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Ruppert, Janet – ProQuest LLC, 2023
Teenagers today are coming of age under unprecedented, pervasive networks of institutional mass surveillance technologies. Surveillance technologies spreading in youth spaces are impacting young people's prospects today and are expected to continue in the future. Additionally, today's teenagers will be tomorrow's decision-makers, tasked with…
Descriptors: Social Justice, Observation, Telecommunications, Algorithms
Ménager, David H. – ProQuest LLC, 2021
This dissertation presents a novel theory of event memory along with an associated computational model that embodies the claims of view which is integrated within a cognitive architecture. Event memory is a general-purpose storage for personal past experience. Literature on event memory reveals that people can remember events by both the…
Descriptors: Artificial Intelligence, Computer Software, Models, Information Processing
Michael Joseph King – ProQuest LLC, 2022
This research explores the emerging field of data science from the scientometric, curricular, and altmetric perspectives and addresses the following six research questions: 1.What are the scientometric features of the data science field? 2.What are the contributing fields to the establishment of data science? 3.What are the major research areas of…
Descriptors: Data Science, Bibliometrics, Qualitative Research, Statistical Analysis
Jiaqing Tong – ProQuest LLC, 2022
Though efforts have been made for centuries, how concepts are represented in the brain is still elusive. The embodiment view claims that the sensory, motor and other brain areas through which people acquire concept information during life experiences represent this information during concept retrieval. Some compelling neurobiological evidence…
Descriptors: Concept Formation, Brain Hemisphere Functions, Evidence, Models
Zhun Deng – ProQuest LLC, 2021
Machine learning has achieved state-of-the-art performance in many areas, including image recognition and natural language processing. However, there are still many challenges and mysteries attracting numerous researchers. This dissertation comprises a series of works concerning problems at the intersection of computer science theory, adversarial…
Descriptors: Learning Analytics, Instructional Design, Artificial Intelligence, Computer Science
Neftali David Watkinson Medina – ProQuest LLC, 2020
Contemporary research in cognitive and neurological sciences confirms that human brains perform object detection and classification by identifying membership to a single class. When observing a scene with various objects, we can quickly point out and answer queries about the object we recognize, without needing to know what the unknown objects…
Descriptors: Classification, Artificial Intelligence, Technology Uses in Education, Educational Technology
Demszky, Dorottya – ProQuest LLC, 2022
Language is central to education, being the core medium of instruction. Researchers and practitioners have long used manual methods to analyze instructional language like classroom discourse and instructional texts, with the goal of facilitating student-centered instruction. In this dissertation, I offer three studies demonstrating how natural…
Descriptors: Natural Language Processing, Student Centered Learning, Textbook Content, Evaluation Methods
Rachmatullah, Arif – ProQuest LLC, 2021
This dissertation conducted a science classroom intervention using two instructional approaches, computational modeling and paper-based pictorial modeling, in the context of food webs. A series of research papers were written on the impact of the intervention on students' attitudes and learning, and on teachers via professional development and…
Descriptors: Teaching Methods, Science Instruction, Food, Intervention
Yun, Xi – ProQuest LLC, 2013
Constraint satisfaction problems are a powerful way to abstract and represent academic and real-world problems from both artificial intelligence and operations research. A constraint satisfaction problem is typically addressed by a sequential constraint solver running on a single processor. Rather than construct a new, parallel solver, this work…
Descriptors: Problem Solving, Programming, Mathematics, Satisfaction
Deng, Houtao – ProQuest LLC, 2011
This dissertation transforms a set of system complexity reduction problems to feature selection problems. Three systems are considered: classification based on association rules, network structure learning, and time series classification. Furthermore, two variable importance measures are proposed to reduce the feature selection bias in tree…
Descriptors: Classification, Mathematics, Programming, Artificial Intelligence
Beemer, Brandon Alan – ProQuest LLC, 2010
The research presented in this dissertation focuses on the organizational and consumer need for knowledge based support in unstructured domains, by developing a measurement scale for dynamic interaction. Addressing this need is approached and evaluated from two different perspectives. The first approach is the development of Knowledge Based…
Descriptors: Artificial Intelligence, Intellectual Disciplines, Interaction, Classification
Wu, Stephen Tze-Inn – ProQuest LLC, 2010
This thesis aims to define and extend a line of computational models for text comprehension that are humanly plausible. Since natural language is human by nature, computational models of human language will always be just that--models. To the degree that they miss out on information that humans would tap into, they may be improved by considering…
Descriptors: Comprehension, Semantics, Syntax, Short Term Memory
El-Bathy, Naser Ibrahim – ProQuest LLC, 2010
The study of this dissertation provides a solution to a very specific problem instance in the area of data mining, data warehousing, and service-oriented architecture in publishing and newspaper industries. The research question focuses on the integration of data mining and data warehousing. The research problem focuses on the development of…
Descriptors: Research Problems, Information Retrieval, Artificial Intelligence, Computer Science
Tan, Lin – ProQuest LLC, 2009
Commenting source code has long been a common practice in software development. This thesis, consisting of three pieces of work, made novel use of the code comments written in natural language to improve software reliability. Our solution combines Natural Language Processing (NLP), Machine Learning, Statistics, and Program Analysis techniques to…
Descriptors: Computer Software, Coding, Reliability, Improvement

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