Basic Information
The Course Covers Theoretical and Applied Aspects of Learning Analytics, Including# Goals and Uses, Approaches and Common Tools (predictive Modeling, Dashboards, Social Network Analysis) Data Representayions, Ethical Dilemmas and Adoption. The Course Project Asks Students to Analyze a Data Set of Their Choice. Open Data Is Available. At The End of The Course The Student Will Know# 1. to Critically Analyze Literature in The Area of Learning Analytics 2. to Define Research Question and Variables That Are Suitable For Learning Analytics and Data Mining 3. to Understand Main Topics and Approaches in The Area of Learning Analytics. 4. to Analyze Simple Data-sets in Order to Identify Learning Processes And Outcomes. 5. to Grasp Dilemmas About Policy, Ethics and Adoption of Learning Analytics. 6. to Use Learning Analytics Thechniques and Tools to Improve Learning And Instructional Design.
Faculty: Education in Science and Technology
|Undergraduate Studies
|Graduate Studies
Pre-required courses
216009 - Quantitative Research Methods
Semestrial Information
Weekly Hours
2.5 Academic Credit • 2 Lecture Hours • 1 Discussion Hours
Responsible(s)
Ido Roll
Registration Groups
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Weekly Hours
2.5 Academic Credit • 2 Lecture Hours • 1 Discussion Hours
Responsible(s)
Ido Roll
Notes
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הרישום לקבוצה 21 הינו ידני בלבד. יש להעביר למרצה פרופ/ח עדו רול קו"ח וגליון ציונים בצירוף בקשה לרישום עד לתאריך 26.01.23 תשובות יימסרו עד לתאריך 26.02.23
Registration Groups
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Weekly Hours
2.5 Academic Credit • 2 Lecture Hours • 1 Discussion Hours
Responsible(s)
Ido Roll
Registration Groups
|
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