Dynamics of Student Modeling: A Theory, Algorithms, and Application to Quantum Mechanics DocumentsThis material has 17 associated documents. Select a document title to view a document's information. Main DocumentDynamics of Student Modeling: A Theory, Algorithms, and Application to Quantum Mechanics
written by
Lei Bao
A good understanding of how students understand physics is of great importance for developing and delivering effective instructions. This research is an attempt to develop a coherent theoretical and mathematical framework to model the student learning of physics. The theoretical foundation is based on useful ideas from theories in cognitive science, education, and physics education. The emphasis of this research is made on the development of a mathematical representation to model the important mental elements and the dynamics of these elements, and on numerical algorithms that allow quantitative evaluations of conceptual learning in physics.
Published January 1, 1999
This file is included in the fulltext index. Primary Documents (16)Table of ContentsA good understanding of how students understand physics is of great importance for developing and delivering effective instructions. This research is an attempt to develop a coherent theoretical and mathematical framework to model the student learning of physics. The theoretical foundation is based on useful ideas from theories in cognitive science, education, and physics education. The emphasis of this research is made on the development of a mathematical representation to model the important mental elements and the dynamics of these elements, and on numerical algorithms that allow quantitative evaluations of conceptual learning in physics.
Released under a © Lei Bao
Published January 1, 1999
This file is included in the fulltext index. Chapter 1: Physics Education: the Physics of Education in Education of PhysicsChapter 1 provides a context for this research study within Physics Education Research.
Released under a © Lei Bao
Published January 1, 1999
This file is included in the fulltext index. Chapter 2: Student Models of PhysicsChapter 2 introduces the model of student learning of physics. A mathematical representation is developed for the physical models and student model states.
Released under a © Lei Bao
Published January 1, 1999
This file is included in the fulltext index. Chapter 3: Model Analysis Algorithms I: The Concentration FactorThis chapter presents a method to study the structure of student responses in a multiplechoice test, providing information on the distribution of student responses. The results are used to analyze the state of student mental models. Sample applications with FCI data confirm the method.
Released under a © Lei Bao
Published January 1, 1999
This file is included in the fulltext index. Chapter 4: Model Analysis Algorithms II: Model EstimationThis chapter presents an algorithm for quantitative evaluations of student mental models that goes beyond simple scores. This algorithm can provide better information about student understandings and how to improve instructions. A great deal of information can be retained for easy extraction and use. Graphic representations make the results much easier to understand.
Released under a © Lei Bao
Published January 1, 1999
This file is included in the fulltext index. Chapter 5: Refinements and ExtensionsThis chapter contains examples of student model analysis that require modifcations and additions to the algorithms presented previously. Mixed model states, coherence of responses, and model triggers are explored.
Released under a © Lei Bao
Published January 1, 1999
This file is included in the fulltext index. Chapter 6: Model Based Research on Student Difficulties with Quantum MechanicsThis chapter introduces studies on student difficulties in learning Quantum Mechanics. The model evaluation process is used to investigate student understanding of classical prerequisites for quantum mechanics and important quantum concepts.
Released under a © Lei Bao
Published January 1, 1999
This file is included in the fulltext index. Chapter 7: Student Difficulties with Classical PrerequisitesThis chapter presents results of studies of student understanding of potential energy diagrams, total energy, and probability in classical mechanics. This background is important for the quantum mechanics. Tutorials are presented to help students with these topics, although they remain difficult.
Released under a © Lei Bao
Published January 1, 1999
This file is included in the fulltext index. Chapter 8: Student Models of Quantum MechanicsThis chapter presents research on several common student models in quantum mechanics. Instructional approaches and a multiple choice test to test them are described.
Released under a © Lei Bao
Published January 1, 1999
This file is included in the fulltext index. Chapter 9: Summary and SpeculationsThis chapter summarizes the new theory of student models and the numerical methods developed.
Released under a © Lei Bao
Published January 1, 1999
This file is included in the fulltext index. Appendix A: FCI and FMCE testThe appendix provides two standard concept tests used in this research.
Published January 1, 1999
Appendix B: Supplemental Calculations and Simulations for the Concentration FactorThis appendix provides examples of the student model analysis.
Released under a © Lei Bao
Published January 1, 1999
Appendix C: Supplemental Calculations for Model Evaluations and a New MultipleChoice Instrument on Newton III with Isolated Physical FeaturesThis appendix gives an example calculation involving multimodel states. A concept survey on Newton's Third Law is also provided.
Released under a © Lei Bao
Published January 1, 1999
Appendix D: Questions to Probe the Student Understandings on Classical Prerequisites of Quantum MechanicsThis appendix contains concept questions on classical and quantum mechanics.
Released under a © Lei Bao
Published January 1, 1999
Appendix E: Quantum TutorialsThis appendix contains three tutorials on quantum mechanics and classical prerequisites for quantum mechanics. Topics include Potential Energy Diagrams, Classical Probability, and LED's  Energy Band Structure.
Released under a © Lei Bao
Published January 1, 1999
BibliographyBibliography for the research work.
Released under a © Lei Bao
Published January 1, 1999

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