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Table 3 The EDL-CF for ID and eTUT: dimensions and statements

From: Towards an educational data literacy framework: enhancing the profiles of instructional designers and e-tutors of online and blended courses with new competences

EDL competence dimension EDL competence statements
Data collection Know where to find the right data/data sources
Know how to obtain/access data
Understand data quality and limitations (e.g., accuracy, completeness)
Data management Identify the technologies to preserve data
Know and apply data manipulation methods
Know and apply data curation and data re-use methods
Understand Data Description (Metadata)
Data analysis Know and apply the basic data analysis methods
Understand and apply the basic data analysis process steps
Understand and apply the basic data presentation methods
Data comprehension & interpretation Understand data (e.g., measurement error, discrepancies within data, key take-away points)
Understand statistics
Know how to interpret data (e.g., explanations of patterns, identification of hypotheses, connection of multiple observations)
Generate potential connections to instruction
Make decisions based on data
Data application Use data to inform instruction
Know how to share and cite data
Evaluate the data-driven intervention
Data ethics Explain the use of informed consent
Know how to protect individuals' data privacy, confidentiality, integrity and security
Understand authorship, ownership, data access (governance), re-negotiation and data-sharing