Browsing by Author "Seyam, Mohammed Saad Mohamed Elmahdy"
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- Behind the Counter: Exploring the Motivations and Perceived Effectiveness of Online Counterspeech Writing and the Potential for AI-Mediated AssistanceKumar, Anisha (Virginia Tech, 2024-01-11)In today's digital age, social media platforms have become powerful tools for communication, enabling users to express their opinions while also exposing them to various forms of hateful speech and content. While prior research has often focused on the efficacy of online counterspeech, little is known about peoples' motivations for engaging in it. Based on a survey of 458 U.S. participants, we develop and validate a multi-item scale for understanding counterspeech motivations, revealing that differing motivations impact counterspeech engagement between those that do and not find counterspeech to be an effective mechanism for counteracting online hate. Additionally, our analysis explores peoples' perceived effectiveness of their self-written counterspeech to hateful posts, influenced by individual motivations to engage in counterspeech and demographic factors. Finally, we examine peoples' willingness to employ AI assistance, such as ChatGPT, in their counterspeech writing efforts. Our research provides insight into the factors that influence peoples' online counterspeech activity and perceptions, including the potential role of AI assistance in countering online hate.
- Cybersecurity Management System: Defense and ResponseHuang, Chenxiang (Virginia Tech, 2023-01-19)Cybersecurity attacks such as phishing, malware, and ransomware have become a major concern in recent years, with many individuals and organizations suffering financial losses as a result. Most people are unaware of the different types of cybersecurity attacks and have not seen examples of them. To address this problem, we developed the Cybersecurity Management System: Defense and Response (CMSDR) cloud software application. It provides both the "Defense" and "Response" to cybersecurity attacks, with educational materials and examples to help users learn about different types of cybersecurity attacks, and a computer-aided reporting and notification system to help organizations respond to ongoing incidents. CMSDR is a universal application that can be used on any platform with a web browser. Any company or organization can effectively run CMSDR on their own server computer for cybersecurity defense and response.
- Incorporating LLM-based Interactive Learning Environments in CS Education: Learning Data Structures and Algorithms using the Gurukul platformRachha, Ashwin Kedari (Virginia Tech, 2024-09-24)Large Language Models (LLMs) have emerged as a revolutionary force in Computer Science Education, offering unprecedented opportunities to facilitate learning and comprehension. Their application in the classroom, however, is not without challenges. LLMs are prone to hallucination and contextual inaccuracies. Furthermore, they risk exposing learning processes to cheating illicit practices and providing explicit solutions that impede the development of critical thinking skills in students. To address these pitfalls and investigate how specialized LLMs can enhance engagement among learners particularly using LLMs, we present Gurukul, a unique coding platform incorporating dual features - Retrieval Augmented Generation and Guardrails. Gurukul's practice feature provides a hands-on code editor to solve DSA problems with the help of a dynamically Guardrailed LLM to prevent explicit code solutions. On the other hand, Gurukul's Study feature incorporates a Retrieval Augmented Generation mechanism that uses OpenDSA as its source of truth, allowing the LLM to fetch and present information accurately and relevantly, thereby trying to overcome the issue of inaccuracies. We present these features to evaluate the user perceptions of LLM-assisted educational tools. To evaluate the effectiveness and utility of Gurukul in a real-world educational setting, we conducted a User Study and a User Expert Review with students (n=40) and faculty (n=2), respectively, from a public state university in the US specializing in DSA courses. We examine student's usage patterns and perceptions of the tool and report reflections from instructors and a series of recommendations for classroom use. Our findings suggest that Gurukul had a positive impact on student learning and engagement in learning DSA. This feedback analyzed through qualitative and quantitative methods indicates the promise of the utility of specialized LLMs in enhancing student engagement in DSA learning.
