1. IMSTD:Intelligent Multimedia System for teaching Databases By : NAZLIA OMAR Supervisors: Prof. Paul Mc Kevitt Dr. Paul Hanna School of Computing and Mathematical Sciences Faculty of Informatics University of Ulster

2. Intelligent Multimedia System for Teaching Databases (IMSTD) Literature Review Objectives of research + Proposed work Comparison with previous work + Contribution to the knowledge Conclusion

3. Difficulty in Databases subject SubjectVery difficult DifficultEasyVery easy Introduction to Databases -7.776.97.7 Entity-Relationship Modelling -48.7 2.6 Normalization12.871.812.82.6 The Relational Model-71.825.62.6 SQL2.641.048.75.0 Table 1: Percentage of the difficulty of the Databases subject

4. Objectives of research To design and implement a transformation tool To design and implement the components of an ITS To create a rich, face-to-face learning interaction through the use of a pedagogical agent To integrate all of the above components to form IMSTD To evaluate students’ and educators’ attitudes towards this ITS

5. Literature Review in ITS in Databases

6. Literature review in systems that apply NLP in Databases

7. Architecture of IMSTD

8. Prospective Tools Macromedia Authorware Brill’s tagger Microsoft Agent

9. Proposed research work Step 1 : Read natural language input text into IMSTD Step 2: Part of speech tagging using Brill’s tagger

10. Proposed research work

11. Step 3: Classifying and removing redundancies and plurals

12. Proposed research work Step 4: Apply heuristics Step 5: Refer to history

13. Proposed research work Step 6: Produce preliminary model

14. Proposed research work Step 7: Human intervention Step 8: Produce final model Step 9: Incorporate into ITS

15. Comparison with other ITS in Databases

16. Comparison with other systems that apply NLP in Databases

17. Contribution to the knowledge A new technique to transform a natural language database specification into an ER model The formation of new heuristics

18. Conclusion Questionnaire results support the evidence that Data Modelling is difficult Proposed project will contribute to knowledge Worked examples show that the project is achievable within the time period