基于大数据的自学考试现状、困境与破解途径
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摘要
高等教育自学考试是一种个人自学、社会助学和国家考试相结合的高等开放教育形式。自1981年创立以来,自学考试不仅为实现教育公平、提高国民素质做出了重要的历史贡献,而且也积累了丰富的考试数据资产,如何从数据挖掘的视角来分析自学考试面临的问题并促使其改革转型,是大数据时代自学考试研究的重要命题。通过对2003-2017年全国自学考试积累的海量考试大数据进行分析发现,当前我国自学考试正面临报考规模大幅下滑、地域发展不够平衡、专业设置脱离社会需求、课程设置不够科学、助学手段相对单一、考试与毕业难度大等诸多困境。为了更好地实现自学考试的改革转型,自学考试的决策者应鼓励和引导优质民办高校力量参与办学,推进自学考试课程与优质慕课的相互融合,加强自学考试大数据的建设和应用。这些基于大数据支持的实践措施,有助于转变自学考试的培养目标,补强自学考试的教育功能,满足社会发展对高素质劳动者的需求,同时也有助于自学考试与普通高校及其他高等教育形式形成错位竞争、优势互补的教育生态环境。
Since founded in 1981,the self-taught examination of higher education is a kind of higher open education form,which combines individual self-study,social assistance and national examinations.The self-taught examination not only made a significant contribution to realizing the education fair,improving national quality,but also accumulated rich exam data assets.How to analyze the problems which the self-taught exam faces in order to improve its reform and transformation from the perspective of data mining is one of the important issues of self-taught examination study in the big data era.By the analysis of the massive examination big data from 2003 to 2017,it is found that selftaught examination is facing many difficulties at present,such as the large decline in the scale of examination,unbalanced regional development,the disconnect of specialty setting from social demand,unscientific curriculum setting,relatively single means of study aid,and great difficulty in graduation.In order to better realize the reform and transformation of selftaught examination,decision-makers should encourage and guide high-quality private colleges to participate in selftaught examination,promote the mutual integration of self-taught examination courses and high-quality MOOCs,and strengthen the construction and application of self-taught examination big data.These measures based on the big data,help to shift the educational target of self-taught examination,reinforce the education function of self-taught examination,meet the needs of social development of high-quality workforce,as well as help self-taught examination,and ordinary universities and other institutions of higher education to form an educational environment with dislocation competition,and complementary advantages.
Since founded in 1981,the self-taught examination of higher education is a kind of higher open education form,which combines individual self-study,social assistance and national examinations.The self-taught examination not only made a significant contribution to realizing the education fair,improving national quality,but also accumulated rich exam data assets.How to analyze the problems which the self-taught exam faces in order to improve its reform and transformation from the perspective of data mining is one of the important issues of self-taught examination study in the big data era.By the analysis of the massive examination big data from 2003 to 2017,it is found that selftaught examination is facing many difficulties at present,such as the large decline in the scale of examination,unbalanced regional development,the disconnect of specialty setting from social demand,unscientific curriculum setting,relatively single means of study aid,and great difficulty in graduation.In order to better realize the reform and transformation of selftaught examination,decision-makers should encourage and guide high-quality private colleges to participate in selftaught examination,promote the mutual integration of self-taught examination courses and high-quality MOOCs,and strengthen the construction and application of self-taught examination big data.These measures based on the big data,help to shift the educational target of self-taught examination,reinforce the education function of self-taught examination,meet the needs of social development of high-quality workforce,as well as help self-taught examination,and ordinary universities and other institutions of higher education to form an educational environment with dislocation competition,and complementary advantages.
引文
[1]艾瑞深研究院,中国校友会网(2017).2017中国大学评价研究报告[EB/OL].[2018-11-03].http://www.cuaa.net/cur/2017/2017dxpm.shtml.
[2]江波,王奕俊(2014).“慕课”透视及应对[J].中国高等教育,(7):18-22.
[3]教育部在线教育研究中心(2016).2016中国慕课行业白皮书[EB/OL].[2018-10-11].http://www.datayuan.cn/article/7868.htm.
[4]习近平(2017).决胜全面建成小康社会,夺取新时代中国特色社会主义伟大胜利--在中国共产党第十九次全国代表大会上的报告[Z].北京:人民出版社:30.
[5]中华人民共和国教育部(2015).《国家中长期教育改革和发展规划纲要》中期评估--学前教育专题评估报告[EB/OL].[2018-11-24].http://www.moe.gov.cn/jyb_xwfb/xw_fbh/moe_2069/xwfbh_2015n/xwfb_151130/151130_sfcl/201511/t20151130_221728.html.
[6]中华人民共和国教育部(2017).教育部等四部门关于实施第三期学前教育行动计划的意见[EB/OL].[2018-04-17].http://www.moe.edu.cn/srcsite/A06/s3327/201705/t20170502_303514.html.
(1)总规模:包括学历教育部分和非学历教育部分。
(2)科次通过率:当年自考考试通过的科次数占当年考试总科次数的百分比。
(3)毕业率:当年自考毕业生人数占当年注册在案自考考生总数的百分比。
[2]江波,王奕俊(2014).“慕课”透视及应对[J].中国高等教育,(7):18-22.
[3]教育部在线教育研究中心(2016).2016中国慕课行业白皮书[EB/OL].[2018-10-11].http://www.datayuan.cn/article/7868.htm.
[4]习近平(2017).决胜全面建成小康社会,夺取新时代中国特色社会主义伟大胜利--在中国共产党第十九次全国代表大会上的报告[Z].北京:人民出版社:30.
[5]中华人民共和国教育部(2015).《国家中长期教育改革和发展规划纲要》中期评估--学前教育专题评估报告[EB/OL].[2018-11-24].http://www.moe.gov.cn/jyb_xwfb/xw_fbh/moe_2069/xwfbh_2015n/xwfb_151130/151130_sfcl/201511/t20151130_221728.html.
[6]中华人民共和国教育部(2017).教育部等四部门关于实施第三期学前教育行动计划的意见[EB/OL].[2018-04-17].http://www.moe.edu.cn/srcsite/A06/s3327/201705/t20170502_303514.html.
(1)总规模:包括学历教育部分和非学历教育部分。
(2)科次通过率:当年自考考试通过的科次数占当年考试总科次数的百分比。
(3)毕业率:当年自考毕业生人数占当年注册在案自考考生总数的百分比。