Colin Milligan & Allison Littlejohn

Self-regulated learning and MOOC participation

Paper session M18: Self-Regulation Date: Friday 28th August 2015, Time: 17:15

Outline

• MOOCs and Self-Regulated Learning,• Study context, participants and method,• Findings,• Reflection on implications, limitations and future work.

Introduction and background

FORETHOUGHT

PERFORMANCE

SELF-REFLECTION

Massive Open Online Courses

FORETHOUGHT

PERFORMANCE

SELF-REFLECTION

• Massively popular• Content-centric, pedagogically simplistic

• Our interest, how are they being used by professionals

• Formalising and updating knowledge,• Preparing for career move,• Networking and access to other professionals.

FORETHOUGHT

PERFORMANCE

SELF-REFLECTION

Self-Regulated Learning

Self-regulation is the ‘self-generated thoughts, feelings and actions that are planned and cyclically adapted to the attainment of personal goals’ - Zimmerman, 2000.

FORETHOUGHT

PERFORMANCE

SELF-REFLECTION

FORETHOUGHT

PERFORMANCE

SELF-REFLECTION

Phases and sub-processes of SRL

Phase Forethought Performance Self-reflectionSub-processes Goal setting

Self-efficacy Task interest/value

Learning and Task strategies

Help seekingInterest enhancement

Self-evaluationSelf-satisfaction/affect 

  

FORETHOUGHT

PERFORMANCE

SELF-REFLECTIO

N

SRL and Online learning

• Highly self-regulated learners adopt different strategies to low self-regulators

Azevedo & Cromley , 2004

• Higher levels of self-efficacy lead to more persistence online.Chang, 2005

• Successful online interaction is dependent on an individual’s self-efficacy and overall ability to self-regulate.

Cho & Kim, 2012; Cho and Jonassen, 2009

• Goal-setting increases performance in an online e-portfolio based system,

Chang, Liang, & Liao 2013

FORETHOUGHT

PERFORMANCE

SELF-REFLECTION

SRL and MOOCs

• Do MOOC environments demand high levels of self-regulation, or suit learners with particular SR skills?

• Do high and low self-regulators behave differently?

• Does an individual’s level of SRL affect their participation?

Research Questions and

Study Design

Research Questions

• RQ1 How are MOOCs currently designed to support self-regulated learning?

• RQ2 What self-regulated learning strategies do professionals apply in a MOOC?

• RQ3 How can MOOCs be designed to encourage professionals to self-regulate their learning?

Context and Cohort

• Participants in the Fundamentals of Clinical Trials MOOC offered by edX 2013-4.

• Recruited via course announcement (wk4/12)• Participants were professionals across a range of role –

medicine, healthcare, statistics, bioscientists, pharmacists.

• 35 interviewees [16m, 19f], 23 countries• Drawn from 350 survey respondents.

22k participants174 countries

Video, with commentary...

Instrument: SRL Questionnaire

• A measure of SRL for each respondent. Items were tailored to encourage participants to reflect specifically on their learning practices in the MOOC.

• Adapted from SRL in non-formal contexts instrument, previously validated (Fontana et al, 2015).

• This in turn was adapted from existing instruments: • MSLQ (Pintrich et al, 1991); MAI (Schraw & Dennison, 1994);

OSLQ (Barnard-Brak et al, 2010); LS (Warr & Downing, 2000); OS (Rigotti, Schyns & Mohr, 2008).

• Instrument available from figshare: http://figshare.com/articles/SRLMQ/866774

SRL Profiles

F1 S

elf-e

fficac

y

F2 G

oal S

ettin

g

F3 T

ask I

nter

est V

alue

P1 Ta

sk st

rate

gies

etc.

P2 Hel

p-se

ekin

g

P3 In

tere

st Enh

ance

men

t

SR1 Sel

f-eva

luat

ion

SR2 Sel

f-sat

isfac

tion

-3.00

-2.00

-1.00

0.00

1.00

2.00

PL-MOOC 213

Instrument: Semi-structured interview

• Explored various aspects of MOOC learning, structured around SRL sub-processes including self-efficacy, goal-setting and learning and task strategies, as well as patterns of help-seeking.

• Available from figshare: • http://

figshare.com/articles/Interview_Script_SRL_in_Massive_Open_Online_Courses/767290

• 5

••2

• 6

•••

•

•

•

•••

••

•

•

•3

••

•

•

•

Findings

Sub-process High group Low groupGoal setting detailed, learning/mastery goals set, emotionally

invested, and focused on role or careergoals, if set, were typically focused on participation.

Self-efficacy clear and detailed descriptions demonstrating individual responsibility

less detailed descriptionsalmost half indicated low self-efficacy.

