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Filtering by: Creator Hall, Lynn L. Remove constraint Creator: Hall, Lynn L. Committee Member Tadepalli, Prasad Remove constraint Committee Member: Tadepalli, Prasad Degree Level Doctoral Remove constraint Degree Level: Doctoral

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  • Effectiveness of integration of internet technologies in support of teaching and learning computer science programming

    Creator:
    Hajebi, Mojgan
    Abstract:
    In spite of wide spread adoption of the internet technology in teaching and learning, little research exists on the use and the effect of web incorporation in teaching and learning. Immediate clarification of how, when, and for whom the web integration in education is beneficial is needed. This qualitative study...
    Resource Type:
    Dissertation
    Full Text:
    Programmi ng Abstract Approved: - (L--l"-- ~~==-.!~-------- Margaret L. Niess In spite of wide spread

  • Computing Resource Usage as a Factor of Student Success

    Creator:
    Moissinac, Béatrice
    Abstract:
    Learning Analytics and other branches of Educational Research such as Computing Education Research (CER) implicitly assume that students, especially college students, have no barriers to access learning platforms or software packages. This assumption may be attributed to such pervasive beliefs such as "everyone has a device", or "everyone can access...
    Resource Type:
    Dissertation

  • Conceptual Representations within the Social and Material Contexts of an Engineering Workplace and Academic Environments

    Creator:
    Barner, Matthew S.
    Abstract:
    Situated cognition theory emphasizes the role that social and material contexts have on learning and knowledge application. Several studies of engineering workplace environments have noted differences between the social and material contexts of the workplace and those of undergraduate engineering education. No existing research has studied the social and material...
    Resource Type:
    Dissertation

  • Analytical Methods for Improving Causal Inference

    Creator:
    Sinha, Meghamala
    Abstract:
    Causal inference is an important analytical tool to bridge the gap between prediction and decision-making. However, learning a causal network solely from data is a challenging task. In this work, various techniques have been explored for a better and improved causal network learning from data. Firstly, the problem of learning...
    Resource Type:
    Dissertation
    Full Text:
    information Criterion (BIC), defined as BIC(G | D) =| θ | × log(n)2× log(L(G | D)) where log(L(G | D)) is

  • Inclusive Software Design and Its Methods for Beyond-WIMP User Interfaces

    Creator:
    Fallatah, Abrar
    Abstract:
    While digital inclusivity researchers and software practitioners have been trying to address exclusion biases in Windows, Icons, Menus, and Pointers (WIMP) user interfaces (UIs) for a long time, little has been done to investigate if and how inclusive software design and its methods that have been devised for WIMP UIs...
    Resource Type:
    Dissertation
    Full Text:
    /cafes depicted on a map of the university campus. C1= Dining Hall Cafe, C2= Engineering School Cafe, C3

  • Learning and Improving Policies for Probabilistic Planning Problems

    Creator:
    Issakkimuthu, Murugeswari
    Abstract:
    In this work, we study the problem of learning and improving policies for probabilistic planning problems. In the first part, we train neural network policies for probabilistic planning problems modeled as factored Markov decision problems. The objective is to train problem-specific neural networks via supervised learning to imitate the action...
    Resource Type:
    Dissertation
    Full Text:
    L+1 layers of nodes. Z l = {zlk} denotes layer l, where zlk is the k’th node in layer l and its

  • New learning modes for sequential decision making

    Creator:
    Judah, Kshitij
    Abstract:
    This thesis considers the problem in which a teacher is interested in teaching action policies to computer agents for sequential decision making. The vast majority of policy learning algorithms o er teachers little flexibility in how policies are taught. In particular, one of two learning modes is typically considered: 1)...
    Resource Type:
    Dissertation
    Full Text:
    Objective U(θ, T ) . . . . . . . . . . . . . . . . . . 11 2.4 Critique Data Objective L(θ, C

  • Simulator-Defined MDP Planning with Applications in Natural Resource Management

    Creator:
    Alkaee Taleghan, Majid
    Abstract:
    This work is inspired by problems in natural resource management centered on the challenge of invasive species. Computing optimal management policies for maintaining ecosystem sustainable is challenging. Many ecosystem management problems can be formulated as MDP (Markov Decision Process) planning problems. In a simulator-defined MDP, the Markovian dynamics and rewards...
    Resource Type:
    Dissertation
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    would also like to thank Kim Hall, Professor H. Jo Albers, and Mark Crowley for their collaboration on

  • Sliding-mode control of the super maneuverable aircraft

    Creator:
    Koo, Chang Sul
    Abstract:
    In this thesis, A nonlinear methodology for the control of the highly maneuverable, high performance aircraft HARV (F-18) is studied by using sliding-mode control (SMC). This control law, which takes a continuous function when the input constraints are not considered, satisfies the reachability condition by which concerned states are driven...
    Resource Type:
    Dissertation
    Full Text:
    '(x,t) for i = 2, , m and _g l 2ax 0. By substituting (2.5.9) for u2 into (2.5.8), the equation of

  • Explanations and Processes to Enable Humans to Assess AI with Respect to Manipulable Properties

    Creator:
    Dodge, Jonathan E.
    Abstract:
    Assessing AI systems is difficult. Humans rely on AI systems in increasing ways, both visible and invisible, meaning a variety of stakeholders need a variety of assessment tools (e.g., a professional auditor, a developer, and an end user all have different needs). We posit that it is possible to provide...
    Resource Type:
    Dissertation
    Full Text:
    throughout a training cycle . . . . . . . . 177 L Data Appendix - CNNs trained to overfit to opponents