Social Learning and Knowledge Sharing Technologies Lecture Slides about Social Patterns & Graph Theories

© author(s) of these slides including research results from the KOM research network and TU Darmstadt; otherwise it is specified at the respective slide

31-Oct-14

Dr.-Ing. Johannes Konert

Dr.-Ing. Christoph Rensing

KOM - Multimedia Communications Lab

Template Teaching v.3.4

KnowShare__3_SocialDesignPatterns_GraphTheory__2014.10.31__v1.1.pptx

Social Patterns &

Graph Theories Basics

Social Learning and Knowledge Sharing Technologies

31.10.2014

1. Theories and Challenges

2. Structures and Pattern

Modeling Context

4. Context-Awareness

Search Context Detection

3. Services and Mechanisms

Peer Tutoring Collabora. Tasks

Contextual Services

5. Evaluation

Foundations and Learning Theories

Challenge: Resource Selection & Navigation

Challenge: Coopera-tion & Collaboration

Challenge: Feedback & Targeting

Peer Assessment & Feedback Learning

Analytics

Learning Path Transparency

Offline Evaluation

Hypothesis validation

Formative and summative

Resources

Social Patterns

Graph Theory Basics

Scripted Collaboration

Re- com- men- der

Human

Resource User / Learner

KOM – Multimedia Communications Lab 2

Approaches to Modern

Web Application Development

MVC, ACID, CRUD REST,

LAMP <-> MEAN, PaaS

Social Media Systems Design Aspects

Content vs. User

Relationship Types

Roles, Levels, Badgets, Achievements

as an instrument for Guidance

Responsibility and Democracy

Ambient Intimacy

Graph Theory Basics

What have

subways, emails and rivers in common?

(or users, tags, resources)

Image sources: http://www.seawaterfoundation.org/siteImages/rivers_art.jpg,, http://vnfa8y5n3zndutm1.zippykid.netdna-cdn.com/wp-content/uploads/2011/12/url7.jpg, http://images.all-free-

download.com/images/graphiclarge/s_bahn_71263.jpg, http://de.roblox.com/item.aspx?seoname=U-Bahn&id=28172595, http://faculty.kutztown.edu/rieksts/225/graphs/tripartite_files/image002.jpg,

Lecture 3

Social Patterns & Graph Theories Basics


Motivation

1. Challenge: Resource Selection

& Navigation

4. Challenge: Cooperation & Collaboration

2. Challenge: Targeting

(How to find resources? How to navigate?)

How to motivate to reach learning goals?

Modern Web App Dev (Basics)

Social Systems Design Patterns

Graph Theory (Basics)

3. Challenge: Feedback

(How to design Peer Feedback/Assessment?)

(What is the path to the goal?)

(Who is the best candidate?)

How to establish a “community” sense?

Challenges

How to tell “what’s next”?


At the end of the lecture / exercise you will be able…

Learning objectives of lecture 3

..to repeat aspects to keep in mind when designing a new Social Learning and Knowledge Sharing System.

..to decide based on the aspects which components you want to use.

..to select and focus on specific Social System Design Patterns to support your system characteristics.

..to differentiate (basic) types of graph representations and you can decide and explain to which type example graphs belong to




Image source: ok/FreeDigitalPhotos.net

Placement in the context of the lecture



Modeling Context





Contextual Services

5. Evaluation






Analytics


Offline Evaluation



Resources

Social Patterns

Graph Theory Basics


Re- com- men- der

Human



Codecademy Airbnb

Examples of Modern Web Applications

Characteristics (some..)

Changes in one GUI widget cause reload/filtering of data in other app parts

Far beyond text-based websites

Responsive Layout


.. with Web Application we mean: an application running (and displayed) in the browser

.. with Modern we mean: system design solutions supporting development, maintenance,

performance and responsiveness of web applications beyond and in contrast to websites.

