Learning Networks

http://www.flickr.com/photos/lifeinverted/5651315924/

E-Learning 3.0 anyone, anywhere, anytime, and AI

SPeL 2011: International Workshop on Social and Personal Computing for Web-Supported Learning Communities

Neil RubensActive Intelligence GroupKnowledge Systems Lab 岡本/植野

University of Electro-CommunicationsTokyo, Japanhttp://ActiveIntelligence.org

Evolution of eLearning: eLearning 1.0eLearning uses technology to enhance Learning

To understand where the eLearning might be going, we need to take a quick look at where it's been

‣ eLearning 1.0:

‣ Web 1.0:

‣ reading: content became easily accessible

‣ logging: user’s activities could be logged and analyzed

‣ Learning Theories:

‣ Behaviorism: learning is manifested by a change in behavior, environment shapes behavior, contiguity

‣ Cognitivism: how human memory works to promote learning

Evolution of eLearning: eLearning 2.0‣ eLearning 2.0:

‣ Web 2.0:

‣ writing: anybody can easily create content (e.g. blogs, wiki, etc.)

‣ socializing: interaction is easy (e.g. facebook, twitter, etc.)

‣ Learning Theories:

‣ Constructivism: constructing one's own knowledge from one's own experiences (enabled through writing)

‣ Social Learning: people learn from one another (enabled through socializing)

http://www.flickr.com/photos/christian78/2960519381

eLearning 3.0?

Evolution of Systems

E-Learning 2.0

HTML- or Text

Multimedia

Databases/RSS

Social/Communicative

Integrated

Intelligent

Static

Interactive

Dynamic

Collaborative

Personal

Contextual

Connected

E-Learning 1.0

Greller, 2011

Review of Predictions: eLearning 3.0

consume(transfer(transmit(cer.fy(

create,(form,(share(par.cipate((reflect(evidence(

socialise(connect(create((together)(collaborate(recognise(

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Greller,(2011(Greller, 2011

Review of Predictions: eLearning 3.0

Review of Predictions: eLearning 3.0�

RIS, www.ris.uvt.ro - 15

e-Learning 1.0 e-Learning 2.0 e-Learning 3.0

Meaning is Dictated Socially constructed Socially constructed and Contextually reinvented

Technology is Confiscated at the classroom door (digital refugees)

Cautiously adopted (digital immigrants)

Everywhere (ambient, digital universe)�

Teaching is Teacher to student Teacher to student and student to student (progressivism)

Teacher to student, student to student, student to teacher, people-‐technology-‐�people (co-constructivism)

Classrooms are located

In a building (brick)

In a building or online (brick and click)

Everywhere (thoroughly infused into society: cafes, bowling alleys, bars, workplaces, etc.)

Teachers are Licensed professionals

Licensed professionals Everybody, everywhere

Hardware and software supply

Are purchased at great cost and ignored

Are open source and available at lower cost

Are available at low cost and are used purposively

Industry views graduates as

Assembly line workers

As ill-‐prepared assembly line workers in a knowledge economy

As co-‐workers or entrepreneurs

(adopted from Moravec 2009: 33)

Following this chart one can see that within e-Learning context technologies change the classroom dynamic, main learning stakeholders’ roles and responsibilities, students’ expectations for learning. However, the transformation in meaning generation presents the most important shift observed through these changes.

Wheeler emphasizes that „If Web 1.0 was the ‘Write Web’ and Web 2.0 is the ‘Read/Write Web’, then Web 3.0 will be the ‘Read/Write/Collaborative Web’” (ibid.). But we think that Web 3.0 will be ‘Read/Write/Collaborative/Intelligent Web’ when the machine facilities the human thinking greatly and Twitter must be an effective tool in this process due to a number of its communicative conceptual characteristics as a means of communication; a place to share and consume information, a new real-time search engine, a service for Web users, a platform o debate, a tool for listening and analyzing, a perfect traffic generator, an excellent means to meet new people and create new connections, and talk about what you are doing right now (Pouy 2009: 22).

Pouy declares that Twitter is a new means of communication because it allows for analyzing people’s thoughts, perceptions and interests in real time. He thinks that it is the only real-time search engine currently available. Twitter is growing exponentially and can be a model for other platforms. Since it has an exemplary acceleration process allowing for relaying new information fast, re-tweeting vs. content creation Twitter is certainly not a tool that is massively used by the general public, such as Facebook or YouTube, but due to its qualitative audience, where users also are opinion leaders or potential ones, namely Twitter can be used as a sophisticated means or organizing platform for all types of organizational communications (ibid: 39).

