European Journal of Education最新文献

Introduction to Computer Science is traditionally the first course that all computer science and software engineering majors take. The course introduces many problem-solving techniques which can be challenging for many freshman students. In order to mitigate some of the issues of this course, we, at the Higher Education Institute, introduced a new prerequisite course, Introduction to Programming Logic, which is a required course for all students who have not taken any previous computer science course. In the Summer Session of 2022, we included prize-based learning in one of the sections of the course. Prize-based learning is similar to both problem-based learning and project-based learning in many aspects, including the principle of student-centred learning. However, it differs with respect to the motivation for student success. This approach utilises the students' ambition to win, to encourage students to work harder and learn more both inside as well as outside the classroom.

The relevance of the research topic is due to the enrichment of the musical language and methods of performing works of the 20th and 21st centuries, as well as a significant update in the means of their transmission to the listener. The study aimed to reveal the tendencies of modern pianism in the context of Western (Italy) and Eastern (China) traditions, which contribute to the realisation of its uniqueness in the process of formation of high-level professionals. This study is based on theoretical and practical methods. Theoretical methods include analysis, comparison and synthesis. Practical methods are online monitoring with systematisation and questioning. In China, the reliance on folklore is manifested in 85%, the philosophical interpretation of the content of musical works and their interpretation in 80%, the perfection of the mastery of performance technique in 95% and the synthesis of the achievements of Chinese and world performance practice in 80%. The spiritual and semantic aspect of piano performance in the framework of both countries is meaningful in 85%, the material and technical basis in 80% and ethnic self-identification in 82%. The present findings can be used both in pedagogical and performance practices of different countries, traditions and cultures.

In recent years, the intersection of self-efficacy and technological readiness has become increasingly relevant in educational research, particularly within specialised fields like music education. Understanding how these factors interplay can offer valuable insights into enhancing educational practices and fostering academic achievement among music students. This study investigates the relationship between music students' self-efficacy, academic performance and artificial intelligence (AI) readiness within the context of Chinese Music education. Adopting a random sampling method, the researchers distributed questionnaires to 1082 Chinese music students to assess their self-efficacy, academic performance and AI readiness. Utilising SPSS (version 27) and AMOS (version 24) for data analysis, the researchers explored the statistical relationships among these variables. The findings indicate that a significant 63% of variations in students' academic performance can be explained by the combined influence of self-efficacy and AI readiness. This highlights a strong relationship between these factors and students' overall success in their professional pursuits. Specifically, students' self-efficacy uniquely predicts 52% of changes in academic performance, emphasising the importance of self-belief in academic achievement, whereas their AI readiness uniquely predicts 60% of changes in academic performance, showcasing the critical role of technological fluency in driving academic success. These results provide valuable insights into the interconnected dynamics of self-efficacy, academic performance and AI readiness among Chinese music students. The study underscores the significance of confidence, technological proficiency and their impact on students' educational trajectories, offering implications for enhancing educational practices and fostering student success in the context of music education.

As artificial intelligence (AI) has been integrated into foreign language (FL) education, learners' well-being is influenced by various factors, including technological, personal and contextual elements. However, few studies explored how external and internal factors jointly shape FL learners' well-being in the era of generative AI. To fill this gap, this study explores the effects of generative AI acceptance, perceived teachers' enthusiasm and self-efficacy on FL learners' well-being by investigating 613 university learners of English as a foreign language (EFL). The structural equation modelling results reveal that (1) generative AI acceptance positively predicts EFL learners' well-being and self-efficacy; (2) perceived teachers' enthusiasm does not predict learners' well-being and positively predicts EFL learners' self-efficacy; and (3) the self-efficacy for receptive skills mediates the relationship between generative AI acceptance/perceived teachers' enthusiasm and EFL learners' well-being, whereas self-efficacy for productive skills does not play the mediation role. This research broadens the understanding of the antecedents of EFL learners' well-being and extends the application of self-efficacy theory in the AI-driven educational environment, providing significant pedagogical implications.

