Recommendation, Trust and Reputation Management in a Group Online Mentorship System

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1 Recommendation, Trust and Reputation Management in a Group Online Mentorship System Oluwabunmi Adewoyin and Julita Vassileva University of Saskatchewan, Canada

2 E-Learning vs. Online Mentorship Systems Mentoring is a life-altering relationship that triggers mutual growth, learning and development. It provides two major functions: Career function Psycho-social function Group mentoring vs one-on-one mentoring Individualized learning opportunity Human-to-human interaction Possible opportunity for faceto-face meeting, if the mentorship goes on smoothly. 2

3 Stages in Mentoring Stage 1 Stage 2 Stage 3 Stage 4 Initiation Orientation courtship Getting established Dependency Nurturing Maturing Independence autonomy Termination Figure 1: Stages in mentoring process (Hay, 1995) 3

4 Existing Online Mentorship Systems Features: Websites are just information boards Manual matchmaking, except MentorNet One-to-one mentoring Examples: MentorNet, CyberMentor, the Electronic Emissary project, ihelp 4

5 Automatising Online Mentoring Recommending mentors to mentees Related work in recommender systems: contentbased recommendation, group recommendation, reciprocal recommendation Monitoring and supporting communication through the stages Trust and reputation mechanisms allow to gradually establish trust between communicating agents 5

6 Stage 1: Initiation Initiation stage Sign up stage for both the mentors and mentees. Profile information of mentees and mentors are stored in a centralized database. 6

7 Stage 2: Identification and Grouping Identification and grouping stage. Profiles of the mentees and mentors retrieved from database Clustering mentors and mentees using content-based filtering augmented with trust (if previously interacted) 7

8 Stage 3: Group Matching Group Matching stage Group of mentors are matched to group of mentees using the reciprocal recommendation 8

9 Stage 4: Maturing and Independence Maturing and independence stage. Detecting conflicts explicit and implicit Group recommendation techniques for suggesting discussion topics Reinforcement of trust and reputation modeling by capturing evidence of conformity to and consistency in the required activities, and mentor-mentee bonding Motivating participation by rewarding active and beneficial participation 9

10 Stage 5: Termination Termination stage Decision is made on whether to dissolve or continue group interaction and mentor-mentee relationship. Based on the trust and reputation values from stage 4 Persisting implicit conflict 10

11 Techniques to be used in workflow Initial Grouping Matching groups Maturity and independence Termination Content filtering Trust and reputation Reciprocal recommendation Group recommendation 11

12 Conclusion Online Mentorship systems have been underexplored as an area of Intelligent Learning environments Matchmaking has been done manually so far No group matching of mentors to mentees Applying Trust and Reputation techniques and Recommender techniques would be potentially useful and novel contribution The proposed workflow combines a range of techniques at different stages of the mentorship process serving as a high-level roadmap for future research Future: investigating, implementing and evaluating the techniques proposed in each stage in a online mentoring group for women in science and engineering at the University of Saskatchewan. 12

13 References Alboaie, L. and Buraga, S. C. (2009). Trust and Reputation in e-health Systems. Interna-tional Conference on Advancements of Medicine and Health Care through Technology, IFMBE Proceedings, Volume 26, pp Anwar, M. and Greer, J. (2006). Reputation Management in Privacy-enhanced E-learning. In Proceedings of the 3rd Annual Scientific Conference of the LORNET Research Net-work (I2LOR-06), Montreal, Canada. Baudisch, P. (1999). Joining collaborative and content-based filtering, In: Interacting with Recommender Systems, Online Proceedings of the CHI '99 Workshop. Bhuiyan, T.; Josang, S. and Xu, Y. (2010). Trust and Reputation Management in Web- based Social Network, In: Web Intelligence and Intelligent Agents. ISBN Bogers, T. and Bosch, A. (2009).Collaborative and Content-based Filtering for Item Rec-ommendation on Social Bookmarking Websites. ACM RecSys 2009 Workshop on Rec-ommender Systems and the Social Web, USA. Hay, J. (1995) Transformational Mentoring, McGraw Hill Book Company. Lewis, G. (1996). The Mentoring Manager. Institute of Management Foundation, Pitman Publishing. McKimm, J.; Jollie, C. and Hatter, M. (2007). Mentoring: Theory and Practice. Developed from Preparedness to Practice, mentoring scheme July NHSE/Imperial College School of Medicine. Pizzato, L.; Rej, T.; Chung, T.; Koprinska, I. and Kay, J. (2010). RECON : A Reciprocal Recommender for Online Dating. RECSYS 10 Barcelona, Spain. Ragins, B. R. and Kram, K. E. (2007). The Roots and Meaning of Mentoring. URL: [Accessed: 08-July-2012]. 13

14 THANK YOU 14

Recommendation, Trust and Reputation Management in a Group Online Mentorship System

Recommendation, Trust and Reputation Management in a Group Online Mentorship System Oluwabunmi Adewoyin 1 and Julita Vassileva 2 Department of Computer Science University of Saskatchewan, Canada ofa531@mail.usask.ca