This is all about an ECAR report that was released a few weeks ago. Report was compiled over about a year and had a large number of contributors. It’s a great example of collaboration across organizations for profit and non-profit, scientific, etc.
39% is the Key Number
- In the US, only this percentage completes a 4-year program.
- This is a national challenge, because the US has slipped from #1 or #2 completion in the world to #12
- How Can Predictive Learning Analytics Help? It provides the ability to predict the future with a reasonable level of accuracy give you the ability to intervene on behalf of the student
What is Predictive Learning Analytics?
- The statistical analysis of historical and current data derived from the learning process to create models that allow for predictions that improve learning outcomes
- Subset of larger learning analytics field
- Uses sophisticated mathematical models rather than user-defined rules. Example: Academic Early Alert Systems
- OAAI: the Open Academic Analytics Initiative
- Apereo Learning Analytics Initiative
Data Sources, Relevance & Diversity
- LMS: academic technology’s first killer app
- What’s been successful is the penetration and usage of LMS
- What data from conventional data sources are systematic, significant predictors of course success? High school GPA? Race/Ethnicity? First in Family to Attend College? NONE OF THEM!
- Academic Technology data is a systematic predictor of course success – caveat is that the academic material is connected in a deep and meaningful way. Having a number of triggers help to track actionable details.
- Embedding Predictive Analytics
- Strategic Importance other Data Points: underrepresented student groups.
- Conclusion: Learning Data Comes in Many Flavors and Relevance, i.e. Activity (behavioral) data and Static Data (survey data, student aptitude, extra-curricular activities, demographics and prior educational experience).
- There are very few institutions that employe full-time Predictive Learning Analytics professionals.
How it Works, What is the Data Impact?
- Historical data and predictive analytics are used to generate a predictive model
- We want to tease out and surface those patterns that result in successful outcomes
- After first month, predictive model can provide predictions of the final grades based on the # of content views of the students in the current course offering
- Examples of what can go wrong: what if students are viewing the content from mobile application (data incomplete); what if one of the historical course has hundreds of course topics, where other courses have tens of course topics? (data is inaccurate)
- Garbage In, Garbage Out
- Data quality: accurate, complete, unique, timely, consistent, valid, reliable, integrity
Brightspace Student Success System
- Created a predictive model for a course
- A number of screen shots showed how it was implemented with a group of students, with drilldowns on where students were having difficulty.
- Good visualizations are critical to easily decoding information and making it useful
- ETL/Data Integration > Data Warehouse & MDM > BI & Data Visualization > Predictive Analytics
Strategic Implementation Considerations
- Institutional Stages of analytics usage
- Organizational leadership, culture & skills
- gaining access to learning data
- Ethics & privacy
Institutional Stages of Analytics Usage
- Basic: past trends & data observations
- Automated: automatically perform analytics & provide results directly to end-users
- Predictive: large amounts of data is crunched
Silos are antithetical to successful implementation; investing in new skill sets is imperative.
Gaining Access to Learning Data
- Activity, clickstream data
- It’s the fuel on which LA runs
- Extracting sample data sets is often a good start
Ethics & Privacy
- Ethics: using LA for good and not evil
- Privacy: balance the need to protect confidentail records while maximizing the benefits of LA
- Often requires new policies and procedures
- LA “task force” to address ethics and privacy issues
- JISC code of practice
- SURF Learning Analytics SIG
- How do you best approach the introduction of PA to a group of people who don’t even know what it does? EDUCAUSE has some great white papers on this (“Penetrating the Fog”). Give examples of products, strategies and solutions.
- Have you done anything to look at the performance of blended/flipped classrooms? We get asked this a lot! We’ve looked at some of the open course offerings of MiT, Blackboard usage patterns. Many folks are interested in using it for academic course design.