..with Approaches we mean: Technologies and Paradigms used to develop Modern Web

Applications (this excludes hardware and runtime maintenance aspects)

Components of

a Modern Web Application

Image source: http://www.codeproject.com/Articles/645753/Challenges-and-solutions-Architecture-of-a-Modern

Approaches to Modern Web Application Development

Distributed System(s)

..so forget this illustration


Web server

Components of a (Modern) Web Application

Image sources: http://www.computero.com/media/HP-server.jpg, DryIcons/Shine, Tango IconSet

Server Client

Operating System (OS)

Script language DB


Model Controller

<!DOCTYPE html>

<html>..</html> View

Web browser

Script language Local state


MVC (Pattern)

Model encapsulates the data (objects) state

View displays the data, is user interface and allows user actions

Controller reacts on user actions, coordinates model(s) and system

communication

Modern Web Applications


Web server

Server Client


Script language DB


Web browser


Model Controller View Model Controller View


MVC (Pattern)



Web server

Server Client


Script language DB


Web browser


Model Controller

View Model Controller

View


ACID (Database Design Properties)

Atomicity (all or nothing)

Consistency (constraint-based valid states)

Isolation (concurrency control)

Durability (no loss after commit)



Web server

Server Client


Script language DB


Web browser


Model Controller


View


CRUD (Persistent Storage [Interface] Properties)



Web server

Server Client


Script language DB


Web browser


Model Controller


View

Operation SQL HTTP

Create INSERT PUT / POST

Read (Retrieve) SELECT GET

Update (Modify) UPDATE PUT / PATCH

Delete (Destroy) DELETE DELETE

We

b S

erv

ice

/ A

PI


REST (Property)

Representational state transfer

Stateless server & cachable responses

uniform ressource and service addresses

Alternative representations (?)

Interface-based operations

(identify, create, modify, delete)

New aspects:

Hypermedia as state transition machine

Using many HTTP methods



Web server

Server Client


Script language DB


Web browser


Model Controller


View

We

b S

erv

ice

/ A

PI

HTTP-based example: http://www.airbnb.com/places public class MyPlaces {

@GET

@Produces(MediaType.TEXT_PLAIN)

public String getIt() {

return "Darmstadt, Frankfurt, München";

}

@GET

@Produces(MediaType.APPLICATION_JSON)

public String getIt() {

return "{ ‘places‘:

[‘Darmstadt‘,‘Frankfurt‘,‘München‘]}";

}

}


LAMP (Paradigm)

Linux OS

Apache Webserver

MySQL DB

PHP Server-side Language

(Also popular as XAMP or XAPP)



Web server

Server Client


Script language DB


Web browser


Model Controller


View

We

b S

erv

ice

/ A

PI


MEAN (Paradigm)

Node.js operating language

Express Webserver framework

MongoDB NoSQL storage

AngularJS client-binding

(Also known as AMEN)



Web server

Server Client


Script language DB


Web browser


Model Controller


View

We

b S

erv

ice

/ A

PI

New aspects:

MEAN adds a client-layer component to

the stack

All JavaScript


Total number based on Wikipedia entries on ‚database‘, ‚webserver‘, ‚web application framework‘,…

from 2014-10-29 (only to get a idea of dimensions)

Modern Web Application Development

Database

(~50)

Webserver

(~30)

Server: Web App

Framework (~130)

Template

Engine (~90)

Client: Web

App Framework

(JS: ~40)

SQLite

HyperSQL

MySQL

PostgreSQL

Cassandra

MongoDB

(Microsoft IIS)

Apache HTTP

Apache Tomcat

Jetty

Boa

NginX

Mongoose WS

lighttpd

(Node.js)

Full solution frameworks:

ASP.NET MVC, GWT

PHP (CakePHP, Zend)

Ruby (on Rails)

Python (Django, Pyramid)

Java Servlets (Spring, JSF, Struts)

ExpressJS

PHP / Smarty

Genshi

Cheetah

Mustache

JSP

Jade

Dojo

MochiKit

script. aculo.us

ExtJS

YUI

Qooxdoo

jQuery

Ember.js

AngularJS


PaaS (Pattern)

Platform as a Service

Cloud-Service model for delivery

of a (scalable, reliable) operating

platform for applications

Client creates and maintains

application



Web server

Server Client


DB


Web browser


Model Controller


View

We

b S

erv

ice

/ A

PI

Script language

https://www.heroku.com/ https://cloud.google.com/appengine/ https://www.openshift.com/


Social System

Design Patterns

Image and book reference: http://www.amazon.com/Designing-Social-Interfaces-Principles-Experience/dp/0596154925, http://www.amazon.com/Building-Social-

Applications-Gavin-Bell/dp/0596518757/

Placement in the context of the lecture



Modeling Context





Contextual Services

5. Evaluation






Analytics


Offline Evaluation



Resources

Social Patterns

Graph Theory Basics


Re- com- men- der

Human



“The main issue with designing and maintaining a social web

application is not the technology, it’s the psychology as people and

their activities are the core of the application.”

