the control group with general online discussion to discuss the differences in learning performance and technology acceptance of learners between two groups. Furthermore, prior knowledge and computer-mediated communication (CMC) ability are regarded as the background variables to discuss the differenced in learning performance and technology acceptance of learners between two groups. What is more, lag sequential analysis (LSA) is also used for discussing the effective learning behavior model of learners in the experimental group.
    The research result shows that, in comparison with general online discussion, IPCS assisted online discussion could significantly facilitate leaners’ overall learning performance and sub-item multiple perspectives. IPCS could also promote the learning performance of learners with low CMC ability as well as enhance the complexity of the discussion content so as to more deeply comprehend and understand the discussion issue. In terms of technology acceptance, both groups do not achieve remarkable statistical differences and present generally high technology acceptance. However, learners in the experimental group show higher average scores on technology acceptance than those in the control group, revealing learners’ positive and satisfactory attitudes towards IPCS. According to the qualitative interview data and the behavior analysis in the learning process, functions of multiple calculation and perspective comparison could facilitate the comprehension of discussion content. When a learner is able to focus the thinking on different cutting points of the same issue or review the discussion content after browsing the post information, IPCS would effectively facilitate learners’ learning performance during online discussion.

    Based on the research result, suggestions for the improvement of IPCS teaching and Moodle discussion as well as further research directions are proposed in this study. Overall speaking, discussion learning, natural language processing, social network, and data visualization are combined in this study to develop IPCS for the innovative and effective learning of technology assisted online discussion. It would contribute to facilitating online discussion in e-learning.
    Reference: Acar, O., Turkmen, L., & Roychoudhury, A. (2010). Student Difficulties in Socio‐scientific Argumentation and Decision‐making Research Findings: Crossing the borders of two research lines. International Journal of Science Education, 32(9), 1191–1206. doi:10.1080/09500690902991805
    Althaus, S. L. (1997). Computer-mediated communication in the university classroom an experiment with on-line discussions. Communication Education, 46(3), 158. doi:10.1080/03634529709379088
    Anker-Hansen, J., & Andrée, M. (2015). Affordances and Constraints of Using the Socio-Political Debate for Authentic Summative Assessment. International Journal of Science Education, 37(15), 2577–2596. doi:10.1080/09500693.2015.1087068
    Bakeman, R., & Gottman, J. M. (1997). Observing interaction: An introduction to sequential analysis, 2nd ed. New York: Cambridge University Press. doi:10.1017/CBO9780511527685
    Bell, P., & Linn, M. C. (2000). Scientific arguments as learning artifacts: designing for learning from the web with KIE. International Journal of Science Education, 22(8), 797–817. doi:10.1080/095006900412284
    Buder, J., Schwind, C., Rudat, A., & Bodemer, D. (2015). Selective reading of large online forum discussions: The impact of rating visualizations on navigation and learning. Computers in Human Behavior, 44, 191–201. doi:10.1016/j.chb.2014.11.043
    Camarero, C., Rodríguez, J., & San José, R. (2012). An exploratory study of online forums as a collaborative learning tool. Online Information Review, 36(4), 568–586. doi:10.1108/14684521211254077
    Cela, K. L., Sicilia, M. Á., & Sánchez, S. (2015). Social Network Analysis in E-Learning Environments: A Preliminary Systematic Review. Educational Psychology Review, 27(1), 219–246. doi:10.1007/s10648-014-9276-0
    Chang, H.-Y., Hsu, Y.-S., & Wu, H.-K. (2014). A comparison study of augmented reality versus interactive simulation technology to support student learning of a socio-scientific issue. Interactive Learning Environments, 24(6), 1148–1161. doi:10.1080/10494820.2014.961486
    Chen, C.-Y. (2012). The influence of perceived information overload on student participation and knowledge construction in computer-mediated communication. Instructional Science, 40(2), 325–349. doi:10.1007/s11251-011-9179-0
    Christenson, N., Chang Rundgren, S.-N., & Zeidler, D. L. (2014). The Relationship of Discipline Background to Upper Secondary Students’ Argumentation on Socioscientific Issues. Research in Science Education, 44(4), 581–601. doi:10.1007/s11165-013-9394-6
    Cooper, L. W. (2001). A Comparison of Online and Traditional Computer Applications Classes. T.H.E. Journal, 28(8).
    Cotton, D., & Yorke, J. (2006). Analysing online discussions: What are students learning?, 9.
