This course provides a deep dive into the essential tools, techniques, and methodologies used in analyzing data within Learning Management Systems (LMS). It is designed to empower educators, instructional designers, and administrators to use LMS data to make informed decisions that enhance student engagement, improve learning outcomes, and optimize course delivery.
Through hands-on activities, students will learn how to collect, process, analyze, and interpret LMS data. The course will cover key topics like data collection techniques, data visualization, predictive analytics, and reporting. By the end, participants will be equipped to leverage LMS analytics to personalize learning experiences, identify at-risk students, and optimize content and course structure.
Learning Objectives:
Upon completing this course, learners will be able to:
Understand the role of data analytics in educational settings and its impact on student success.
Identify and extract relevant data from an LMS for analysis.
Use statistical and analytical tools to evaluate LMS data.
Visualize data to communicate findings effectively.
Use predictive analytics to identify trends, at-risk students, and engagement levels.
Create actionable insights from data to improve the learning experience and course outcomes.
Build effective reports and dashboards for ongoing monitoring of LMS data.
Target Audience:
Educators looking to personalize and optimize learning experiences.
LMS administrators wanting to improve student engagement and success.
Instructional designers aiming to refine course content based on data insights.
Educational managers interested in reporting and trend analysis.
Course Overview
Learn to unlock valuable insights from large datasets using industry-standard tools like Excel, R, and Python. Master the techniques for analyzing and interpreting data to make informed business decisions.
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