The quote is no citation of other authors, but written by JK based on [Crumlish et al 2009] and [Bell 2009]

The main issue


Overview on Social System Design Aspects

1. Challenge: Resource Selection

& Navigation

4. Challenge: Cooperation & Collaboration

2. Challenge: Targeting

3. Challenge: Feedback

How to motivate to reach learning goals?

How to design Peer Feedback/Assessment?

How to establish a “community” sense?

How to tell “what’s next”?

Content vs. User

Roles, Levels, Badges, Achievements

Responsibilities and Democracy

Relationship Types

Ambient Intimacy


Publisher-led

Product-led

Interest-Led

Image sources: taken screenshots from each website on 29.10.2014

Structural Patterns

Content vs. User


Publisher-led

Product-led

Interest-Led (hybrids exist)

Image sources of examples: taken screenshots from each website on 29.10.2014

Structural Patterns

Content vs. User

Publisher

Publisher

Interest

Interest

Interest

Product


Content-centric

User-centric

Event-centric


Structural Patterns

Content vs. User


Content-centric

User-centric

Event-centric (hybrids exist)


Structural Patterns

Content vs. User

Content (Event)

Content Event Content (User)

User (Content)

User


Publisher Product Interest

Content Media Syndication Customer Exchange Learning/Sharing

Event Marketing Franchise Gathering/Exchange

User VIP Promotion Grouping Friendship

Illustration by J.Konert, no specific reference for these dimensions, but see [Bell2009, p. 123ff] for aspects

Structural Patterns

Most interesting for Social Learning and Knowledge Sharing are

Interest-led

Content-centered

Content vs. User


(some relationship arrows are omitted for better readability)

Image source: Tango Icon set,

Relationship Types

Relationship Types

Site owner

Users

Users

Resources

Conversation

Meta-Data Categories Tags Groups

Friendship

Following

Following

Bookmarking

Following

Ownership

Ownership

Sharing

Sharing Following

Ownership

Sharing

Ownership Following


Technically

Symmetric relationships

Discovery of people/groups

Request, Acknowledgement, Decline, Ignore, Remove

Asymmetric relationships

Follow (Fan), Unfollow, Bookmark

Filter

Structure and Content creation

Group creation, deletion, handover ownership

Content creation, deletion, (remaining after account deletion)

Tagging

Privacy and Visibility settings for user-data, content, structures

Search and Recommendation (PULL, PUSH)

Administration (reporting, deletion, reasoning, explanation) [see later slides]

See [Crumlish et al, 2009], p.354-379 for further details. * read http://socialseriousgames.de/post/5437302687/social-serious-gaming-chi-2011-impressions for further details

Relationship Types

Make content and profile creation easy, syndicate and recommend this technically

and allow structure to emerge later on

[cf. Crumlish et al., p378]

Symmetric

Asymmetric


What is reputation?

It’s the general opinion (judgment) (more technically,

a social evaluation) of (and by) the public (or a group or

only a person) towards an entity (person, organization, object or group of entities)

– as distinct and different from the background (others) – concerning the likelihood of the

entity to behave in a certain way in the future [under certain circumstances].

It is a ubiquitous, spontaneous and highly efficient mechanism of social control.

[Crumlish et al. 2009, p. 153], citing Ted Nadeau “Reputation 2.0”

Good.

So let’s give people something that helps for reputation.

Consider

Cooperativeness vs. Competitiveness

Comparability

Quality vs. Quantity

Honor User Loyalty and Progress



Named Levels

Reflect the experience (and/or reputation)

Usual measures are

Activities

Likes/Follower

Completion of tasks/quests (if applicable)

(similar, but not ordered, are badges (or labels)..

