Rima Alhaidar

Dr. Rima Alhaidar

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Research Focus & Metrics

Academic Career Length

3Years (2024-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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19 June 2024 in Journal of Experimental Child Psychology
Verified
Journal Article
Closed access
RARima Alhaidar
Rima Alhaidar
MMMerle Mahon
Merle Mahon
CDChris Donlan
Chris Donlan

18 April 2026 in SSRN Electronic Journal
Verified
Preprint
Open access
RARima Alhaidar
Rima Alhaidar
MMMerle Mahon
Merle Mahon
CDChris Donlan
Chris Donlan
We examined the numerical skills of three-year-old English–Arabic bilingual children who are exposed to both Western and Eastern Arabic numerals. We used a forced-choice single and multidigit transcoding task comparing performance with English vs. Arabic spoken inputs and Western vs. Eastern numeral targets. We investigated the relationships between transcoding skills and age, spoken number sequence knowledge, language skills, and understanding of cardinality. Across all pairings of language and notation, knowledge of the cardinal principle emerged as the strongest unique predictor of transcoding accuracy, consistent with previous findings of mutual cross-linguistic transfer in the development of cardinality (Alhaider et al., 2024). At the same time, present findings reveal a predominant representation of English rather than Arabic language across transcoding skills, likely the result of differential levels of experience. The number range of stimuli successfully identified in the transcoding task far exceeded the highest number produced in children’s explicit verbal count, indicating emergent knowledge of correspondences between structural properties of spoken and written numbers. Taken together these results suggest that the early development of bilingual numeracy rests on cross-linguistic understanding of cardinality alongside language-specific mapping from spoken to written forms.

2 November 2026 in Healthcare
Verified
Journal Article
Open access
PDF file
MAMadhawi K. Altaib
Madhawi K. Altaib
RARima Alhaidar
Rima Alhaidar
ZAZakiyah A. Alsiddiqi
Zakiyah A. Alsiddiqi
LALamya Aldukair
Lamya Aldukair
SSSara F. Bin Shalhoub
Sara F. Bin Shalhoub
AAAseel Alkadhi
Aseel Alkadhi
Background/Objectives: This study examined knowledge, attitudes, comfort, perceived usefulness, and institutional context regarding artificial intelligence (AI) among speech–language pathology (SLP) students and clinicians in Saudi Arabia. Methods: This exploratory cross-sectional online survey used a questionnaire informed by Austin et al. and was distributed through snowball sampling. Data from 122 participants (75 students, 16 interns, and 31 practicing clinicians) were analyzed. Groups were compared using Kruskal–Wallis tests with Holm correction and linear regression with HC3-robust standard errors adjusted for gender and frequency of ChatGPT use. Results: The majority (97.5%) of the participants had used ChatGPT, and 77% used it three or more times per week, yet self-rated knowledge was moderate. Comfort with AI was moderate to high, and concern about AI replacing SLPs was low to moderate. The participants were uncertain about AI’s ability to administer and analyze assessments and rated administrative tasks as its most useful application. After Holm correction, only perceived usefulness differed across the three group comparisons, with interns rating it higher than students. Across 16 adjusted group comparisons, only perceived student academic use was rated higher by interns than by students. No group differences were significant among participants aged 18–24 years. Most participants (70.5%) reported having no institutional AI guidelines. Conclusions: Participants used AI frequently and held generally positive but cautious views, with few group differences. These findings support AI literacy training in SLP curricula and SLP-specific guidelines for responsible AI use.