麻豆传媒高清版

Overview

Indicative content includes:

• Data; the definitions and concepts.
• Contextualisation of data.
• Analytical methods using data.
• Ethics of processing data with and without automatic decisions.
• Data Protection legislation (DPA, GDPR, HIPAA, COPPA, etc.).
• Data collection mechanisms.
• Storage mechanisms for data (in broad terms).

Assessment Strategy

-threshold -Equivalent to 40%.Uses key areas of theory or knowledge to meet the Learning Outcomes of the module. Is able to formulate an appropriate solution to accurately solve tasks and questions. Can identify individual aspects, but lacks an awareness of links between them and the wider contexts. Outputs can be understood, but lack structure and/or coherence.

-good -Equivalent to the range 60%-69%.Is able to analyse a task or problem to decide which aspects of theory and knowledge to apply. Solutions are of a workable quality, demonstrating understanding of underlying principles. Major themes can be linked appropriately but may not be able to extend this to individual aspects. Outputs are readily understood, with an appropriate structure but may lack sophistication.

-excellent -Equivalent to the range 70%+.Assemble critically evaluated, relevant areas of knowledge and theory to constuct professional-level solutions to tasks and questions presented. Is able to cross-link themes and aspects to draw considered conclusions. Presents outputs in a cohesive, accurate, and efficient manner.

Learning Outcomes

• Discuss the role of data and analytics in the 'data economy'.

• Distinguish different classes of data.

• Examine appropriate methods to collect and store data.

• Recognise potential legal and ethical consequences of collection, processing, and use of data.