随着人们对娱乐、健康运动、休闲等方面的追求日益增长,对夜间活动高品质和丰富性的要求也相应提高,由此导致城市和乡村的夜间公共活动空间需求不断增多。而研究发现,目前作为夜间活动使用重要场所的夜间公共空间,其相关研究国内外关注...随着人们对娱乐、健康运动、休闲等方面的追求日益增长,对夜间活动高品质和丰富性的要求也相应提高,由此导致城市和乡村的夜间公共活动空间需求不断增多。而研究发现,目前作为夜间活动使用重要场所的夜间公共空间,其相关研究国内外关注均显不足,尤其是研究动态与综述方面。基于此,该文依托中国工程科技知识中心——战略咨询智能支持系统,以2000年至2023年为时间跨度,对CNKI和Web of Science数据库进行检索,形成可视化分析报告。依此对国内外现状趋势及热点进行比较研究,并对夜间公共空间研究方向、数据类型和方法等进行系统分析。最后得出夜间公共空间的发展趋势、研究方向及研究特点,总结当前研究之不足,并为未来夜间公共空间研究提供参考。展开更多
The study investigated user experience, display complexity, display type (tables versus graphs), and task difficulty as variables affecting the user’s ability to navigate through complex visual data. A total of 64 pa...The study investigated user experience, display complexity, display type (tables versus graphs), and task difficulty as variables affecting the user’s ability to navigate through complex visual data. A total of 64 participants, 39 undergraduate students (novice users) and 25 graduate students (intermediate-level users) participated in the study. The experimental design was 2 × 2 × 2 × 3 mixed design using two between-subject variables (display complexity, user experience) and two within-subject variables (display format, question difficulty). The results indicated that response time was superior for graphs (relative to tables), especially when the questions were difficult. The intermediate users seemed to adopt more extensive search strategies than novices, as revealed by an analysis of the number of changes they made to the display prior to answering questions. It was concluded that designers of data displays should consider the (a) type of display, (b) difficulty of the task, and (c) expertise level of the user to obtain optimal levels of performance.展开更多
文摘随着人们对娱乐、健康运动、休闲等方面的追求日益增长,对夜间活动高品质和丰富性的要求也相应提高,由此导致城市和乡村的夜间公共活动空间需求不断增多。而研究发现,目前作为夜间活动使用重要场所的夜间公共空间,其相关研究国内外关注均显不足,尤其是研究动态与综述方面。基于此,该文依托中国工程科技知识中心——战略咨询智能支持系统,以2000年至2023年为时间跨度,对CNKI和Web of Science数据库进行检索,形成可视化分析报告。依此对国内外现状趋势及热点进行比较研究,并对夜间公共空间研究方向、数据类型和方法等进行系统分析。最后得出夜间公共空间的发展趋势、研究方向及研究特点,总结当前研究之不足,并为未来夜间公共空间研究提供参考。
文摘The study investigated user experience, display complexity, display type (tables versus graphs), and task difficulty as variables affecting the user’s ability to navigate through complex visual data. A total of 64 participants, 39 undergraduate students (novice users) and 25 graduate students (intermediate-level users) participated in the study. The experimental design was 2 × 2 × 2 × 3 mixed design using two between-subject variables (display complexity, user experience) and two within-subject variables (display format, question difficulty). The results indicated that response time was superior for graphs (relative to tables), especially when the questions were difficult. The intermediate users seemed to adopt more extensive search strategies than novices, as revealed by an analysis of the number of changes they made to the display prior to answering questions. It was concluded that designers of data displays should consider the (a) type of display, (b) difficulty of the task, and (c) expertise level of the user to obtain optimal levels of performance.
