MOOCs: drivers, data and diversity

Photo by Andrew Wulf on Unsplash

Introduction

We have now produced and run, several times each, four Massive Open Online Courses (MOOCs) with our partner FutureLearn.  The College portfolio continues to both grow and diversify.  Two of our three faculties are represented while the third has two solid, funded proposals in place for delivery in Spring 2020.  In addition to sharing the budget and opportunities to engage, we have also succeeded in producing courses which meet the needs of a variety of the  ‘learner archetypes’, as defined by FutureLearn. One feature of the platform we are yet to explore is the Lead Generator, whereby a landing page can be included in a course to encourage learners to engage further with the provider, e.g., through online programmes or, in our case, Royal Holloway, University of London’s International Summer School.

Motivation

The benefits of MOOCs, and therefore the strategic drivers of our activities in this area are summarised below.

Of these, Recruitment and a definition of Research extended to include the analysis of the rich data MOOCs provide are the most relevant to the launch of the International Summer School at Royal Holloway.

The E-Learning Team’s involvement in this Summer School relates to the use of Moodle as part of a blended approach to teaching, learning and assessment, but we can contribute more. Our MOOCs demonstrate a great international reach and a diversity of learners, while the FutureLearn platform provides a rich seam of data about our learners.

Measurements

Education makes a habit of dragging its heels when it comes to digital innovation; discussions are often reduced to binary arguments which focus on crises rather than opportunity.  The MOOC landscape is pock-marked by reports that retention rates are low.  Such measurements are designed for traditional campus-based teaching and learning, with the accompanying barriers in the form of fees, prior qualifications and inflexible modes of delivery.

Analysing the rich data generated by our MOOCs to identify the course profile(s) best suited to recruiting to the Summer School presents opportunities to move away from the retention data, to delve deeper and learn more about our new audiences, and to inform other College initiatives as part of our cross-disciplinary role.

Research questions

1. From how many countries did each of our most recent MOOC runs attract learners?

2. Outwith the UK, in which countries were most of our learners based for each of our most recent MOOC runs?
(% of enrolments)

3. How ‘youthful’ were the learners on our most recent MOOC runs?
(expressed as a % of learners aged under 26 years)

For the next two questions the Parker Berger index was used to provide an indication of the diversity of our learners in terms of age and country.

The Berger–Parker index equals the maximum p_i value in the dataset, i.e. the proportional abundance of the most abundant type. This corresponds to the weighted generalized mean of the p_i values when q approaches infinity, and hence equals the inverse of true diversity of order infinity (1/^∞D).

It is simple measure of the numerical importance of the most abundant species,

d = Nmax / N

where Nmax is the number of individuals in the most abundant species, and N is the total number of individuals in the sample.

The reciprocal of the index, 1 minus d, is often used, so that an increase in the value of the index accompanies an increase in diversity and a reduction in dominance. We plot the dominance index d. In order to overcome H5P’s limitations (we used the Chart tool on this post and it only supports integers) we then multiply the reciprocal by 100 to provide a whole number.

For example:

Total number of learners  N = 10 000
Largest age group (26-35), Nmax = 2550
d= 0.255
1 minus d = 0.745
Multiplied by 100 to provide a whole number = 75

Read more about this here: https://en.wikipedia.org/wiki/Diversity_index#Berger.E2.80.93Parker_index

4. In terms of enrolments how internationally diverse are our most recent MOOCs?
(out of 100 with a higher number meaning greater diversity)

5. In terms of age of learners how diverse are our most recent MOOCs?
(out of 100 with a higher number meaning greater diversity)

6. In terms of the learner archetypes, to what extent did our most recent MOOC runs reach those learners self-identifying as ‘Explorers’ or ‘Preparers’, i.e., those most likely to be in the Summer School target group?
(% of enrolments)

Conclusion

1. 1. Using Open Data in Business stands out as having the most extensive and diverse international reach, and a learner profile matching that of the International Summer School target audience: students; under-26 year olds; and those who use MOOCs as investments in their futures.
   2. Accounting for Death in Warfare  is similar to the above in terms of the high proportion of under 26 year-olds enrolled and a diverse international profile, albeit from a smaller number of countries.
   3. Beyond the Ballot has by far the most enrolments but UK-based learners account for almost half of these, while very few fit the learner archetypes to which the International Summer School is likely to appeal.
   4. The RAF in the Cold War has a well above average UK enrolment base and and the least youthful learners but has enjoyed exposure to learners in the USA, one of the target markets.
   5. Future course development plans include three MOOCs which will have a similar audiences to those on Accounting for Death in Warfare, and one is aimed squarely at those who are considering or are about to begin Undergraduate study.  The content, target audience and timing of these courses fits well with next year’s Summer School run.