Akademik Veri Yönetim Sistemi
Visualizations and Dashboards for Learning Analytics, Sahin M.,Ifenthaler DSahin M.,Ifenthaler D., Editör, Springer Nature, Berlin, 2021
Learning analytics aim to understand and optimize learning and learning environments by using learner, instructor, and system interaction data. Likewise, a subfield of learning analytics, assessment analytics aim to monitor the learners and learning process, tracking, and recording assessment data, provide feedback, predict the future state of learners, and especially make progress in learning outcomes using especially assessment data. Assessment analytics dashboards enable the visualization of the data obtained from the assessment results and interactions with an assessment task. Thus, it provides learners and instructors to monitor and reflect on their online teaching and learning patterns. The prime purpose of this chapter linking e-assessment results with assessment analytics dashboards. For this purpose, an evidence-centered assessment analytics process model has been proposed and explained in detail. In this chapter, assessment analytics framework, basic e-assessment approaches, measurement theories, sequential pattern analysis, classification algorithms, and the creation of the caution index are presented, respectively. After this, the goals of e-assessment analytics and data visualization options such as graphs and charts that matching those goals are discussed. Consequently, this chapter is expected to guide users in establishing e-assessment analytics process and visualization of the analytics’ results.