In the context of higher education, Institutional Research (IR) has increasingly emphasized the use of data-driven tools such as student surveys to enhance educational practices and university operations. This study addresses challenges in managing and improving student surveys through advanced visualization techniques. We propose a third visualization method—a stacked bar graph—alongside two existing methods, the heatmap and bar graph with line overlay. This third method visually represents the progression of respondent dropout across questions, offering a detailed view of response continuity. The three visualization methods were used to compare pre- and post-improvement survey data, highlighting key factors such as question design and response behavior. The results indicate that reducing the number of questions and providing clear instructions significantly improve response rates, especially in the later sections of the surveys. The third visualization method effectively highlights these improvements by enabling precise monitoring of dropout trends and response continuity. This study situates its contributions within the interdisciplinary framework of Eduinformatics, integrating education and informatics to optimize educational processes. The proposed visualization methods offer practical tools for evaluating the quality of student surveys and ensuring the validity of collected data. While primarily aimed at student surveys, these methods have broader applicability to other survey-based research contexts.

错误:搜索内容不能为空,请输入英文关键词
错误:关键词超出字数限制,请精简
高级检索

Expanding Technology-Enhanced Quality Improvement in Surveys (TEQUIS): New Visualization Techniques for Monitoring and Enhancing Web Survey Responses

  • Sayaka Matsumoto,
  • Kunihiko Takamatsu,
  • Shotaro Imai,
  • Tsunenori Inakura,
  • Masao Mori

摘要

In the context of higher education, Institutional Research (IR) has increasingly emphasized the use of data-driven tools such as student surveys to enhance educational practices and university operations. This study addresses challenges in managing and improving student surveys through advanced visualization techniques. We propose a third visualization method—a stacked bar graph—alongside two existing methods, the heatmap and bar graph with line overlay. This third method visually represents the progression of respondent dropout across questions, offering a detailed view of response continuity. The three visualization methods were used to compare pre- and post-improvement survey data, highlighting key factors such as question design and response behavior. The results indicate that reducing the number of questions and providing clear instructions significantly improve response rates, especially in the later sections of the surveys. The third visualization method effectively highlights these improvements by enabling precise monitoring of dropout trends and response continuity. This study situates its contributions within the interdisciplinary framework of Eduinformatics, integrating education and informatics to optimize educational processes. The proposed visualization methods offer practical tools for evaluating the quality of student surveys and ensuring the validity of collected data. While primarily aimed at student surveys, these methods have broader applicability to other survey-based research contexts.