This document outlines a pilot study examining self-directed learning experiences in FutureLearn MOOC courses. The study will involve an online survey, weekly and daily learning logs, and interviews with 59 adult learners. The research questions focus on how daily life, technology, individual/collaborative learning, and learner adaptations influence MOOC experiences. A phenomenological approach and grounded theory will be used to analyze expectations, experiences, and reflections. Preliminary findings show learners engaging mostly through viewing content individually, with time constraints and technical issues as challenges. The study aims to understand factors in learners' self-directed learning zones.

1. Self-Directed Learning in Trial
FutureLearn courses
Inge Ignatia de Waard

2. What to expect?
• Background
• Literature foci
• Research environment
• Target population
• Research questions
• Methodology
• Findings
• Towards main study
• Two main challenges

3. Prelude to PhD: pilot study
Internal FutureLearn course August 2013 – invitation only.

4. Literature foci
• Self-directed learning: andragogy concept of Knowles
(1975), enhanced by Merriam (2002)
• Multiple learner concepts: mobile learning: Vavoula
(2005); Song & Hill (2007); Kop & Fournier (2011)
• Technology and mobility: Sharples, Taylor & Vavoula
(2007); Sharples (2013); de Waard (2013)
• Individual  collaborative learning: Kop & Fournier
(2011); Kop & Bouchard (2011); Milligan, Margaryan &
LittleJohn (2013)

5. SDL among MOOC types
SDL rather in xMOOC or cMOOC or … ?
• xMOOC versus cMOOC: Siemens (2005); Fournier, Kop
& Durand (2014); Ross, Sinclair, Knox, Bayne, and
Macleod (2014)
Drop out or self-directed learning choice? Clow (2013)
Learner success in MOOC = diverse: Bentley et al. (2014)
cMOOC xMOOC

6. Additional elements of SDL
Unclear for MOOC, but elements from mLearning, online
learning and some MOOC literature:
• Online learning research related (e.g. Garrison, 1997 &
2003)
• Design influences SDL (Loyens, Magda, Rikers, 2008)
• Seen in relation to Lifelong learning (Arrigo et al., 2012)

7. Mapping SDL MOOC territory
Overall learning TELearning (mobile, online) MOOC learning
Prior knowledge (Mobile) Seamless Learning Group size
Collaborative / individual
learning
Learning with new tools: digital
skills
Global learners: possible non-native
languages, different cultural
backgrounds,
Formal and informal Contextualized learning Content is very modular, certification
very diverse
Different degrees of
certification
Shorter courses MOOC casualness: on top of other
learning, as spare time action,
superficial curiosity. Leisure learning.
Course/Learning expectations Just-in-time learning: disaster
relief, performance support
Less tutor support (in general)
Unforeseen circumstances
challenging participation
Tech savy or willing. Organised outside class/curriculum
(mostly)
Personal traits (including
motivation)
Mixed online and face-to-face
interactions
Personal interactions within MOOC
are publically available
Learning is not confined to
the course group
Additional tech learning
options: augmented learning,
gamification
Learning analytics used as algorithms
due to group size data available

8. Pilot: trial FutureLearn courses
2 closed beta courses in FutureLearn rolled out
from 27 August 2013 and lasted for 2 weeks.
These closed beta courses consisted of two courses
(The secret Power of Brands and New Ecology),
each of them providing two weeks of content and
interactions to the participants.

9. Research environment
FutureLearn in development
Roll out courses
• Running alpha trial courses from 29 July 2013, quickly adapting for optimal
user experience
• Running beta closed courses from 27 August 2013, two weeks
• Rolling out first public beta courses from 15 September 2013, full courses
8 – 10 week courses
Design
• Based on mobile learning principles: simple design, content in bitesize
chunks.
• Current: expert content delivery, share and peer-discussion.
Pipeline
• Social learning: conversations
• Increased collaborative learning, learner based content creation.
• More learner-centered
• Sharing learner expertise

10. Target population
Informal adult learners engaged in two beta-
courses of FutureLearn
• The target population: learners interested in
FutureLearn (website registration, answering
social media & news article calls).
• Online pre-course survey for consent