- Mixed Method Study of Experiences of Non-Computer Science Majors in Introductory Computer Science CoursesParajuli, Khushi (Virginia Tech, 2024-01-04)With the unprecedented growth of the Computer Science field, there is an underlying assumption that undergraduate students would naturally gravitate towards Computer Science courses or acquire related skills, irrespective of their career interests. However, this research challenged that assumption, focusing on the experiences and attitudes of Non-Computer Science majors enrolled in Computer Science courses. The objective of this study is to gain a comprehensive understanding of the experiences and attitudes of Non-Computer Science majors taking Computer Science courses. The research questions seek to uncover the factors influencing their engagement in Computer Science. This research employs a mixed-method study, starting with a quantitative phase followed by a qualitative one. Quantitative data is analyzed using factor analysis and inferential statistics, followed by thematic analysis on the qualitative data. The findings reveal that stereotypes associated with the Computer Science field are established as early as high school. These stereotypes, particularly affecting females, sometimes act as barriers, discouraging further pursuit of Computer Science. Addressing these stereotypes becomes crucial for fostering inclusivity in the field. To counteract these stereotypes, it is proposed that Computer Science and its applications should be promoted as early as freshmen year of high school. By introducing students to the field early, we can potentially mitigate the impact of stereotypes and encourage a diverse range of individuals to pursue Computer Science. Further exploration into the experiences of Computer Science majors is recommended to deepen our understanding and inform targeted interventions.
- Promoting Universal Access to E-government Services --- A Comprehensive Conceptual Framework from Citizens' PerspectiveAl Drees, Asma Ayed S. (Virginia Tech, 2023-06-26)The world moves toward the era of a smart society that is human-centered, sustainable, and inclusive. Countries employed new information and communication technologies to deliver services and engage citizens in the decision-making process. These services are evolving and in the near future, we can expect a plethora of new services related to Smart Society 5.0 and Industry 4.0, in addition to more traditional services. The possibility of these new technologies to foster sustainable development can only be obtained when all target users have fair access to the offered services. In the e-government context, ensuring service quality is crucial for success. While many factors contribute to service quality, user experience is becoming increasingly important. Governments need to put citizens at the center of the design process of their services and ensure that all target users have an enhanced experience with the offered e-services. Moreover, e-government constantly changes over time and continues to drive opportunities and open new possibilities for potential developments. Therefore, it is highly recommended that government agencies regularly evaluate citizens' experience with the offered services and investigate the factors that significantly influence their adoption behavior. However, numerous research efforts investigated the user experience of e-government from the lens of specific government services in an individual or specific range of countries. There has been a lack of a global e-government adoption framework to evaluate users' adoption behaviors of e-government services. Despite successful efforts to formalize certain aspects of user experience, there remains a need for a comprehensive and systematic framework for user experience evaluation. Therefore, the main objective of this thesis is to conduct a comprehensive study of the state of the art in user experience evaluation and develop a unified framework that integrates existing knowledge on the topic. It provides a systematic approach for enhancing user experience by providing guidelines on how to evaluate users' adoption behaviors of e-government services efficiently as a reference for future investigations. The research approach was conducted through two main phases. The first phase aims to design the proposed conceptual framework to evaluate users' adoption behaviors of e-government services. Hence, we have conducted a systematic literature review on user experience towards e-government services and cover all different aspects to better understand target users and enhance their overall experience. This systematic review informed the design of a holistic conceptual framework by investigating factors that significantly affect users' adoption of e-government services globally. The proposed framework provides a standard overarching process for future research in the e-government domain by providing an established methodology for evaluating users' adoption behaviors of e-government services. This framework is global, it is used to evaluate users' adoption behaviors of e-government in any country to ensure that citizens have a good experience with e-government services in that country. The framework includes the most common significant factors influencing users' adoption behaviors of e-government that represent the necessary steps to enhance citizen experience and boost their adoption behavior. The second phase implies the utilization of the proposed framework to evaluate users' adoption behaviors of e-government by developing a reference implementation of e-government adoption based on the proposed framework. The quantitative research methodology was employed using a web-based questionnaire to evaluate the e-government adoption behavior. The questionnaire contains a set of measurement items pertaining to each factor that existed in the proposed framework to investigate their potential relationships. The questionnaire underwent an iterative process of testing and validation to ensure the reliability and credibility of the measurement items. Then, the multivariate statistics, including the structural equation modeling, have been adopted to analyze and examine the framework relationships. Preliminary results of this thesis include two user studies investigating user experience towards specific e-government services to support the development of the conceptual framework. Then, the proposed framework alongside the reference implementation were applied to evaluate the Saudi e-government adoption by evaluating the adoption behavior and developing an explanatory model for the adoption behaviors of Saudi citizens. The contributions of this thesis can be summarized by conducting a systematic literature review on user experience towards e-government services to inform the design of the proposed framework. Then, developing a global conceptual framework for evaluating users' adoption behaviors of e-government. Overall, this thesis provides valuable insights into enhancing citizen experience and increasing their adoption of e-government services, which supports government agencies, practitioners, and policymakers.
