Observing learning activity

Laboratoire d'InfoRmatique en Image et Systèmes d'informationLIRIS UMR 5205 CNRS/INSA de Lyon/Université Claude Bernard Lyon 1/Université Lumière Lyon 2/Ecole

Centrale de Lyon

http://liris.cnrs.fr

OBSERVINGAN OPEN LEARNING PROCESS?

Alain MILLE

Lyon- 16/6/2014

Argument

Context : Massively OPEN Online Course

Observing (the learning process) for understanding and acting!

Learner(s)Tutor(s)Teacher(s)Designer(s)Researcher(s)

Constructing relevant knowledge From heterogeneous and evolving situationsFor very different skills and tasksFrom different sources!

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What’s the problem for a learner

The learner knows: What he/she does during the learning activity What are his/her learning goals (if any…) The context in which he/she does the activity

The learner does not know: The epistemological context of the lesson The didactical context The pedagogical context The implementation choices for the activity What are doing the others How to assess his/her level How to ask for help

?

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What’s the problem for a teacher

The teacher knows: The epistemological context of the lesson The didactical context The pedagogical context (The productions of the learner, if he/she can access to

them)

The teacher does not know: How the learner does the activity What is the goal of the learner What are the external educational resources of the

learner How the learner works with the others ...

?

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What’s the problem for a tutor

The tutor knows: The didactical context The pedagogical context The content of the forums, chats, blogs, …

The tutor does not know: How the learner does the activity What is the goal of the learner What are the external educational resources How the learner works with the others The epistemological context…

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What’s the problem for a designer?

The designer knows: The pedagocical context The general rules for Computer Human Interactions The logics of the proposed activity

The designer does not know: The learner experience of his/her design The real Information Architecture (including other tools

the learner uses) The way the learners are able to collaborate

?

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What’s the problem for a researcher?

The researcher knows: Different theories and methods according to his/her

speciality Different ontological context according to his/her speciality How to interpret relatively consistent data sets

The researcher does not know: How to normalize different data sets from different

platforms How to normalize different data from different learners on

the same platform How to assess the learning level when very different

learning goals are present and unknown How to study very dynamic and various learning situations

?

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How can they learn what they don’t know?

For the teacher, the designer, the tutor and the researcher:

All of them = ONE team DESIGN ORIENTED RESEARCH to share their knowledge

during the design activity, and to learn from each other

WWW

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How can they learn what they don’t know?

For the teacher, the designer, the tutor and the researcher:

All of them = ONE team DESIGN ORIENTED RESEARCH to share their knowledge

during the design activity, and to learn from each other

During the Mooc, learner activity is interpreted through :

The INTERACTION traces!

But, how to construct interpretation knowledge for such traces?

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What is an interaction trace?

We know that: A trace is constructed by an « agent » on the basis of

what can be « observed » in the environment of an activity

The question becomes: « What does it means « to observe »?

How does the process begin? How does the process end? Does it end?

How to understand what has been observed?

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Observing + understanding (1)

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Observing + understanding (2)

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Observing + understanding (3)

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2 interpretation paths = 2 # stories

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What is the true story?

The Fox knows (surely) / its versionThe Jay knows (if able to testify to…), probably another one version

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More formally…

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Modeled Trace

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Managing M-Traces (TBMS)

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http://liris.cnrs.fr/sbt-dev/tbs/doku.php?id=public:ktbs

Trace Based Management System (RDF lib)

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OBSERVING A MOOC

The learner get an ID and logs in (User-ID) From the platform (With an Open ID)

The learner selects a learning activity (Activity-ID) On the platform -> choosing a course (by defining its proper activity)

The learner asks to be traced His trace is identified by [User-ID]+[Activity-ID] His trace is stored in an independent repository, gathering

server information and client information The user can see and manage his M-Trace

Learners can “give” their traces to the teacher, manager of the learning activity for tutoring, managing, …, other purposes

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Illustration (Lyon’s experiment)

Platform DB

PlatformListener

Logs

U_1

Platform page

Browser(client)

PlatformServer

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Illustration (what we do/server side)

Platform DB

PlatformListener

Logs

U_1

Platform page

Browser(client)

PlatformServer

kTBS– users/ (platform)

+ trace listener

Trace BasedManagement

System

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Illustration (what we did/server side)

Platform DB

PlatformListener

Logs

U_1

Platform page

Browser(client)

PlatformServer

kTBS– users/ platform

+ trace listener

Trace BasedManagement

System

BrowserExtension

+ browser listener

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Illustration (trace based assistance/ navigator side)

Platform DB

PlatformListener

Logs

U_1

Platform page

Browser(client)

PlatformServer

kTBS– users/ platform

+ trace listener

M-traceAssistant

BrowserExtension

Browser (client) parameterizedObsels collection

kTBSRequests

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What does it change? (1)

1) Augmented Reflexivity on the Learning Activity

Both server and navigator events together

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What does it change? (2)

2) Indicators engineering

Designing Indicators-> trace transformation

Getting, sharing indicators-> store of indicators

Computing indicators-> new transformed traces

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What does it change? (3)

