Conference Agenda

The Swedish Education Act (SFS 2010:800) sets out the right to an equal education, an education that is expected to be compensatory and to offset differences in pupils' different circumstances. Despite the Education Act, the Organisation for Economic Co-operation and Development (OECD) (2015) review, Improving Schools in Sweden, showed that differences in equivalence between and within schools in Sweden have increased and that many Swedish schools have failed to systematically address the problem. Furthermore, the OECD (2015) reported that many schools were left alone in their efforts to remedy the problems following the inspections by the Swedish Schools Inspectorate. Based on these findings, the Swedish government commissioned the Swedish National Agency for Education to initiate school improvement work (Utbildningsdepartementet, 2015; 2019). In 2016, the National Agency for Education presented a plan to carry out the assignment and since then, nearly 150 principals and almost 400 schools and preschools have now participated in the improvement work called the Collaboration for the Best School (SBS) (Skolverket, 2022). Thus, SBS is one of the most comprehensive initiatives undertaken in Sweden in recent times.

This paper presents the preliminary results of a study of the work of process facilitators in the Collaboration for Best Schools (SBS). The process facilitators have positions at the National Agency for Education, with an assignment to, in pairs, support school organizers and schools to improve schools. The study aims to develop knowledge about the practical work of process facilitators with school organizers, principals and teachers in order to promote their capacity for improvement. A need of such knowledge is highlighted by for example Blossing (2021). Based on sociocultural theories (Jakobsson; 2012; Säljö, 2005; Wartofsky, 1979)., the following questions were investigated: What tools do process facilitators use? How are these tools used? The research contribution of this paper provides insights in school improvement in the Swedish context, thus contributing to the national and international perspectives.

The study is based on observations of dialogues, so-called process meetings, between process facilitators and representatives of school organizers, principals and teachers respectively, on interviews with process facilitators and on document analysis. The results show that process facilitators use different categories of tools for different purposes such as focusing thoughts, deepening understanding, monitoring systematic quality work, eliciting commitment and promoting improvement capacity and ownership. Furthermore, they show that in the use of the identified tools there are critical incidents or turning points that have both positive and negative impacts on the development of participants' understanding and improvement capacity. These critical incidents relate to ownership, simplification, processing, repeated constructive feedback and model focus. The SBS model for how to conduct baseline analyses and formulate action plans guides the use of tools by process facilitators. It appears that the dominance of the model presents both opportunities and challenges for process facilitators to balance.

The conclusion is that there is potential for process facilitators to develop the use of tools to contribute to the development of understanding and improvement capacity of participants in SBS and that work is needed to support process facilitators in this. The study implies that the critical incidents that have a positive impact on the development of participants' understanding and improvement capacity can be strengthened, while the critical incidents that have a negative impact need to be worked away. Support could be in the form of skills development related to critical incidents in the use of tools by process facilitators.

This study is a quantitative analysis of empirical research on the relationship between emotional intelligence (EI) and academic performance (AP).

Emotional intelligence, as related with how an individual recognizes and manages his or her emotions, has made tremendous impact in scientific circles since the development of the concept. Countless researches have been done in order to assure its prominent role in an individual’s success in life. With the increasing demand for success in the developing world, the priority of emotional intelligence has also been regarded as an opportunity. Since emotional intelligence has been referred as crucial in many parts of people’s lives, it can be expanded into the world of language learning. In Kazakhstan, most people complain about not being able to master the English language. The problem underlying this may be the effects of emotional intelligence and its subscales on learning. For this reason, this study has been conducted to fill a gap in the literature of education by focusing on the relationship between emotional intelligence and academic performance.

The literature on emotional intelligence (EI) suggests that individuals with higher cognitive processing abilities tend to perform better on cognitive tasks (Saklofske et al., 2012). In secondary education, interpersonal and intrapersonal skills play a crucial role due to the social, contextual, and personal changes and stresses that occur during this period. Adolescents' emotional development and identity formation are significantly influenced by their peer groups, with the school environment being particularly relevant (Duncan et al., 2006; Eccles and Roeser, 2009; Monreal and Guitart, 2012).

