The rise of Artificial Intelligence technology has raised concerns about the potential compromise of privacy due to the handling of personal data. Private AI prevents cybercrimes and falsehoods and protects human freedom and trust. While Federated Learning offers a solution by model training across decentralized devices or servers, thereby…

Modern Information Technology (IT) infrastructure and open-source software (OSS) have revolutionized our ability to access and process data, enabling us to tackle increasingly complex problems and challenges. While these technologies provide substantial benefits, they often expose users to vulnerabilities that can severely damage individuals and…

Recently, with the advancement in 2D imaging techniques and 3D visual sensors such as LiDAR, RGB-D cameras, etc. The use of 2D and 3D data is ubiquitous in various fields like autonomous driving, AR, and VR. Therefore, we are faced with an ever-increasing demand for approaches toward the automatic processing and analysis of data from multiple…

The Human-focused Facilitation (HFF) program was evaluated to provide evidence of the effectiveness of the processes used to build facilitator knowledge, skills, and dispositions. This study used an explanatory sequential, mixed-methods design to analyze data from Human-focused Facilitation participants and a focus group that did not participate…

This exploratory case study examined how and if career counselors learned about the impact of automation and artificial intelligence (AI) on occupations, including which actions, activities, and conditions helped or hindered their learning, and what impact this learning had on their professional practice. The data included questionnaires and…

In this thesis, we incorporate information theory into statistical signal processing and machine learning in order to achieve robust learning in presence of outliers (or generally in environments with non-Gaussian structure). In other words, by incorporating information theory especially when structure of environment is non-Gaussian, the…

We are currently in a century of data where massive amount of data are collected and processed every day, and machine learning plays a critical role in automatically processing the data and mining useful information from it for making decisions. Despite the wide and successful applications of machine learning in different fields, the robustness of…

Spatio-temporal processes are ubiquitous and prevalent across disciplines. Understanding the mechanisms underlying processes and integrating this information into models is of great interest, as it can improve forecasting accuracy and align with scientific motivation. Examples of such models include Partial Differential Equation (PDE) Models or…

This dissertation investigates how collective process-oriented documentation tools, combined with Natural Language Processing (NLP) techniques, can enhance knowledge construction in hands-on, open-ended learning environments, such as makerspaces. Through a three-year design-based research, the study developed and tested a collective documentation…

Today's globally-recognized servant leadership philosophy was born from a series of essays written by Robert Greenleaf in the 1970s. In his manifesto, Greenleaf underscored how through the precedence of a desire to serve and then to lead, servant leaders are motivated to help meet the needs of others. Researchers identify various dimensions and…

The present dissertation reports two experiments that examine implicit and explicit language learning methods and their impacts on early vocabulary, grammar, and phonological acquisition, in addition to working memory, proactive/reactive control, and fluid intelligence, as well as learner motivation. Experiment 1 investigated adult L2 acquisition…

The Leading-to-Calculus Framework (LTCF) is a collection of math courses meant to prepare students for calculus. From its inception, however, scholars have marked out a number of problems with its approach, particularly for students of color: its content and activities are often too broad, its structure is too rigid, and it fails to regularly…

Artificial intelligence (AI) aims to build intelligent systems that can interact with and assist humans. During the interaction, a system learns the requirements from the human user and adapts to the needs to complete tasks. A popular type of interactive system is retrieval-based, where the system uses a retrieval function to retrieve relevant…

Artificial intelligence (AI) has become more prevalent in education in recent years. Specifically, the perception of generative AI chatbots that generate essays based on the input of student prompts has invoked mixed reviews among educators. The negative learning implications of generative AI chatbots include plagiarism, academic dishonesty, and…

The purpose of this mixed-method survey-based study addresses the underexplored area of undergraduate student perceptions of artificial intelligences (AI) impact in academia, specifically within the FCSEI in Romania. This research study will provide comprehensive findings on how AI can revolutionize teaching methodologies, learning processes, and…