    Dado, M., & Bodemer, D. (2017). A review of methodological applications of social network analysis in computer-supported collaborative learning. Educational Research Review, 22, 159–180. doi:10.1016/j.edurev.2017.08.005
    Damon, W., & Killen, M. (1982). Peer Interaction and the Process of Change in Children’s Moral Reasoning. Merrill-Palmer Quarterly, 28(3), 347–367.
    Darabi, A., & Jin, L. (2013). Improving the quality of online discussion: the effects of strategies designed based on cognitive load theory principles. Distance Education, 34(1), 21–36. doi:10.1080/01587919.2013.770429
    Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User Acceptance of Computer Technology: A Comparison of Two Theoretical Models. Management Science, 35(8), 982–1003. doi:10.1287/mnsc.35.8.982
    Driver, R., Newton, P., & Osborne, J. (2000). Establishing the Norms of Scientific Argumentation in Classrooms. Science Education, 84(3), 287–312. doi:10.1002/(SICI)1098-237X(200005)84:3<287::AID-SCE1>3.0.CO;2-A
    Eid, M. I. M., & Al-Jabri, I. M. (2016). Social networking, knowledge sharing, and student learning: The case of university students. Computers & Education, 99, 14–27. doi:10.1016/j.compedu.2016.04.007
    Franz, T. M., & Vicker, L. A. (2010). Using a Virtual Class to Demonstrate Computer-Mediated Group Dynamics Concepts. Teaching of Psychology, 37(2), 124–128. doi:10.1080/00986281003626573
    Gao, F., Zhang, T., & Franklin, T. (2013). Designing asynchronous online discussion environments: Recent progress and possible future directions. British Journal of Educational Technology, 44(3), 469–483. doi:10.1111/j.1467-8535.2012.01330.x
    Gleicher, M., Albers, D., Walker, R., Jusufi, I., Hansen, C. D., & Roberts, J. C. (2011). Visual comparison for information visualization. Information Visualization, 10(4), 289–309. doi:10.1177/1473871611416549
    Grace, M., Lee, Y. C., Asshoff, R., & Wallin, A. (2015). Student Decision-Making about a Globally Familiar Socioscientific Issue The value of sharing and comparing views with international counterparts. International Journal of Science Education, 37(11), 1855–1874. doi:10.1080/09500693.2015.1054000
    Guldberg, K. (2007). Tutor roles in facilitating reflection on practice through online discussion. Educational Technology & Society, 10(1), 61–72.
    Hasan, B., & Ahmed, M. U. (2007). Effects of interface style on user perceptions and behavioral intention to use computer systems. Computers in Human Behavior, 23(6), 3025–3037. doi:10.1016/j.chb.2006.08.016
    Hew, K. F., & Cheun, W. S. (2003). Evaluating the participation and quality of thinking of pre-service teachers in an asynchronous online discussion environment:part I. Internation Journal of Instru, 30(3), 16.
    Hung, M.-L., & Chou, C. (2014). The Development, Validity, and Reliability of Communication Satisfaction in an Online Asynchronous Discussion Scale. The Asia-Pacific Education Researcher, 23(2), 165–177. doi:10.1007/s40299-013-0094-9
    Hwang, G.-J., Yang, L.-H., & Wang, S.-Y. (2013). A concept map-embedded educational computer game for improving students’ learning performance in natural science courses. Computers & Education, 69, 121–130. doi:10.1016/j.compedu.2013.07.008
    Hyde-Clarke, N. (2013). Facebook and public debate: An informal learning tool for the youth. Journal of African Media Studies, 5(2), 131–148. doi:10.1386/jams.5.2.131_1
    Iandoli, L., Quinto, I., De Liddo, A., & Buckingham Shum, S. (2016). On Online Collaboration and Construction of Shared Knowledge: Assessing Mediation Capability in Computer Supported Argument Visualization Tools. Journal of the Association for Information Science and Technology, 67(5), 1052–1067. doi:10.1002/asi.23481
    Jeong, A., & Frazier, S. (2008). How day of posting affects level of critical discourse in asynchronous discussions and computer-supported collaborative argumentation. British Journal of Educational Technology, 39(5), 875–887. doi.org/10.1111/j.1467-8535.2007.00789.x
    Johnson, D., Sutton, P., & Poon, J. (2000). Face-to-Face vs. CMC Student communication in a technologically rich learning environment. In ASCILITE 2000 (p. 15). Australia.