The question is posing „What is the main goal of using Twitter in e-learning 3.0?”

We think Twitter will bridge or facilitate the transition between e-Learning 2.0 to 3.0.

(Ogorshko, 2011)

Our Predictions: eLearning 3.0Typical predictions of eLearning 3.0:

Learning -> Technologies

Limitation: Needed technologies may not be available

Our Predictions:

Technologies -> Learning

‣ What new technologies will become available?

‣ What aspects of Learning Theories could be activated by using and extending new technologies?

http://etc.usf.edu/clipart/28000/28015/tower_pisa_28015.htm

Why do we need eL 3.0?Whats Wrong with 2.0?

Challenges: Is this Social?

(S. Goel, et al. 2011)

People Talking Social

6=

;

1

Limitations: Broken Knowledge Cycle‣ Problem: The current cycle of knowledge creation/utilization is inefficient !

‣ large portion of created content is never utilized by others* only 0.05% of twitter messages attracts attention (Wu et. al., 2011) only 3% of users look beyond top 3 search results (Infolosopher, 2011)

‣ large parts of created contents are redundant (Drost, 2011)

‣ Peak Social – the point at which we can gain no new advantage from social activity (Siemens 2011)

*there are some personal benefits e.g. externalization, crystallization, etc.Knowledge

utilize

create

Redundant

Novel

U0lized

Existing Knowledge

InformationOverload

Web 3.0

http://www.technodiscoveries.com/2010/01

Radar Networks & Nova Spivack, 2007

Web$3.0$Seman&c(Web(

Web$1.0$The(Web(

Web$x.0$Meta(Web(

Web$2.0$Social(Web(

Degree(of(Social(Connec&vity(

Degree(of(Informa&

on(Con

nec&vity(

Connects$informa6on$ Connects$people$

Connects$knowledge$ Connects$intelligence$

Steve(Wheeler,(University(of(Plymouth,(2011(

AI is poised to Play a Major Role‣ AI has been successful in ‘restricted’ domains e.g. chess

‣ In more open domains (e.g. eLearning) success of AI has been limited:

‣ More Complexity -> More Parameters -> More Data, More Computational Resources

‣ Large scale data and computational resources have not been easily available

‣ Things are changing:

‣ Large-scale data is becoming available (BIG/Open data)

‣ Large-scale Computational resources are becoming accessible (cloud computing)

* more specifically Machine Learning

BIG/Open data‣ Open data: freely available to everyone to use and republish as they wish;

e.g. wikipedia, twitter, data.gov, etc.

‣ Big data:

‣ amount of data generated is growing by 58% per year (Gantz, 2011)

‣ pieces of content shared on Facebook 30 billion/month (McKinsey, 2011)

‣ Big Data in eLearning

‣ KDD Cup 2010: 36 Million ITS records (PSLC, CMU)

‣ Learning Dataset: > 30 Million tweets (Rubens & Louvigne et. al., 2011)

‣ includes data on how users learn outside of the classroom (not typically available)

Data ScienceLarge data sets can potentially provide a much deeper understanding of both nature and society. Social scientists are getting to the point in many areas at which enough information exists to understand and address major previously intractable problems. (Science, 2011)

‣ Traditional:

‣ Hypothesis -> Model -> Validation (data)

‣ Limitations

‣ Sometimes is disconnected from the reality

‣ Validation data is often biased by the initial hypothesis

‣ Time Consuming: model must be explicitly programmed

‣ Data-driven

‣ Data -> Model

‣ Advantages

‣ model is constructed automatically by utilizing AI methods

‣ large number of dimensions could be analyzed

‣ can handle complexity well

Learning Theories

(Ireland, 2007, link)

Learning Analytics‣ Education is, today at least, a black box. We don't really know:

‣ How our inputs influence or produce outputs.

‣ Which academic practices need to be curbed and which need to be encouraged.

We are essentially swatting flies with a sledgehammer and doing a fair amount of peripheral damage.

‣ Once we better understand the learning process — the inputs, the outputs, the factors that contribute to learner success — then we can start to make informed decisions that are supported by evidence.

(Siemens, 2011)

Analysis of Large-scale Distributed Collaborative LearningAudi reached out to public to help to define what Progress IS.

What is Progress: faster, cheaper, eco, comfortable, beautiful?

People could collaborate, discuss, and vote for each others definition of progress.> 100,000 tweets

In collaboration with:

eLearning 3.0

‣ Automatically discover new Learning Models

‣ by applying AI methods

‣ to BIG data