Journal of East China Normal University(Educational Sciences) >
How to Build Future School: Prospective Analysis and Practical Enlightenment of Application Scenarios of AI in Education
Accepted date: 2022-05-30
Online published: 2022-08-24
From the perspective of time change, the development of learning technology has an impact on the state, operation mechanism and cultural atmosphere of schools in different social and historical periods. Therefore, in the case of artificial intelligence as the main driving force of future social development, what kind of future schools will appear and how we should effectively build future schools are important topics of current education field. In order to respond to this problem, using the basic ideas of future research method, the application scenarios of future school education governance driven by artificial intelligence are prospectively analyzed. This paper analyzes the characteristics of core elements, including structure and context of future school driven by artificial intelligence. On this basis, the construction path of future schools is proposed. First, under the innovative idea of learning-drive logic, we should pay attention to the practical problems in different educational scenes. Second, based on the design-based research methods, continuous improvement method is used to promote the integration artificial intelligence in education. Third, under the interdisciplinary and institutional cooperation, sustainable development mechanisms should be explored to help the construction of future schools.
Huiying Cai , Haixia Dong , Xu Chen , Xiaoqing Gu . How to Build Future School: Prospective Analysis and Practical Enlightenment of Application Scenarios of AI in Education[J]. Journal of East China Normal University(Educational Sciences), 2022 , 40(9) : 45 -54 . DOI: 10.16382/j.cnki.1000-5560.2022.09.005
1 | 奥恩. (2018). 教育的未来: 人工智能时代的教育变革(李海燕等译). 北京: 机械工业出版社. |
2 | 蔡慧英, 卢琳萌, 董海霞. (2021). 基于证据启发的学习设计: 让教师教学站在理解教育规律的基础上. 现代远程教育研究, 33 (4), 11- 19. |
3 | 德勤. (2019). “互联网+”启发物流模式创新. 中国投资(中英文), 17, 76- 77. |
4 | 顾小清, 蔡慧英. (2021). 预见人工智能的未来及其教育影响——以社会性科幻为载体的思想实验. 教育研究, (5), 137- 147. |
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, (1), 4- 12. |
6 | 郭重庆. (2015). 互联网+: “破坏性”创新带来的变革. 文汇报, 2015?06?12(06). |
7 | 郝祥军, 顾小清. (2021). 高等教育如何转向未来技能培养——来自德国“未来技能”项目报告的启示. 现代远距离教育, (5), 33- 42. |
8 | 米尔斯. (2017). 社会学的想象力(李康译). 北京: 北京师范大学出版社. |
9 | 苏竣. (2021). 开展人工智能社会实验 探索智能社会治理中国道路. 中国行政管理, (12), 21- 22. |
10 | 任翠英. (2018). 中小学生校外教育研究. 上海: 华东师范大学博士学位论文. |
11 | 王永固, 许家奇, 丁继红. (2020). 教育4.0全球框架: 未来学校教育与模式转变——世界经济论坛《未来学校: 为第四次工业革命定义新的教育模式》之报告解读. 远程教育杂志, (03), 3- 14. |
12 | 张治, 李永智. (2017). 迈进学校3.0时代——未来学校进化的趋势及动力探析. 开放教育研究, 23 (04), 40- 49. |
13 | 朱永新, 杨帆. (2020). 重新定义教育: 未来学习中心的形态构建与实践畅想——朱永新教授专访. 苏州大学学报(教育科学版), (04), 83- 91. |
14 | Ala-Mutka, K., Redecker, C., Punie, Y., Ferrari, A., Cachia, R., & Centeno, C. (2010, February). The future of learning: European teachers’ visions. In Report on a foresight consultation at the 2010 eTwinning Conference, Seville. |
15 | Bell, W. (1997). The purposes of futures studies. The Futurist, 31 (6), 42- 45. |
16 | Bhimdiwala, A., Neri, R. C., & Gomez, L. M. (2021). Advancing the design and implementation of artificial intelligence in education through continuous improvement. International Journal of Artificial Intelligence in Education, 1- 27. |
17 | Bonfield, C. A., Salter, M., Longmuir, A., Benson, M., & Adachi, C. (2020). Transformation or evolution?: Education 4.0, teaching and learning in the digital age. Higher Education Pedagogies, 5(1), 223?246. |
18 | Bryk, A. S., Gomez, L. M., Grunow, A., & LeMahieu, P. G. (2015). Learning to improve: How America’s schools can get better at getting better. London: Harvard Education Press. |
19 | Burri, R. V. (2018). Envisioning futures: Imagining technoscientific worlds in film. European Journal of Futures Research, 6 (17), 1- 14. |
