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Understanding Student Learning Using Learning Management Systems and Basic Analytics

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Presentation delivered to the Nevada Conference on Digital Learning, April 12, 2014 in Las Vegas, Nevada.

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Understanding Student Learning Using Learning Management Systems and Basic Analytics

  1. 1. Understanding Student Learning Using Learning Management Systems and Basic Analytics Michael Wilder and Matt Bernacki
  2. 2. What is learning analytics? “Learning analytics is the measurement, collection, analysis, and reporting of data about learners and their contexts, for the purposes of understanding and optimizing learning and the environments in which it occurs.” (1st International Conference on Learning Analytics and Knowledge, 2011)
  3. 3. Characterized as “an engine with five stages” • Capture • Report • Predict • Act • Refine (Campbell, DeBlois, and Oblinger, 2007)
  4. 4. Application • Predicting outcome achievement • Course and program dashboards • Curricular evaluation • Prioritizing learning outcomes • Set course and instructional policies • Defining academic quality (Bach, 2011)
  5. 5. Also good for • Curricular improvement • Intervention and support services “Early warning system” • Individualizing learning per student based on our interpretation of their data • Researching how students use the tools we build and learn with them. • Improving operational efficiency of the university • Comparison of performance with peer universities
  6. 6. Major research groups • Educational data mining “How can we extract value from these big sets of learning-related data?” • Learning analytics “How can we optimize opportunities for online learning?” • Academic analytics “How can we substantially improve learning opportunities and educational results at national or international levels?” (Ferguson, 2012)
  7. 7. Predictors and indicators • Activity indicators (Number of logins, time spent in the learning environment) • Performance indicators (Grades, quiz scores) • Dispositional indicators (Age, GPA, prior learning experience, financial status) • Student artifacts (Essays, blog and discussion forum posts, media productions (Brown, 2012)
  8. 8. A CASE STUDY: BLACKBOARD LEARN
  9. 9. Basic Data Analysis Tools Where to find them
  10. 10. Course analytics • All User Activity inside Content Areas • Course Activity Overview • Course Performance • Overall Summary of User Activity • Student Overview for Single Course • User Activity in Forums • User Activity in Groups Mapping It Out, Part III: Closing The Loop
  11. 11. • select cm.course_name, count(cc.pk1) as LearningModules from course_main cm, course_contents cc where cm.pk1 = cc.crsmain_pk1 and cc.cnthndlr_handle = „resource/x-bb-lesson‟ and cm.pk1 in [list of courses in given term] group by cm.course_name order by cm.course_name;
  12. 12. • select cm.course_name, count(*) replies from forum_main fm left join msg_main mm on fm.pk1 = mm.forummain_pk1 left join conference_main confmain on confmain.pk1 = fm.confmain_pk1 left join conference_owner co on co.pk1 = confmain.conference_owner_pk1 left join course_main cm on cm.pk1 = co.owner_pk1 where mm.msgmain_pk1 is not null and co.owner_table = 'COURSE_MAIN„ and co.owner_pk1 in [list of courses in given term] group by cm.course_name;
  13. 13. Analytics in education can be viewed as existing in various levels, ranging from individual student, classroom, department, university, region, state/province, national, and international. Buckingham Shum (2012) groups these organizational levels as micro-, meso-, and macroanalytics layers. What can analytics reveal about learning in general?
  14. 14. ANALYTICS FOR LEARNING
  15. 15. Research Question How does motivation and learning behavior influence reading comprehension? Environment nStudy, a web browser with tools to support learning Method 1) Survey on motivation 2) Pretest 3) Observe behavior during 20 minutes of reading 4) A comprehension test 5) ANALYTICS Analytics Look at number of times a student used a tool and its relationship to learning Findings …
  16. 16. Mastery  SRL  Learning Performance Avoidance goals are not ideal for learning 25 Highlighting Note taking Reviewing annotation s Seeking more information Monitoring progress Mastery Approach Performance Approach Textbase Comprehension Increase (%) Situation Model Comprehension Increase (%) Performance Avoidance ACHIEVEMENT GOALS SRL BEHAVIORS LEARNING OUTCOMES
  17. 17. Research Question Does the student’s reason for seeking help from software help affect whether the help helps? Environment Cognitive Tutor, an intelligent tutoring system for math Method 1) Survey students‟ achievement goals 2) Observe their problem solving behaviors in CT 3) ANALYTICS 26
  18. 18. Analytics Findings • Achievement goals predicted students‟ tendency to learn from hints • Students with Mastery approach goals were more likely to learn from hints • Those with strong performance approach goals were less likely to learn from hints Student ID Outcome Duration stu_324w8b BUG 69 stu_324w8b BUG 6 stu_324w8b BUG 5 stu_324w8b INITIAL_HINT 6 stu_324w8b HINT 2 stu_324w8b HINT 4 stu_324w8b OK 19 stu_324w8b OK 12 stu_324w8b ERROR 15 stu_324w8b OK 4
  19. 19. Research Question Can educating students about learning principles and showing them how use them influence their behavior and learning in an online course? Environment Research Methods course in Blackboard Learn Method 1) Train 30 students re: Learning Principles; don‟t train 30 others 2) Let them learn 3) ANALYTICS 28Analytics =

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