Data Analytics - Education
Use and interpret data analytics to assess and evaluate educational data in order to improve learning outcomes and education quality.
Aware of different types of education data
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
Conducts research using education data
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.
Analyses educational data
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 data analysis findings
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