What is learning analytics?
Learning analytics is much more than a tool; rather it is a process and can span many diverse approaches to help improve learning outcomes. The focus of learning analytics is to provide actionable information that can improve teaching and learning.
While there are many definitions of learning analytics, UW–Madison has contextually defined it as the undertaking of activities designed to improve student outcomes by informing structure, content, delivery, or support of the learning environment. In practical terms learning analytics uses data generated within courses to inform and improve teaching and learning on our campus.
More information about learning analytics at UW–Madison is available from the Learning Analytics Center of Excellence. Also before leveraging any learning analytics approaches please review UW–Madison’s Learning Analytics Guiding Principles, which state that students are real and diverse individuals, and not just their data or information. The principles — beneficence, transparency, privacy and confidentiality, and minimization of adverse impacts — aim to uphold the dignity of students while ensuring learning analytics are used to improve educational outcomes.
What can I use learning analytics for?
Learning analytics can be used by multiple stakeholders (eg. advisors and students) in addition to instructors. There are a variety of ways that an instructor can use learning analytics. To help instructors understand the educational benefits, a Learning Analytics Functional Taxonomy was explored and adapted by campus fellowships. The following are the different categories included in the taxonomy.
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Access learning behavior
Learning analytics can collect user-generated data from learning activities and offer trends in learning engagement. Analyzing those trends can reveal students’ learning behavior and identify their learning styles. This approach measures engagement and student behavior rather than performance, giving instructors insight into how their students interact with their course materials.
Individualized learning
Adaptive or individualized learning systems apply learning analytics to customize course content for each learner. Furthermore, user profiles and other sets of data can be collected and analyzed to offer greater personalized learning experiences. This approach uses continuous feedback to help individual students in their learning.
Predict student performance
Based on already existing data about learning engagement and performance, learning analytics applies statistical models and machine learning techniques to predict later learning performance. By doing so, likely at-risk students can be identified for targeted support. Focus is on using data to prompt the instructor to take immediate action to intervene and help a student course correct before it is too late.
Evaluate social learning
Learning analytics can be applied to investigate a learner’s activities on any digital social platform — such as online discussions in Canvas — to evaluate the benefits of social learning. This measures and tracks student-to-student and student-to-instructor interactions to help understand if students are benefiting from social learning in their course.
Improve learning materials & tools
Learning analytics can track a student’s usage of learning materials and tools to identify potential issues or gaps, and offer an objective evaluation of learning materials and tools. This allows instructors to make deliberate decisions about modifying approaches. Using aggregate student data, instructors can see ways to improve the process of learning or the structure of their course.
Visualize learning activities
This approach traces all learning activities performed by users in a digital ecosystem to produce visual reports on the learning process. The reports can support both students and teachers to boost learning motivation, adjust practices and leverage learning efficiency. This is about facilitating awareness and self-reflection in students about their learning patterns and behaviors.
What are my learning analytics tool options?
Learning analytics is a relatively new and fluid space. Institutions, vendors and consortiums like Unizin are actively developing new tools to collect and analyze data about learning environments. Currently the most readily available learning analytics tools on campus for instructors are analytics tools within Canvas, Kaltura, and the Engage eText reader. More information about these tools and how to use them is listed below:
- Canvas’s New Analytics is a learning analytics tool that allows you to filter and compare sections and individuals to class averages, for all grade-based Canvas activities such as Assignments, Quizzes, and Discussions.
- Canvas Quiz Logs contain some information on students taking quizzes or exams through Canvas. This data should NOT be used for academic integrity questions or concerns.
- Instructors can look at other views in Canvas to learn more about student activity and course materials. For example, on the People page in Canvas you can see when students last accessed the course. In addition, Quiz Statistics may be useful to see where students need additional support or where a quiz question needs modification.Other student course-access reports can be accessed that use third-party tools. There are also resources for interpreting the course-access reports and some tips on how to use them.
- Kaltura Mediaspace provides some pretty advanced analytics, especially if you embed your video in Canvas through the Canvas-Kaltura Integration.
- Top Hat is an active learning platform that allows instructors to engage with students through various online activities. Top Hat includes some data and analytics about student activity in a course.
- Piazza is a student-driven question and answer service. Students can ask and collaboratively answer questions; instructors can endorse the best answers and provide clarification. Instructors can view patterns of students’ activity, including the number of unique users per day and the number of posts per day, broken down by weeks.
Atomic Assessments provides advanced quizzing functionality; instructors can review reports and analytics about students’ activity.
Are the tools integrated into Canvas?
Currently, New Analytics is part of the Canvas interface, and you can also access Quiz Logs and course-access reports in Canvas. Other tools may be integrated within a Canvas course and depending on how they are set up, you may be able to access analytics within Canvas. (For example, Kaltura has this functionality if you use the Gallery feature in Canvas.)
Who can I talk to for more information?
Our learning technology consultants are happy to help you choose the best tool to fit your needs and start using it to improve student success. Contact the DoIT Help Desk to schedule an appointment with a DoIT Academic Technology consultant. In addition, the Learn@UW KnowledgeBase offers helpful documents for instructors, course owners and students. Other learning analytics information, resources, events and news are available on the Learning Analytics Center of Excellence website.