3) Collaborative interpretation of the learning activity

Primary trace (trace model + obsels)

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What does it change? (3)

3) Collaborative interpretation of the learning activity

Transformed trace (shared with the teacher)

A

A

Primary trace (trace model + obsels)

Transformed trace (for sharing with the teacher)

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What does it change? (3)

3) Collaborative interpretation of the learning activity

Transformed trace (for sharing with a peer)

Transformed trace (shared with the teacher)

A A

A

Transformed trace (shared with a peer)

A B

Primary trace (trace model + obsels)

Transformed trace (for sharing with the teacher)

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What does it change? (3)

3) Collaborative interpretation of the learning activity

A A

A

A B

Primary trace (trace model + obsels)

Transformed trace (for sharing with the teacher)

Transformed trace (for sharing with a peer)

Transformed trace (shared with the teacher)

Transformed trace (shared with a peer)

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What does it change? (4)

4) Explaining the interpretation

o1, o2, o3, …, ot, …, ol

o1, o2, o3, …, ot, …, om

o1, o2, o3, …, ot, ok…, on

T2

T0

tb

ta

T1

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What does it change? (4)

4) Explaining the interpretation

o1, o2, o3, …, ot, …, ol

o1, o2, o3, …, ot, …, om

o1, o2, o3, …, ot, ok…, on

Why do you say that Ot is true in T2?T2

T0

tb

ta

T1

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What does it change? (4)

4) Explaining the interpretation

o1, o2, o3, …, ot, …, ol

o1, o2, o3, …, ot, …, om

o1, o2, o3, …, ot, ok…, on

Why do you say that Oi is true in T2?T2

T0

tb

ta

T1

Because of tb(o2,oi)/T1

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What does it change? (4)

4) Explaining the interpretation

o1, o2, o3, …, ot, …, ol

o1, o2, o3, …, ot, …, om

o1, o2, o3, …, ot, ok…, on

Why do you say that Oi is true in T2?T2

T0

tb

ta

T1

Because of tb(o2,oi)/T1

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What does it change? (5)

5) Building normalized traces from different sources

Log trace (EDx)

Primary-Trace (Edx) Primary-trace (Claroline) Primary-trace (Coursera)

Data (EDx)Log trace (Coursera)

Data (Coursera)Log trace (Claroline)

Data (Claroline)

MoocDB Trace (any platform)

Gathering information

Gathering information

Gathering information

Transformed-Trace Transformed-TraceTransformed-Trace

Transformed-Trace

Transformed-Trace

Transformed-Trace

Transformed-Trace

Transformed-TraceTransformed-Trace

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What does it change? (…)

6) Replay in a new context7) Building patterns of good practices8) Mapping Trace Models to ontologies

6-1) To build ontologies from shared experience6-2) To build Trace Models according to a precise semantics9) Discovering « learning patterns »7-1) Batch -> preparing traces to be mined7-2) Interactively -> for diagnosis and remediation10) Building automata from traces8-1) Interactively to manage missing data8-2) For simulation, prediction, …

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What does it change? -> the web!Think WEB

Any interesting thing should be accessed through an URL ID information Traces Store of indicators Educational Resources …

Learner dashboard = set of widgets conected together Linked data

Think Semantic Web Adding semantics to the description of the activity Enabling reasoning on the activity Making possible trace models mapping…

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Main challengesTechnical challenges

Performance (RDF) -> Web Semantic question (*) Privacy (Auth2) (*) Normalization?

Research challenges User experience (traces) (*) Capitalizing and sharing experience (level, protocols,

mechanisms, …)(*) Fine grained sharing -> new privacy questions

« Interactive » learning analytics (*) Managing negociations during the interpretation process

How to assist the collaborative interpretation between different actors / traces?

Connecting local semantics (trace model) to shared semantics (ontologies)

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Other readings and references

Research questions and methods on the MOOCs What's new? (with surveys’ references)

Traced Experience Based Reasoning (other examples of using M-Traces for learning)

https://www.zotero.org/groups/coat_cnrs (a collaborative bibliography)

The GitHub of the kTB(M)S

The GitHub of TraceMe

The publications of SILEX

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One other story?

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Discussion…

Thank you for your questions!

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Illustration with « TRACE-ME » (1)

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Illustration with « TRACE-ME » (2)

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Illustration with « TRACE-ME » (3)

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Illustration with « TRACE-ME » (4)

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Illustration with « TRACE-ME » (5)

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Illustration with « TRACE-ME » (6)

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Illustration with « TRACE-ME » (7-1)

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Illustration with « TRACE-ME » (7-2)

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Illustration with « TRACE-ME » (7-3)

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Illustration with « TRACE-ME » (8)

https://chrome.google.com/webstore/detail/moluti/eibmcehgadjapieaijmmdbgoblacgpii

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Illustration with « TRACE-ME » (9-1)

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Illustration with « TRACE-ME » (9-2)

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Illustration with « TRACE-ME » (9-3)

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Illustration with « TRACE-ME » (9-4)

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Illustration with « TRACE-ME » (10-1)

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Illustration with « TRACE-ME » (10-2)