Browsing by Author "Alshehri, Abeer"

Now showing 1 - 2 of 2

Restricted
Attitudes and perceptions of Saudi students towards their non-native EMI instructors
(2022-09-21) Alshehri, Abeer; Cowie, Claire
This thesis examines undergraduate students’ attitudes toward non-native English speaker (NNES) instructors in an EMI context in Saudi Arabia. It also investigates their perceptions of the speech of those instructors, in terms of three speech constructs: intelligibility, perceived comprehensibility, and perceived foreign accentedness (ICA) (see Munro and Derwing, 1995). Globalisation has contributed to the worldwide internationalisation of higher education (Graddol, 2006). With this trend, English has been increasingly used as the medium of instruction for content-based courses at the higher education level (Dearden, 2014), and NNES instructors are teaching in English instead of their first languages. NNES often speak with an accent, which has long been recognised as a marker of social identity, and attitudes towards certain varieties of English reflect attitudes about the speakers of those varieties (Garrett et al., 2003). Little research has been done on NNES English medium instruction (EMI) instructors and the students’ attitudes and perceptions towards them in terms of the ICA. Inbar- Lourie and Donitsa-Schmidt (2020; 2013) and Karakas (2017) have demonstrated students’ preferences for and beliefs about native English speaker (NES) instructors in comparison to NNES/local instructors. However, instructors in the Saudi EMI context are rarely NES and are more typically local (Saudi), from the wider Arab region, or South Asian. This study contributes to the existing literature on EMI by extending the understanding of students’ implicit and explicit attitudes towards NNES EMI instructors from different L1 backgrounds, and by putting on display their perceptions of these instructors. The current study used exploratory sequential mixed methods. In the first (qualitative) phase, four semi-structured interviews and two focus groups were used to explore the experiences of EMI students with their NNES EMI instructors and to identify factors relevant to attitudes. The first phase fed into the measures of the second (quantitative) phase, which employed an Implicit Association Test (IAT) to measure implicit attitudes, an attitudinal questionnaire to measure explicit attitudes, and speech perception experiments to measure the three speech constructs. Students’ attitudes and perceptions were measured towards Saudi, Egyptian, and South Asian instructors, and a total of 110 participants responded to the online study by using Qualtrics platforms. The combinations of methodologies revealed consistent patterns in the Saudi students’ implicit and explicit attitudes towards their NNES EMI instructors. Measures of IATs revealed a preference towards Arab instructors and associated them with positive teaching traits, especially Saudi instructors and to a lesser extent Egyptian instructors. Explicit attitude findings aligned with the implicit results: the Saudi instructors were the most preferred, followed by the Egyptian instructors, and lastly, the South Asian instructors. It was evident from the interviews and the explicit attitudes questionnaires that use of Arabic alongside English in the classroom played a major role in the appeal of Arab instructors. Although respondents in the qualitative phase acknowledged that the evaluation of instructors should be in accordance with subject-level expertise, many were ready to offer opinions on accent and comprehensibility. In the speech perception measures, South Asian instructors were perceived to be the most accented. However, the more objective measure of intelligibility showed that respondents had the same difficulty understanding Egyptian voices as South Asian voices. The research concludes that even if Saudi participants expressed negative attitudes against a certain instructor, this does not always imply that they are unable to comprehend them. Furthermore, the results of this study indicated that a favourable attitude does not necessarily entail high intelligibility and comprehensibility. There was a more favourable attitude towards Egyptian instructors than Indian/Pakistani instructors, though they were rated as being less intelligible and less comprehensible than Indian/Pakistani speakers. Therefore, listeners’ language attitudes need to be carefully examined before reaching a conclusion, particularly when it comes to the speech constructs, for example, listeners may react adversely to particular accents and thus declare them to be incomprehensible even though the accent does not impair their intelligibility. The findings offer implications for different stakeholders at the university, including students, instructors, and university decision-makers. For university students, it is recommended to increase students’ awareness regarding the discriminatory and prejudiced attitudes to NNES instructors and their accents within EMI contexts.
27 0
Restricted
Explainable Goal Recognition Systems
(Saudi Digital Library, 2025) Alshehri, Abeer; Vered, Mor
This thesis explores human-centered approaches to explaining and understanding why goal recognition (GR) agents predict specific goal hypotheses. Goal recognition is the process of inferring an agent’s hidden goal from its observed behaviour, playing a crucial role in AI with various practical applications. Since the field’s inception, understanding the behaviour, decisions, and actions of ar- tificial intelligence (AI) agents has been a core focus of research. As these systems grow increasingly complex, their reasoning processes often become opaque to end users, raising significant challenges in high-stakes and collaborative environments. Lack of transparency can undermine trust and hinder effective decision-making. Enhancing au- tonomous agents’ explainability is vital, enabling users to comprehend and trust the reasoning behind these systems’ predictions. Understanding how humans generate, select, and convey explanations can serve as a ba- sis for developing effective explainable agents. Explaining the behaviour and predictions of GR agents engaged in sequential decision-making presents unique challenges. Tra- ditional approaches to explainability often focus on aligning an agent’s behaviour with an observer’s expectations or making the reasoning behind decisions more transparent. Building on insights from cognitive science and philosophy, this thesis delves deeper into understanding the nature of explanations within human cognition. The central contribution of this work is the introduction of the eXplainable Goal Recog- nition (XGR) model, a novel framework that generates counterfactual explanations for GR agents. The XGR model addresses “why” and “why not” questions by leverag- ing insights from two human-agent studies and proposing a conceptual framework for human-centred explanations of GR. Building on these foundations, the thesis extends the XGR model by introducing the Hypothesis-Driven XGR model, which integrates the emerging decision-making paradigm of Evaluative AI. Our empirical evaluations demon- strate that the proposed models enhance trust in GR agents and effectively support user decision-making, outperforming baseline approaches across key domains. This research presents the first systematic investigation into human-centred explanations for goal recognition systems in sequential decision-making domains. It advances the field of explainable AI and provides practical methods to improve user understanding and trust in GR systems.
21 0