    Jyothi, S., McAvinia, C., & Keating, J. (2012). A visualisation tool to aid exploration of students’ interactions in asynchronous online communication. Computers & Education, 58(1), 30–42. doi.org/10.1016/j.compedu.2011.08.026
    Kallio, H., Pietilä, A.-M., Johnson, M., & Kangasniemi, M. (2016). Systematic methodological review: developing a framework for a qualitative semi-structured interview guide. Journal of Advanced Nursing, 72(12), 2954–2965. doi:10.1111/jan.13031
    Karpudewan, M., & Roth, W.-M. (2016). Changes in Primary Students’ Informal Reasoning During an Environment-Related Curriculum on Socio-scientific Issues. International Journal of Science and Mathematics Education, 16(3), 401–419. doi:10.1007/s10763-016-9787-x
    Kemp, N., & Grieve, R. (2014). Face-to-face or face-to-screen? Undergraduates’ opinions and test performance in classroom vs. online learning. Frontiers in Psychology, 5. doi:10.3389/fpsyg.2014.01278

    Kim, J., Jo, I.-H., & Park, Y. (2016). Effects of learning analytics dashboard: analyzing the relations among dashboard utilization, satisfaction, and learning achievement. Asia Pacific Education Review, 17(1), 13–24. doi:10.1007/s12564-015-9403-8
    Lambropoulos, N., Faulkner, X., & Culwin, F. (2012). Supporting social awareness in collaborative e-learning: A case study. British Journal of Educational Technology, 43(2), 295–306. doi:10.1111/j.1467-8535.2011.01184.x
    Lederer, A. L., Maupin, D. J., Sena, M. P., & Zhuang, Y. (2000). The technology acceptance model and the World Wide Web. Decision Support Systems, 29(3), 269–282. doi:10.1016/S0167-9236(00)00076-2
    Lee, H., Kim, J. W., & Hackney, R. (2011). Knowledge hoarding and user acceptance of online discussion board systems in eLearning: A case study. Computers in Human Behavior, 27(4), 1431–1437. doi:10.1016/j.chb.2010.07.047
    Lee, Y. C., & Grace, M. (2012). Students’ Reasoning and Decision Making About a Socioscientific Issue A Cross-Context Comparison. Science Education, 96(5), 787–807. doi:10.1002/sce.21021
    Levinson, R. (2006). Towards a Theoretical Framework for Teaching Controversial Socio‐scientific Issues. International Journal of Science Education, 28(10), 1201–1224. doi:10.1080/09500690600560753
    Li, L.-Y. (2019). Effect of Prior Knowledge on Attitudes, Behavior, and Learning Performance in Video Lecture Viewing. International Journal of Human–Computer Interaction, 35(4–5), 415–426. doi:10.1080/10447318.2018.1543086
    Lin, S. S., & Mintzes, J. J. (2010). Learning argumentation skills through instruction in socioscientific issues The effect of ability level. International Journal of Science and Mathematics Education, 8(6), 993–1017. doi:10.1007/s10763-010-9215-6
    Liu, D., Guo, F., Deng, B., Qu, H., & Wu, Y. (2017). egoComp: A node-link-based technique for visual comparison of ego-networks. Information Visualization, 16(3), 179–189. doi:10.1177/1473871616667632
    Lo, H.-C. (2009). Utilizing Computer-mediated Communication Tools for Problem-based Learning. Educational Technology & Society, 12(1), 205–213.
