Maria Shobeiry
Biographic Data
| ID | 9043931 |
|---|---|
| NAME | Maria Shobeiry |
| GIVEN NAMES | Maria |
| FAMILY NAME | Shobeiry |
| SIGNATURE | SHOBEIRY M |
| AFFILIATIONS | University of Tehran |
| ORCID | 0000-0002-2499-0366 |
| VERIFIED | Yes |
| TOTAL WORKS | 3 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 3 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2021 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 0 |
The impact of AI-mediated gamified flipped learning on adult English language learners’ vocabulary learning and motivation in mobile-assisted language learning contexts
While there is increasing interest in the role of artificial intelligence (AI) in second language instruction, the interplay between AI-mediated gamification and flipped learning on vocabulary development and motivation in adults remains underexplored. This research addresses a notable gap by exploring the impact of an AI-assisted gamified tool integrated into a flipped classroom framework on vocabulary acquisition and learner motivation among in…
IELTS examiners' kiwi accent and iranian IELTS candidates' identity and speaking performance in New Zealand
This study explores the influence of IELTS examiners' New Zealand accent (aka, Kiwi accent) on the speaking performance of 45 men and women Iranian IELTS candidates within the framework of communication accommodation theory (CAT) from the post-structuralism perspective in which identity is considered to be a dynamic approach. This is a mixed-method explanatory sequential design in which the candidates' speaking scores on a real IELTS test were co…
Personalized learning reliability of tell me morea dynamic approach
This study investigated the personalized learning reliability of Tell Me More (TMM) (i.e. the extent to which two hypothetical identical learners receive the same level of instructional and learning support while using a courseware) within the dynamic framework of Tetzlaff, Schmiedek, and Brod (2020), in which personalized learning is considered to be the most reliable and effective when learners’ characteristics are dynamically assessed during t…
No prominent works on this page.
Personalized learning reliability of tell me morea dynamic approach
This study investigated the personalized learning reliability of Tell Me More (TMM) (i.e. the extent to which two hypothetical identical learners receive the same level of instructional and learning support while using a courseware) within the dynamic framework of Tetzlaff, Schmiedek, and Brod (2020), in which personalized learning is considered to be the most reliable and effective when learners’ characteristics are dynamically assessed during t…
IELTS examiners' kiwi accent and iranian IELTS candidates' identity and speaking performance in New Zealand
This study explores the influence of IELTS examiners' New Zealand accent (aka, Kiwi accent) on the speaking performance of 45 men and women Iranian IELTS candidates within the framework of communication accommodation theory (CAT) from the post-structuralism perspective in which identity is considered to be a dynamic approach. This is a mixed-method explanatory sequential design in which the candidates' speaking scores on a real IELTS test were co…
The impact of AI-mediated gamified flipped learning on adult English language learners’ vocabulary learning and motivation in mobile-assisted language learning contexts
While there is increasing interest in the role of artificial intelligence (AI) in second language instruction, the interplay between AI-mediated gamification and flipped learning on vocabulary development and motivation in adults remains underexplored. This research addresses a notable gap by exploring the impact of an AI-assisted gamified tool integrated into a flipped classroom framework on vocabulary acquisition and learner motivation among in…
Psychology (2 works) · Artificial Intelligence (1 work) · Blended Learning (1 work) · Comprehension approach (1 work) · Computer Science (1 work) · Cooperative learning (1 work) · Dynamic assessment (1 work) · Educational technology (1 work) · EFL/ESL Teaching and Learning (1 work) · Engineering (1 work)