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Thesis_Bao Wang.pdf (9.03 MB)

ETD Abstract Container

Abstract Header

Computational Approaches to Construct and Assess Knowledge Maps for Student Learning

Wang, Bao
http://orcid.org/0000-0002-9896-5542
http://rave.ohiolink.edu/etdc/view?acc_num=miami1658186699766213

Abstract Details

2022, Master of Science, Miami University, Computer Science and Software Engineering.
Knowledge maps have been widely used in knowledge elicitation and representation to evaluate and guide students’ learning. To improve upon current computational approaches to construct and assess knowledge maps, this thesis adopts a hybrid methodology that combines machine learning techniques and network science. By providing methods to extract features to evaluate knowledge maps and expand the assessment scope by accounting for group interaction and multiple expert maps, this thesis addresses the overall gap of current approaches for map construction and assessment. Specifically, this thesis offers three major contributions: 1) identifying necessary and sufficient graph features for knowledge maps evaluation, 2) assessing the role of group interaction during knowledge map construction and how group size affects the quality of map construction, and 3) providing an algorithmic framework to capture differences between student maps and multiple expert maps. Finally, this thesis examines the implications for the fields of network science and educational technology of applying knowledge maps in student learning.
Philippe Giabbanelli, Dr. (Advisor)
119 p.
Computer Science; Education
Knowledge maps; Map assessment; Graph features; Feature selection; Group interaction; Multiplicity of expert maps

Recommended Citations

Citations

  • Wang, B. (2022). Computational Approaches to Construct and Assess Knowledge Maps for Student Learning [Master's thesis, Miami University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=miami1658186699766213

    APA Style (7th edition)

  • Wang, Bao. Computational Approaches to Construct and Assess Knowledge Maps for Student Learning. 2022. Miami University, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=miami1658186699766213.

    MLA Style (8th edition)

  • Wang, Bao. "Computational Approaches to Construct and Assess Knowledge Maps for Student Learning." Master's thesis, Miami University, 2022. http://rave.ohiolink.edu/etdc/view?acc_num=miami1658186699766213

    Chicago Manual of Style (17th edition)

miami1658186699766213
174
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This open access ETD is published by Miami University and OhioLINK.