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D293 Section 2

Assessment and Learning Analytics Section 2 "Data & Analytics"

PromptAnswer
Doctor Analogy for Analytics Describe Symptoms -> Diagnose / Explain Why -> Predict Outcome -> Prescribe Treatment / Take Action
Analytics Type: Descriptive Facts: "What happened in the PAST?" Based on data gathered from information.
Analytics Type: Diagnostic Answers "Why?" "Why did it happen?" Analyzes PAST Information to Find Out "Why?"
Analytics Type: Predictive Makes Predictions. Uses data from the PAST to predict the FUTURE. "What is likely to happen?"
Analytics Type: Prescriptive Suggests Solutions. Offers Recommendations Based on Possible Outcomes. Identifies the Best Outcomes. "What should be done in the FUTURE?"
Define: Quantitative Analysis Data, Facts, and Numbers. Often used in Descriptive Analytics.
Define: Qualitative Analysis Subjective. Observations, Reflections, and Interviews. Often used in Diagnostic Analytics,
Define: Social Network Analysis Patterns and Trends in Relationships. {Learner x Learner, Learner x Instructor} Often used in Predictive Analytics
Define: Data For Improvement "How to Improve?" Identify Weaknesses in Course. Make Data Informed Decisions.
Define: Data For Research "What is happening?" Gather and Generate Knowledge About Aspects of the Learning Process. Study behaviors, patterns, and effectiveness. Often uses comparison.
Define: Data For Accountability "Where is it working? Why are there issues?" Assess Performance, Demonstrate Efficiency
Define: Data For Interpretation The Process of deriving insights from data
Data Collection Ethics Consider Privacy and Impact. Use Empathy
Data: Activity Measures Learner Participation
Data: Performance Measures How well learners trained. Instructor Performance, Impact on Business Goals. "Did it decrease costs?"
What is Nominal Data? Named Data Only. No Numbers. Separates Data into Categories. Nominal data is labels or names with no order. 🔹 Example: Hair color (blonde, brown, black) 🔹 Just categories—can't be ranked or measured.
What is Ordinal Data? Ordinal data is ordered categories, but no exact difference between them. 🔹 Example: Survey ratings (poor, fair, good, excellent) 🔹 You can rank, but can't do math with them
What is Interval Data? Interval data has equal spacing between values, but no true zero. 🔹 Example: Temperature in °C or °F 🔹 You can add/subtract, but not multiply/divide
What is Ratio Data? Ratio data has equal intervals and a true zero point. 🔹 Example: Weight, height, time, money 🔹 You can do all math operations (add, subtract, multiply, divide)
What are Scoring Guides? Guide to assist with grading or scoring. Examples: Rubrics or Structured Observation Guides
Educational Data Mining: User Knowledge Modeling What Content Does the Learner Know?
Educational Data Mining: User Behavior Modeling Meaning of Patterns. Are students motivated?
Educational Data Mining: User Experience Modeling Are Learners Satisfied?
Educational Data Mining: User Profiling What groups do learners cluster into?
Educational Data Mining: Domain Modeling How should modules be divided?
Educational Data Mining: Learning Component / Instructional Principal Analysis What Components Work?
Educational Data Mining: Trend Analysis What changes over time?
Educational Data Mining: Adaptation / Personalization How to personalize the learning experience for each learners needs.
Created by: rebeccan
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