华东师范大学学报(教育科学版) ›› 2022, Vol. 40 ›› Issue (9): 67-77.doi: 10.16382/j.cnki.1000-5560.2022.09.007
杜华1, 顾小清2
出版日期:
2022-09-01
发布日期:
2022-08-24
基金资助:
Hua Du1, Xiaoqing Gu2
Online:
2022-09-01
Published:
2022-08-24
摘要:
理解被广泛认为是教育的重要价值追求,“为理解而教,为理解而学”已然成为学界共识。知识理解是概念转变的基础,知识应用与创新的前提,是学习者高阶思维发展的关键,是深度学习的旨向。人工智能为学习者提供更多样的知识呈现方式与形态,提供更精准的学习分析,创设智能化的真实学习情境,为学习者的概念转变与知识理解创造了良好的条件。正是基于这样的背景,我们以概念转变为切入点,以上海方略教育研发的智能全息盒子为主要的智能仿真学习环境,开展了一项实证研究,旨在探究智能仿真学习环境对学习者概念转变的影响,由此窥察人工智能促进知识理解的诸多可能。研究结果表明,人工智能所建构的智能仿真学习环境,对于学习者概念转变具有积极的促进作用。
杜华, 顾小清. 人工智能促进知识理解:以概念转变为目标的实证研究[J]. 华东师范大学学报(教育科学版), 2022, 40(9): 67-77.
Hua Du, Xiaoqing Gu. Artificial Intelligence for Knowledge Understanding: An Empirical Study Aimed at Conceptual Change[J]. Journal of East China Normal University(Educational Sciences), 2022, 40(9): 67-77.
1 | 陈家刚. (2013). 促进理解性学习的课程和教学设计原则. 全球教育展望, 42 (01), 53- 61. |
2 | 陈明选, 刘径言. (2012). 教育信息化进程中教学设计的转型——基于理解的视角. 电化教育研究, 33 (08), 10- 16. |
3 | 邓峰, 钱扬义. (2007). 国外几种科学概念转变教学模式简介与评析. 中学化学教学参考, (04), 61- 63. |
4 | 杜华, 顾小清. (2020). 教育技术学理论五问——兼论教育技术学之于教育学理论建构的贡献. 教育研究, 41 (01), 148- 159. |
5 | 顾小清. (2021). 当现实逼近想象: 人工智能时代预见未来教育研究. 开放教育研究, 27 (01), 4- 12. |
6 |
郭炯, 郝建江. (2019). 人工智能环境下的学习发生机制. 现代远程教育研究, 31 (05), 32- 38.
doi: 10.3969/j.issn.1009-5195.2019.05.004 |
7 | 胡卫平, 刘建伟. (2004). 概念转变模型: 理论基础、主要内容、发展与修正. 学科教育, (12), 34- 38. |
8 | 牟智佳. (2017). “人工智能+”时代的个性化学习理论重思与开解. 远程教育杂志, 35 (03), 22- 30. |
9 |
彭聪. (2015). 我国概念转变教学策略的研究综述. 教育导刊, (09), 54- 57.
doi: 10.3969/j.issn.1005-3476.2015.09.013 |
10 | 乔纳森. (2008). 技术支持的思维建模: 用于概念转变的思维工具(顾小清译). 上海: 华东师范大学出版社. |
11 | 舒杭. (2020). 学习分析技术支持的概念转变过程研究. 上海: 华东师范大学博士论文. |
12 | 孙崇勇. (2012). 认知负荷的测量及其在多媒体学习中的应用. 苏州: 苏州大学博士论文. |
13 | 孙艳超. (2016). 可视化工具支持的概念转变研究. 上海: 华东师范大学博士论文. |
14 | 闫志明, 唐夏夏, 秦旋, 张飞, 段元美. (2017). 教育人工智能(EAI)的内涵、关键技术与应用趋势——美国《为人工智能的未来做好准备》和《国家人工智能研发战略规划》报告解析. 远程教育杂志, 35 (01), 26- 35. |
15 | 袁维新. (2003). 概念转变学习的内在机制探析. 教育研究与实验, (02), 49- 54. |
16 |
王燕. (2014). “理解性教学”的理念与实践. 上海教育科研, (02), 77- 79.
doi: 10.3969/j.issn.1007-2020.2014.02.023 |
17 | 王珏, 解月光. (2017). 基于前概念体系的学习者认知诊断方法研究——以初中物理“力与运动”主题为例. 电化教育研究, 38 (9), 122- 128. |
18 | 杨玉桓, 汪波, 雷颜萍, 李秀玉. (1988). 浅谈试卷的信度与效度. 天津教育, (11), 19- 20. |
19 | 张良, 关素芳. (2021). 为理解而学: 人工智能时代的知识学习. 湖南师范大学教育科学学报, 20 (01), 55- 60. |
20 | 张琼, 胡炳仙. (2016). 知识的情境性与情境化课程设计. 课程. 教材. 教法, 36 (06), 26- 32. |
21 | 邹一娜, 周勇. (2011). 课堂探究学习活动中概念教学策略研究. 全球教育展望, 40 (02), 82- 87. |
22 |
Brown, J. S., Collins, A., &Duguid, P. (1989). Situated Cognition and the Culture of Learning. Educational Researcher, 18 (1), 32- 42.
doi: 10.3102/0013189X018001032 |
23 |
DiSessa A. A. (1982). Unlearning Aristotelian physics: A study of knowledge-based learning. Cognitive science, 6 (1), 37- 75.
