人工智能背景下法学高等教育的改革

doi:10.13766/j.bhsk.1008-2204.2019.0224

北京航空航天大学学报社科版 ›› 2020, Vol. 33 ›› Issue (5): 153-160.DOI: 10.13766/j.bhsk.1008-2204.2019.0224

人工智能背景下法学高等教育的改革

赵艳红

安徽财经大学管理科学与工程学院, 安徽蚌埠 233000

收稿日期:2019-07-10 发布日期:2020-10-10
作者简介:赵艳红(1980-),女,山东济南人,讲师,硕士,研究方向为大数据、人工智能与法律.
基金资助:
安徽省哲学社会科学规划项目（AHSKQ2018D04）；安徽财经大学校级教研项目（acjyyb2018131）

Reform of Higher Education of Law in the Era of Artificial Intelligence

ZHAO Yanhong

School of Management Science and Engineering, Anhui University of Finance and Economics, Bengbu Anhui 233000, China

Received:2019-07-10 Published:2020-10-10

摘要/Abstract

摘要： 人工智能的发展给法律领域带来诸多冲击。为应对人工智能技术对法律领域的挑战，中国的法学高等教育应当因时而宜进行一定的改革，培养学生的法律适用能力、大数据思维能力、计算思维能力以应对人工智能时代对法律人才所提出的新要求。但从目前的实践状况来看，中国的法学高等教育在培养目标、课程体系、实践条件等方面均难以满足人工智能时代法律人才的培养需求。因此，应从师资和课程两方面促进学生法律适用能力的培养，从理论和实践两方面打造人工智能法律课程体系，同时借助人工智能法律系统改革传统的教学方式。

关键词: 人工智能, 法律变革, 法学教育, 法律适用能力, 大数据思维能力, 计算思维能力

Abstract: The development of artificial intelligence has brought challenges to the field of law. Higher education of law in China should cultivate students' legal practice ability, big data thinking ability and computational thinking ability to cope with the new requirements for legal talents brought by artificial intelligence. However, from the current practice, the legal education in China is difficult to meet the training needs of legal talents in the era of artificial intelligence in terms of training objectives, curriculum system and practical conditions. So it is suggested that, firstly, we should promote the cultivation of students' ability to apply law from the aspects of teachers and courses; secondly, the course system of artificial intelligence law should be create from both theoretical and practical aspects; finally, the traditional teaching method should be reformed with the aid of artificial intelligence legal system.

Key words: artificial intelligence, legal reform, law education, legal practice ability, big data thinking ability, computational thinking ability

中图分类号:

赵艳红. 人工智能背景下法学高等教育的改革[J]. 北京航空航天大学学报社科版, 2020, 33(5): 153-160.

ZHAO Yanhong. Reform of Higher Education of Law in the Era of Artificial Intelligence[J]. Journal of Beijing University of Aeronautics and Astronautics Social Sciences Edition, 2020, 33(5): 153-160.

参考文献

[1] 中国教育部.教育部关于加快建设高水平本科教育全面提高人才培养能力的意见[EB/OL].(2018-10-08)[2018-12-30].http://www.moe.gov.cn/srcsite/A08/s7056/201810/t20181017_351887.html.
[2] HAN J W, KAMBER M, PEI J. 数据挖掘概念与技术(原书第3版)[M]. 范明,孟小峰,译.北京:机械工业出版社, 2007:41-49.
[3] PATCHA A, PARK J M. An overview of anomaly detection techniques:Existing solutions and latest technological trends[J]. Computer Networks, 2007, 51(12):3448-3470.
[4] ROMERO C, VENTURA S. Data mining in education[J]. Wiley Interdisciplinary Reviews:Data Mining and Knowledge Discovery, 2013, 3(1):12-27.
[5] 中国政府网.全国高校思想政治工作会议12月7日至8日在北京召开[EB/OL]. (2016-12-08)[2018-12-30]. http://www.gov.cn/xinwen/2016-12-08/content_5145253.htm#allContent.
[6] SLAVIN R E. Synthesis of research on cooperative learning[J]. Educational Leadership, 1981, 38(5):655-660.
[7] WANG W Q, MA Y H. Online social network user behavior analysis-With RenRen Case[M]//ZU Q, HU B. Human centered computing. Berlin:Springer International Publishing, 2016:925-929.
[8] WOOK Y, YAHAYA Y H, WAHAB N, et al. Predicting NDUM student's academic performance using data mining techniques[C]//Second International Conference on Computer & Electrical Engineering. Piscataway:IEEE Press, 2009:357-361.
[9] 徐鹏,王以宁,刘艳华,等.大数据视角分析学习变革——美国《通过教育数据挖掘和学习分析促进教与学》报告解读及启示[J].远程教育杂志,2013,31(6):11-17.
[10] ROMERO C, ESPEJO P G, ZAFRA A, et al. Web usage mining for predicting final marks of students that use Moodle courses[J]. Computer Applications in Engineering Education, 2013, 21(1):135-146.
[11] LUAN J. Data mining and its applications in higher education[J]. New Directions for Institutional Research, 2002(113):17-36.
[12] PARACK S, ZAHID Z, MERCHANT F. Application of data mining in educational databases for predicting academic trends and patterns[C]//IEEE International Conference on Technology Enhanced Education. Piscataway:IEEE Press, 2012:1-4.
[13] 陈益均,殷莉.基于数据挖掘的学生成绩影响模型的研究[J].现代教育技术,2013,23(1):94-96.
[14] 王林丽,叶洋,杨现民.基于大数据的在线学习预警模型设计——"教育大数据研究与实践专栏"之学习预警篇[J].现代教育技术,2016,26(7):5-11.
[15] 吴青,罗儒国.基于网络学习行为的学习风格挖掘[J].现代远距离教育,2014(1):54-62.

人工智能背景下法学高等教育的改革

Reform of Higher Education of Law in the Era of Artificial Intelligence

RichHTML

PDF

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 6

编辑推荐

Metrics

本文评价

[1]	于文轩. 人工智能与公共管理:机遇与挑战[J]. 北京航空航天大学学报社科版, 2020, 33(4): 50-54.
[2]	陈洪连, 吕玉雪. 智能监察:价值、逻辑与反思[J]. 北京航空航天大学学报社科版, 2020, 33(4): 86-96.
[3]	丁晓东. 大数据与人工智能时代的个人信息立法——论新科技对信息隐私的挑战[J]. 北京航空航天大学学报社科版, 2020, 33(3): 8-16,71.
[4]	李海英, 徐小露. 人工智能时代中国个人信息保护法的选择[J]. 北京航空航天大学学报社科版, 2020, 33(3): 17-24.
[5]	孙治博, 史成坤, 耿向伟, 李梓源, 付博. “人工智能+工程实践”的综合创新训练教学研究[J]. 北京航空航天大学学报（社会科学版）, 2019, 32(6): 148-151.
[6]	岳悍惟. 论判决书研习式教学[J]. 北京航空航天大学学报（社会科学版）, 2018, 31(6): 116-120.