Support for Resource-Based Learning on the Internet

GKEL___Support for RBL on the Internet___v.12___2011_MA.ppt

KOM - Multimedia Communications LabProf. Dr.-Ing. Ralf Steinmetz (Director)

Dept. of Electrical Engineering and Information TechnologyDept. of Computer Science (adjunct Professor)

TUD – Technische Universität Darmstadt Rundeturmstr.10, D-64283 Darmstadt, Germany

Tel.+49 6151 166150, Fax. +49 6151 166152 www.KOM.tu-darmstadt.de

Diplom.-Inform. Mojisola Anjorin

[email protected] Tel.+49 6151 166160

03. May 2011© 2011 author(s) of these slides including research results from the KOM research network and TU Darmstadt. Otherwise it is specified at the respective slide

Support for Resource-Based Learning on the Internet

Resource Based Learning

Social Search Model

CROKODIL

Recommendation Systems

Activity Ratings

Semantic Tagging

Tag Types

Personal Resource Network

Community Resource Network

Collaboraive Filtering

Explanations

Feedback Loop

Ranking Recommendation

Results

Thursday, May 19, 2011Welcome to my talk on “Support for Resource-Based Learning on the Internet”.

KOM – Multimedia Communications Lab

Resource-Based Learning

2

Thursday, May 19, 2011

Resource-based learning (RBL) means learning by using resources found on the Web such as on blogs, YouTube, Wikipedia, in forums or searching via Google. This form of learning started about 10 years ago. Even school pupils are now asked to prepare a homework using information found on the Internet. As we can see, search is an important part of RBL.


Types of Search Behavior

Informational Navigational Transactional

A. Broder, 2002: A Taxonomy of Web Search

59.3% 28% 12.7%

3

Thursday, May 19, 2011Search on the Web has been classified by Information Management scientists. For example, Broder in 2002 classifies search as Transactional search, where a user goes directly to a website like Amazon and buys a book. Navigational like when a user goes directly to a known website like Spiegel Online to read the news. Informational search however is more a browsing or a search for information like googling to find out the meaning of folksonomy. The most often performed search is informational search and this fits to the RBL form of searching.


Social Search Model

Before SearchGather

Requirements

Formulate Representation

Social Interactions

Social Interactions

During Search Foraging

Sensemaking

Social Interactions

Social Interactions

After Search

Organize Distribute Do Nothing

Social Interactions

4

B.M.Evans & E.H.Chi, 2009: An elaborated model on social search

Thursday, May 19, 2011The social search model from Evans and Chi describes the search process not as a solitary act but rather as a social process. In the Before Search stage, the reasons for the search and what to be searched for are determined. For example, a school pupil gets the assignment to present a talk on a topic in the news. The pupil probably goes on SchülerVZ and asks others in her class what they will be presenting and asks where they are searching for information. During the search, the user browses several web pages going from one page on to the other and trying to find information which is relevant to the topic...this is called foraging and sensemaking. In the after search phase, the user saves the found pages and can send these by email to others or prints these out or hopes to use these later.


During Search Foraging

Sensemaking

Add Resources to Activity

Tagging

Recommendations

Before SearchGather

Requirements

Formulate Representation

Create Activity TreeChat

Form Groups

Text Messages

After Search

Organize Distribute Do Nothing

Browse Knowledge Network

Activity Experiences

TaggingRecommendations

ChatText Messages

5

Thursday, May 19, 2011CROKODIL is a BMBF project with the aim to provide support for RBL in a learning community. I have mapped the activities in CROKODIL to the social search model to classify the features offered. In the Before Search stage, the learners can create an activity, like the assignment to prepare a presentation, groups are formed having this common assignment or having similar tasks. The interaction here is supported on the platform with a chat and text messages. During the search, resources found on the Web are attached to the activities created before the search, recommendations are also made by the system informing about similar resources already stored by others on the platform. The learner can also give tags to these resources to use these to classify the resource in order to find the resource later on. After the search, the learner can browse the knowledge network and see what others have stored, find what other resources have the same tags...add new tags to the resources, recommendations are made showing similar resources from other activities or users. Finally, the learner writes about her experiences when working on the activity as a form of reflection when the activity is completed. In this stage, the learner can again contact other learners via the chat or text message functionality on the platform.

