This tool will help teams view student activity and workload in an online graphical format, supporting curriculum planning and analysis. By categorising student activity following the Learning Design taxonomy, teams are prompted to consider different types of student activity, which results in more conscious design decisions. As the data is stored in the database, rather than Ms Word documents, it can be analysed together with student feedback and outcome data, helping universities and colleges to improve course design based upon sound evidence gathered through the use of this tool.
Providing learning material to students that is of interest, at the right level, and stretches their learning, has always been a challenge, but with a student population that is more often working, both in part- or fulltime jobs, alongside their studies, it is now more important than ever to ensure that the demands of their studies are balanced. Student workload contributes to students’ decisions around withdrawing from study and is among the most important course-related factors influencing student drop-out (Bowyer, 2014). Abott (2003) reported that falling behind with course work was the most commonly cited reason for withdrawal, more than a third of respondents cited this as the main reason for leaving their course. From survey data as recent as 2012/2013, 26% of students stated the amount of study time required as a reason for withdrawal.
We have developed a proof of concept tool to ascertain the course-directed workload on a week-by-week basis. It will enable staff to record course directed workload using a taxonomy of seven activity types (assimilative, finding and handling information, communication, productive, experiential, interactive/adaptive and assessment) originally developed by Conole (2012). By linking this information to student outcome information, we will be able to start providing insight into the impact of workload on student outcomes, e.g. relate the amount and type of workload to student satisfaction and pass rates.
With Jisc funding, we will develop an online tool which enables staff involved in course design and production to map the workload of a module using a taxonomy of Learning Design activity categories.
Look and feel of the tool
The tool will be easy to use, and the workload information will be stored in a database. It will be possible to export the data to Excel or other tools for analysis. This will allow teams to combine the information with other information sources such as student satisfaction and success data.
By Jitse van Ameijde, Lisette Toetenel, Vicky Marsh, Nai Li and David Cook (Institute of Educational Technology, The Open University). Please email Jitse.van.Ameijde@open.ac.uk for any questions.