    Manku, G. S., Jain, A., & Das Sarma, A. (2007). Detecting near-duplicates for web crawling. In Proceedings of the 16th international conference on World Wide Web - WWW ’07 (p. 141). Banff, Alberta, Canada: ACM Press. doi:10.1145/1242572.1242592
    Marbouti, F., & Wise, A. F. (2016). Starburst: a new graphical interface to support purposeful attention to others’ posts in online discussions. Educational Technology Research and Development, 64(1), 87–113. doi:10.1007/s11423-015-9400-y
    Marei, H. F., & Al-Khalifa, K. S. (2015). Pattern of online communication in teaching a blended oral surgery course. European Journal of Dental Education, 20(4), 213–217. doi:10.1111/eje.12163
    Murphy, E. (2004). Recognising and promoting collaboration in an online asynchronous discussion. British Journal of Educational Technology, 35(4), 421–431. doi:10.1111/j.0007-1013.2004.00401.x
    Nam, Y. (2017). Promoting Argumentative Practice in Socio-Scientific Issues through a Science Inquiry Activity. EURASIA Journal of Mathematics, Science and Technology Education, 13. doi:10.12973/eurasia.2017.00737a
    Newman, M. E. J. (2001). Scientific collaboration networks. I. Network construction and fundamental results. Physical Review E, 64(1). doi:10.1103/PhysRevE.64.016131
    Nicolaidou, I., Kyza, E. A., Terzian, F., Hadjichambis, A., & Kafouris, D. (2011). A framework for scaffolding students’ assessment of the credibility of evidence. Journal of Research in Science Teaching, 48(7), 711–744. doi:10.1002/tea.20420
    Ouyang, F., & Scharber, C. (2017). The influences of an experienced instructor’s discussion design and facilitation on an online learning community development: A social network analysis study. The Internet and Higher Education, 35, 34–47. doi:10.1016/j.iheduc.2017.07.002
    Papadouris, N., & Constantinou, C. P. (2010). Approaches employed by sixth-graders to compare rival solutions in socio-scientific decision-making tasks. Learning and Instruction, 20(3), 225–238. doi:10.1016/j.learninstruc.2009.02.022
    Reitz, F. (2010). A Framework for an Ego-centered and Time-aware Visualization of Relations in Arbitrary Data Repositories. ArXiv:1009.5183 [Cs]. Retrieved from http://arxiv.org/abs/1009.5183
    Roschelle, J., & Teasley, S. D. (1995). The Construction of Shared Knowledge in Collaborative Problem Solving. In C. O’Malley (Ed.), Computer Supported Collaborative Learning (pp. 69–97). Berlin, Heidelberg: Springer Berlin Heidelberg. doi:10.1007/978-3-642-85098-1_5
    Sadler, T. D. (2004). Informal Reasoning Regarding Socioscientific Issues A Critical Review of Research. Journal of Research in Science Teaching, 41(5), 513–536. doi:10.1002/tea.20009
    Sadler, T. D., & Zeidler, D. L. (2005). Patterns of informal reasoning in the context of socioscientific decision making. Journal of Research in Science Teaching, 42(1), 112–138. doi:10.1002/tea.20042
    Sadler, T. D., Barab, S. A., & Scott, B. (2007). What Do Students Gain by Engaging in Socioscientific Inquiry? Research in Science Education, 37(4), 371–391. doi:10.1007/s11165-006-9030-9
    Sampson, V., & Clark, D. B. (2009). A Comparison of the Collaborative Scientific Argumentation Practices of Two High and Two Low Performing Groups. Research in Science Education, 41(1), 63–97. doi:10.1007/s11165-009-9146-9
    Seethaler, S., & Linn, M. (2004). Genetically modified food in perspective: an inquiry‐based curriculum to help middle school students make sense of tradeoffs. International Journal of Science Education, 26(14), 1765–1785. doi:10.1080/09500690410001673784
    So, H. J. (2009). When groups decide to use asynchronous online discussions: collaborative learning and social presence under a voluntary participation structure: Asynchronous online discussion. Journal of Computer Assisted Learning, 25(2), 143–160. doi:10.1111/j.1365-2729.2008.00293.x
    Solli, A., Hillman, T., & Mäkitalo, Å. (2017). Navigating the Complexity of Socio-scientific Controversies—How Students Make Multiple Voices Present in Discourse. Research in Science Education. doi:10.1007/s11165-017-9668-5
    Spitzberg, B. H. (2006). Preliminary Development of a Model and Measure of Computer-Mediated Communication (CMC) Competence. Journal of Computer-Mediated Communication, 11(2), 629–666. doi:10.1111/j.1083-6101.2006.00030.x
    Stolz, M., Witteck, T., & Marks, R. (2013). Reflecting socio-scientific issues for science education coming from the case of curriculum development on doping in chemistry education. Eurasia Journal of Mathematics, Science and Technology Education, 9(4), 361–370. doi:10.12973/eurasia.2014.945a
    Sundar, S. S. (2008). The MAIN Model: A Heuristic Approach to Understanding Technology Effects on Credibility. Digital Media, 73–100. doi:10.1162/dmal.9780262562324.073
