Saudi Cultural Missions Theses & Dissertations
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Item Restricted Enhancing the Accessibility of Voice Assistants for Individuals with Dysarthria through Non-Verbal Voice Cue Interaction(Cardiff University, 2024) Jaddoh, Aisha; Lozides, FernandoAbstract16 0Item Restricted Towards Supporting People with sight loss in Dynamic Indoor spacing by Utilizing Surveillance Cameras(The University of Sheffield, 2024-07-11) Alrashidi, Abdulaziz; Gotoh, YoshiNavigating unfamiliar places often creates various challenges for visually impaired people (VIPs), thus restricting their independence. Recent studies on indoor wayfinding for VIPs mostly focuses on large spaces such as airports and hospitals, overlooking more compact spaces such as cafes, halls and other smaller venues. These spaces are often characterised by their dynamic nature, with people constantly moving and furniture being rearranged. It leads to user needs that are not sufficiently met by existing assistive technologies (ATs), and poses technical challenges when de veloping cost-effective solutions. The challenges in visiting unfamiliar dynamic environments (UDEs) and the required informa tion to support navigation and wayfinding were investigated as a user study with ten VIPs. This study involved methods for interviewing participants and observing them perform walking jour neys in an unfamiliar room. The qualitative analysis reveals user requirements, useful verbal guid ance and preferred method of their delivery. The need for addressing localisation and mapping was highlighted in the user study as key functional requirements. When developing affordable ATs in UDEs, surveillance cameras have good potential as a plat form because they are widely available infrastructure. This lead to investigating people localisa tion under occlusion and generating semantic representation of dynamic environments from a single view stationary camera.14 0Item Restricted Adopting Augmented Reality to Explore Historical Artifacts in Saudi Arabia Historical Museums(University of Technology Sydney, 2024-06-26) Alakhtar, Rayed A; Hussain, FarookhHistorical locations have many artifacts of generations that people from other cultures might not know about. Visitors to these locations want to understand the novel stories of buildings, people's lifestyles, and artifacts of centuries past. Tourism has become a digitized industry. This means that tourism is now employing technology to enhance tourism experience of locations. Technology that has been used for digital tourism is referred to as Augmented Reality. Augmented Reality is a promising technology that can deliver better understanding of the historical artifacts in Saudi Arabia. This research adopted the technology of Augmented Reality to deliver better understanding of the historical artifact in Saudi Arabia Museums. This research aims to Investigating the user experiences and expectation when exploring Saudi artifacts in historical and general locations in Saudi Arabia and to establish whether using AR technology provides an enhanced understanding of the usage of the historical artifacts and gives a richer historical context to Saudi visitors. The result of this research shows with appropriate media characteristics, museum visitors can gain a deeper understanding of non-touchable historical artifacts using the Augmented Realty application in Saudi Arabia historical museums.20 0Item Restricted A Human-Centered Approach to Improving Adolescent Real-Time Online Risk Detection Algorithms(Vanderbilt University, 2024-05-15) Alsoubai, Ashwaq; Wisniewski, PamelaComputational risk detection holds promise for shielding particularly vulnerable groups from online harm. A thorough literature review on real-time computational risk detection methods revealed that most research defined 'real-time' as approaches that analyze content retrospectively as early as possible or as preventive approaches to prevent risks from reaching online environments. This review provided a research agenda to advance the field, highlighting key areas: employing ecologically valid datasets, basing models and features on human understanding, developing responsive models, and evaluating model performance through detection timing and human assessment. This dissertation embraces human-centric methods for both gaining empirical insights into young people's risk experiences online and developing a real-time risk detection system using a dataset of youth social media. By analyzing adolescent posts on an online peer support mental health forum through a mixed-methods approach, it was discovered that online risks faced by youth could be laden by other factors, like mental health issues, suggesting a multidimensional nature of these risks. Leveraging these insights, a statistical model was used to create profiles of youth based on their reported online and offline risks, which were then mapped with their actual online discussions. This empirical study uncovered that approximately 20% of youth fall into the highest risk category, necessitating immediate intervention. Building on this critical finding, the third study of this dissertation introduced a novel algorithmic framework aimed at the 'timely' identification of high-risk situations in youth online interactions. This framework prioritizes the riskiest interactions for high-risk evaluation, rather than uniformly assessing all youth discussions. A notable aspect of this study is the application of reinforcement learning for prioritizing conversations that need urgent attention. This