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作 者:王健崭[1] Wang Jianzhan
机构地区:[1]中国药科大学马克思主义学院,南京210009
出 处:《江苏高教》2023年第9期114-120,共7页Jiangsu Higher Education
基 金:2022年度江苏高校哲学社会科学研究思想政治工作专题项目“医药院校家国情怀教育融入思政课教学研究”(2022SJSZ0031);2022年度教育部产学合作协同育人项目(220903230040427);2020年度江苏省高等教育学会高校外语教育“课程思政与混合式教学”专项课题“基于文化自信的大学英语课程思政建设”(2020WYKT097)。
摘 要:人工智能的飞速发展为高校思政课教学的加速跃升带来了前所未有的机遇。伴随着思政课教学全过程、全场景的数据采集和智能分析,人工智能从智能化教学场景打造、个性化学习资源供给、智慧化学生测评体系建设三个维度充分发挥其优势,促进思政课教学模式创新发展。但是,应系统审视人工智能赋能思政课教学在"场景-资源-测评"三方面存在的技术风险,比如:智能化教学场景的滥用,对大学生数据隐私权的侵犯以及算法黑箱背后的数据依赖。面对这些问题,要加快人工智能在思政课教学中的深度转化,实现智能化教学场景的合理运用、大学生学习数据的合理使用以及透明算法下价值对技术的主导,从而促进人工智能与思政课教学的深度融合,构建人机协同的思政课教学新生态。The rapid development of artificial intelligence has brought unprecedented opportunities for the acceleration of ideological and political teaching.Along with the data collection and intelligent analysis of the whole process and scene of ideological and political course teaching,artificial intelligence gives full play to its advantages from the three dimensions of intelligent teaching scene building,personalized learning resources supply and intelligent student evaluation construction,and promotes the innovative development of ideological and political course teaching mode.However,we should also systematically examine the technical risks in the three aspects of"scene-resource-evaluation"in the teaching of ideological and political courses with AI empowerment.For example:the abuse of intelligent teaching scene,the violation of college students'data privacy and the data dependence behind the algorithm black box.In the face of these problems,we should speed up the deep transformation of artificial intelligence in ideological and political course teaching,realize the reasonable application of intelligent teaching scene,the rational use of college students'learning data and the dominance of value over technology under transparent algorithm,so as to promote the deep integration of artificial intelligence and ideological and political course teaching,and build a new ecology of man-machine collaboration in ideological and political course teaching.
分 类 号:G641[文化科学—高等教育学]
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