I'm delighted to announce today that the Engagement Analytics suite is now available at:
Engagement Analytics provides a quick 'traffic light' snapshot view of the ten students in your course you should be concerned about based on a configurable risk calculation. It also links through to a report on all students in your course, as well as a detailed explanation of how risk is calculated for a particular student.
Indicators of engagement/risk
The risk percentages shown in the block are the result of three indicators:
- Login activity: how often, how recently, and how long are students logging in?
- Forum activity: are students reading, posting, replying?
- Assessment activity: are students submitting their assessed work, and are they submitting on time?
These indicators were selected as the most evidence-based following a review of the literature. How important are logins vs forums vs assessments in predicting success in your course? It depends on the course, so Engagement Analytics allows you to configure the weighting of each - eg 60% logins; 30% assessment; 10% forums. Inside each indicator you can modify how it calculates risk: the number of logins before someone is not at risk; how many days before an assessment is too late and therefore risky; the number of forum posts you expect students to write each week; etc.
Write your own indicators
You can write your own indicators using our documented indicator architecture, and they'll have equal status with our login/forum/assessment indicators. So if you think that completion tracking, diagnostic quiz scores, or downloading files are the real indicators of student engagement, then write an indicator! If you've got an idea feel free to propose here.
Pedagogy/Philosophy of analytics
Engagement Analytics takes a 'Level 3' approach to learning and teaching (Biggs, 1999), and views learning as "what the student does" (as opposed to "what the student is" or "what the teacher does"). By understanding what students are doing we can better guide them to do the things we know will help them learn. It does not focus on "what the student is" (age;IQ;GPA;etc). Of course, that doesn't stop you from writing an indicator that plugs in to your student management system though. As an education researcher I encourage you to have a read of the Biggs article if you haven't yet, as it has some insights that are useful for analytics.
To make the most of Engagment Analytics, a teacher needs to specify what they think learning is in their course - ideally they are already communicating this to their students anyway. Engagement Analytics is not an AI/SciFi analytics tool; its usefulness is only in knowing if students are doing what you have specified you want! It also won't follow up students automagically; you know your students best, and a carefully crafted email/phone call/message should work better than a robotic email.
Help us make it better
Please let us know if you have any issues, ideas or comments - ideally over the next few months while we still have some funds left ;)
Many thanks to:
- The NetSpot Innovation Fund for generous funding
- NetSpot developers Ashley Holman & Adam Olley for writing the code, and Kim Edgar for project management / documentation support
- The expanded project team of Jacques van der Meer, Angela Carbone, Emily Spencer, Robert Nelson, Hariz Halilovich, Keryn Pratt, Tom Apperley & Nathan Bailey
Dr Phillip Dawson, Monash University, Melbourne Australia