innovative method uses decision-making processes to flag conversations as high or low priority. After training several deep learning models, the study identified Bi-Long Short-Term Memory (Bi-LSTM) networks as the most effective for categorizing conversation priority. The Bi-LSTM model's capability to retain information over long durations is crucial for ongoing online risk monitoring. This dissertation sheds light on crucial factors that enhance the capability to detect risks in real time within private conversations among youth.21 0Item Restricted Developing and Assessing a Holistic eLearning 4.0 Model for Higher Education in Saudi Arabia(Saudi Digital Library, 2023-12) Alnassar, Mohammad; Issa, TThe lives of people worldwide have changed as a result of the rapid technological advancements in many industries. Technology has also transformed the way that knowledge is presented to students, notably throughout the eLearning 1.0, 2.0, and 3.0 stages, and has helped to diversify the teaching and learning methods applied in the education sector. According to the literature, there are few issues pertaining to the Semantic Web (eLearning 3.0) that have yet to be thoroughly examined. However, because eLearning 4.0 is the latest generation of eLearning, relatively few researchers have considered the factors and sub- factors that facilitate its implementation. The factors and sub-factors that need to be taken into account for the effective implementation of eLearning . in Saudi Arabia’s higher education sector to realise its Vision 2030 goal of achieving excellence in education and technology and address issues with the present higher education system, have attracted only a small amount of research attention. There is also a lack of models that may facilitate the successful and effective application of eLearning 4.0 in Saudi Arabia. The purpose of this study is to bridge these research gaps by offering an eLearning 4.0 model and recommendations as a road map for stakeholders in light of eLearning 4.0's relatively recent appearance. A holistic eLearning 4.0 model for higher education in Saudi Arabia will be proposed to facilitate the integration of eLearning 4.0 and its technologies in the higher education sector. This study contributes to the research field in two main ways. The first contribution of this research is a model that identifies the factors and sub-factors essential for the integration of eLearning 4.0 at institutions in Saudi Arabia. It is aligned with one of Saudi Arabia’s Vision 2030 goals: to promote education and technology based on achievable KPIs. Second, the findings of this study offer a quantitative and qualitative indication of how higher education institutions in Saudi Arabia perceive and are aware of the possible application of eLearning 4.0. Although the scope of this research was restricted to the perspectives of academic staff and students at education institutions in Saudi Arabia, the findings, model, and recommendations of this research provide guidelines regarding the factors and sub-factors that need to be taken into consideration in order to successfully implement eLearning 4.0 for stakeholders in higher education.51 0Item Restricted An Investigation into Matching Learning Material to the Different Needs of Arabic Learners with Dyslexia(Saudi Digital Library, 2023-11-29) Alghabban, Weam Gaoud; Hendley, RobertDyslexia is a common learning disability that affects people’s ability to spell, read words and their fluency in language. Adaptive e-learning is becoming increasingly popular as a tool to help individuals with dyslexia. It provides more-customised learning experiences and interactions based on the learners’ characteristics. Each learner with dyslexia has unique characteristics for which content should ideally be suitably tailored. However, adaptation to satisfy the individual needs and characteristics of learners with dyslexia is limited. In particular, the benefits of adapting e-learning based on dyslexia type or reading skill level have not yet been sufficiently explored, despite the type of dyslexia and the learner’s reading skill level being critical factors. Most previous studies have focused upon the technological aspects and have been marked by inadequately designed and controlled experiments to assess the system’s effectiveness. This limits the ability to understand the effectiveness of adaptation. This thesis aims to increase understanding about the value of adaptation of learning material based on individual dyslexia types and reading skill levels and to understand how this affects the learning experience of learners with dyslexia. To do this, an empirical evaluation through three controlled experiments with a reasonable number of subjects has been undertaken and assessed using the following metrics: learning gain, word understanding, learner satisfaction and perceived level of usability. In all three experiments, careful experimental design and precise reporting of results are all considered. A dynamic, web-based e-learning system that matches learning material based on dyslexia type and/or reading skill level was implemented to support these experiments. Across the three experiments, the findings reveal that matching learning material to dyslexia type, reading skill level and the combination of both, yields significantly better short- and long-term learning gains and improves the learners’ perception of their learning.19 0Item Restricted The Use of Proxies in Designing for and with Autistic Children: Supporting Friendship as a Case Study(2022-09-11) Alabdullatif, Aljawharah; Pain, HelenParticipatory