..given for specific behavior or characteristics..can be extended endlessly)


Newbie Active

member Contri- butor

Trend setter Expert Leader Enthusiast



Achievements (or Awards)

Reflects accomplished activities

Used to encourage quality

over quantity behavior

Common

Can be reversible

Seldom

Can be unexpected

and hidden

Image source: Konert 2014, .p 67; cf. Konert et al. 2013, Crumlish 2009, p. 166ff




Image source: https://s3.amazonaws.com/codecademy-blog/assets/intro-new-profile/whole_page.jpg

Example: codecademy.com Profile

Qualitative, single, static Achievements

Badgets for specific skills

Points (as a kind of level)


A Social Web Application should

offer a unique, protected identity

(by email or OpenID etc.)

offer privacy settings

(reasonable defaults, private, protected, public profile and activities)

enforce community guidelines (code of conduct)

grow organically (managed by owner and community)

provide tools for collective governance

(reports, privileges, isolation, timed bans, ..)

allow collaborative filtering (votes, tagging)

never forget that all data belongs to the users

(and that this implies rights to it)

Cf. [Bell, 2009, p. 209-224], [Crumlish et al, 2009, p. 383-397]; image taken from https://info.yahoo.com/legal/sg/yahoo/comms/

Responsibilities



User-generated content administration “Duty of housekeeping”

Easy content creation benefits

Diversification: more variety, specificity, more use/benefits for users

Identification: own content supports emotional binding

Iceberg effect:

Lot of content with low quality

(that should remain under the surface)

..and: illicit content

(18+, NS-symbols, ..)

Solutions:

Youth protection

Content administration

Algorithmic Quality assessment

Responsibilities

Quality of content

Amount

Acceptable quality

Image source: hhttp://www.vertriebslexikon.de/bilder/Eisberg-2009.jpg



Responsibilities

User-generated content administration

A little bit of German law (selection)

Operator is not responsible for law infringement of users

But operator must react promptly, if informed

§10 TMG - Speicherung von Information Diensteanbieter sind für fremde Informationen, die sie für einen Nutzer speichern,

nicht verantwortlich, sofern (1) sie keine Kenntnis von der rechtswidrigen Handlung oder der Information haben und ihnen im

Falle von Schadensersatzansprüchen auch keine Tatsachen oder Umstände bekannt sind, aus denen die rechtswidrige Handlung oder die Information offensichtlich wird, oder

(2) sie unverzüglich tätig geworden sind, um die Information zu entfernen oder den Zugang zu ihr zu sperren, sobald sie diese Kenntnis erlangt haben.

Satz 1 findet keine Anwendung, wenn der Nutzer dem Diensteanbieter untersteht oder von ihm beaufsichtigt wird.

§1004 BGB - Beseitigungs- und Unterlassungsanspruch (1) Wird das Eigentum in anderer Weise als durch Entziehung oder Vorenthaltung des Besitzes

beeinträchtigt, so kann der Eigentümer von dem Störer die Beseitigung der Beeinträchtigung verlangen. Sind weitere Beeinträchtigungen zu besorgen, so kann der Eigentümer auf Unterlassung

klagen. (2) Der Anspruch ist ausgeschlossen, wenn der Eigentümer zur Duldung verpflichtet ist.



Responsibility of Content Administration

User-generated content administration

Setting up prompt reaction and administration of content

Categories of procedures for

administration of UGC*

Algorithm-based

User-based

Operator-based

Requirements to procedures for

administration of UGC*

Correctness of taken decisions

(to delete)

Cost efficiency

Speed of decision taking

in each single case

Amount of content

that can be processed

Complexity of content

that can be processed

*UGC = user-generated content




Operator-based User-based Algorithm-based

Central e.g. SecondLife e.g. Knuddels e.g. Chatsystems

Distributed ? e.g. Wikipedia e.g. P2P Sharing




Operator-Based Responsibility

(Complex-Decision)

User-Based Intermediation

(Fuzzy-Decision)

Algorithm-Based Mass-Processing

(Pre-Decision)

Complexity of content

Amount of Content that can be processed

Examples:

Email complaints

Claim button

Word detection (NLP)



Ambient Intimacy

Key aspect for social learning success

(beside serendipity)

“..is about being able to keep in touch with people with

a level of regularity and intimacy that you wouldn’t

usually have access to, because time and space

conspire to make it impossible.” *

Removing cold ambience and the feeling of being with

others using the application may dramatically increase

app stickiness and in the context of SLKST the

learning success (as it is mainly about self-regulation,

continuity and connecting people by content).