doi: 10.1207/s15516709cog0601_2 |
24 | Foley, B. J. (1999). Visualization tool: Models, Representation and Knowledge Integration. Berkeley: University of California. |
25 |
Gobert J. D, Clement J. J. (1999). Effects of student-generated diagrams versus student-generated summaries on conceptual understanding of causal and dynamic knowledge in plate tectonics. Journal of Research in Science Teaching, 36 (1), 39- 53.
doi: 10.1002/(SICI)1098-2736(199901)36:1<39::AID-TEA4>3.0.CO;2-I |
26 | Halford G. S. (2014). Children's understanding: The development of mental models. Psychology Press. |
27 | Hart, S. G. , Staveland, L. E.. (1988). Development of NASA-TLX(Task Load Index): results of empirical and theoretical research. Advances in Psychology, 52 (6), 139- 183. |
28 |
Hynd C. R. (2001). Refutational texts and the change process. International Journal of Educational Research, 35 (7-8), 699- 714.
doi: 10.1016/S0883-0355(02)00010-1 |
29 | Kaiser, M. K., Proffitt, D. R., Whelan, S. M., &Hecht, H. (1992). Influnce of animation on dynamical judgments. Journalof Experimental Psychology:Human Perception and Performance. 18(3), 669- 689. |
30 |
Kendeou P., Walsh E. K., Smith E. R., et al. (2014). Knowledge revision processes in refutation texts. Discourse Processes, 51 (5-6), 374- 397.
doi: 10.1080/0163853X.2014.913961 |
31 | Larkin D. (2012). Using the conceptual change model of learning as an analytic tool in researching teacher preparation for student diversity. Teachers College Record, 114 (8), 1- 35. |
32 | Lewis, E. L. (1991). The process of scientific knowledge acquisition among middle school students learning thermdynamics. Berkeley: University of California. |
33 | Liu T. C. (2010). Developing Simulation-based Computer Assisted Learning to Correct Students' Statistical Misconceptions based on Cognitive Conflict Theory, using" Correlation" as an Example. Educational Technology & Society, 13 (2), 180- 192. |
34 | Michotte, A. (1963). The perception of causality. London: Methuen. |
35 |
Mitchell I., Baird J. (1986). Teaching, learning and the curriculum 1: The influence of content in science. Research in Science Education, 16 (1), 141- 149.
doi: 10.1007/BF02356828 |
36 | Novak J. D., Gowin D. B., &Bob G. D. (1984). Learning how to learn. Cambridge: Cambridge University Press. |
37 | Paas, F. (1993). Instructional control of cognitive load in the training of complex cognitive tasks. Hague: University of Twente. |
38 |
Potvin P., Sauriol É., &Riopel M. (2015). Experimental evidence of the superiority of the prevalence model of conceptual change over the classical models and repetition. Journal of Research in Science Teaching, 52 (8), 1082- 1108.
doi: 10.1002/tea.21235 |
39 | Prinz A., Golke S., &Wittwer J.,. (2018). Refutation texts compensate for detrimental effects of misconceptions on comprehension and metacomprehension accuracy and support transfer. Journal of Educational Psychology, 111 (6), 1- 87. |
40 |
Scaife, M., Rogers, Y. (1996). External cognition: How do graphical representations work?. International Journal of Human-Compter Studies, 45 (2), 185- 213.
doi: 10.1006/ijhc.1996.0048 |
41 |
Sellmann D., Liefländer A. K., &Bogner F. X. (2015). Concept maps in the classroom: A new approach to reveal students’ conceptual change. The Journal of Educational Research, 108 (3), 250- 257.
doi: 10.1080/00220671.2014.896315 |
42 | She H. C., Liao Y. W. (2010). Bridging scientific reasoning and conceptual change through adaptive web‐based learning. Journal of Research in Science Teaching, 47 (1), 91- 119. |
43 | Snir, J., Smith, C., &Grosslight, L. (1993). Conceptually ehanced simualtions: A computer tool for science teaching. Journal of Science and Technology, 2 (2), 373- 388. |
44 | Solomon S. H., Medaglia J. D., Thompson-Schill S. L.. (2019). Implementing a concept network model. Behavior research methods, 51 (4), 1717- 1736. |
45 | Ting C. Y., Sam Y. C., &Wong C. O. (2013). Model of conceptual change for INQPRO: A Bayesian Network approach. Computers & Education, 65, 77- 91. |
46 | Trundle K. C., Bell R. L. (2010). The use of a computer simulation to promote conceptual change: A quasi-experimental study. Computers & Education, 54 (4), 1078- 1088. |
47 |
Tsang, P. S., Velazquez, V. L. (1996). Diagnosticity and multidimensional subjective workload ratings. Ergonomics, 39 (3), 358- 381.
doi: 10.1080/00140139608964470 |
48 |
Tseng C. H., Tuan H. L., &Chin C. C. (2010). Investigating the influence of motivational factors on conceptual change in a digital learning context using the dual‐situated learning model. International Journal of Science Education, 32 (14), 1853- 1875.
doi: 10.1080/09500690903219156 |
49 |
Wandersee J. H. (1990). Concept mapping and the cartography of cognition. Journal of research in science teaching, 27 (10), 923- 936.
doi: 10.1002/tea.3660271002 |
50 |
Yin Y., Tomita M. K., &Shavelson R. J. (2014). Using formal embedded formative assessments aligned with a short-term learning progression to promote conceptual change and achievement in science. International Journal of Science Education, 36 (4), 531- 552.
doi: 10.1080/09500693.2013.787556 |
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