Design (PD) is an approach for designing new technologies which involves end users in the design process. It is generally accepted that involving users in the design process gives them a sense of ownership over the final product which enhances its usability and acceptance by the target population. Employing a PD approach can introduce multiple challenges especially when working with autistic children. Many approaches for involving autistic children and children with special needs were developed to address these challenges. However, these frameworks introduce their own limitations as well. There is an ethical dilemma to consider in the involvement of autistic children in the design process. Although we established the ethical benefit of involving children, we did not address the ethical issues that will result from involving them in these research projects. Among other issues, the nature of design workshops we as a community currently run require working with unfamiliar researchers and communicating with them while social and communication differences are one of the main diagnostic criteria for autism. When designing for autistic children and other vulnerable populations an alternative (or most often an additional) approach is designing with proxies. Proxies for the child can be one of several groups of other stakeholders, such as: teachers, parents and siblings. Each of these groups may inform the design process, from their particular perspective, and as proxies for the target group of autistic children. Decisions need to be made about what stages in the design process are suited to their participation, and the role they play in each case. For this reason, we explore the role of teachers, parents, autistic adults and neurotypical children as proxies in the design process.15 0Item Restricted How Does Bias Affect Users of Artificial Intelligence Systems?(2023) Bubakr, Hebah Abdullah; Baber,ChrisIn large companies, artificial intelligence (AI) is being used to optimise workflow and ensure efficiency. An assumption is that the AI system should remain unaffected by bias or prejudices to contribute to providing fairer results. For example, in the recruitment process, AI ensures that each applicant is judged by the exact criteria in the job description. Our results suggest otherwise; therefore, we wondered whether the problem of bias extends from the training data (which, replicates existing inequalities in organisations) to the design of the AI systems themselves. These learning systems are dependent on knowledge elicited from human experts. However, if the systems are trained to perform and think in the same way as a human, most of the tools would use unacceptable criteria because people consider many personal parameters that a machine should not use. The question remains whether the potential impact of bias is considered in the design of an AI system. In this thesis, several experiments are conducted to study unconscious bias in the application of AI with the aid of two qualitative frameworks and two quantitative questionnaires. We first explore the unconscious bias in user interface designs, then examine programmers’ understanding of bias when creating a purposely biased machine using medical databases. A third study addresses the effect of AI recommendations on decision-making, and finally, we explore whether user acceptance is dependent on the type of AI recommendation, testing various suggestions. This project raises awareness of how the developers of AI and machine learning might have a narrow perspective of ‘bias’ as a statistical problem rather than a social or ethical problem. This limitation is not because they are unaware of these wider concerns but because the requirements relating to the management of data and the implementation of algorithms might restrict their focus to technical challenges. Consequently, bias outcomes can be produced unconsciously because developers are simply not attending to these broader concerns. Creating accurate and effective models is important but so is ensuring that all races, ethnicities and socioeconomic levels are adequately represented in the data model (O’Neil, 2016).24 0Item Restricted Electrtactons: Designing and Evaluating Electrotactile Cues(2023-06-05) Alotaibi, Yosuef; Brewster, StephenElectrotactile feedback is a novel haptic feedback modality that can be used to evoke a desired level of alertness and emotion or convey multidimensional information to the user. However, there is a lack of research investigating its basic design parameters and how they can be used to create effective tactile cues. This thesis investigates the effect of Electrotactile feedback on the subjective perception of specific sensations, such as urgency, annoyance, valence and arousal, to find the number of distinguishable levels in each sensation. These levels are then used for designing structured, abstract, electrotactile messages called Electrotactons. These have potential benefits over vibration-based cues due to the greater flexibility of the actuators. Experiments 1, 2 & 4 investigated the effects of manipulating the basic electrotactile parameters pulse width, amplitude and pulse frequency on perceived sensations. The results showed that all parameters have a significant effect on the perceived sensations, except for pulse frequency not having an effect on valence. Also, pulse frequencies of 30 PPS and above did not influence the perceived sensations. Experiment 3 investigated the use of pulse width, amplitude and pulse frequency to convey three types