This presentation gives a brief overview of the findings and used methods to come to an understanding of how experienced online learners self-direct their informal learning inside FutureLearn MOOCs. The presentation is part of the FutureLearn Network presentations given during the CALRG 2016 conference.

1. Self-directed informal learning
in FutureLearn MOOCs:
methods & main findings
Inge de Waard, Agnes Kukulska-Hulme, Mike Sharples

2. FutureLearn start
• Known: online learning, enrolled students, adult learners
• Unknown: actual FutureLearn experience
Different Learning: from formal to informal, from mandatory to voluntary

3. Exploring: avoiding assumptions
• Quantitative research: premise, hypothesis
• Questions risk guided by premise. Premise wrong, results wrong
• Qualitative research: exploration => avoid assumptions
• Memo-writing, data analysis iteration, conscious interpretation

4. FL-learning experience: data collection
Expectations
(pre-course)
Experiences
(self-reported
Learning logs)
Reflections
(one-on-one
interviews)

5. Morse, J. M., Stern, P. N., Corbin, J., Bowers, B., Clarke, A. E., & Charmaz, K. (2009).
Developing grounded theory: The second generation (developing qualitative inquiry), p. 17.
Glaser & Strauss
Discovery (1967)
Glaser (1987) Theoretical
Sensitivity
Glaser (1992, 1994, 1996,
1998, 2001, 2003, 2005,
2006)
Glaserian GT
Stern (1995)
Charmaz (2000,
2006, [2014])
Constructivist GT
Strauss (1987)
Qualitative analysis
Straussian GT
Strauss
Glaser
Clark (2003, 2005, 2008)
Situational analysis
Strauss & Corbin (1990, 1998)
Corbin & Strauss (2008)
Schatzman (1991)
Dimensional
analysis
Bower (1987)
Caron & Bower (2000)
Bower & Schatzman (2009)

6. Selecting target population
• Methodologic rigour: qualitative GT sample at least 12 learners (52 learners)
• Adult learners => experienced adult learners (avoid novelty remarks)
• At least 3 years of online learning experience

7. Selecting courses
Science of Medicines:
diabetes, heart,
depression (Monash
Uni, Australia)
Decision Making in a
Complex and Uncertain
World: economy and
networks (Uni
Groningen,
Netherlands)
Basic Science:
Understanding
Experiments (OU,
United Kingdom)
Different courses to obtain cross-course findings

8. Data collection
• Pre: online survey: background information & selection
• During: self-reported learning logs: 2 per ‘learning week’
• Post: one-on-one structured interviews

9. Investigating
What comprises the informal learning journey of experienced, adult
online learners engaging in individual and/or social self-directed
learning using any device to follow a FutureLearn MOOC?
• Which individual characteristics influence the learning experience?
• What are the technical and media elements influencing the learning
experience?
• How does individual and social learning affect the participants’
learning?
• Which actions (if any) did the learners undertake to organise their
learning?

10. Data analysis
• Open coding, line-by-line coding (verify categories), focused coding =>
theoretically saturate core concepts
• Memo writing: own assumptions, possible relations

11. Emerging data (DeDoose)

12. Memo’s making sense

13. Self-directed Informal Learning experience:
5 components, 2 key inhibitors/enablers
Intrinsic
Motivation &
Personal
Learning
Goals
Individual
Characteristics
(motivation)
Technical &
Media
elements
Individual & Social
learning
Context (people
& content)
Organising
Learning
(learning
goals)

14. Individual characteristics
• Motivation: choosing a course, personal and/or professional reasons
for completing learning episode (any length), edutainment
• Personal traits influencing the learning process: perseverance, self-
confidence, emotional language describing learning

15. Technical & media elements affecting learning
• Devices used for learning
• FutureLearn course & media elements
• Learning new tools provided in FL-course

16. Individual & Social learning
• Individual learning actions
• Social learning: connecting and sharing: looking for answers (help-seeking) versus
experience sharing, differences per course
• Different social learning actions per course: choosing who to interact with,
reflective actions, cohort learning, language

17. Organising learning
• Personal goal setting: range of personal learning goals, selecting content,
curated content benefit, building on personal learning actions
• Planning: available time, time investment in social learning, keeping notes
• Taking notes

18. Context
• Contextualizing content
• Proximity to context as motivator
• Peers and context

19. Future research
Personalised learning
• Impact of generic assignments, enabling learners to fit the assignment to their contexts
(contextualize pedagogical approach)
• Impact of enabling to set & realise personal learning goals (platform development)
• Patterns of engagement while considering motivation and learning goals.
• SRL outside professional FutureLearn MOOCs, including all SRL sub-processses
• Neurobiological research: measuring brain activity in learners that are engaged in
FutureLearn courses (find trigger points for increased motivation and learning goals –
interdisciplinary research).

20. Gratitude for ongoing wisdom & guidance
My two inspiring supervisors
• Mike Sharples
• Agnes Kukulska-Hulme

21. Questions? Remarks? Contact? …
21
E-mail: ingedewaard (at) gmail.com
Blog: ignatiawebs.blogspot.com
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