As a trainer and consultant it is extremely satisfying to realize that learners fully understand an idea. It is a magical moment when their eyes light up and they start to leapfrog forward, digesting whole concepts, one after another. As they input their own personal data into the assessment tools, they start to see patterns and can analyze themselves and others in a new light.
We are on the verge of an exciting new development in this field. Personality Style, Learning Style, and Career Planning assessments from the 1950’s to the 1990’s polled people on various elements on printed forms to use the data to build a more successful life. Then in the mid 1990’s, with the use of the internet, the assessment tools could poll on line (see linked example) and give individuals their results almost instantaneously with greater ability to compare with others responses. Now in 2014, with the use of Data-Driven Learning Analytics educators can combined the previous assessment data with student interaction in online education tools to create a more integrated and customized learning environment.
Check out this amazing info-graphic by Wlodarczyk (2013) titled Learning Analytics 101, which answers questions about data-driven learning analytics and assessment. What can it do? This process can predict future student performance; it can intervene when students are struggling, to provide unique feedback tailored to their answers; and it can personalize the learning process for each and every student. Data driven Learning analytics challenges the traditional “efficient learners hypothesis” that states “all students begin at equal levels and progress similarly”.
This chart also gives a strong visual of where the data comes from, how it is interrelated and fed to a dashboard. This dashboard can be used by faculty, teachers, administrators and researchers to improve the granularity and value of the data to help improve the learning environment of the individual learners.
The bottom of this info-graphic explains that with this data, educators in the future will continually shift their role between instructor, facilitator and analyst. Benefits of using student data learning analytics are that they:
- can help educators identify students who are initially slow but surge ahead later
- can be customized to student’s needs, allowing students to get a better, faster picture of their performance
- help every student in a course answer every question, insuring they interact with all course material.
- can identify common wrong answers and create custom responses crafted to help address specifics of each particular wrong answer
- allow for online peer grading and self-grading – educators can monitor correlations between current vs. past performance and teacher vs. peer/self-grading
This site’s post of March 13 discussed “Flipped Classroom”. Khan Academy and other instructional websites are constantly analyzing the student data to create improved video examples to help the individual learners understand the concepts. They also have developed sections for the coach, teacher or parent to have unprecedented visibility into what their students are learning. This allows them to focus on specific concepts to reinforce the ideas that may need additional attention. Again this reemphasizes the role of the educator as an instructor, facilitator and analyst.
I am excited about “Data Driven Learning Analytics and Assessment”. I am committed to using these tools to help students be successful in overcoming obstacles (hurdles) on their own unique learning path. I am also committed to assisting other adult educators on how using this technology can assist them in their learning environments.