5. Intelligent monitoring and evaluation of digital geometry figures drawn by students
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Arindam Mondal
Abstract
This chapter proposes a feasible implementation of a student-specific automated system of learning and tutoring of school level geometry concepts. Unlike the usual geometry drawing or tutoring software, the proposed system can intelligently assess the student’s understanding of a geometry concept by testing the student with relevant problems and accordingly takes him to a higher or lower level of concepts. The diagram drawn by a student in a digital interface is evaluated to find the degree of geometric correctness which is otherwise a challenging task. For tutoring primary school level geometry, a figure database with different difficulty levels is maintained while for secondary school level tutoring, earlier developed text-to-diagram drawing functionality is incorporated. The novelty of the tutoring system lies in the fact that no such system exists that can draw, recognize and compare digital geometry diagrams and adjust the diagram based content/problems through different learning and testing stages based on dynamic student-specific responses. The representative test cases cited in this study clearly demonstrates the usefulness and intelligent treatment of the system.
Abstract
This chapter proposes a feasible implementation of a student-specific automated system of learning and tutoring of school level geometry concepts. Unlike the usual geometry drawing or tutoring software, the proposed system can intelligently assess the student’s understanding of a geometry concept by testing the student with relevant problems and accordingly takes him to a higher or lower level of concepts. The diagram drawn by a student in a digital interface is evaluated to find the degree of geometric correctness which is otherwise a challenging task. For tutoring primary school level geometry, a figure database with different difficulty levels is maintained while for secondary school level tutoring, earlier developed text-to-diagram drawing functionality is incorporated. The novelty of the tutoring system lies in the fact that no such system exists that can draw, recognize and compare digital geometry diagrams and adjust the diagram based content/problems through different learning and testing stages based on dynamic student-specific responses. The representative test cases cited in this study clearly demonstrates the usefulness and intelligent treatment of the system.
Chapters in this book
- Frontmatter I
- Preface V
- Contents XI
- 1. Medical color image enhancement: Problems, challenges & recent techniques 1
- 2. Exploring the scope of intelligent algorithms for various community detection techniques 19
- 3. An unsupervised graph-based approach for the representation of coronary arteries in X-ray angiograms 43
- 4. A study of recent trends in content based image classification 65
- 5. Intelligent monitoring and evaluation of digital geometry figures drawn by students 95
- 6. Rough set and soft set models in image processing 123
- 7. Quantum inspired simulated annealing technique for automatic clustering 145
- 8. Intelligent greedy model for influence maximization in multimedia data networks 167
- Index 183
Chapters in this book
- Frontmatter I
- Preface V
- Contents XI
- 1. Medical color image enhancement: Problems, challenges & recent techniques 1
- 2. Exploring the scope of intelligent algorithms for various community detection techniques 19
- 3. An unsupervised graph-based approach for the representation of coronary arteries in X-ray angiograms 43
- 4. A study of recent trends in content based image classification 65
- 5. Intelligent monitoring and evaluation of digital geometry figures drawn by students 95
- 6. Rough set and soft set models in image processing 123
- 7. Quantum inspired simulated annealing technique for automatic clustering 145
- 8. Intelligent greedy model for influence maximization in multimedia data networks 167
- Index 183