    Tytler, R. (2012). Socio-Scientific Issues, Sustainability and Science Education. Research in Science Education, 42(1), 155–163. doi:10.1007/s11165-011-9262-1
    Van Blankenstein, F. M., Dolmans, D. H. J. M., Van der Vleuten, C. P. M., & Schmidt, H. G. (2013). Relevant prior knowledge moderates the effect of elaboration during small group discussion on academic achievement. Instructional Science, 41(4), 729–744. doi:10.1007/s11251-012-9252-3
    Venkatesh, V. (2000). A theoretical extension of the technology acceptance model, four longitudinal field studies. Management Science, 46(2), 186–204. doi:10.1287/mnsc.46.2.186.11926
    Wang, Q., & Woo, H. L. (2007). Comparing asynchronous online discussions and face-to-face discussions in a classroom setting. British Journal of Educational Technology, 38(2), 272–286. doi:10.1111/j.1467-8535.2006.00621.x
    Wang, Q., Woo, H. L., Quek, C. L., Yang, Y., & Liu, M. (2012). Using the Facebook group as a learning management system: An exploratory study: Using Facebook group as an LMS. British Journal of Educational Technology, 43(3), 428–438. doi:10.1111/j.1467-8535.2011.01195.x
    Weinberger, A., & Fischer, F. (2006). A framework to analyze argumentative knowledge construction in computer-supported collaborative learning. Computers & Education, 46(1), 71–95. doi:10.1016/j.compedu.2005.04.003
    Weinberger, A., Stegmann, K., & Fischer, F. (2007). Knowledge convergence in collaborative learning: Concepts and assessment. Learning and Instruction, 17(4), 416–426. doi:10.1016/j.learninstruc.2007.03.007
    Xie, K., Yu, C., & Bradshaw, A. C. (2014). Impacts of role assignment and participation in asynchronous discussions in college-level online classes. The Internet and Higher Education, 20, 10–19. doi:10.1016/j.iheduc.2013.09.003
    Yang, F. (2017). Examining the reasoning of conflicting science information from the information processing perspective—an eye movement analysis. Journal of Research in Science Teaching, 54(10), 1347–1372. doi:doi.org/10.1002/tea.21408
    Yang, F. Y., & Tsai, C. C. (2010). Reasoning about science-related uncertain issues and epistemological perspectives among children. Instructional Science, 38(4), 325–354. doi:10.1007/s11251-008-9084-3
    Yeo, T. M., & Quek, C. L. (2014). Scaffolding high school students’ divergent idea generation in a computer-mediated design and technology learning environment. International Journal of Technology and Design Education, 24(3), 275–292. doi:10.1007/s10798-013-9257-5
    Yu, S. Y. (2013). Detecting collaboration patterns among iSchools by linking scholarly communication to social networking at the macro and micro levels, Library and Information Science Research e-journal, 23(2), 14.
    Zhang, L., Beach, R., & Sheng, Y. (2016). Understanding the use of online role-play for collaborative argument through teacher experiencing: A case study. Asia-Pacific Journal of Teacher Education, 44(3), 242–256. doi:10.1080/1359866X.2015.1081673
    Zohar, A., & Nemet, F. (2002). Fostering students’ knowledge and argumentation skills through dilemmas in human genetics. Journal of Research in Science Teaching, 39(1), 35–62. doi:10.1002/tea.10008
    Description: 碩士
    國立政治大學
    圖書資訊與檔案學研究所
    106155005
    Source URI: http://thesis.lib.nccu.edu.tw/record/#G0106155005
    Data Type: thesis
    DOI: 10.6814/NCCU201900506
    Appears in Collections:[Graduate Institute of Library, Information and Archival Studies] Theses

    Files in This Item:

    File SizeFormat
    500501.pdf3452KbAdobe PDF20View/Open


    All items in 政大典藏 are protected by copyright, with all rights reserved.


    社群 sharing

    著作權政策宣告 Copyright Announcement
    1.本網站之數位內容為國立政治大學所收錄之機構典藏,無償提供學術研究與公眾教育等公益性使用,惟仍請適度,合理使用本網站之內容,以尊重著作權人之權益。商業上之利用,則請先取得著作權人之授權。
    The digital content of this website is part of National Chengchi University Institutional Repository. It provides free access to academic research and public education for non-commercial use. Please utilize it in a proper and reasonable manner and respect the rights of copyright owners. For commercial use, please obtain authorization from the copyright owner in advance.

    2.本網站之製作,已盡力防止侵害著作權人之權益,如仍發現本網站之數位內容有侵害著作權人權益情事者,請權利人通知本網站維護人員(nccur@nccu.edu.tw),維護人員將立即採取移除該數位著作等補救措施。
    NCCU Institutional Repository is made to protect the interests of copyright owners. If you believe that any material on the website infringes copyright, please contact our staff(nccur@nccu.edu.tw). We will remove the work from the repository and investigate your claim.
    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library IR team Copyright ©   - Feedback