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Approximate Plan of the Course

Approximate Plan of the Course. 21.4. Introduction 28.4 . ActiveMath Vorstellung /Introduction to ActiveMath 12.5. Benutzermodellierung/user modeling 19 . 5. . in structional design 2.6. support of meta-cognition 9.6. XML knowledge representation, adaptive hypermedia

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Approximate Plan of the Course

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  1. Approximate Plan of the Course • 21.4.Introduction • 28.4. ActiveMath Vorstellung /Introduction to ActiveMath • 12.5. Benutzermodellierung/user modeling • 19.5. .instructional design • 2.6. support of meta-cognition • 9.6.XML knowledge representation, adaptive hypermedia • 16.6. collaborative learning/ Lernen in Gruppen • 23.6. diagnosis • 30.6. action analysis • 7.7 further topics (tutorial dialogues, mobile learning..) • 14.7. student project reports

  2. Learning by Constructing Knowledge Interpreting information rather than recoding KNOWLEDGE CONSTRUCTION Make sense of information Relate to preexisting knowledge relate to personal experience elaborate new information restructure existing schemas internal process -> self-regulate, -inspect when, why, how?

  3. What are Meta-Cognitive Activities? When, why, how (cognitive, strategies and self) • self-regulation • planning and monitoring, evaluating problem solving • planning and monitoring of learning • Role in collaborative learning • constructing relationships between concepts • reflection • Self-explanation of examples • self-explanation of exercises • analysis • actively seeking help or information

  4. How to Stimulate Meta-Cognition • PROVIDE structure(s) • REQUEST articulation of strategies and knowledge • for self-explaining examples, exercises • why is this step done? • how does the step correspond to the plan? • Is this solution finished? (for monitoring) • compare the solutions! • MAKE AWARE: erroneous examples • Web! • More in Wizard of Oz experiments

  5. Problem solving: How to Solve it, George Polya • Understand the problem • Plan a solution • Execute the plan, keep track of solution • Analyze whether it worked • Generalize solution Bild von Buch und Polya

  6. Open Learner Model

  7. Andes: Sample instructional material Problem Statement Worked out solution Situation Diagram Free Body Diagram

  8. SE-Coach of Andes • User interface: • workbench presents examples (PME, latency data) • incrementally promts SE • has tools for SE (browser, templates) • student model (BN) for plan recognition and mastery from reading, menu selection, template filling... • BN includes model of correct SE with rules, action nodes • adequate minimal help when?: if SE not performed and • due to lack of attention, guide to example parts. • If due to lack of knowledge, request SE

  9. The Interface: Masking User Interface • Helps students focus attention and SE-Coach monitor it

  10. SE-Coach of Andes, Help Self-explanation of examples • Records time of reading steps of worked-out example (latency data) • If time too short and prediction of prerequisite low then promt explanation menu (+support) • Menus contain either prerequisite Newtonian Physics laws or plan steps

  11. SE-Coach of Andes: Help, promts Solution step xxx Self-explain: This fact is true because... The role of this fact in the solution plan is to ... This choice is correct because... The role of this choice in the solution plan is to... Using the rule browser and plan browser

  12. Prompts to Self-Explain • Stimulate self-questioning on relevant explanations

  13. SE-Coach Hints

  14. Justify Solution Steps: Rule Browser

  15. Identify Goal Structure - Plan Browser • Encodes abstract solution plan

  16. SE exercises in Geometry Explanation Tutor self-explanation of exercises • students explain steps in own words or name of principle • evaluate student‘s restricted input (correct? category?) • helps through restricted dialogue to arrive at mathematically precise explanation • knowledge-based: hierarchy of 149 explanation categories. For each rule • one or more correct and complete ways to state each geometry rule • numerous incomplete or incorrect ways

  17. Category: complem-angles-sum-180 the sum of the measures of compl angles is 180 degrees Category: complem-angles-sum-180 compl angles are 180 degrees Geometry Explanation Tutor, example explanations complete and correct incomplete or incorrect