KOM – Multimedia Communications Lab 6

Thursday, May 19, 2011CROKODIL has a platform, where learners can set up a profile, set up friends or groups, create activities, view their resources and read their text messages. The chat function is in the upper right hand corner and the tags used are shown down in the right hand lower corner. The platform is used for the before and after stages of searching.

KOM – Multimedia Communications Lab 7

Thursday, May 19, 2011During search, CROKODIL offers a Firefox addon which is installed in the browser and shows the activity tree. A section of text on the website is highlighted and pulled across to the addon, where it is attached to the activity which is currently activated. When saving, tags can be attached to the resources.


Semantic Tagging

Japan

News

Nuclear

EnergyApril

2011

8

Thursday, May 19, 2011In CROKODIL, several concepts are implemented such as the pedagogical concept with the activities and the reflection of the experiences made. We also have implemented the concept of semantic tagging. For example I am a learner in CROKODIL, I find a news article about nuclear energy and tag this with News, I read this in April 2011, the disaster happened in Japan and it’s about a nuclear energy disaster.

Resource

my resource

has tagmy tag

Tag



April

2011NewsJapan

Nuclear

Energy

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Thursday, May 19, 2011This forms a structure: me, a learner, having a resource, having my tags which tag my resource. This forms a personal resource network or a personal knowledge network.

Resource

my resource

has tagmy tag

Tag


Personal Resource Network (Personomy)

10

Thursday, May 19, 2011Viewing this abstractly, this forms a graphical structure...objects form the nodes and the relationships the edges between the nodes. This is known as a personomy.

Resource

my resource

has tagmy tag

Tag


April

2011NewsJapan

Nuclear

Energy

Semantic Tagging?!

11

Thursday, May 19, 2011So why do we call this semantic tagging? I have shown here the tags having different colors, this shows a sort of classification...Nuclear energy describes the topic of the news article, it is a news article as the green tag shows, the location of the nuclear energy disaster was in Japan and this event happened around April 2011


CROKODIL Tag Types

Resource

has tag

Location Tag

Event Tag

Topic Tag

Type Tag

has tag

has tag

has tag

Person Tag

Taghas tag

has tag

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Thursday, May 19, 2011In CROKODIL, we have these 6 tag types, the generic tag having no type, a location tag, a type tag, a topic tag, an event tag and a person tag for example Angela Merkel.

Resource

Topic TagResource

Type Tag owns resource

owns tag

has taghas tag

has friendowns resource

owns tag

has tag


Wikipedia


Crokodil

Project

13

Thursday, May 19, 2011So back to the graphical structure which gets built...when several learners are on the platform and they store resources and tag them, resources could be connected by the same tag. This is called a community resource network or Community knowledge network.

Resource

Topic TagResource


owns tag

has taghas tag

has friendowns resource

owns tag

has tag


Community Resource Network (Folksonomy)

14

Thursday, May 19, 2011This builds such a graphical structure which combines individual personomies to build a folksonomy.

Resource

Groupbelongs to

Sub-Activity

has activity

has resource

Activity

has sub-activity

belongs to

has activity

owns resource


CROKODIL Groups and Activities

Prepare GKEL Presentation

Participate in GKEL Activities

15

Thursday, May 19, 2011In CROKODIL we additionally have groups and activities. For example the activity GKEL activities belongs to the group GKEL and I just prepared a GKEL presentation.


CROKODIL Groups and Activities

Resource

Groupbelongs to

Sub-Activity

has activity

has resource

Activity

has sub-activity

belongs to

has activity

owns resource

16

Thursday, May 19, 2011Abstractly this can be viewed as a folksonomy with additional social relationships and activities to give pedagogical structure to the knowledge network.With these structures, information about other learners or connected activities can be inferred by traversing the relationships between nodes. One challenge here is identifying what is important especially when the network grows to a larger network over time. Another challenge is finding connections between sub-graphs where no structural connection exists.


Recommender Systems

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Thursday, May 19, 2011We all know recommender systems such as in Amazon. Recommendations help to identify what

is important - as well as what could be new and interesting


Recommender Systems

Furniture

Chair

Knowledge-Based

Collaborative-Filtering

Content-Based

Hybrid

Structure-Based

Resource

my resource

has tag

my tag

Topic Tag

my friend

Resource


owns tag

has taghas tag

Groupbelongs to

my group

Sub-Activity

has activity

belongs to

Activity

has sub-activity

my activity

Thursday, May 19, 2011There are different kinds of recommender systems. Most systems combine different approaches

in hybrid systems. Collaborative-filtering uses the ratings of users on the platform to determine which resources or tags are important or most used or known. Structure based recommender systems we just saw when the relationships between nodes are used to traverse the graph to find related nodes. Content based methods compare the content of the web pages to determine the similarity between them. Knowledge based methods use other sources of information to determine relationships between objects. Such as Furniture an Chair may not be connected but via Wikipedia, the category Furniture-Chair is determined and the connection made.


