Seminario eMadrid 2015 05 22 (UAM) Su White - Incorporando MOOCs en la formación presencial

@suukii http://blog.soton.ac.uk/mobs/home/

Bending MOOCs into face to face teaching

Su WhiteUniversity of Southampton, UK

21/05/15


Our MOOCsOceans Shipwrecks

Developing your research project

Portus Web Science Digital marketing

ContractManagement Waterloo

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Learning by doing

• Desire• Expertise

ambition

• Deadlines• Conceptualiation

reality • Students• Understanding

realisation

• Refinements• Optimisation

Reflection

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Teaching (& blending)

Orchestrated• Preparation for

– Instruction– Discussion– Structured reflection– Independent learning

• Vehicle for– Enhancing motivation– Sustaining motivation

Enviornmental• Practice or rehearse

– Skills– Argumentation

• Revise/prepare• For tests and examinations• After a break (vacation)• Contextual reminder

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Blending (and teaching/learning)

purposeful• Flipped classroom• Structured exercise

– Revise for test– Consult for extended writing– Make the basis of class

discussion– Use as an exemplar of

independent research

environmental• Let the learners decide

– Access as a resource– Available if wanted

• Independent or semi-independent learning

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Our MOOCsOceans Shipwrecks


Portus Web Science Digital marketing

ContractManagement Waterloo

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Web Science

• Flipped/blended– Masters– Undergraduate– Generic

• Personal blending– Review of approaches

• Revisions in pipeling

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Oceans

• Resources– Outreach– Public Awareness

• Classroom– Motivation

• Educational Development– Exemplars

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Digital marketing

• Courses– Masters– Undergraduate

• After the event using archives of discussion

• Extension of existing face to face methods

• Next time– In parallel

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• Began as outreach/load balancing– Augmenting existing

support– Used for recruitment

• Individual Integrated– Generic – all levels

• Independent– appropriated

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Contract management

• Courses• Generic business– Illustrative

• Potential - clients• Professional

development

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Portus

• Courses– Summer schools– Undergraduate– Masters

• Application– Virtual fieldwork– Flipped classroom

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Shipwrecks

• Public Awareness• Courses– Marine archeology

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Mini MOOC

• Next off the stock• Developed by the library• Using/showcasing archive

collection• Courses

– Nothing planned.. But– Introduction to archives for

history students at all levels

• Public awareness– Same principle

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Learning and change

• Constructive alignment– Learning in the most

appropriate way– Matching activities with

valued skills, knowledge and understanding

– Trust the subject expert

• Pace and scaffolding• Keeping the learner on

task• Modelling (learning)

behavioursWe may change our use depending on the stage of learning

But also trust the learners to decide21/05/15


Trust

• Trust humans to see insights

• Academics are smart• They like to be efficient• Change needs trust to

happen– Coffee room

conversations – I trust my friends

– Reputation can work too

• Like teachers– Student understanding

evolves over time– Understandings can

develop– There can be

understanding memes– There is value in

modelling

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Final thoughts

– Let the learners decide what is valuable

– Academics can’s unlearn– All students are on

different paths

• Thank you • Any Questions??

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FOLLOW WHAT WE DO

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Curation activityMendeley Group:● Over 300 academic sources

related to MOOCs● All tagged and classified● Open Group

● you can join● You can follow

Scoop.it page● Daily curation● Grey Literature● MOOC news and journalistic

articles

http://www.scoop.it/t/moocs-and-heis

http://www.mendeley.com/groups/2754851/mooc-observatory/

A work in progress


Other groups

FLAN

• FutureLearn Academic Network

• Regular meetings• Some PhD students – across

the UK

Collaborations• Southampton• UEA• Reading

– Sharing data– Research roadmap– Bidding for funding

e.g. Leverhulme, ESRC

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Not used – for ref

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Courses and Runs

Some figures: a “quiet” MOOC

Some figures: A busy MOOC

Source:

Our Courses


MOOCs• Researching

– Behaviours, beliefs and understandings of MOOCs

• Building– a collaborative network of labs

and researchers

• Creating– tools to automatically and

efficiently log and annotate MOOC related artefacts

• Assembling– a definitive historic archive for

current and future researchers

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Building a toolkit:tools, methods and methodologies

DataWilde.g.

twitter

Manual to auto’

Processing

NVivoWorldWare

Custom

• Logging– the ‘What? When? Where?

Why? and How?’ of MOOC activity

• Charting– the growth and evolution

of MOOCs• Developing

– expertise in MOOC data collection and analysis;

• Tracking – platforms and technologies

Moving from manual towards automatic21/05/15


Questions

Stakeholders:• What are the

motivations and rewards for academics running MOOCs

• How are academics integrating MOOCs with their face to face teaching

• What are the models for harnessing existing MOOCs to bring additional expertise into the classroom?

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Questions

Learners:• How can groupwork insights

and learning analytics be combined to enhance the learners’ exerience of MOOCs?

• What role can MOOCs play in enhancing employability of young people?

• What role do MOOCs play in enhancing digtial literacies?

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Researching

Learner experiences• learner engagement

and motivations• how MOOCs are

impacting recruitment on F2F courses

Hosting Experience• Moderating discussions

Stakeholders• Educator attitudes• Institutional motivationPotential• Blended MOOCs• Personalisation in

MOOCs • Affordances

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Perspectives

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Curating

Mendeley • publications collection

ScoopIt• Grey literature

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74 MOOC Datasets

FOR EACH OF OUR MOOC RUNS:● Comments● Enrolments● Peer Review Assignments● Peer Review Reviews● Question Response (quizzes)● Step Activity● Total Figures

MOOC Runs Datasets

2 14 + 4 surveys

3 21 + 6 surveys

2 14 + 4 surveys

2 14 + 4 surveys

1 7 + 2 surveys

1 7 + 2 surveys

1 7 + 2 surveys

24 Survey DatasetsFOR EACH OF OUR MOOC RUNS:● Entry Survey● Exit Survey

Data Analysis (some examples)

● Learner activity patterns● Text Mining● Network graphs from comment data● Comment classification● Step Completion Timings

MOOC/Learners network

Author: Graeme Earl

Learner Activity Patterns (comments per day/week)

Busy Mondays! End of Course (last mentoring day)

Learner Activity Patterns (comments per user)

N. of users

N. of Comments

Active social learners?

Highly active social learners?

How many of these completed the course?

Discussion generation analysisZeemap: place yourself in the world map

Most Popular task

Reflection step

Steps (x) by number of comments that they generate (y)

The ZeeMap

Twitter MOOC Data Analysis

‘dalmooc’ Twitter Seach NodeXL Graph/Tim O’Riordan ©2014/cc-by-sa 3.0

● Our MOOCs also generate data in other social media.

● This example is from our Digital Marketing MOOC.

● Learners were interacting with each other outside the Futurelearn Platfrom (Twitter in this case)

● We also have this dataset in our observatory.

Text mining of Portus MOOC comments● Undertaking primary research about development

and communication of archaeological knowledge (see next slide)

● Using concordance (AntConc), topic maps and other approaches to mine comments

● e.g. undertaking specific research such as examining the multisensory nature of creative writing on the course through co-occurrence of words (in this case “smell”)

Author: Graeme Earl

Training

● NVivo● Facilitation/Demonstration● Statistical Analysis (with R)● Visualisation methods● Text Mining