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Role of Learning Analytics to Evaluate Formative Assessments: Using a Data Driven Approach to Inform Changes in Teaching Practices


Affiliations
1 Department of CSE - KG Reddy College of Engineering & Technology, Center for Engineering Education Research, KLE Technological University, India
2 Department of ECE - KG Reddy College of Engineering & Technology, Center for Engineering Education Research, KLE Technological University, India
 

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One of the most challenging tasks for faculty in their role as a teacher is to design, administrate, and evaluate formative assessments. This results in a lot of faculty not utilizing the formative assessments as a form of student feedback and make regular changes to the course. In this study, we explore the role of technology in helping faculty implement and analyze formative assessments. We believe the advancement of technology and its increasing applications in education may result in development of novel solutions to this impediment through learning analytics. This paper explores the use of such data analytics to address the challenges impeding the capacity of instructors to provide personalized feedback at scale.

The study was implementing in the Computer Science and Engineering Department where a group of faculties who teach undergraduate engineering students. The faculty designed and administered a set of formative assessments in multiple courses through the learning management system. The data collected from the formative assessments was analyzed using learning analytics and the results were used to provide actionable recommendations that could better support students to achieve the learning outcomes of the course. The data was analyzed to understand and optimize the learning process of the students in the course. The results of the paper will provide insights to engineering educators on how they could take a data driven approach and harness the power of technology to better support their students. This approach will also help direct students towards deeper and self-regulated learning.


Keywords

Learning Analytics, Formative Assessments, Canvas, Data Driven Approach.
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Abstract Views: 328

PDF Views: 205




  • Role of Learning Analytics to Evaluate Formative Assessments: Using a Data Driven Approach to Inform Changes in Teaching Practices

Abstract Views: 328  |  PDF Views: 205

Authors

Rayapudi Hima Sagarika
Department of CSE - KG Reddy College of Engineering & Technology, Center for Engineering Education Research, KLE Technological University, India
Rohit Kandakatla
Department of ECE - KG Reddy College of Engineering & Technology, Center for Engineering Education Research, KLE Technological University, India
Ashwini Gulhane
Department of CSE - KG Reddy College of Engineering & Technology, Center for Engineering Education Research, KLE Technological University, India

Abstract


One of the most challenging tasks for faculty in their role as a teacher is to design, administrate, and evaluate formative assessments. This results in a lot of faculty not utilizing the formative assessments as a form of student feedback and make regular changes to the course. In this study, we explore the role of technology in helping faculty implement and analyze formative assessments. We believe the advancement of technology and its increasing applications in education may result in development of novel solutions to this impediment through learning analytics. This paper explores the use of such data analytics to address the challenges impeding the capacity of instructors to provide personalized feedback at scale.

The study was implementing in the Computer Science and Engineering Department where a group of faculties who teach undergraduate engineering students. The faculty designed and administered a set of formative assessments in multiple courses through the learning management system. The data collected from the formative assessments was analyzed using learning analytics and the results were used to provide actionable recommendations that could better support students to achieve the learning outcomes of the course. The data was analyzed to understand and optimize the learning process of the students in the course. The results of the paper will provide insights to engineering educators on how they could take a data driven approach and harness the power of technology to better support their students. This approach will also help direct students towards deeper and self-regulated learning.


Keywords


Learning Analytics, Formative Assessments, Canvas, Data Driven Approach.



DOI: https://doi.org/10.16920/jeet%2F2021%2Fv34i0%2F157212