Title Data Science Research Group Knowledge sharing session

The Information Technology Department’s Data Science Research Group coordinator, Ms Sana Fathima, organised a Knowledge Sharing Session-1. The session had two presentations, the first on Data science, Big data and Data analytics concept by Ms Sana Fathima, Lecturer IT and the second on Identifying learning styles from chat conversation using ontology-based dynamic Bayesian network model by Dr Amal Al Abri, Head-IT. 

Ms Sana started her presentation explaining the meaning of the Data science, Big data and Data analytics and continued talking about their roles and the required skill sets to become of one of them. She also explained their roles and responsibilities and how the professionals from all these fields join forces to increase the revenue of a company though an example scenario using Netflix data streaming. The second presentation by Dr Amal was on identifying learning styles from chat conversations using ontology-based dynamic Bayesian network model. The presentation gave insights on how a learner’s chat can be helpful in discovering important information relating to the learner characteristics like preferences and learning styles, such that through this information personalisation can be provided to the learners as per their needs. The presentation focused on the use of ontology-based dynamic Bayesian network model to extract the learning style based on the preferable learning objects of the learners which as a result support the personalisation process by recommending the suitable learning material to each learner.

The session was attended by 19 members from the department of IT and had an effective knowledge transfer.

Feedback was collected from the participants. All expressed their satisfaction with the facilities and organisation of the event. On an average the overall feedback from the participants was 4.23 on a scale of 5.