Image sources: own facebook profile feed and video as listed above. * quote from http://www.reboot.dk/page/1236/en ; cf. [Crumlish et al 2009, p.135-152]

Ambient Intimacy

See Video for Interview with Twitter founder Evan Williams of Obvious http://www.technologyreview.com/video/416292/twitter-and-ambient-intimacy/


GRAPH THEORY



Modeling Context





Contextual Services

5. Evaluation






Analytics


Offline Evaluation



Resources

Social Patterns

Graph Theory Basics


Re- com- men- der

Human



A Graph G is a pair of sets (Vertexes and Edges)

𝐺 = (𝑉, 𝐸), 𝑉 = 𝑥1, … , 𝑥𝑛 , 𝐸 ⊆ 𝑉 2, 𝑉 ∩ 𝐸 = ∅

Vertexes of a Graph are 𝑉 𝐺 , Edges are 𝐸(𝐺)

Number of vertextes 𝑉 = 𝑛 = |𝐺| is called the order of G

Number of Edges 𝐸 = 𝑚 = 𝐺

Two vertexes 𝑥𝑖 , 𝑥𝑗 ∈ 𝑉(𝐺) are adjacent, if 𝑥𝑖 , 𝑥𝑗 ∈ 𝐸 𝐺 .

Two edges are adjacent if they have an end in common.

The degree 𝑑 𝑥 = |𝐸 𝑥 | of 𝑥 is the number of edges at 𝑥

A path is a non-empty (sub)graph 𝑃 = (𝑉, 𝐸) of the form

𝑉 = 𝑥0, 𝑥1, … , 𝑥𝑘 , 𝐸 = {𝑥0𝑥1, 𝑥1𝑥2, … , 𝑥𝑘−1𝑥𝑘} where 𝑥𝑖 distinct. 𝐸 is the length of P

A tree is a graph where any two vertexes are connected by exactly one unique path

Restrictions: This lecture only treats nontrivial, finite graphs and mostly simple

graphs, i.e. 𝐕 > 𝟎, 𝑮 known and < ∞ , no loops, no double edges

This and following slides are based on [Diestel2006]

Graphs Defined

𝑥1 𝑥2

𝑥3 𝑥4

𝑥5


Vertexes represent users*

Edges represent relations

(friendships) **

Metrics of interest

Which users belong closely to each other?

Which users spread information?

Which users are popular (trendsetting)?

A directed graph (or digraph) 𝐷 = (𝑉, 𝐴) is with

V a finite, nonempty set of vertices and

A a set of ordered pairs of distinct elements of V

called arcs, 𝐴 = {(𝑥𝑖 , 𝑥𝑗)} with 𝑖 ≠ 𝑗, 𝑥𝑖 , 𝑥𝑗 ∈ 𝑉

meaning directed arcs from 𝑥𝑖 to 𝑥𝑗

In-degree 𝑑− 𝑥 of a vertex x is the number of arcs into x.

Out-degree equally defined for out-going arcs from x.

Image source: jscreationzs / FreeDigitalPhotos.net ; [[Oellermann, 2013, p.7]

Social Network Graphs

* Could be as well locations, resources, etc.., but is less common ** could be anything else like “exchanged emails”, “have been at the same spot”, “have a goal in common”. It is very usual to define the edges to the needs of your analysis


Metrics of interest

Which users belong closely to each other?

Which users spread information?

Which users are popular (trendsetting)?

Image source: jscreationzs / FreeDigitalPhotos.net ; [INSNA,2014]

Social Network Graphs

Range (diversity) Number of links to different others (others are defined as different to the extent that they are not

themselves linked to each other, or represent different groups or statuses)

(Tie) strength Amount of time, emotional intensity, intimacy, and reciprocal services (frequency and multiplexity are

also often used as a measure of strength) of a specific link.

Centrality Extent to which an actor is central to a network. Various measures (including degree, closeness, and

betweeness) have been used as indicators of centrality. Some measures of centrality weight an

actor's links to others by the centrality of those others.

