1. SeL-LR&SD, LREC 2010, Valletta, Malta 1 Semantic Annotation for Semi- Automatic Positioning of the Learner Kiril Simov, Petya Osenova Linguistic Modelling Department, IPP, Bulgarian Academy of Sciences Supporting eLearning With Language Resources and Semantic Data LREC 2010 22st May, 2010, Valletta, Malta

2. SeL-LR&SD, LREC 2010, Valletta, Malta 2 Plan of the Talk Positioning Task (PT) Semantic Annotation Application to Positioning Task

3. SeL-LR&SD, LREC 2010, Valletta, Malta 3 Positioning Task Within Lifelong Learning settings the learner needs to find (with the help of a tutor) an optimal learning path Identification of the learning path is done by comparison of the learner’s competence to a target competence

4. SeL-LR&SD, LREC 2010, Valletta, Malta 4 Competence Characteristics that individuals have and use in appropriate, consistent ways in order to achieve desired performance. These characteristics include knowledge, skills, aspects of self-image, social motives, traits, thought patterns, mind- sets, and ways of thinking, feeling and acting. (Dubois, David D. and William J. Rothwell, Competency-Based Human Resource Management, Davies-Black Publishing, Palo Alto, 2004, p. 16.)

5. SeL-LR&SD, LREC 2010, Valletta, Malta 5 Positioning in a Learning Network A learning network connects actors, human as well as agents, institutions and learning resources. (Kalz et al. 2007) Positioning: learner’s competence can be automatically compared to a set of concept evidences of the target competence within a learning network

6. SeL-LR&SD, LREC 2010, Valletta, Malta 6 Knowledge Rich Approach A learning network is a set of resources including tutors, experts, learning materials and learners, whose connections are mediated by ontologies Conceptual information within the ontology represent the target competence in a field of study The target competence of a learning path is represented via a curriculum Learner’s competence is represented in text form

7. SeL-LR&SD, LREC 2010, Valletta, Malta 7 Semantic Annotation for PT The semantic annotation explicates the conceptual part of the target and learner’s competence Grammar-based semantic annotation with concepts; Discourse segmentation; Lexical chains creation to support the concept annotation; and Sentiment analysis for evaluation of the concept usage in the text

8. SeL-LR&SD, LREC 2010, Valletta, Malta 8 First Version of KRA Q: Name some of the technical specifications of different kinds of monitors A: Output device, monitor, display devices of a PC; … Common concepts: CRT monitor, display, monitor Missing concepts: contrast, frame rate, graphical elements, image, LCD monitor, picture, pixel, ratio, refresh rate, rendering, resolution, screen, size, VGA Additional concepts: types, devices, Output device, PC, power, space

9. SeL-LR&SD, LREC 2010, Valletta, Malta 9 Conclusion We assume the positioning task to be performed on the basis of concept annotation of curriculum and learner’s profile (CV and tests) The result from the semantic annotation represents the target and the learner’s competence Comparison of the two competences facilitates the tutor to define an optimal learning path for the learner