20 | Chassignol, M., Khoroshavin, A., Klimova, A., & Bilyatdinova, A. (2018). Artificial Intelligence trends in education: A narrative overview. Procedia Computer Science, 136, 16- 24. |
21 | Gardner, J. , Brooks, C. , & Baker, R. (2019). Evaluating the Fairness of Predictive Student Models Through Slicing Analysis. In The 9th International Conference on Learning Analytics & Knowledge, pp. 225–234. |
22 | HolonIQ. (2018). Education in 2030: Five scenarios for the future of learning and talent. Retrieved from https://www.holoniq.com/2030/ |
23 | Ilom?ki, L., & Lakkala, M. (2018). Digital technology and practices for school improvement: innovative digital school model. Research and Practice in Technology Enhanced Learning, 13 (1), 1- 32. |
24 | Inayatullah, S. (1990). Deconstructing and reconstructing the future: Predictive, cultural and critical epistemologies. Futures, 22 (2), 115- 141. |
25 | Inayatullah, S. (2017). Gaming, Ways of Knowing, and Futures. Journal of Futures Studies, 22 (2), 101- 106. |
26 | Institute for the Future. (2018). AI Forces Shaping Work & Learning. California: Institute for the Future contributors. |
27 | Leahy, S. M., Holland, C., & Ward, F. (2019). The digital frontier: Envisioning future technologies impact on the classroom. Futures, 113, 1- 10. |
28 | Martinez-Maldonado, R., Elliott, D., Axisa, C., Power, T., Echeverria, V., & Buckingham Shum, S. (2020). Designing translucent learning analytics with teachers: An elicitation process. Interactive Learning Environments, 30 (6), 1- 15. |
29 | McDowall, A., Mills, C., Cawte, K., & Miller, J. (2021). Data use as the heart of data literacy: An exploration of pre-service teachers’ data literacy practices in a teaching performance assessment. Asia-Pacific Journal of Teacher Education, 49 (5), 487- 502. |
30 | Munigala, V., Oinonen, P., & Ekman, K. (2018). Envisioning future innovative experimental ecosystems through the foresight approach. Case: Design Factory. European Journal of Futures Research, 6 (1), 1- 16. |
31 | Paul, D., & Genevieve, B. (2011). Divining a digital future. Mess and mythology in ubiquitous computing. Cambridge: The MIT Press. |
32 | Popenici, S. A., & Kerr, S. (2017). Exploring the impact of artificial intelligence on teaching and learning in higher education. Research and Practice in Technology Enhanced Learning, 12 (1), 1- 13. |
33 | Ranson, S., Farrell, C., Peim, N., & Smith, P. (2005). Does governance matter for school improvement?. School Effectiveness and School Improvement, 16 (3), 305- 325. |
34 | Renz, A., & Hilbig, R. (2020). Prerequisites for artificial intelligence in further education: Identification of drivers, barriers, and business models of educational technology companies. International Journal of Educational Technology in Higher Education, 17 (1), 1- 21. |
35 | Roll, I., & Wylie, R. (2016). Evolution and Revolution in Artificial Intelligence in Education. International Journal of Artificial Intelligence in Education, 26 (2), 582- 599. |
36 | Seldon, A., & Abidoye, O. (2018). The fourth education revolution: Will artificial intelligence liberate or infantilise humanity. Buckingham: University of Buckingham Press. |
37 | Selwyn, N., et al.. (2020). What might the school of 2030 be like? An exercise in social science fiction. Learning, Media and Technology, 45 (1), 90- 106. |
38 | Vincent-Lancrin, S. and van der Vlies, R. (2020). Trustworthy artificial intelligence (AI) in education: Promises and challenges . OECD Education Working Papers, 218. |
39 | Williamson, B., & Eynon, R.. (2020). Historical threads, missing links, and future directions in AI in education. Learning, Media and Technology, 45 (3), 223- 235. |
40 | Yan, Y., Yang, L. (2019). Exploring contradictions in an EFL teacher professional learning community. Journal of Teacher Education, 70 (5), 498- 511. |
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