This post was co-authored by Sue Lowe, Quality Controller – Digital Education and Ian Elliott, Lead Learning Designer.
Background
As mature students with jobs and family commitments, UCEM students can sometimes struggle to balance their coursework workload. UCEM has provided supported online learning programmes for many years, and currently offers approximately 100 modules at both undergraduate and postgraduate levels. We are passionate about enabling our students to succeed in their learning and to carry that forward into their careers in the built environment.
Our modules are designed to guide students through their learning via a range of activities and resources with formative and summative assessment points. As part of the UCEM Transform project, all modules were redeveloped in 2020–21 to fully align with our current educational framework of student outcome-led design (assessment first), participatory experience (problem solving and competency based) and online presence (tutoring and facilitating). Activities are designed in line with the five UCEM learning types: active acquisition, exchange, reflection, production and practice. Interaction is built in using Moodle tools or learning technology such as H5P or Storyline. A sense of community is provided through online discussions in forums, Padlet boards and webinars.
The problem
However, despite this redevelopment work, we sometimes received feedback from students who felt that their study workload was a little too heavy, and that they were sometimes finding it difficult to understand where they should prioritise their time.
While Module Leaders, Tutors and Learning Designers do have a good sense as to how long an activity should take on average, there is always the potential for discrepancy, leading to some weeks or modules having a slightly heavier workload than others.
The solution
To address these issues, UCEM launched the HELP (Higher Engagement, Lower Pressure) initiative in 2022, with the goal of ensuring that the study workload was fair, manageable, and consistent across all modules; part of this meant a focus on ensuring that any material not directly relevant to students’ assignments would be clearly marked as further study. The initiative focused on directed study hours, rather than the self-directed study which students also need to carry out during a module. The Digital Education Team decided to create a tool that would facilitate a consistent and fair outcome.
We explored existing study hour calculators used by other institutions and while we found several good examples, most calculate reading time only. This was not sufficient for our needs. For example, we liked the Wake Forest University (no date) Workload Estimator 2.0; the commentary was useful and the calculations based on literature. However, the choices didn’t fit our modules; the only part that would be useable for us would be the calculator for reading elements. As UCEM’s modules incorporate a wide range of activities, we also needed to be able to calculate time for learning opportunities such as engaging with videos, interactive quizzes, forum discussions and webinars.
A further challenge was that different institutions apply different reading times. Reading time of course varies depending on the purpose (e.g. skim versus detailed reading) as well as what is being read (an academic journal or industry report versus VLE forum post or a blog post). The University of London (Bodenham 2014) suggests 200–400 words per minute, depending. Wake Forest University (no date) worked on a page basis ranging, for example, from 67 pages per hour (450 words per page, no new concepts) to 9 pages per hour (450 words per page, many new concepts).
There are some instances of more detailed calculation assumptions for digital education, for example, the Open University advises twice the length of a video, 5 minutes per figure (van Ameijde and Edwards 2015). While also online learning like the Open University, UCEM modules are more condensed and focused on industry requirements.
So, we decided to create our own standards to ensure consistency in mapping student workload across all modules. My colleague Ian Elliott cleverly developed a draft study hours calculator using Excel. To make it obviously connected to UCEM Transform modules and activity types and resources, we organised the calculator to reflect them, colour coded in line with the design jam learning type cards.
Ian built in the study time assumptions which we developed based on wider research as well as through mapping existing modules with the help of our learning designers. It’s incredibly difficult to find a solution to fit every context but we need to start somewhere.
Learning designers then used the UCEM study hours calculator in their discussions with Module Leaders and Tutors to rework weeks in modules that were deemed heavy. In doing so, they continued to ensure a range of activity types and resources were built into the modules, and that these fed into the assessment.
The UCEM study hours calculator also provides an overall module view as shown in Figure 1, as well as more detail on a week-by-week basis. The figures in the colour-coded columns are percentages, showing the proportion of time spent on each learning type; a quick visual check of this during development can show where certain weeks might be particularly heavy or light on, say, exchange, active acquistion or production and can help to inform design decisions.
Source: UCEM (2023)
Figure 1 shows how one Level 7 module changed after Ian redeveloped it as part of the HELP initiative. As a result of this work, directed study hours were reduced to an average of around six per week.
The impact
As of April 2023, the study hours calculator has been used in two semesters of development. We have found the UCEM study hours calculator to be a useful tool in managing student workload. All of UCEM’s academic modules have been redeveloped as part of the HELP project, and regular use was made of the study hours calculator. The time assumptions used in the pilot proved to be successful and were used again in the second semester. The calculator has been received positively by academic staff as well as learning designers and the wider Digital Education team.
More importantly, the impact of this initiative on student outcomes and satisfaction is clear. Module success rates (students passing their module) significantly improved across all modules as a result of the HELP project. Modules that began in Autumn 2022 saw a significant increase in success rates compared to their previous iteration.
Qualitative data from student end-of-module evaluations has shown a significant increase in student satisfaction regarding workload. Students were more satisfied overall, with comments including appreciation for how focused the material was.
Looking at the example Level 7 module mentioned above, the assignment results remained good and comparable to the previous year, and student comments included praise such as ‘Assessment topics covered were focused and stimulating.’ Students scored the following statements out of five:
- Overall, I was satisfied with the quality of the module. After HELP, this rose to 4.4 / 5; an increase of 0.2.
- My module provided me with opportunities to apply what I have learnt. After HELP, this rose to 4.8 / 5; an increase of 0.5.
- There was sufficient variety of study resources (e.g. presentation, quiz, video, reading). After HELP, this rose to 4.8 / 5; another increase of 0.5.
Conclusion
The UCEM study hours calculator was developed to support the HELP initiative. This was launched in response to feedback from students that their study workload was a little too heavy, and that they needed a simpler approach to manage their time. The goal was to ensure that students’ study workload was fair, manageable, and consistent across all modules and the study hours calculator was key to achieving this goal. The calculator enabled learning designers to support academics achieve a level of consistency in study workload that had not previously been possible.
The results we have seen fully vindicate the decision to develop the study load calculator. They demonstrate that students appreciate the reductions in study time across their modules. The impact overall on the UCEM student experience has been highly positive, with quantitative and qualitative feedback demonstrating that it has helped many students to balance their workload more effectively.
References
Bodenham L (2014) ‘Speed up your reading skills’, University of London [online]. Available at: www.london.ac.uk/news-opinion/london-connection/top-tip/reading-skills [accessed 12 April 2023].
van Ameijde J and Edwards C (2015) ‘Reading speeds’, Student Workload Evaluation Project – End of Stage 2 Interim Report. Milton Keynes: The Open University.
Wake Forest University (no date) ‘Workload Estimator 2.0’ [online]. Available at: https://cat.wfu.edu/resources/tools/estimator2/ [accessed 12 April 2023].
Acknowledgement
Photo by Ali Yılmaz on Unsplash
Sue Lowe | SCMALT, SFHEA | I’m Quality Controller (Digital Education) at the University College of Estate Management. I worked previously at the Open University and studied – online and at a distance – for a Masters in Online & Distance Education.