Connecting Teacher-Made Assessments to Course Learning Outcomes Through Learning Analytics: An Empirical Model

Connecting Teacher-Made Assessments to Course Learning Outcomes Through Learning Analytics: An Empirical Model

Julia Chen (The Hong Kong Polytechnic University, Hong Kong) and Dennis Foung (The Hong Kong Polytechnic University, Hong Kong)
DOI: 10.4018/978-1-5225-6986-2.ch006

Abstract

This chapter explores the possibility of adopting a data-driven approach to connecting teacher-made assessments with course learning outcomes. The authors begin by describing several key concepts, such as outcome-based education, curriculum alignment, and teacher-made assessments. Then, the context of the research site and the subject in question are described and the use of structural equation modeling (SEM) in this curriculum alignment study is explained. After that, the results of these SEM analyses are presented, and the various models derived from the analyses are discussed. In particular, the authors highlight how a data-driven curriculum model can benefit from input by curriculum leaders and how SEM provides insights into course development and enhancement. The chapter concludes with recommendations for curriculum leaders and front-line teachers to improve the quality of teacher-made assessments.
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Introduction

This chapter presents an innovative model that uses learning analytics (LA) to investigate the extent to which teacher-made course-embedded assessments of a blended learning course are connected to the course’s intended learning outcomes. The models, which were developed with Structural Equation Modeling (SEM), serve as an empirical approach to examine the alignment of assessments with learning outcomes. This simple empirical approach has practical implications for teachers, course leaders, and program coordinators. Using the developed models, teachers can evaluate the effectiveness of their assessment instruments with an evidence-based approach.

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