SACM - United States of America
Permanent URI for this collectionhttps://drepo.sdl.edu.sa/handle/20.500.14154/9668
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Item Restricted EFL SAUDI UNIVERSITY LEARNERS' PERCEPTIONS AND USE OF GENERATIVE AI SOFTWARE IN LANGUAGE LEARNING(The University of Memphis, 2025) Almohammadi, Asaad Hamed; Thrush, EmilyAs generative artificial intelligence (AI) tools become increasingly integrated into educational ecosystems, understanding how learners interact with these technologies is crucial, particularly in underrepresented English as a Foreign Language (EFL) contexts. This dissertation investigates the perceptions and usage patterns of Saudi university students as they interact with generative AI software to support their English language learning. While AI technologies like ChatGPT, Grammarly, and QuillBot are rapidly transforming academic practices, limited research has explored their impact from the learner’s perspective in non-Western, non-native English-speaking environments. This mixed-methods study, grounded in the Technology Acceptance Model (TAM), was conducted at one of the largest educational institutions in Saudi Arabia. The quantitative phase included 317 valid student responses analyzed using JASP. Principal Component Analysis confirmed the TAM-based factor structure, and repeated-measures ANOVA tested for differences across demographic variables such as gender, academic level, and years of English study. Findings indicated generally favorable perceptions of generative AI tools, with perceived ease of use rated higher than perceived usefulness. While no major gender-based differences were observed, modest distinctions emerged across academic levels and language study history. To contextualize these patterns, the qualitative phase involved 17 semi-structured interviews analyzed thematically using Quirkos. The qualitative findings provided deeper insight into how students incorporated AI tools into their learning routines across reading, writing, speaking, and listening tasks. Themes included increased learner autonomy, more personalized and immediate feedback, enhanced motivation, and flexible pacing. However, students also raised concerns about the accuracy of the tool, its insensitivity to context, the lack of critical reflection, and the risk of over-reliance on automated feedback. These nuanced findings were presented using bilingual excerpts (Arabic and English) to preserve cultural and linguistic authenticity. Together, the mixed-methods results suggest that generative AI tools offer both pedagogical opportunities and challenges. While learners recognize the value of these tools for improving task efficiency and engagement, they also navigate tensions between convenience and cognitive growth. Overuse of AI software, particularly for writing, may inhibit deeper learning and reduce confidence in independent language production. This dissertation contributes to the evolving body of research on AI in education by centering learner voices in a global context. It advances the theoretical application of TAM in EFL environments and underscores the need for culturally responsive, pedagogically guided integration of AI tools. The findings hold implications for curriculum designers, instructors, and edtech developers seeking to balance innovation with integrity in technology-enhanced language learning.25 0Item Restricted The Impact of ChatGPT Use on the Motivation and Basic Psychological Needs of Saudi EFL Students(Arizona State University, 2025) Alwadai, Abdullah; Smith, BryanThe advent of generative artificial intelligence (GenAI) represents a significant technological breakthrough, enabling models like ChatGPT to facilitate human-like interactions, personalized learning, constructive feedback, and so on. The sophistication of generative AI has attracted considerable attention from researchers who explore its potential benefits for language learners. However, since it was released a few years ago, research on ChatGPT’s effectiveness in enhancing language learning motivation for English as a foreign language (EFL) learners remains limited. To this end, this research utilized the self-determination theory (SDT) to investigate the extent to which engaging in informal interactions with ChatGPT in extramural contexts influences motivation and the basic psychological needs for autonomy, competence, and relatedness. To achieve this, a quasi-experimental design was employed with fifty EFL Saudi undergraduate students majoring in English, divided equally into an experimental and a control group. The experimental group participated in nine sessions over three weeks, engaging in informal self-directed interactions with ChatGPT on common everyday topics, while the control group responded to the same topics in writing without using AI, following the same number of sessions. The post-test results analyzed using analysis of covariance (ANCOVA) indicated a substantial increase in autonomous motivation and a decrease in controlled motivation in the experimental group after the treatment. Moreover, the results revealed a significant increase in autonomy exclusively in the experimental group. However, no statistically significant difference was observed in competence and relatedness after the intervention. Informed by these findings, a number of implications and pedagogical recommendations for language instructors, policymakers, and other stakeholders were proposed.61 0Item Restricted Investigating and Enhancing Online Software Development Resources: Automated Responses, Semantic Search, and Tagging in Video Tutorials(Florida State University, 2024) Tayeb, Ahmad; Haiduc, SoniaThe field of software development is rapidly evolving, requiring developers to continually refine their skills and adapt to new technologies. While video tutorials have become a popular medium for learning new concepts and techniques, challenges persist in interactive engagement, search functionality, and effective tagging. This dissertation explores innovative methods to enhance software development video tutorials by addressing these challenges using advanced large language models and transformer-based models. Firstly, we explore developers' preferences in terms of online learning resources in the era of AI-driven chatbots like ChatGPT. Despite the rise of AI chatbots, which offer instant, personalized responses, video tutorials remain a preferred medium due to their visual and detailed explanations. However, our study also revealed opportunities for improving video tutorials by integrating interactive elements and leveraging AI technologies, setting the foundation for our subsequent projects. Building on these insights, we introduce VidTutorAssistant, a system that leverages Generative Pre-trained Transformer (GPT) models to automate responses to video tutorial viewers' questions, thereby increasing interactive engagement in video tutorials and enhancing the learning experience. Next, we present an improved video tutorial search method, ISM, that leverages transformer-based models to create semantically dense vectors from video data, enabling a more intuitive and efficient search experience. By capturing the contextual meaning of queries and video content, ISM surpasses traditional search methods, helping developers find the most relevant tutorials and specific content within them. Finally, we introduce BM25-BERT, a hybrid approach for refining video tagging that combines traditional BM25F methods with transformer-based models. By re-ranking candidate tags initially generated by BM25F to improve context-awareness and accuracy, this method significantly enhances tutorial discoverability. Through empirical studies and user evaluations, this dissertation advances software engineering and educational technology by offering innovative solutions to enhance video tutorials and examining the impact of AI tools on developers' learning preferences. By rigorously assessing the proposed methodologies, this research contributes to both academic research and practical applications.26 0Item Restricted EXAMINING SAUDI ARABIAN'S PERCEPTIONS AND ADOPTION OF CHATGPT(Texas Tech University, 2024-05-10) Huda, Asiri; Xu, ShanThis paper explores the compatibility, benefits, and adoption rate of ChatGPT among Saudi Arabian populations, recognizing the nation’s unique cultural landscape. As AI technologies like ChatGPT redefine human-tech interactions globally, understanding their reception in diverse cultural contexts is imperative. Through qualitative and quantitative analysis, this study elucidates Saudi perceptions and usage patterns of ChatGPT, offering insights for businesses, policymakers, and developers to align AI innovations with societal values and preferences effectively. This research paper seeks to address the perception and adoption of ChatGPT among Saudi Arabian individuals. The importance of this study lies in the potential to bridge the gap between cutting-edge technology and the unique cultural and societal dynamics of the Saudi Arabian populace. By analyzing the perceptions and experiences of Saudi Arabian users, we can identify areas where ChatGPT can be harnessed to enhance communication. When the needs of Saudi Arabian users are identified, it can lead to integration of AI into their daily lives and contributing to the ongoing technological transformation in the region. The three theories that can be used to understand ChatGPT adoption in Saudi Arabia are Diffusion of Innovations Theory and Cultural Dimension Theory60 0