E-learning Activities Recommender System (ELARS) Department of Informatics, University of Rijeka Radmile Matejčić 2, 51000 Rijeka, Hrvatska Tel.: + 385 51 584 700 Fax: + 385 51 584 789 http://www.inf.uniri.hr E-learning Activities Recommender System (ELARS) Nataša Hoić-Božić, Martina Holenko Dlab Division of multimedia systems and e-learning .

Outline Introduction ELARS recommender system System structure Experimental results and Conclusions Future plans - "E-learning Recommender System" project DAAD WS 2014 26/8/2014

Introduction Collaborative learning activities (e-tivities) Web 2.0 tools  interactivity Recommender systems  personalization PhD thesis: Recommender system for activities in computer-supported collaborative learning (defended in July 2014) Supervisors: Professor Vedran Mornar and Associate Professor Nataša Hoić-Božić DAAD WS 2014 26/8/2014

ELARS - E-Learning Activities Recommender System Personalization of collaborative e-learning activities performed using Web 2.0 tools recommendations for students and groups before and during e-tivities Activity level estimation  quantity and continuity of student’s (group’s) contributions enable recommendations generation support teachers in evaluation of students’ work DAAD WS 2014 26/8/2014

ELARS system structure DAAD WS 2014 26/8/2014

Activity model Course activities: Items for recommendations: classified (6 different types) grouped in learning modules Items for recommendations: Optional e-tivities Web 2.0 tools Collaborators Advice Mind mapping Your activity level is not satisfying so it is highly recommended that you participate to a greater extent. DAAD WS 2014 26/8/2014

Activities workflow example DAAD WS 2014 26/8/2014

Student and group models Student’s characteristics Learning styles (VARK model) Web 2.0 tools preferences Knowledge level Activity level Group’s characteristics DAAD WS 2014 26/8/2014

Subsystem for generating recommendations Ranking items according to usefulness support students in decision Filter appropriate advice from pre-defined set Techniques adapted to the educational domain include pedagogical rules teachers can modify the recommendation criteria DAAD WS 2014 26/8/2014

Recommending offered optional e-tivities Usefulness: similarity student ↔ e-tivity (teachers criteria) Technique: content-based 0.80 0.67 0.50 student group DAAD WS 2014 26/8/2014

Recommending possible collaborators Usefulness: similarity (teachers criteria) Technique: content-based 0.90 0.87 0.86 0.82 Homogeneous 0.33 0.45 0.67 0.90 Heterogeneous DAAD WS 2014 26/8/2014

Recommending Web 2.0 tools offered for certain e-tivity Usefulness: student’s preference of the target tool (prediction of missing values) Technique: hybrid (collaborative filtering + content-based) student group 0.90 0.32 -0.5 DAAD WS 2014 26/8/2014

Providing advice Technique: knowledge-based Useful/not useful DAAD WS 2014 26/8/2014

ELARS web application http://161.53.18.114/elars DAAD WS 2014 26/8/2014

ELARS demo http://161.53.18.114/elarsdemo DAAD WS 2014 26/8/2014

Learning modules and activities DAAD WS 2014 26/8/2014

Decision activities DAAD WS 2014 26/8/2014

Activity levels and advice DAAD WS 2014 26/8/2014

Experimental results and Conclusion Evaluation focused on pedagogical aspects two e-courses (University of Rijeka, Croatia) control and experimental group: better results (points) for e-tivities survey: students are satisfied with received recommendations and find the system useful Good results on experimental courses and students’ satisfaction provide motivation for further work and improvements. DAAD WS 2014 26/8/2014

Future plans - "E-learning Recommender System" project "E-learning Recommender System" project supported by University of Rijeka Future plans recommendations algorithms improvements improvements of ELARS authoring component for teachers creating and evaluating didactical models for the use of Web 2.0 based e-tivities in different types of blended and online higher education e-courses DAAD WS 2014 26/8/2014

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