  18. Geometry Explanation Tutor, example

  19. SciWise and ThinkerTools * Meta-cognitive activities: hypothesize investigate Formulate Question Inquiry cycle analyze patterns transfer model

  20. ThinkerTools: Form for Inquiry Learning Project outline • Question • which general topic chosen, Why? • Which questions to investigate,Why? • Hypothesize • write down predictions, 2 different hypotheses • explaination for hypothesis • Investigate • describe how you investigate, justify this way • show data etc in table, graph,.. • Analyze • describe patterns • discuss (poss errors) • Model • summarize conclusions, relate to question • how data support conclusion

  21. SciWise: reflective goal-driven inquiry Task advisors General advisors inquirer presenter assessor cognizer socializer questioner hypothesizer investigator analyzer modeler edvaluator Inventor planner reasoner representer collaborator debator mediator communicator advisors incl cognitive and social aspects

  22. A Sequence of interactions with agents • Student start research by consulting Task Advisor • Get advice from General Purpose Advisor • Work with system Developer Advisor (Modifier) to try to improve General Purpose Advisor

  23. Advisor Agent: Helena Hypothesizer • Hi, here are some things I can do for you: • (1)describe characteristics of a good hypothesis • (2) suggest strategies for creating hyps and advisors • (3) evaluate your hyps to see whether they need revision ...good strategy to start with...the Inventor might be asked

  24. SciWise advisor: Ian Inventor • So you need help coming up with ideas for your hypotheses? I‘m the right advisor for that. I know billions of ways to gernerate ideas. Pick the strategy that best suits you • fast and loose • control freak. Good choice! Fast and loose is my favorite Relax and turn your mind loose.Think of as many ideas as you can find in 5 minutes. The ideas can be crazy or serious...

  25. SciWise Agents‘ knowledge BDI agent knows: its expertise, goals when useful, how to get more info, decide what to do, learn, other agents agent has condition-action rules to control behaviour IF another advisor recommends you THEN pop up IF start THEN show examples of how others did this task agent has knowledge base for advice and assistance strategies for achieving goals (be inventive...) which advisors can help for a problem assessment criteria examples of good and bad hypotheses

  26. Mind Maps

  27. Make Connections (project) • between concepts in different contexts: • Fraction: proportion – increase/decrease – part-of • between maths and real world problems • Decimals: 2,50 = 2 euro + 50 cent • 2,5 = 2 hours + 30 minutes

  28. ‚IMPROVE method‘(coll mathematics) • meta-cognitive prompts: • what is the problem? Read aloud! Describe concepts in own words! Which category of problems? • differences /sim of this and other problems? • Which strategy/principle is appropriate here? How can the plan carried out? Why is the strategy appropriate? • explain reasoning during problem solving by answering prompts • when failed to solve or no agreement , then show prompts

  29. Erroneous Examples

  30. Erroneous Examples, Bruchrechung

  31. Protocols of Human Dialogs, 69 prompts • Any thought about this sentence? • Do you want to say something about this? • Could you explain what you are thinking? • Could you explain the concept discussed in the sentence? • Please explain what this sentence says • what do you think? • What could you learn from the paragraph? • Anything else? • Why? • How‘s that? ....

  32. Wizard of Oz • Write meta-cognitive prompts and actions on cards • group: learner, tutor, protocol • add actions and prompts later if necessary • How to foster self-regulation? • which types of meta-reasoning for problem solving/ for learning /for self-control? • Which (prompts for) SE and other meta-cognition? • does explicit meta-cognitive guidance help? • which knowledge would an inventor agent need? • … • Which functionalities of erroneous examples?

  33. Woz instructional design:Jörg,… • Newtonean physics • Arrage question with dependency • Make student understand formula: diagams, real world actions • Provide more knowledge about gravity, electo-magnetics, • Tried to ask for similarities and differences, dependencies • Ask – don‘t tell (basic facts, support by examples)

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