[目的/意义] 通过对iSchool联盟成员的可视化相关课程进行分析，归纳总结其课程设置情况及特点，为我国图情档学科人才培养的进一步提升提供启发和借鉴。[方法/过程] 通过网络收集45所iSchool联盟成员的98门课程信息；采用描述统计、内容分析、文本分析等方法对课程的基本情况、先导知识、课程内容、教学目标、教学方式和考核方式进行分析和归纳，总结课程设置特点。[结果/结论] iSchool可视化课程设置呈现出4个特点：层次化的课程体系和针对性的教学目标；学科交叉融合的课程内容；灵活多样的教学方法；全面合理的考核方式。据此，从教学目标和课程内容、实践教学、师资力量、先修课程体系、教材和案例库5个角度为后续课程建设提出建议。
[Purpose/significance] By analyzing the visualization related courses of the iSchool alliance members, this paper summarizes the situation and characteristics of course settings, to provide inspiration and references for the further improvement of the talent cultivation of LIS in China. [Method/process] This study collected information on 98 courses from 45 iSchool alliance members through the Internet. Through descriptive statistics, content analysis and text analysis, this study analyzed the basic situation, prerequisites, teaching contents, teaching objectives, teaching methods and assessment methods of courses, and summarized the characteristics of course settings. [Result/conclusion] This paper finds there are four characteristics of iSchool visualization course settings:hierarchical course system and targeted teaching objectives; interdisciplinary course contents; flexible teaching methods; comprehensive and reasonable assessment ways. Based on this, this paper puts forward suggestions for the follow-up course construction from five aspects of teaching objectives and course contents, practical teaching, teachers, prerequisite curriculum system, teaching materials and case base.
[1] 陈为.数据可视化[M].北京:电子工业出版社, 2013.
[2] 司莉,何依.iSchool院校的大数据相关课程设置及其特点分析[J].图书与情报,2015(6):84-91.
[3] 闫慧,张钰浩,张鑫灿,等. iSchools联盟数据科学教育项目现状调查[J]. 情报资料工作, 2018(4):95-100.
[4] 曾粤亮.国外iSchools数据科学项目人才培养模式的特点与启示[J].图书情报知识,2018(4):109-118.
[5] 杨瑞仙,万佳琦.UIUC iSchool数据科学课程群调查研究[J].图书情报工作,2020,64(16):122-131.
[6] WANG Y Y, LIN C S. A survey of data science programs and courses in the iSchools[J]. Proceedings of the Association for Information Science and Technology, 2019, 56(1):801-802.
[7] SONG I Y, ZHU Y. Big data and data science:opportunities and challenges of iSchools[J]. Journal of data and information science, 2017, 2(3):2017-2018.
[8] 陶俊,何晓东.面向图书情报的数据科学专业课程结构比较研究[J].图书馆学研究,2019(6):10-16.
[9] 苏日娜,杨沁.LIS学科中数据科学课程体系设置研究——以iSchools高校课程调研为中心[J].图书馆论坛,2019,39(4):40-49.
[10] 曹树金,王志红,刘慧云.论大数据时代下的图书情报学教育——基于iSchool院校"大数据"相关课程调查及思考[J].情报理论与实践,2017,40(12):17-22.
[11] 甘春梅,林晶晶,张悦韵.北美iSchool院校社交媒体类课程设置及其特点分析[J].山东图书馆学刊,2021(1):85-91,109.
[12] 司莉,姚瑞妃.图书情报专业研究生数据素养课程设置及特征分析——基于iSchool联盟院校的调查[J].图书与情报,2018(1):28-36,101.
[13] 姜婷婷,郭倩,徐亚苹,等.北美iSchools信息构建课程体系研究[J].图书情报知识,2017(5):89-96.
[14] LI S, ZHUANG X Z, XING W M, et al. The cultivation of scientific data specialists[J]. Library hi tech,2013,31(4):700-724.
[15] SHAO G, QUINTANA J, ZAKHAROV W, et al. Exploring potential roles of academic libraries in undergraduate data science education curriculum development[J]. The journal of academic librarianship,2021,47(2):102320.
[16] 望俊成,武山山,梁娜,等.基于"知识维-职场维-用户维"的课程需求调查研究——以《数据可视化》课程需求调查为例[J].情报学报,2016,35(8):793-799.
[17] 望俊成,李幸,郭传斌,等.中信所《数据可视化》课堂的设计:基于翻转课堂的理念[J].情报学报,2016,35(8):800-805.
[18] KERREN A. Information visualization courses for students with a computer science background[J]. IEEE computer graphics and applications,2013,33(2):12-15.
[19] 叶继元.iSchools与学科整合[J].图书情报工作,2007(4):6-9,51.
[20] 司莉,曾粤亮,陈传夫,等. 国外iSchools图书情报与档案管理研究生学位项目特征分析[J]. 图书情报知识, 2018, 185(5):22-34.
[21] 朝乐门,邢春晓,王雨晴.数据科学与大数据技术专业特色课程研究[J].计算机科学,2018,45(3):3-10.