Learning and Task

strategies

note taking standardactive engagement, most did not change approach (did not feel the need to change),

minority made active decision to change based on time pressures.

only a minority took notesmore passive in approachalmost half changed approach as original approach had been ineffective,

remainder had faced challenges but not changed: citing time pressures as a barrier (as opposed to a driver for change)

Help-seeking overwhelmingly positive about the benefits of learning from others.

almost half lurkersremainder active and positive about participating in discussion forum

mixed view of benefits from learning from others. three quarters lurkers. remainder negative about participation – primarily due to poor experiences in this MOOC.

SRL Profiles

F1 S

elf-e

fficac

y

F2 G

oal S

ettin

g

F3 T

ask I

nter

est V

alue

P1 Ta

sk st

rate

gies

etc.

P2 Hel

p-se

ekin

g

P3 In

tere

st Enh

ance

men

t

SR1 Sel

f-eva

luat

ion

SR2 Sel

f-sat

isfac

tion

-3.00

-2.50

-2.00

-1.50

-1.00

-0.50

0.00

0.50

1.00

1.50

2.00

PL-MOOC 213

‘Low Self efficacy:I hoped I can get the certificate, but I found it quite difficult for me.

I tried to get through the course. Well because of my work I don’t have very much time and so I may not achieve my original goal. When asked whether she takes notes (learning and task strategy): Not in this course. Sometimes I will consult my text book that I have.

SRL Profiles

F1 S

elf-e

fficac

y

F2 G

oal S

ettin

g

F3 T

ask I

nter

est V

alue

P1 Ta

sk st

rate

gies

etc.

P2 Hel

p-se

ekin

g

P3 In

tere

st Enh

ance

men

t

SR1 Sel

f-eva

luat

ion

SR2 Sel

f-sat

isfac

tion

-3.00

-2.50

-2.00

-1.50

-1.00

-0.50

0.00

0.50

1.00

1.50

2.00

PL-MOOC 152

Self-efficacy:I’m sure after this course I’ll be much better in dealing with my daily job tasks.

Help-seeking:So if something is not clear for me or something I need to understand I check the ongoing discussion related to this issue.

Strategic (learning and task strategies):When I’m studying in the MOOC I get very concentrated on the video content and the homework content and the assignments and whatever resource is needed to provide these assignments.

I don’t distract myself much more because of the time constraints.

SRL Profiles

F1 S

elf-e

fficac

y

F2 G

oal S

ettin

g

F3 T

ask I

nter

est V

alue

P1 Ta

sk st

rate

gies

etc.

P2 Hel

p-se

ekin

g

P3 In

tere

st Enh

ance

men

t

SR1 Sel

f-eva

luat

ion

SR2 Sel

f-sat

isfac

tion

-3.00

-2.50

-2.00

-1.50

-1.00

-0.50

0.00

0.50

1.00

1.50

2.00

PL-MOOC 334

Help-seekingI’ve never really been a study group person, I’ve always been a study group person leader, I’ve always kind of worked with them to help them. So it’s hard for me to…I haven’t made any friends in class! 

If you learn from other people who don’t know what they’re talking about you could teach yourself the wrong thing. … I read them but I take them with a grain of salt, I’m like ‘I don’t know if this person knows what they’re talking about’.

I don’t interact probably as much as I could.

Conclusions and Reflection

Conclusions

• Individuals behaved in different ways in the MOOC, • This is in part due to their ability to self-regulate aspects of

their learning,• We can use profiles as an indicator of an individual’s

strengths and weaknesses.

Reflection: Limitations

• Small sample,• inherent in qualitative research.

• Limited range of SRL ability,• all participants were self-regulating their learning to a significant

degree. Broad variability of other factors (e.g. motivation, experience f online learning) within sample.

• Lack of external measure of success• Difficult to link behaviour and performance.

• Profiles more useful for extremes and atypical patterns • Refine the instruments to make them more

informative/sensitive.

Reflection: Implications

Can profiles be helpful as a tool to help learners and providers• Providers can understand the skills and gaps in their

learners, designing environments and tasks that cater to the range of needs.

• Individuals can be encouraged to reflect on their learning, developing greater awareness of their learning needs and strengths and weaknesses.

Reflection: Future Work

• Study different MOOC contexts,• to see if our observations are generalisable.

