Causal model progressions as a foundation for intelligent learning environments

Artificial Intelligence

Volumn 42, Issue 1, 1990, Pages 99-157

  White, Barbara Y ^a   Frederiksen, John R ^a  

^a BBN TECHNOLOGIES   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; ELECTRIC NETWORKS--EDUCATION;

CAUSAL MODEL PROGRESSIONS; INTELLIGENT LEARNING ENVIRONMENTS;

EDUCATION;

EID: 0025383364     PISSN: 00043702     EISSN: None     Source Type: Journal    
DOI: 10.1016/0004-3702(90)90095-H     Document Type: Article

References (52)

1. Learning to program in LISP
2. Diagnostic models for procedural bugs in basic mathematical skills
3. Pedagogical, natural language and knowledge engineering techniques in SOPHIE I, II and III
4. Repair theory A generative theory of bugs in procedural skills
5. Categorization and representation of physics problems by experts and novices
6. Qualitative student models
7. Potential difference and current in simple electric circuits A study of students' concepts
8. Component models of physical systems
9. Reasoning from first principles in electronic troubleshooting
10. Causal and teleological reasoning in circuit recognition
11. How circuits work
12. Assumptions and ambiguities in mechanistic mental models
13. A qualitative physics based upon confluences
14. Phenomenology and the evolution of intuition
15. The nature of conceptual understanding in biomedicine: The deep structure of complex ideas and the development of misconceptions
16. Understanding reflective problem solving
17. Development of an articulate instructional system for teaching arithmetic procedures
18. Qualitative process theory
19. Causal reasoning about quantities
20. Using qualitative simulation to generate explanations
21. Mental models and understanding: A problem for science education
22. Intelligent tutoring systems for electronic troubleshooting
23. Intelligent tutors as intelligent testers
24. The genetic graph: A representation for the evolution of procedural knowledge
25. A qualitative approach to electricity
26. The role of a mental model in learning to operate a device
27. Commonsense reasoning about causality: Deriving behavior from structure
28. Expert and novice performance in solving physics problems
29. Dynamic student modelling in an intelligent tutor for LISP programming
30. Guidon-Watch: A graphic interface for viewing a knowledge-based system
31. OREO: Adding orientation to a dynamic qualitative simulation
32. On looking into the black box: Prospects and limits in the search for mental models
33. Understanding instructions The role of an explanatory schema
34. Learning to program = learning to construct mechanisms and explanations
35. Meno-II: An AI-based programming tutor
36. Reinventing electricity
37. Explaining complex engineering devices
38. The use of aggregation in causal simulation
39. Modeling expertise in troubleshooting and reasoning about simple electric circuits
40. QUEST: Qualitative understanding of electrical system troubleshooting
41. Progressions of qualitative models as a foundation for intelligent learning environments
42. Intelligent tutoring systems based upon qualitative model evolutions
43. Qualitative models and intelligent learning environments
44. ThinkerTools: Enabling children to understand physical laws
45. Qualitative analysis of MOS circuits