As an administrator or instructor, you’re already familiar with some types of learning analytics. Grades and student feedback are both forms of analytics in use in the classroom. On a larger scale, major standardized tests, like the GRE or SAT, have provided the opportunity to assess student learning. The advent of online learning has opened up new ways to analyze student learning and student use of online learning resources. The use of active online learning components makes big data, like learning analytics, easily accessible and available to institutions, administrators and instructors.
Learner Activity Data
Online courses or online supplements to traditional courses provide a wide variety of data on learner activity, or use of the course and course resources. Online learning systems, like your LMS and other LTI-compatible solutions, allow you to see how students are using online learning, interacting with material and even engaging with one another.
Online learning can provide you with traditional learner data, like grades, but also with new forms of learner data. With this information, you can adjust and adapt teaching to meet student needs.
Types of Data
Many online courses, from specialized courses to MOOCs rely upon video learning. Video analytics allow instructors to track the use of videos, how well they’re working, who is watching them, and even which parts of the video are attracting the most attention or video hot spots.
- A hot spot is a point in a video that students have not only watched, but rewound and re-watched. Hot spots might reveal points of interest or points of confusion.
- Integrated video quizzes assess student understanding of video lectures and presentations.
- Video analytics also provide information about search terms, illustrating what students are studying and reviewing.
Specialized user data can allow institutions and instructors to recognize students or groups of students who may be struggling and address those students’ needs.
Using Learning Analytics
How can institutions and instructors respond to the information available through video and learning analytics? These analytics can improve classroom and online learning for students, maximizing the value of their time and financial investments.
The effective use of learning analytics can enable:
- Improved student outcomes.
- Higher quality instruction.
- Real-time feedback about instruction quality.
- Improved responsiveness to student needs and desires.
Think about a relatively basic and traditional analytic strategy used in the classroom–pre- and post-tests. The pre-test shows you what students already know, before instruction begins. The pre-test is scored and assessed, allowing the instructor to adjust the planned curriculum to meet the learning needs of the students. The pre- and post-test does not provide day-to-day feedback on individual lessons. Modern learning data and analytics do provide that information.
Using video analytics, presented in online dashboards through YuJa, an instructor reviews student use of a recent lecture capture. A number of students have re-watched the lecture capture more than once, and there are several clear hot spots on the video, particularly concerned with certain material in the video. The instructor notes a number of questions on the same subject in the real-time discussions. In response, the instructor adds additional learning resources to the Learning Channel, perhaps filming an additional video or sharing relevant videos from an external site. The students now have the answers they need and can do well on later class assessments. The learning analytics available allowed the instructor to immediately and effectively adjust the curriculum and lesson plans to meet student needs.