Aligning with the principles of positive psychology, a critical aspect that has gained prominence in academic territory over the past 2 decades is the concept of well-being. And the recent scholarly articles have underscored the centrality of teachers' psychological well-being (PWB). Given that the well-being and success of teachers are contingent upon their workplace environment, external factors such as the behaviours of the principals wield considerable influence over them. In alignment with this premise, the present investigation sought to scrutinise the structural interplay between principal transformational leadership behaviours (TLB), well-being and success within a cohort of 520 Chinese English as a Foreign Language, who were selected through convenience sampling. After the distribution of three self-report scales among the participants to assess their perceptions of principals' behaviour, PWB and success, structural equation modelling (SEM) was utilised for statistical analysis to evaluate the hypothesised model. The outcomes of the analysis revealed that principal TLB explained 62% of the variance in the participants' success and 57% of the variance in their PWB. The implications of these findings for the extant literature are deliberated upon, leading to recommendations for policymakers and practitioners based on the results.

In recent decades, research has explored tension between women academics' motherhood and institutional discourse. This study, however, delves into the performances of nine Chinese women academics who are mothers and their body boundaries between motherhood and career progression based on semistructured interview data, using thematic analysis driven by the Butlerian theoretical concept of bodies. This approach contributes to a more nuanced understanding of academic mothers in the Chinese higher education context. The findings show that academic mothers strategically perform their bodies by maintaining, crossing and disciplining their body boundaries to satisfy social and institutional discourses. The findings reveal that academic mothers constantly face the tension between career expectations and motherhood. This study has implications for policy makers in academia, higher education institutions and women academics.

To navigate the labour market graduates turn to their social network for valuable resources. However, existing disparities in accessing and exerting network resources may result in more precarious transition outcomes for first-generation graduates. To gain deeper insight into how social networks facilitate the transition process, this study focuses on the network actors and resources that are perceived as valuable by graduates. Over a 4-month period commencing at graduation, 22 graduates, encompassing both first-generation and continuing-generation students, were bi-weekly tasked with mapping their social networks. Results show that graduates rely strongly on close contacts, making graduates dependent on the experience of their parents with a certain field of work, which often results in an implicit advantage for continuing-generation graduates. Moreover, higher education institutions fail to use their power to embed valuable institutional resources or network actors into graduates' networks after graduation, which creates limited opportunity structures, in particular, for first-generation graduates.

This study aimed to develop and evaluate the psychometric properties of the Educational Leadership Scale for Faculty Members (ELSF) in Arabic. The scale was rigorously tested using both traditional methods—exploratory factor analysis (EFA) and confirmatory factor analysis (CFA)—as well as advanced network techniques, including exploratory graph analysis (EGA) and centrality measures. The study sample consisted of 350 faculty members (56% male, 44% female) from various universities, with a mean age of 42.3 years (SD = 7.8). Participants represented a range of academic disciplines, and all were involved in educational leadership roles within their respective institutions. EFA revealed a five-factor structure that explained 68.4% of the total variance. CFA further confirmed the model's adequacy, with fit indices showing a good model fit (CFI = 0.95, TLI = 0.94, RMSEA = 0.06). The ELSF, comprising 22 items across these five dimensions, demonstrated strong internal consistency, with a Cronbach's alpha coefficient of 0.89. Additionally, EGA supported the factor structure identified by traditional methods, reinforcing the stability and consistency of the scale. Centrality measures highlighted Item 18 as the most influential, with betweenness, closeness and strength centrality scores of 0.45, 0.78 and 0.62, respectively, within the ‘Research-Ethical Leadership’ subscale. These findings affirm the ELSF's credibility as a robust tool for assessing educational leadership among faculty members. The scale's strong psychometric properties suggest it is well-suited for application in diverse academic settings, including potential use across Arabic-speaking countries such as Saudi Arabia, Qatar, the United Arab Emirates, Egypt, Oman and Kuwait.

The COVID-19 pandemic has significantly altered teaching methodologies by integrating technology into syllabi, emphasising the crucial role of teacher well-being influenced by positive psychology. Also, as the foremost issues of education, teachers’ individual factors should be considered as their beliefs in their capabilities to persist in the case of difficulties and their emotion regulation (ER) have been underlined in the literature. Therefore, this study examined the correlation between teacher self-efficacy (TSE), resilience and ER and teacher well-being among 424 Chinese teachers. The findings through running the structural equation model revealed that those teachers with a heightened degree of TSE, resilience and ER are more likely to have better well-being. Multiple regression analysis indicated that TSE explained 61% of the variance in teachers’ well-being. Meanwhile, the same analysis found that resilience and ER explained 54% and 51% of the variance in teachers’ well-being, respectively. Succinctly, some educational implications are provided for educational members to attract their attention to the role of these constructs in technology-enhanced teaching.