11. Purposeful sample
• The final sample: 59 FutureLearn course participants. They
were selected from the total cohort based on:
– A diverse mobile device background (ranging from people
without mobiles to those having several)
– A mix of prior social media expertise (varying from none to over
5 years of experience)
– A diverse view on the importance of collaborative learning
(varying from not at all important to very important)
– A diverse experience in MOOC or online learning in general
(ranging from no experience to multiple experiences)

12. Research questions
• What are the learning experiences of adult participants
engaging in individual and collaborative self-directed
learning using multiple devices in a FutureLearn course?
4 sub-questions:
1. What are the elements of daily life affecting the learning
experience?
2. What are the technical aspects influencing learning
experiences for learners?
3. How do the MOOC participants perceive the effect of
individual or collaborative learning on their SDL?
4. Which actions (if any) did the learners undertake to adapt
their learning?

13. Open science of this pilot
• Shared research instruments can be read here (Academia: online
survey questions, learning log templates, interview questions)
• The full mobile impact on MOOC thesis can be accessed here).
• A draft report with literature review and methodology on pilot
study with research instruments, can be found here (with some
brief pointers on writing a probation report).

14. Why a phenomenological approach to
plan the pilot study?
Phenomenological research is a strategy of inquiry in which
the researcher identifies the essence of human experiences
about a phenomenon as described by participants.
The procedure involves studying a small number of subjects
through extensive and prolonged engagement do develop
patterns and relationships of meaning (Moustakas, 1994).

15. Method: 3 stages for collecting data
The pilot stage will consist of 3 stages to grasp the expectations,
experiences and reflections of the FutureLearn participants.
• Phase 1 - expectations: using an online survey which will be
delivered to all pilot study participants two weeks before the
FuturLearn course.
• Phase 2 – keeping learning diary logs: two learning diary logs: a
weekly and a daily learning log, used during the course.
• Phase 3 – reflections: structured focus group interviews planned
once the course has finished.
Expectations Experiences Reflections

16. Phase 1: pre-course online survey
• Tool used: SurveyMonkey (mobile)
• Data collected: prior to course
• Topics covered:
– MOOC experience
– mLearning experience
– Social media experience
– FutureLearn expectations

17. Phase 2: Learning Logs
Built upon Vavoula’s (2005) learning diary templates. The
templates altered for research (adding MOOC elements:
social media, collaborative learning)
• Weekly learning log: reflects type of FutureLearn
interactions the participant engaged in
• Daily learning log: reflects actual learning for each day
the participant engages in FutureLearn.

18. Phase 3: structured 1-on-1 interviews
Looking at the participants reflections on the course,
their devices used, their individual and collaborative
learning experiences, their overall evaluation of the
course and the strategies they adopted related to SDL.

19. Grounded theory to analyse the data
An exploratory methodology => combining
complementary approaches: a phenomenological
approach + grounded theory.
• A grounded theory (GT) approach was chosen to
analyse the data (Charmaz, 2006). Complimentary
characteristics of both methodologies (Creswell, 2006).
• both phenomenology and GT fit research looking for
meaning as perceived by the research subjects.
• Phenomenology fits research investigating the meaning
individuals give to a phenomenon (e.g. learning
experiences), GT permits data like learning experiences
to be analysed.

20. Some First Findings
Which learner activities did you engage in?
(n=47)
Viewing multimedia: 100 %
Reading text based content: 91 %
Reading course discussions: 87 %
Clicking ‘Mark as done’ on articles: 91 %
Taking a Quiz: 83 %
Responding to questions/discussions: 68 %
Searching for additional information on the
internet: 51 %
Viewing activity feed for the course: 30 %
Following other users: 23 %
Adding notes to video: 21 %
Bookmarking content for later retrieval after
the course has ended: 4 %
Did you work on your own or
collaboratively? (n=48)
Mostly on my own: 67 %
A mix of both: 29 %
More of a collaborative learner: 2 %
Not applicable: 2 %
Problems or challenges encountered:
Time related: 40 %
Spare time demands: 40 %
Internet connection: 35 %
Family demands: 30 %
Task-specific: 15 %
Accessing content: 10 %
Using course tools: 10%
Understanding jargon: 5 %
Emotional: 5 %

21. Some Learning Log feedback
• Hardware challenges
• No support from teachers/tutors
• Internet connection challenges
• Course tool problems
• Coping with stringed (one long list) of discussion
threads as learner activity
• Non-mobile user learning logs returned (reason?)
• Environment in development: not optimized for
collaborative learning, mobile communication… so
probing without strong learner interaction option basis
• Asking people to find technical solutions

