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· 분류 : 외국도서 > 인문/사회 > 심리학 > 일반
· ISBN : 9781138089013
· 쪽수 : 282쪽
목차
Part 1: Understanding Deep Comprehension
1. Prose Comprehension Beyond the Page
Jennifer Wiley and Tricia A. Guerrero
2. Prose Comprehension Beyond the Word Revisited
Rolf A. Zwaan
3. A Memory Retrieval View of Text Comprehension
Debra L. Long and Erin M. Freed
4. Standards of Coherence in Reading: Variations in Processing and Comprehension of Text
Marja Oudega and Paul van den Broek
5. What do We Think About When We Learn?
Sidney K. D’Mello
6. Reusing Neural Networks for Deep Comprehension
Manuel de Vega and David Beltran
7. What are We Reading for? A Disciplinary Literacy Perspective on Purpose
Susan R. Goldman and MariAnne George
Part 2: Using Technology to Increase Deep Comprehension
8. Learning Tasks in Electronic Environments: Advances Towards Interactive eTextbooks
Eduardo Vidal-Abarca et al.
9. How can FACT Encourage Collaboration and Self-correction?
Kurt VanLehn, et al.
10. Design Principles for Virtual Humans in Educational Technology Environments
Scotty D. Craig and Noah L. Schroeder
11. AutoTutor: An Intelligent Tutoring System and its Authoring Tools
Zhiqiang Cai and Xiangen Hu
12. The Unreasonable Effectiveness of AutoTutor
Andrew M. Olney
13. Scaffolding Adult Learners’ Reading Strategies in the Intelligent Tutoring System
Haiying Li and Whitney Baer
14. Learning Scientific Inquiry from a Serious Game that Uses AutoTutor
Keith Millis, et al.
Part 3: Measuring Deep Comprehension
15. Using Scenario-based Assessments to Measure Deep Learning
O’Reilly, John Sabatini, and Zuowei Wang
16. Eliciting Deeper Evidence through Conversation-Based Assessments
Blair Lehman and G. Tanner Jackson
17. NLP: Getting Computers to Understand Discourse
Danielle S. McNamara, et al.
18. Deep and Shallow Natural Language Understanding for Identifying Explanation Structure
Peter Hastings, et al.
19. Deep Comprehension of Text Revealed by Talking and Writing While Reading
Joseph P. Magliano, Karyn Higgs, and Keith Millis
20. Big Data for Thick Description of Deep Learning
David Williamson Shaffer