- Technology and International Student Parenting: Implications for Research and Design of Digital Childcare TechnologiesBhatti, Neelma (Virginia Tech, 2022-08-02)Digital technologies such as televisions, touch screen tablets, smartphones, and smart speakers are now frequently encountered and used by young children even before the age of one. These devices facilitate modern parents in their care-giving of young children due to their prevalence in the home environment. The use of these devices is especially common by international student mothers of young children who subscribe to a multiplicity of roles such as being a productive student, efficient mother, and dutiful partner in a new country. This dissertation summarizes four studies exploring the role of technology in international student mothers' life as a parent of young children, and the implications of design and research of technologies for parents based on the transferable learning from these studies. The first and second studies employ auto ethnographic and collaborative approach to involve these mothers as equal stakeholders and collaborators to understand their context of use of technology. The third and fourth studies explore the various uses of technology by caregivers and young children, to obtain certain gratifications. By engaging primary caregivers in in-depth efforts of understanding of their motivations and perceptions about early childhood media exposure, I set forth the praxis between the professional recommendations and their actual lived experiences with technology and young children. Building on these insights, I present a conceptual framework for research which considers the dyadic use of technology due to the close relationship between primary caregivers and young children. Based on the various roles of technology in international student mothers' parenting, I present implications for designing technologies which can assist parents in their care giving duties.
- A User-Centered Design Approach to Evaluating the Usability of Automated Essay Scoring SystemsHall, Erin Elizabeth (Virginia Tech, 2023-09-21)In recent years, rapid advancements in computer science, including increased capabilities of machine learning models like Large Language Models (LLMs) and the accessibility of large datasets, have facilitated the widespread adoption of AI technology, such as ChatGPT, underscoring the need to design and evaluate these technologies with ethical considerations for their impact on students and teachers. Specifically, the rise of Automated Essay Scoring (AES) platforms have made it possible to provide real-time feedback and grades for student essays. Despite the increasing development and use of AES platforms, limited research has specifically focused on AI explainability and algorithm transparency and their influence on the usability of these platforms. To address this gap, we conducted a qualitative study on an AI-based essay writing and grading platform, with a primary focus to explore the experiences of students and graders. The study aimed to explore the usability aspects related to explainability and transparency and their implications for computer science education. Participants took part in surveys, semi-structured interviews, and a focus group. The findings reveal important considerations for evaluating AES systems, including the clarity of feedback and explanations, impact and actionability of feedback and explanations, user understanding of the system, trust in AI, major issues and user concerns, system strengths, user interface, and areas of improvement. These proposed key considerations can help guide the development of effective essay feedback and grading tools that prioritize explainability and transparency to improve usability in computer science education.
- Utilizing Machine Learning Methods for Usability Evaluation in Learning Management SystemsTorres Molina, Richard Andres (Virginia Tech, 2024-05-14)The concept of usability refers to a user's capability to interact with a system to fulfill goals in terms of task completion (effectiveness), time measurement (efficiency), and positive attitude (satisfaction). The strategy for usability evaluation in software systems usually involves questionnaires, user testing, and heuristics. Although these methods have been widely used due to several benefits, there are challenges related to time consumption and embedded bias. In response to these challenges, this work proposes a hybrid approach based on usability questionnaire answers and machine learning algorithms to predict usability scores. We describe three different experiments with features extracted from a Learning Management System. These features were applied in the Machine Learning algorithms Linear Regression, Decision Trees, Random Forest, and Neural Networks in three experiments. Random Forest produces the best performance of average mean square error and root mean square error among machine learning algorithms. The results are promising, though there are alternatives for improvements for better performance of the System Usability Scale and UseLearn scores prediction. This approach has potential as a reliable predictive tool for usability scores, which would help create software systems that better satisfy users' needs.