22. Key findings
• Passive  active participation: a result of self-esteem, learning
preference, assimilating the new platform
• Daily life (personal  professional) affects MOOC learning to a
great extend, but its use can be positive or negative depending on
the interpretation given by the learner (e.g. illness)
• Formal and informal contacts (expert and laymen): we use our
existing network (relevant or not) with the new network (chosen
based on perceived expertise or mutual interest (Rienties, 2013)
• Prior MOOC experiences color active participation (expectations 
MOOC reality)
• Most of all: learners proceed by reaching for some kind of
personally driven balance: time, effort, interest, motivation… There
seems to be a personally defined zone where new (MOOC learning
happens) => increases feeling of success

23. SDL: mapping factors and zones
Comfort
Learning
zone
Technology:
(AS)TAM
AODM
Learner
Generated
Contexts
Digital skills
Personal traits:
motivation, socio-political,
identity, Big Five
Prior
knowledge
Experience
Education
SDL skills
Learning management
capacity
Possible SDL
Learning zone
No Learning
zone /wide gap

24. Taken forward to main study
• Focus on self-directed learning (andragogy) or on
self-determined learning (heutagogy)?
• Only focus on experienced online learners
• Use content diversity of MOOCs
• Explore all emerging elements to filter out major
MOOC elements

25. Two current challenges
Untangling concepts:
• Heutagogy: self-determined learning (beyond
SDL) versus adult learning: self-directed learning
(lifelong learning) versus self-regulated learning
(vocational learning)
• But there is more: autonomous learning,
individual learning, collaborative learning
Creating a learning crossover framework including
learning dichotomies that are relevant to MOOCs

26. References
• Arrigo, M., Kukulska-Hulme, A., Arnedillo-Sánchez, I., & Kismihok, G. (2012). Meta-analyses from a collaborative project in
mobile lifelong learning. British Educational Research Journal, (ahead-of-print), 1-26.
• Garrison, D. R. (1997). Self-directed learning: Toward a comprehensive model. Adult Education Quarterly, 48(1), 18-33.
• Garrison, D. R. (2003). Self-directed learning and distance education. In M. G. Moore & W. Anderson (Eds.), Handbook of
Distance Education (pp. 161-168). Mahwah, NJ: Lawrence Erlbaum.
• Knowles, M. S. (1975). Self-directed learning. New York: association Press.
• Merriam, S. B. (2001). Andragogy and self‐directed learning: Pillars of adult learning theory. New Directions for adult and
continuing education, 2001(89), 3-14.
• Kop, R., & Fournier, H. (2011). New dimensions to self-directed learning in an open networked learning
environment. International journal of Self-Directed Learning, 7(2).
• Loyens, S. M., Magda, J., & Rikers, R. M. (2008). Self-directed learning in problem-based learning and its relationships with
self-regulated learning.Educational Psychology Review, 20(4), 411-427.
• Milrad, M., Wong, L. H., Sharples, M., Hwang, G. J., Looi, C. K., & Ogata, H. (2013). Seamless Learning: An International
Perspective on Next Generation Technology Enhanced Learning. In Z. L. Berge & L. Muilenburg (Eds). Handbook of Mobile
Learning. Routledge.
• Moustakas, C. (1994). Phenomenological research methods. Thousand Oaks, CA: Sage.
• Song, L., & Hill, J. R. (2007). A conceptual model for understanding self-directed learning in online environments. Journal of
Interactive Online Learning,6(1), 27-42.
• Vavoula, G.; O'Malley, C. & Taylor, J. (2005). A study of mobile learning as part of everyday learning. In: Attewell,
Jill and Savill-Smith, Carol (Eds). Mobile Learning Anytime Everywhere: a Book of Papers from MLEARN 2004. (pp. 211–212).
London: Learning and Skills Development Agency.
• Wong, L. H., & Looi, C. K. (2011). What seams do we remove in mobile-assisted seamless learning? A critical review of the
literature. Computers & Education, 57(4), 2364-2381.
• de Waard, Keskin, Koutropoulos (upcoming paper) Exploring future seamless learning research strands for MOOC.

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