Closeness Extent to which an actor is close to, or can easily reach all the other actors in the network. Usually

measured by averaging the path distances (direct and indirect links) to all others. A direct link is

counted as 1, indirect links receive proportionately less weight (e.g. 1/(number of hops)).

Betweeness Extent to which an actor mediates, or falls between any other two actors on the shortest path

between those actors. Usually averaged across all possible pairs in the network.

Prestige Based on asymmetric relationships, prestigious actors are the object rather than the source of

relations. Measures similar to centrality are calculated by accounting for the direction of the

relationship (i.e. in-degree). Prestige can then be defined e.g. as in-degree / out-degree


Representation

Adjacency matrix

For our finite simple graphs a adjacency matrix is a matrix

with zeros on its diagonal and ones (1) for each edge

connecting 𝑥𝑖 and 𝑥𝑗. The matrix is always symmetric if the graph is undirected.

A =

01010

10110

01011

11100

00100

, algorithmically you store an 2-dimensional array A[i][j].

Adjacency list

Storage of all neighbors of the vertexes as a list, e.g.

𝐴 = 𝑥2, 𝑥4 , 𝑥1, 𝑥3, 𝑥4 , 𝑥2, 𝑥4, 𝑥5 , 𝑥1, 𝑥2, 𝑥3 , 𝑥3 ,

algorithmically you store as well a 2-dimensional array

Which way is more efficient?

Depends on sparsity and operations

(Social Network) Graphs

𝑥1 𝑥2

𝑥3 𝑥4

𝑥5


A graph 𝑮 = (𝑽, 𝑬) is called n-partite if V admits a partition into r classes such that

every edge has its ends in different classes. 2-partite is usually called bipartite.

A hypergraph is a generalization of a graph with 𝐸 ⊆ 𝑃 𝑉 \ ∅

In a k-uniform hypergraph all hyperedges have size k.

Thus an k-uniform k-partite hypergraph consists of edges connecting k-tupels of

vertexes that all belong to k disjunct sets.

For hypergraphs see as well http://en.wikipedia.org/wiki/Hypergraph#Bipartite_graph_model

N-partite graphs and k-uniform hypergraphs

𝑥1

𝑥2

𝑥3

𝑥4

𝑥5

𝑥6 𝑥7

bipartite 3-partite

3-partite

3-uniform

𝐻 = 𝑉, 𝐸 , 𝑉 = 𝑉𝑏 ∩ 𝑉𝑔 ∩ 𝑉𝑟 = 𝑥1, 𝑥2, … , 𝑥7 , 𝐸 = { 𝑥1𝑥4𝑥6 , 𝑥2𝑥5𝑥6 , 𝑥2𝑥5𝑥7 , 𝑥3𝑥4𝑥7 }


How to weight the edges in an k-uniform, n-partite graph to

recommend other related vertexes of a disjunctive set?

How to calculate a betweenness centrality of resources in such n-

partite graphs with users, resources and tags?

Emerging aspects

See lectures 8 and 9 on recommender Systems in SLKST context




MVC, ACID, CRUD REST,

LAMP, MEAN, PaaS

Social Media Systems Design Aspects

Graph Theory Basics

Centrality metrics of (un)directed graphs

N-partite, k-uniform hypergraphs

Image sources: http://www.seawaterfoundation.org/siteImages/rivers_art.jpg,, http://vnfa8y5n3zndutm1.zippykid.netdna-cdn.com/wp-content/uploads/2011/12/url7.jpg, http://images.all-free-

download.com/images/graphiclarge/s_bahn_71263.jpg, http://de.roblox.com/item.aspx?seoname=U-Bahn&id=28172595, http://faculty.kutztown.edu/rieksts/225/graphs/tripartite_files/image002.jpg,

Summary

Content vs. User Roles, Levels, Badges, Achievements Relationship Types

𝑥1

𝑥2

𝑥3

𝑥4

𝑥5

𝑥6 𝑥7

Adjacence list

𝐴 = 𝑥2, 𝑥3 , 𝑥1, 𝑥3, 𝑥4 , 𝑥2, 𝑥4, 𝑥5 , 𝑥1, 𝑥2, 𝑥3 , 𝑥3


Ambient Intimacy


Task1 (2p)

Designing the relation of system design aspects and 3 systems as a graph

(connecting social System Design Patterns with Graph Theory)

Task 2 (2p)

A new (fictive) SLKS system is described

Define and describe 6 types of relationships

How would you implement a reputation/progress system if you have to choose

one pattern?

