Technologies that Enhance Learning

1. Technologies that Enhance Learning W. Lewis Johnson Center for Advanced Research in Technology for Education (CARTE) Univ. of So. Calif. / Info. Sci. Inst. http://www.isi.edu/isd/carte johnson@isi.edu

2. Purpose of CARTE • CARTE is: the Center for Advanced Research in Technology for Education at USC / ISI • CARTE is a leader in: • Developing new technologies • Applying them in real learning environments • Our goal: instruction that is • More responsive to student needs • More interactive and collaborative • Motivating and engaging

3. The Next Wave: On-Line Education • Colleges are increasingly delivering instruction on line • Learning materials (lectures, notes) accessed via the Web • Homework submitted via email or on-line quizzes • On-line discussions instead of classroom discussions • Course data managed by course management systems (e.g., Blackboard, Mallard)

4. Shortcomings of On-Line Instruction • Most on-line courses do not differ significantly from conventional courses • Guidance and feedback are limited • Scoring of right & wrong answers • Email places new burdens on instructor • Limited ability to fit the needs and interests of individual learners

5. Example: Introductory Chemistry at USC • Department of Chemistry has incorporated technology extensively into curriculum • Online grades, and exam keys • 3D chemical models, animations • Interactive tutorials, web quizzes • Simulations • Still, they identified unmet needs: • Tutorials that adapt to learner responses • Exercises that focus on learning and applying chemical principles

6. Objectives of Our Research • On-line multimedia that significantly improves (on) classroom instruction • Lessons that keep learners highly motivated • Interactive problem solving experiences, with guidance and feedback • Software that helps learners meet individual learning goals

7. What the Student Sees Now (on demand web cast) PDF or PowerPoint Microsoft Media Player

8. USC DEN – Webcasting (updates) Source encoding High resolution image sync. direct from multiple sources) (computer, video, document camera) Live chat, polling, etc.

9. DEN Technology In The Future • More use of on-line lecture notes and exercises, less talking head video • Improve learning experience for remote AND on-campus students • More support for interactive, collaborative exercises • Greater use of innovative technologies, e.g., guidebots

10. Guidebots • Animated characters that: • Interact with students in learning envs. • Model skills being taught • Help keep learning on track • Act as guides, tutors, teammates • Engage in instructional dialog • Enhance motivation and interest

11. Guidebot-Assisted Learning Projects at CARTE • Virtual reality training environments • Application: military training • Interactive multimedia dramas • Application: health communications • On-line guided problem solving • Applications: medicine, dentistry, chemistry, engineering

12. Roles of Guidebot • To provide voiceover commentary • To ask and answer questions • To offer advice and guidance • To assess learner knowledge • To intervene motivationally

13. Lessons from Educational Psychology • Course should support active learning • Guidebots support individual initiative and sense-making activities • Course should obey principles ofmultimedia learning • Guidebots are designed to obey these principles • Course should enhance learnermotivation • Guidebots enhance both cognitive and motivational aspects of learning

14. Lessons from Expert Tutors • Expert tutors attend to both motivational and cognitive factors (Lepper et al., 1993) • Inspiring learner curiosity and interest • Challenging learners to test their limits • Offering help and reassurance when they encounter difficulties • Our goal is to impart these characteristics into educational software

15. Adele (Shaw, Johnson, Ganeshan) • Designed for use with Web-based courseware • Application: case-based health science courseware • Monitors students solving cases • Gives advice, hints, feedback • Explains rationales for actions • Intervenes if the student makes serious mistakes • Evaluates student performance • Records student performance for later review

16. Applications of Adele • Emergency trauma care • Collaborator: Beverly Wood, MD • Clinical problem solving in medicine • Collaborators: Allan Abbott, MD, Beverly Wood, MD • Clinical problem solving in dentistry • Collaborators: Roseann Mulligan, DDS, School of Gerontology

17. Examples

18. Components of Diagnostic Tutoring • Probablilistic reasoner • To evaluate hypotheses and actions • Diagnostic strategy tracking • Student model • To select content for interventions • Tutorial strategy

19. Student Model • Current implementation tracks student’s understanding of causal relations between physiology and disease • Reflects instructional objectives for undergraduate medical instruction • Overlay model updated • When tutor informs the learner of relationship • When student confirms knowledge of relationship

20. Diagnostic Focus of Attention = instructional objective Smoking Recurrent viral infections Current focus of attention Chronic bronchitis Chronic bronchial inflammation Chronic air passage obstruction Cough

21. Mission Rehearsal Exercise (ICT)

22. An Evaluation of Adele • HBR version tested in focus group test with medical students • Students worked in dyads • Findings: • Students liked the way Adele uses hints to lead them in the right direction • Students tended to ask for hints only when Adele prevented students from proceeding (at diagnosis) • Students liked Adele’s questions about motivation, and spent significant time discussing them

23. Relevant Principles of Multimedia Learning • Guidebots work in part because they adhere to the principles of multimedia learning: • Multimedia Principle • Temporal Contiguity Principle • Coherence Principle • Modality Principle • Individual Differences Principle

24. Other Relevant Psychological Factors • Motivational factors: • Control • Curiosity • Challenge • Confidence • Cognitive factors: • Goal orientation • Inquiry and self-explanation • Meta-cognition • Learning through problem solving

25. Problem 1 • Describe an instructional technology method that supports collaborative learning. Address the following questions: • How does collaboration promote learning? • Under what conditions is it most effective in promoting learning? • What makes your particular method effective, and why?

26. Problem 2 • Describe an instructional technology method that supports problem solving. Address the following questions: • How does problem solving promote learning? • Under what conditions is it most effective in promoting learning? • What makes your particular method effective, and why?

27. Problem 3 • Describe an instructional technology method that employs multimedia. Address the following questions: • How does multimedia promote learning? • Under what conditions is it most effective in promoting learning? • What makes your particular method effective, and why?