What is recommended in CROKODIL?

Friends

Groups

Resources



Activities

TagsApril

2011NewsJapan

Nuclear

Energy

19


In CROKODIL, tags and resources, friends,groups and activities can be recommended.


CROKODIL Activity Ratings

Resourcemy resource

Sub-Activity

has resource

Activity

has sub-activity

my activity

Resource has resourcePrepare GKEL Presentation


20

Thursday, May 19, 2011I will be focusing on introducing collaborative filtering to CROKODIL by introducing rating of resources in the context of a CROKODIL activity. For example, I am preparing a new presentation and I see this picture has been rated with 5 stars and this presentation with 4 stars because maybe the picture was used by others but the presentation not.


Ranking Recommendation Results

Recommendations1.

2.Furniture

Chair

Resource

my resource

has tag

my tag

Topic Tag

my friend

Resource


owns tag

has taghas tag

Groupbelongs to

my group

Sub-Activity

has activity

belongs to

Activity

has sub-activity

my activity

21

Thursday, May 19, 2011In general all recommendation methods weight the resources and offer suggestions of how these resources could be ranked. For example according to the ratings, the picture is ranked higher than the presentation.


CROKODIL Features

Groups

Social Relations

Activity Ratings

Activity Tree



Tag TypesApril

2011NewsJapan

Nuclear

Energy

22

Thursday, May 19, 2011In CROKODIL, it will be interesting when ranking to consider the tag types, for example giving the tag type topic more weight than the tag type type or event or location, then one could consider the social relationships to determine what to prioritize, for example common friends or groups. Also interesting will be the information the hierarchical structure the activities present as well as the ratings in the context of these resources.


Explaining Recommendations

ahh... now I get it!

23


My next idea is explaining recommendations. This helps the user to understand the system better and helps to build trust.


Explaining Recommendations

Most of your friends love this picture!

This presentation was also used in your “Introduction to CROKODIL” activity.

24

Thursday, May 19, 2011The learner reflects on these explanations and learns about relationships that were not obvious before. For example, that most of my friends like this picture...now the picture might be more interesting to me or reminding me that I have already made a presentation introducing CROKODIL...maybe I could use this again.


User Feedback to Recommendations

This presentation was also used in your “Introduction to CROKODIL” activity.

Most of your friends love this picture!

25

Thursday, May 19, 2011Explanations also motivate the learner to give feedback, for example I do not find the picture relevant to my new presentation even though my friends find this picture good. I rather find the old presentation as interesting.


Feedback Loop

Rank

Explain

Feedback

1.

2.

26

Thursday, May 19, 2011The system ranks the resources and suggests the first two selections, the user is given explanations for this and the feedback is received.


Feedback Loop

Rank

Explain

Feedback

1.

2.

27

Thursday, May 19, 2011The feedback now influences the recommendation algorithms and I realize you prefer the presentation, this tells the recommendation system to maybe recommend similar presentations belonging to you rather than popular resources from your friends.


Research Questions

How to exploit social relationships between learners to improve personalized recommendations?

How to exploit folksonomy structures for recommendation algorithms?

How to generate explanations for collaborative and structural recommendations?

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Thursday, May 19, 2011I plan to investigate these three questions. How to use the social relationships in CROKODIL, the friendships and groups. As well as the graphical structure especially considering the special features in CROKODIL such as the activities, the ratings, the tag types. Then how best to generate explanations using this structure and the ratings or tags.


Summary

Resource Based Learning

Social Search Model

CROKODIL

Recommendation Systems

Activity Ratings

Semantic Tagging

Tag Types



Collaboraive Filtering

Explanations

Feedback Loop

Ranking Recommendation

Results

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Thursday, May 19, 2011A mind map as summary


Questions & Contact

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Thursday, May 19, 2011Any questions?

Education

Support for Resource-Based Learning on the Internet