Aware of different types of data in education and the associated stakeholders (assessments, benchmarks, socio-economic, etc.)

Recognises the role of education data in assessing education quality and allocating resources towards the same

Utilises educational data mining and learning analytics to research and build models for learning systems

Understands the value and complexity of different types of data analytics (descriptive, diagnostic, predictive, prescriptive)

Conducts research using education data across a range of indicators (classroom, curriculum, etc.)

Interprets educational data mining and learning analytics to make instructional design decisions, building online learning platforms, etc.

Explains the value and complexity of different types of data analytics to stakeholders

Applies data analytics to effectively evaluate educational programmes, resource allocations, learning outcomes, etc.

Organises regular discussions with educators to understand how data analytics can be used to improve classroom pedagogies

Informs the efforts of the educational policies, IT departments in education, and accreditation agencies using data analytics

Communicates with stakeholders about the usability and effectiveness of data analytics in education

Identifies best practices for using education data to improve learning outcomes and education quality

Prioritises the use of data analytics and other evolving methods (data mining) in improving educational quality

Partners with IT cells and departments to regularly collect and analyse data, keeping in mind data security and privacy