Browsing by Author "Alzahrani, Asma"

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Evaluating the Ferroptosis Potential and Mechanistic Variability of the Ferronucleoside TUC1 in the MIAPaCa2 Cell Line
(University of Birmingham, 2023-12-04) Alzahrani, Asma; Hodges, Nikolas
Addressing the therapeutic challenges of pancreatic ductal adenocarcinoma (PDAC), known for its rapid resistance to treatments like gemcitabine, we examined the capabilities of ferronucleoside 1-(S,Rp) TUC1. Notably, TUC1 demonstrated compelling efficacy against the gemcitabine-resistant MIAPaCa2 cells, closely matching cisplatin. Using MTT assays and accounting for variables like cell confluency and treatment duration, we assessed TUC1's cytotoxic impact. While the outcomes were on par with cisplatin, they varied across experimental conditions. Interestingly, based on cell confluency, we identified apoptosis as the primary cell death pathway, a departure from the initially hypothesized ferroptosis. This study highlights TUC1's complex mechanisms, underlining the need for more comprehensive research to further understand its effects.
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The Development of Correspondence Analysis Techniques using the Family of Cressie–Read Power Divergence Statistics
(The University of Newcastle, 2024-03-14) Alzahrani, Asma; Beh, Eric; Stojanovski, Elizabeth
Correspondence analysis (CA) is a visual statistical technique that has a long and interesting history. It is a powerful multivariate statistical technique that aims to uncover underlying patterns and associations between two or more categorical variables. As datasets continue to expand in complexity and size, there is a growing need for advanced analytical techniques that can handle and extract meaningful insights from such data. The classical approach to CA considers Pearson’s chi-squared statistic as the fundamental measure of association between categorical variables. However, this thesis provides an extension to CA techniques by employing the family of Cressie-Read divergence statistics as a measure to examine the association between the categorical variables. This family includes the most common statistics of association such as Pearson’s statistic, the Freeman-Tukey statistic, the log-likelihood ratio statistic, and the Cressie-Read statistic. Thus, by using the family of Cressie- Read divergence statistics to conduct CA, a more comprehensive understanding can be obtained, which expands the analysis beyond Pearson’s statistic. This thesis describes this approach to CA in detail and highlights its features by providing various applications. Moreover, we further generalise the approach to enable the analysis of multiple categorical variables. A new technique for constructing confidence regions based on the family of Cressie-Read divergence statistics is also explored. Further extensions of this area of CA are also made by showing how it can be used to analyse the association between the variables of a multi-way contingency table. The results of such analyses allow for a highly effective visual exploration of the association structure between categorical variables. Additionally, R functions for all techniques discussed in the thesis are provided. This, in turn, provides a significant contribution for researchers wanting to increase their flexibility in programming and create new and powerful tools for categorical data analysis
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Uncovering Factors Driving the Adoption of Learning Analytics in Higher Education Institutions
(Saudi Digital Library, 2023-09-20) Alzahrani, Asma; Gasevic, Dragan
In higher education institutions (HEIs), learning analytics (LA) has been gaining popularity as a tool for understanding learning and for enhancing teaching and learning outcomes. For example, LA can provide students with insightful data on their learning outcomes. LA also allows students to track their performance in relation to their goals and check how their peers are performing. Teaching staff can have access to various sources of data for evaluating students’ learning performance and receiving up to-date information on students’ learning progress. In addition, LA allows senior managers to identify factors that improve retention or lead to abandonment. Despite the benefits of learning analytics (LA), their adoption can pose challenges. In existing research, LA has been extensively discussed, but the focus has been on its technical aspects and a growing body of literature that aims to understand the socio-technical factors (which are the factors that represent the interrelationship between humans and tools) that shape LA adoption in HEIs. However, the literature does not address the challenges (or success-enablers) and their associated factors within different LA adoption scopes, trust in LA (e.g., trust in LA tools and stakeholders), and the need for LA in unexplored regions (e.g., Saudi Arabia). We sought to fill this gap by focusing on the major factors that affect LA adoption, such as challenges, success enablers, trust, and needs. This is because the successful adoption of LA requires thoughtful consideration of all these socio-technical issues reported by main LA stakeholders. In other words, HEIs can improve the process of LA adoption by taking into account socio-technical issues, allowing them to determine issues pertaining to their adoption or use of LA. This thesis examines the perspectives of key stakeholders, including teaching staff and senior managers in HEIs, towards LA and what factors impact their adoption and use. The thesis findings identify barriers and offer strategies to curb or address the barriers using a socio-technical framework, bringing together social and technical issues to facilitate the adoption of LA in HEIs with informing strategies for the successful adoption of LA. It also contributes to the growing body of literature on LA in HEIs and will have important strategic implications for institutions seeking to adopt LA at various stages of adoption, from the early stages of interest in LA to the full adoption phase. This includes recommendations to overcome the challenges, areas that enable success, trust factors and recommendations to improve the LA adoption process, and the needs related to LA services. In the field of LA, this thesis presents a series of contributions that are represented by a set of factors that influence the adoption of LA in HEIs. First, the thesis empirically identifies the challenges of the adoption of LA and the factors associated with those challenges through the analysis of data collected from senior managers. As a result of this analysis, (i) HEIs can have a better understanding of why LA is difficult to scale LA in different scopes of LA adoption, (ii) changing patterns that may emerge in institutions that adopt LA in varying scopes are identified that provide insight into how institutions can be better prepared to deal with challenges and the ways they could be overcome in the different scopes of LA adoption: no adoption; preparation to adopt or partially adopting; and full adoption. The challenges of LA adoption can be turned into success-enablers if dealt with in the right way. Thus, the second part of this thesis scrutinises the success enablers of LA adoption from the perspective of managers in European HEIs. Aside from senior managers, teaching staff is another main stakeholder group in LA and their perspectives are equally as valuable as those of the senior managers. Therefore, the third part of this thesis covers the challenges that teaching staff may face when using LA. Specifically, the thesis focuses on trust in LA which previously received limited attention in the literature. Trust in LA was examined by analysing quantitative and qualitative data collected from teaching staff at Saudi HEIs focusing on two types of trust: trust in LA tools and trust in LA stakeholders. In addition to discovering trust factors in LA, understanding the teaching staff’s needs could be crucial to ensuring the success and widespread adoption of LA by HEIs. Accordingly, the final part of this thesis is focused on examining the needs of the teaching staff of LA from diverse cultural backgrounds. Particularly, the thesis focused on teaching staff in HEIs in the Middle East (i.e., Saudi Arabia) and compared the findings with studies conducted in other parts of the world – primarily Western and Latin American countries. Finally, the thesis concludes with a discussion of the implications of the findings of this thesis and directions for future research.
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