Social Learning

Presented to : Dr. Abeer El KoranyPresented by : Yomna Hassan

Content

● What is Social Learning● Over the years● Why Social Learning● Research Trends● Potential Future Research

What is Social Learning?● Not a New Trend● Story Telling and Sharing Experiences● Internet -> no time/ place barriers● Social Networks

Social Learning [1]

Over the years [1]

Why social learning?● Motivation to Learn● Encouraging distant learning -> greater content

availability● Social Presence of student as real people -> enhance

learning [2]

Motivation- Analytical Hierarchical Process on EFL case study [3] (2013)

Current Research Trends

Social Learning

PsychologyComputer Sciences

Current Research Trends

● Gamification● Identification of hierarchy of relationships

(Ontology)● SNA

Gamification

How to Identify Award System[1] (2012)

Promoting Certain Behaviour of Learning Through Gaming

Game Elements Game Mechanics

Points Rewards

Levels Status

Trophies Badges

achievements achievements

virtual goods self expression

leaderboards competition

virtual gifts Alturism

Gamification for Learning in Healthcare [4] (2013)

- Patient recognize the behaviors that might compromise her/his health

- Train non-specialist medical and paramedical staffs on the procedures for diagnosis and patients follow-up

- UBICARE project-> de-hospitalization of patients suffering from peritoneal dialysis and chronic heart failure.

- The Edugames are simulations that, using the learning-by-doing approach allow specific skills related to both treatment protocols and the possible actions to take in emergency situations to be acquired.

- User Profile is matched to existing cases by DSS

Social -Learning - Software Engineering[5] (2014)

- Continuous social screencasting is a promising technique for sharing and learning about new software development tools.

- Steps:- Individuals perform a software engineering task. - Information about that task is recorded, even if that record is only a

memory. - Another person later performs or plans to perform a new software

engineering task.- Elements of the new task are compared against the record of prior

tasks.- Relevant elements of the prior tasks are extracted and presented to

the person performing the new task in the form of a recommendation, improving the accomplishment of that task or future tasks.

Ontology for E-Learning

Ontology for E-Learning [6] (2013)- Social network analysis (SNA) is treating the students'

interaction merely as node and edge with less meaning. - Ontology structure of e-learning Moodle that can enrich

the relationships among students, as well as between the students and the teacher.

Classification of Learning Material [7] (2014)

SNA and Learning

SNA and Learning [8] (2014)

1. Performance Analysis2. Drop-off rate3. Recommendation - Courses, study groups4. Personalization - Individualization

Social Networks Adapting Pedagogical Practice[9] (2009)

- Network Visualization Tool- Allows academic staff to identify patterns of

student behaviour and facilitate appropriate interventions as required

Recommendation of Material[10] (2011)

- Clustering algorithm (neighborhood estimation , prediction of users interest)

- The recommendation is based on the tags defined by the network learners and the items to be recommended include not only contents but also social connections that could enrich the user’s learning process.

- suggest new learning activities, users, and discussion groups according to the user’s learning and knowledge needs.

Influence of Relationships[11] (2011)-Positive/ Negative Influence (not only PIDS)-Selection algorithm named Weight Positive Influence Dominating Set (WPIDS)

Recommendation of Material[7] (2014)

● Based on Profile, context and Level of Interaction and collaboration● According to students needs and feedback● Data is seen as important: relevance, presentation, context, accessibility

Content RecommendationService by Exploiting Mobile Social Interactions [12] (2014)

Individual learning content is able to be recommended according to the behavioral characteristics of the response message of individual learners in the community

Potential work

- Drop-off reasons and rates analysis- IoT Integration (for personalization)- Storage Overhead (Characterising important

factors in mobile environments)- Standardization

References[1]Social Learning: the organization learns how to learn, Social Business Manifesto, May 2012.

[2]N. Adman et. al, Online Social Learning Model , International Conference on Teaching and Learning in Computing and Engineering,2014..

[3]Hsu, Liwei. "Leveraging Interactivities on Social Networking Sites for EFL Learning." International Journal of English Language Education 1.3 (2013): pp-244.

[4]Simões, Jorge, Rebeca Díaz Redondo, and Ana Fernández Vilas. "A social gamification framework for a K-6 learning platform." Computers in Human Behavior 29.2 (2013): 345-353.

[5]Murphy-Hill, Emerson. "The Future of Social Learning in Software Engineering." (2014): 1-1.

[6] N.Yusof et al., Ontology Development of e-Learning Moodle for Social Learning Network Analysis , World Academy of Science, Engineering and Technology Vol:7 2013-06-21

[7]Di Bitonto, P., et al. "Distance Education and Social Learning in e-Health." International Journal of Information and Education Technology 4.1 (2014): 71-75.

[8]Brinton, Christopher G., and Mung Chiang. "Social learning networks: A brief survey." Information Sciences and Systems (CISS), 2014 48th Annual Conference on. IEEE, 2014.

[9]Bakharia, Aneesha, Elizabeth Heathcote, and Shane Dawson. "Social networks adapting pedagogical practice: SNAPP." Same Places, Different Spaces. ascilite 2009 (2009).

[10]Di Bitonto, Pierpaolo, Teresa Roselli, and Veronica Rossano. "Recommendation in e-learning social networks." Advances in Web-Based Learning-ICWL 2011. Springer Berlin Heidelberg, 2011. 327-332.

[11]Wang, Guangyuan, et al. "Positive influence dominating set in e-learning social networks." Advances in Web-Based Learning-ICWL 2011. Springer Berlin Heidelberg, 2011. 82-91.

[12]Chao, H., et al. "A M-Learning Content Recommendation Service by Exploiting Mobile Social Interactions." (2014): 1-1.