of information simultaneously encoded into an electrotactile cue. This was the first attempt to design Electrotactons using the basic parameters of electrotactile feedback. The results showed overall recognition rates of 38.19% for the complete Electro- tactons. For the individual component parameters, pulse width had a recognition rate of 71.67%, amplitude 70.27%, and pulse frequency 66.36%. Experiment 5 investigated intensity and pulse frequency to determine how many distinguishable levels could be perceived. Results showed that both intensity and pulse frequency significantly affected perception, with four distinguishable levels of intensity and two of pulse frequency. Experiment 6 investigated the use of intensity and pulse frequency from in Experiment 5 to improve the design of Electrotactons on three body locations using two different size electrodes. The results showed overall recognition rates of up to 65.31% for the complete Electrotactons. For the individual component parameters, intensity had a recognition rate of 68.68%, and pulse frequency 94.41%. These results add significant new knowledge about the parameter space of electrotactile cue design and help designers select suitable properties to use when creating electrotactile cues.22 0Item Restricted Toward Leveraging Artificial Intelligence to Support the Identification of Accessibility Challenges(2023) Aljedaani, Wajdi Mohammed; Ludi, Stephanie; Wiem Mkaouer, MohamedContext: Today, mobile devices provide support to disabled people to make their life easier due to their high accessibility and capability, e.g., finding accessible locations, picture and voice-based communication, customized user interfaces, and vocabulary levels. These accessibility frameworks are directly integrated, as libraries, in various apps, providing them with accessibility functions. Just like any other software, these frameworks regularly encounter errors. App developers report these errors in the form of bug reports or by the user in user reviews. User reviews include insights that are useful for app evolution. These reports related to accessibility faults/issues need to be urgently fixed since their existence significantly hinders the usability of apps. However, recent studies have shown that developers may incorporate accessibility strategies in inspecting manually or partial reports to investigate if there are accessibility reports that exist. Unfortunately, these studies are limited to the developer. With the increase in the number of received reviews, manually analyzing them is tedious and time-consuming, especially when searching for accessibility reviews. Objective: The goal of this thesis is to support the automated identification of accessibility in user reviews or bug reports, to help technology professionals prioritize their handling, and, thus, to create more inclusive apps. Particularly, we propose a model that takes as input accessibility user reviews or bug reports and learns their keyword-based features to make a classification decision, for a given review, on whether it is about accessibility or not. To complement this goal, we aim to reveal insights from deaf and hard-of-hearing students about Blackboard, which is one of the most common Learning Management systems (LMS) used by many universities, especially in the current COVID-19 pandemic. This occurs to explore how deaf and hard-of-hearing students have challenges and concerns in e-learning experiences during the sudden shift to online learning during COVID-19 in terms of accessibility. Method: Our empirically-driven study follows a mixture of qualitative and quantitative methods. We text mine user reviews and bug reports documentation. We identify the accessibility reports and categorize them based on the BBC standards and guidelines for mobile accessibility and Web Content Accessibility Guidelines (WCAG 2.1). Then, we automatically classify a large set of user reviews and bug reports and identify among the various accessibility models presented in the literature. After that, we used a mixed-methods approach by conducting a survey and interviews to get the information we needed. This was done on deaf and hard-of-hearing students to identify the challenges and concerns in terms of accessibility in the e-learning platform Blackboard. Result: We introduced models that can accurately identify accessibility reviews and bug reports and automate detecting them. Our models (1) outperform two baselines, namely a keyword-based detector and a random classifier; (2) our model achieves an accuracy of 91% with a relatively small training dataset; however, the accuracy improves as we increase the size of the training dataset. Our mixed methods with deaf and hard-of-hearing students have revealed several difficulties, such as inadequate support and inaccessibility of content from learning systems. Conclusion: Our models can automatically classify app reviews and bug reports as accessibility-related or not so developers can easily detect accessibility issues with their products and improve them to more accessible and inclusive apps utilizing the users' input. Our goal is to create a sustainable change by including a model in the developer’s software maintenance pipeline and raising awareness of existing errors that hinder the accessibility of mobile apps, which is a pressing need. In light of our findings from the Blackboard case study, Blackboard and the course material are not easily accessible to deaf students and hard of hearing. Thus, deaf students find that learning is extremely stressful during the pandemic.63 0