How do you handle content administration?

A bonus challenge is included (task 1)

About the Exercise 3


Learner Models & Profiles

Learning Resources

Data Structures for Learning Content

Metadata to describe Learning Resources

Tags to describe Learning Resources

Next week: Lecture 4

Data Structures for Learner and Resources

Knowledge

Topics

Misconceptions

Learning Styles

Experience

…


Thank you for your attention, questions, feedback or hints.

Endslide

[email protected]…. .de [email protected]…. .de


REST, see JAX-RS specs and https://jersey.java.net/documentation/latest/getting-started.html

Crumlish, C.; Malone, E.: Designing Social Interfaces: Principles, Patterns, and Practices for Improving the User

Experience (Animal Guide) (p. 520). Sebastopol, USA: O’Reilly Media, 2009. Letzter Zugriff von

http://www.amazon.com/Designing-Social-Interfaces-Principles-Experience/dp/0596154925

Bell, G.: Building Social Web Applications. Bell, Gavin . Sebastopol: O’Reilly Books, 2009. Letzter Zugriff 29.10.2014 von

http://www.amazon.com/Building-Social-Applications-Gavin-Bell/dp/0596518757

Konert, J.; Gerwien, N.; Göbel, S.; Steinmetz, R. Bringing Game Achievements and Community Achievements Together.

In Proceedings of the 7th European Conference on Game Based Learning (ECGBL) 2013, pages 319–328, Porto

Portugal, 2013. Academic Publishing International. ISBN 978-1- 909507-63-0.

Konert, J.: Interactive Multimedia Learning: Using Social Media for Peer Education in Single-Player Educational Games

(p. 220). Darmstadt, Germany: Springer, 2014. Letzter Zugriff von

http://www.springer.com/engineering/signals/book/978-3-319-10255-9

Diestel, R.: Graph Theory (Graduate Texts in Mathematics) (3rd ed.). Springer, 2006. Letzter Zugriff 30.10.2014 von

http://www.amazon.de/Graph-Theory-Graduate-Texts-Mathematics/dp/3540261834/

Oellermann, O. R.: Topics in Structural Graph Theory. (L. W. Beinecke & R. J. Wilson, Hrsg.). Cambridge, MA, USA:

Cambridge University Press, 2013.

INSNA, International Network for Social Network Analysis, 2004. SNA Measures. , p.1. Available at:

https://www.socialtext.net/data/workspaces/insna-

socnet/attachments/index_of_sna_measures:20041202193540/original/Index of SNA Measures.xls.

Wikipedia, Hypergraphs, Letzer Zugriff 30.10.2014 von http://en.wikipedia.org/wiki/Hypergraph#Bipartite_graph_model

References (order of occurance)


REST, see JAX-RS specs and https://jersey.java.net/documentation/latest/getting-started.html

Crumlish, C.; Malone, E.: Designing Social Interfaces: Principles, Patterns, and Practices for Improving the User

Experience (Animal Guide) (p. 520). Sebastopol, USA: O’Reilly Media, 2009. Letzter Zugriff von

http://www.amazon.com/Designing-Social-Interfaces-Principles-Experience/dp/0596154925

Bell, G.: Building Social Web Applications. Bell, Gavin . Sebastopol: O’Reilly Books, 2009. Letzter Zugriff 29.10.2014 von

http://www.amazon.com/Building-Social-Applications-Gavin-Bell/dp/0596518757

Diestel, R.: Graph Theory (Graduate Texts in Mathematics) (3rd ed.). Springer, 2006. Letzter Zugriff 30.10.2014 von

http://www.amazon.de/Graph-Theory-Graduate-Texts-Mathematics/dp/3540261834/

Further Readings


Directly named on the corresponding slides

Image Sources

Documents

Social Learning and Knowledge Sharing Technologies Lecture Slides about Social Patterns & Graph Theories