Week 5: Educational Data Mining

Ready to roll?? Yeah!

• Plan in advance
• Meet with Bodong one week in advance to finalize plans

1. Scheuer, O. and McLaren, B. M. (2012). Educational data mining (or link 2). In Encyclopedia of the Sciences of Learning, pages 1075–1079. Springer.
2. Baker, R.S.J.d., Yacef, K. (2009) The State of Educational Data Mining in 2009: A Review and Future Visions. Journal of Educational Data Mining, 1 (1), 3-17.
3. Bienkowski, M., Feng, M., & Means, B. (2012). Enhancing teaching and learning through educational data mining and learning analytics. Washington, DC: U.S. Department of Education. (Only pp. 25-36)

• Generalizability
  • Humble theory
• Data literacy of teachers, admins…
• The need for creativity in LA
  • The need for creativity in assessment
• Learning analytics: singular or plural?
• Research methods, analysis techniques
• …

Educational Data Mining is concerned with developing, researching, and applying computerized methods to detect patterns in large collections of educational data – patterns that would otherwise be hard or impossible to analyze due to the enormous volume of data they exist within.

Educational Data Mining is an emerging discipline, concerned with developing methods for exploring the unique types of data that come from educational settings, and using those methods to better understand students, and the settings which they learn in.

(vs. LA?)

• data acquisition
• data preprocessing
• data mining
• validation of results

(vs. LA?)

• Prediction
• Clustering
• Relationship mining
• Distillation of data for human judgment
• Discovery with models

• User knowledge modeling
• User behavior modeling
• User experience modeling
• User profiling
• Domain modeling
• Trend analysis
• Adaptation and personalization

• Scientific inquiry and system evaluation
• Determining student model parameters
• Informing domain models
• Creating diagnostic models
• Creating reports and alerts for instructors, students and other stakeholders
• Recommending resources and activities

• Statistics and visualization
• Web mining
  • Clustering, classification, and outlier detection
  • Association rule mining and sequential pattern mining o Text mining

• Paradigms of research
  • scientific and positivistic
  • naturalistic and interpretive
  • critical theory

• Styles of research
  • Naturalistic and ethnographic
  • Historical and documentary
  • Longitudinal
  • Case studies
  • Experimental
  • Action research

• Data collection and analysis
  • Qualitative
    • Content analysis
    • Grounded theory
    • …
  • Quantitative
  • Mixed methods

• Readings
  • Whatever cases you're interested
  • Bring to the class!!
• Guest speakers: George & Jeff
• Time: 5:30pm
• Location: TBD