Studying determinant factors for effective learning communities has become a priority for sustainable education in Yemen. Yet, comprehensive knowledge of academic self-efficacy (ASE), academic commitment (AC), and learning outcomes (LOs) variables is limited in higher education, particularly. This research aimed to examine the role of these variables in enhancing the learning attainments of Yemeni university students by studying the direct impacts of ASE and AC on LOs, the influence of ASE on AC, and, lastly, how AC mediates the relationship between ASE and LOs. The research employed a meticulously validated measurement model encompassing 12 ASE items, 10 LOs items, and 27 AC items, using robust statistical methods such as EFA, CFA, and SEM. The study engaged 611 students aged 19–27. Empirical findings confirmed the significant impact of ASE on AC and LOs, as well as the impact of AC on LOs, both of which serve as vital factors in the academic context. Moreover, the research identified an indirect influence of ASE on LOs mediated through AC. On the other hand, the results concerning the demographic variables indicated significant differences between gender and age groups, as well as between age and educational level groups. However, no differences were found when comparing gender and level groups or when considering gender, age, and level together for ASE and LOs. In contrast, for students' AC, all comparisons were significant except for the gender and age comparison. The study offers valuable insights into educational practices and policies and concludes with practical recommendations to enhance the academic environment, informed by these study outcomes.

Understanding feedback is critical for students to cope with the complexities of multilingual development and transfer across languages. While it is crucial that students possess feedback literacy (FL) as a tool for engagement growth in writing, little is known about the predictive relationships between L1 FL, L2 FL, and L3 FL and the relationship between them and feedback engagement (FE). Therefore, this study aimed to address these identified research gaps. Data was collected using a questionnaire from 262 Chinese higher education students who majored in French-English language dual programs. Data was analyzed using SPSS 27.0 and AMOS. The results revealed that L1 FL predicted L2 FL, but it did not predict L3 FL. The study also found that L2 FL predicted L3 FL. Furthermore, it was found that L1 FL and L2 FL did not predict FE, whereas L3 FL did. Students' ability to understand feedback and its application mediated their participation and FE in learning, rather than being completely determined by FL established in their L1 and L2. This difference highlighted that L3 FL, on its own, might specifically influence how engaged students were in their learning.

This study analyzes the role of AI technology, particularly Artificial Intelligence (AI) tools, in fostering multiculturalism and improving English instruction across diverse educational settings.This study employs a 24-item Likert scale survey to examine the perspectives of 115 English as a Foreign Language (EFL) instructors about artificial intelligence and multiculturalism. Results indicate a reasonable consensus on the advantages of artificial intelligence in promoting cultural diversity; yet its effectiveness is constrained by obstacles such as language barriers and cultural disparities.The research emphasizes the necessity of integrating artificial intelligence and offering opportunities for EFL teachers to improve their intercultural communication skills and cultural competence. It underscores the necessity of inclusion and representation in fostering supportive educational settings by advocating for instructional methods that promote active engagement, collaboration, and culturally pertinent content.

This study aimed to evaluate Algerian students' acceptance of blended learning (BL). It incorporated eight dimensions derived from the technology acceptance model (TAM) and unified theory of acceptance and use of technology (UTAUT) models and involved validating a research tool consisting of 32 items. Blended learning (BL) in higher education (HE) not only makes education more flexible and accessible but also enhances the overall quality of learning through diverse methods, preparing students for future digital work environments (Zhang et al., 2022). This study aimed to evaluate Algerian students' acceptance of BL. It incorporated eight dimensions derived from the TAM and UTAUT models and involved validating a research tool consisting of 32 items. The final implementation was conducted with 549 undergraduate and master’s students aged between 19 and 33. The results indicated that performance expectancy (PE), effort expectancy (EE), social influence (SI) and facilitating conditions (FC) had a positive direct effect on behavioral intentions (BI). Moreover, BI positively affected actual acceptance (AA). Additionally, there were positive and significant indirect effects of FC on AA through the mediating variables perceived usefulness (PU), social influence (SI) on AA through BI and perceived ease of use (PEU) on AA through PU. However, EE had no significant indirect effect on AA through PU. Furthermore, gender was a significant moderating variable between SI and AA. There was no significant effect of students' residence on the relationships between PEU and PU and PEU and BI. The study offers valuable insights into educational practices and policies, concluding with practical recommendations to enhance the academic environment, informed by these study outcomes. This study finds that the students' place of residence did not significantly moderate the relationships involving PEU. This suggests a uniform perception of BL’s ease of use among students, irrespective of their residential backgrounds. This uniformity is essential for the implementation of BL across diverse regions in Algeria, indicating that a one-size-fits-all approach to BL design might be effective. Researchers measured the contribution of PU, PEU, PE, EE, SI, FC, BI, AA to know the direct and indirect effects among them, as well as the research populations. The questionnaire covered all the study variables, which were applied randomly at Batna 2 University.