• Link with completion and other quantitative data• to strengthen evidence and understand the impact of different

learning strategies

• Perform longitudinal studies,• To see the impact of MOOC learning on practice

• Develop Tools based on the SRL profiles• To help learners self-diagnose their strengths and weaknesses

SRL profiles: OU

Thank youColin MilliganCaledonian AcademyGLASGOW CALEDONIAN UNIVERSITYGlasgow, SCOTLAND

colin.milligan@gcu.ac.uk@cdmilligan

Slides available from: http://figshare.com/preview/_preview/1526107

This work was funded by the Bill & Melinda Gates Foundation. Thanks to Obiageli Ukadike at edX/HarvardX for access and assistance, and Lou McGill for conducting interviews.

Allison LittlejohnInstitute of Educational TechnologyOPEN UNIVERSITYMilton Keynes, ENGLANDAllison.littlejohn@open.ac.uk@allisonl

Extras

ReferencesAzevedo, R., & Cromley, J. G. (2004). Does training on self-regulated learning facilitate students' learning with hypermedia?

Journal of Educational Ppsychology, 96(3), 523.

Bernacki, M. L., Aguilar, A., & Byrnes, J. (2011). Self-regulated learning and technology-enhanced learning environments: An opportunity propensity analysis. In G. Dettori and D. Persico (Eds.), Fostering self-regulated learning through ICT (pp. 1-26). Hershey, PA: IGI Global Publishers.

Chang, M. M. (2005). Applying self-regulated learning strategies in a web-based instruction—an investigation of motivation perception. Computer Assisted Language Learning, 18(3), 217-230

Chang, C-C, Tseng, K-H, Liang, C., & Liao, Y-M (2013) Constructing and evaluating online goal setting mechanisms in web-based portfolio assessment systems for facilitating self-regulated learning. Computers and Education 69, 237-249

Cho M-H & Kim, B. J. (2013) Students self-regulation for interaction with others in online learning environments. Internet and Higher Education 17, 69-75.

Cho, M-H., & Jonassen, D. (2009). Development of the human interaction dimension of the Self-Regulated Learning Questionnaire in asynchronous online learning environments. Educational Psychology, 29, 117–138.

Hu, H., & Gramling, J. (2009). Learning Strategies for Success in a Web-Based Course: A Descriptive Exploration. Quarterly Review of Distance Education, 10(2), 123-134.

Pintrich, P. R. (1999). The role of motivation in promoting and sustaining self-regulated learning. International Journal of Educational Research, 31, 459–470.

Zimmerman, B. J. (2000). Attaining self-regulation: a social cognitive perspective. In M. Boekaerts, M. Zeidner, and P.R. Pintrich (Eds.), Handbook of self-regulation (pp13-39). Academic Press, San Diego, CA.

Further ReadingBackground ReadingAbrami, P. C., Bernard, R. M., Bures, E. M., Borokhovski, E., & Tamim, R. M. (2011). Interaction in distance education and

online learning: Using evidence and theory to improve practice. Journal of Computing in Higher Education, 23(2-3), 82–103. doi:10.1007/s12528-011-9043-x

Anderson, T. (2013). Promise and/or peril: MOOCs and open and distance education. Commonwealth of Learning. Retrieved from http://www.col.org/SiteCollectionDocuments/MOOCsPromisePeril_Anderson.pdf

Breslow, L., Pritchard, D. E., DeBoer, J., Stump, G. S., Ho, A. D., & Seaton, D. T. (2013). Studying learning in the worldwide classroom: Research into edX’s first MOOC. Journal of Research & Practice in Assessment, 8, 13–25.

Daniel, J. (2012). Making sense of MOOCs: Musings in a maze of myth, paradox and possibility. Journal of Interactive Media In Education, 3(0). Retrieved April 8, 2015, from http://jime.open.ac.uk/article/view/2012-18/466

Gasevic, D. Kovanovic, V., Joksimovic, S., & Siemens, G. (2014) Where is Research on Massive Open Online Courses Headed? A Data Analysis of the MOOC Research Initiative. International Review of Research in Open and Distance learning, 15 (5). Retrieved 8 April 2015, from http://www.irrodl.org/index.php/irrodl/article/view/1954/3099/

Kizilcec, R. F., Piech, C., & Schneider, E. (2013). Deconstructing disengagement: Analyzing learner subpopulations in massive open online courses. In Proceedings of the Third International Conference on Learning Analytics and Knowledge (pp. 170–179). New York, NY, USA: ACM. Retrieved 8 April 2015, from: http://dl.acm.org/citation.cfm?id=2460330

Margaryan, A., Bianco, M., & Littlejohn, A. (2015). Instructional quality of Massive Open Online Courses (MOOCs). Computers & Education, 80, 77-83.

Milligan, C., Littlejohn, A., & Margaryan, A. (2013). Patterns of engagement in connectivist MOOCs. Journal of Online Learning & Teaching 9 (2), 149-159.