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Supporting post-secondary educational data usage in the assessment process with information visualization

机译:通过信息可视化支持评估过程中的中学后教育数据使用

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摘要

Programs, institutions, and governments are increasingly looking at data about student learning for both accountability and program improvement activities. Faculties at post-secondary institutions have employed systems to gather vast amounts of assessment data in recent years with the ultimate goal of using the data to improve the student learning experience. Unfortunately, faculty members responsible for this data are unfamiliar with analyzing data sets of this magnitude or complexity and therefore cannot extract actionable insight from the data to inform their program improvement decisions. Approaches to support this process are still developing, referred to largely as Educational Data Mining. Information Visualization is one technique that has shown promise in facilitating the extraction of meaningful information, though there has been little research conducted into where and how visualizations are utilised at a post-secondary level. The ultimate goal of this research is to build a support that encourages the usage of educational data through visualizations. To build one that is effective, a research study was conducted to discover the factors surrounding how educational data was used in this setting.;The research was a three-phase qualitative study aimed at determining the attitudes around data usage as well as what aspects of assessment data usage are currently challenging education staff and faculty members in achieving their program improvement goals. The study included interviews, a focus group, and an open-response survey created using an emergent design methodology. Participants were from institutions in Canada, focused largely at Queen's University. The outcome of the research findings was a model of four major stakeholders in the process of educational data usage and some of the important factors that surround the usage and the interaction between stakeholders. The resulting support tool built from this research aims to support those interactions and specifically identified challenges by bringing the principles from the broader field of information visualization into an accessible form for staff and faculty at post-secondary institutions trying to work with educational data.
机译:计划,机构和政府越来越多地将有关学生学习的数据用于问责制和计划改进活动。大专院校的教职员工近年来已经使用系统来收集大量评估数据,其最终目标是利用这些数据来改善学生的学习体验。不幸的是,负责此数据的教职人员不熟悉分析如此庞大或复杂的数据集,因此无法从数据中提取可行的见解来告知他们的程序改进决策。支持此过程的方法仍在开发中,主要被称为“教育数据挖掘”。信息可视化是一种在促进有意义的信息提取方面已显示出希望的技术,尽管很少有研究针对在高等教育之后的地方以及如何利用可视化进行研究。这项研究的最终目标是建立一种支持,以鼓励通过可视化使用教育数据。为了建立一种有效的方法,进行了一项研究研究,以发现在这种情况下如何使用教育数据的因素。该研究是一个三阶段定性研究,旨在确定对数据使用的态度以及对数据使用的哪些方面当前,评估数据的使用正在挑战教育人员和教职员工实现其计划改进目标。该研究包括访谈,焦点小组和使用新兴设计方法创建的开放式调查。参与者来自加拿大的机构,主要集中在皇后大学。研究结果的结果是教育数据使用过程中四个主要利益相关者的模型,以及围绕这些用法和利益相关者之间相互作用的一些重要因素。这项研究构建的最终支持工具旨在通过将信息可视化的广泛领域的原理引入到尝试使用教育数据的高等院校的教职员工可访问的形式中,以支持这些互动并明确识别挑战。

著录项

  • 作者

    Sivanand, Ajay.;

  • 作者单位

    Queen's University (Canada).;

  • 授予单位 Queen's University (Canada).;
  • 学科 Computer engineering.;Information technology.;Educational technology.
  • 学位 M.A.Sc.
  • 年度 2017
  • 页码 149 p.
  • 总页数 149
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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