People with higher emotional intelligence tend to be more resilient, adapting well to changes, managing stress effectively, and handling challenges more successfully (Schneider et al., 2013). Moreover, students who have better emotional management skills tend to experience greater happiness and have better social relationships (Eryilmaz, 2011). Improved interpersonal management is associated with larger social networks and higher quality friendships (Brackett et al., 2005). In the classroom setting, a larger social network can foster a conducive social environment for cooperative work, group learning, peer support (Hogan et al., 2010), and positive relationships with teachers (Di Fabio and Kenny, 2015). Both the classroom climate, including interactions with classmates and teachers, and a predisposition for learning-oriented abilities are linked to greater academic performance (Brackett et al., 2011; Johnson, 2016).

In summary, there are various plausible theoretical mechanisms that can explain the relationship between EI as a set of skills and optimal academic functioning in secondary education.

The current study is being conducted at Nazarbayev Intellectual school in Turkistan in 2022-2023 academic year. There are 55 10-graders (24 male and 21 female) participating in the study. The data is being collected using an

Emotional intelligence test by Lyusin that has been designed for the purpose of the study and the reliability value was reported as .84. The pre-test using Emotional intelligence test by Lyusin was conducted to students to measure the level of their Emotional intelligence. The pre-test result showed The data will be analyzed using SPSS 23.

The aim of this study is to show the relationship between Emotional intelligence and academic performance by examine the effectiveness of materials to increase students’ Emotional intelligence. The results will be analyzed according to the presets-posttest scores conducted before and after the treatment. It is predicted that the results will show statistically significant dıfferences between participants pretest and posttest scores, which means that the treatment will be found to be effective in terms of increasing secondary school students’ levels of emotional intelligence.

Understanding predictors of academic achievement has been among the essential research focus of sociologists of education. One of the most influential studies in the field dates to 1960s. James S. Coleman and his colleagues (1966) published their famous report on their scientific attempts to unveil determinants of academic achievement differences of students from different social backgrounds in the US. The results underlined the impact of students’ parental resources and classroom composition based on these resources, more than the impact of schools attended by these students. Despite of providing attention to the impact of individual and cumulative socioeconomic disadvantage of students, the report received critics on the lack of attention to possible school effects. Following the concerning critics, some researchers dedicated their large-scale work more into investigating school effects on academic achievement and ignited an increase in studies for the field of school effectiveness research (Burušić et al., 2016; Scheerens, 2016).

Throughout the years, the field not only yielded a list of significant effects emerging from classroom and school settings, but also highlighted the need for utilizing more precise methodological techniques to account for the nature of nested data while investigating these effects on academic achievement. As an invaluable example, John Hattie (2008)proposed evidences from abundant meta-analyses on how teachers, teaching practices, and schools pose impact on student learning. On the teacher and teaching practices, some of the underlined effects pointed the importance of teaching-occupation-related variables such as expectations from students, teacher training, quality of teaching, and professional development available to teachers, and of strategies related to feedback, learning intentions, and so on (Hattie, 2008). On the school, the importance of school characteristics, school and classroom compositions, school curriculum and classroom effects (Hattie, 2008). While such evidence brought undeniable contributions to the comprehension of multiple interacting effects, Creemers and Kyriakides (2008) introduced a dynamic model of how schools impact academic achievement. Within this model, natural clustering inside formal educational institutions, students within classrooms within schools within educational systems, is illustrated. Due to this natural multilayered structures of schools, the field underlined that data collected from students, classrooms and schools violate the observation independency assumption of traditional analytical techniques (de Leeuw & Meijer, 2008; Hox et al., 2018). Therefore, to model such nested data at multiple levels by controlling for observation dependency, the field recommended the utilization of multilevel modelling as the analytical technique to precisely examine the impacts of these classroom and school factors separately and in combination (Burušić et al., 2016).

Conducting research to probe possible classroom and school effects on academic achievement is especially important in the primary schooling level. The reason behind is ascertain, early in the schooling system, which classroom and school variables significantly explain variations in academic achievement, to be able to diminish the impact of cumulative advantage mechanism, or the Matthew effect (Merton, 1968), resulting in enduring achievement gaps and therefore unequal educational gains and opportunities (Diprete & Eirich, 2006). Besides, results from these scientific attempts potentially aid educational policy makers in developing more effective and efficient approaches to supporting learning, assist school administrations in diagnosing students at risk of lagging behind, and help researchers identify possible research gaps in the field. Consequently, regarding these considerations on the relevance of the classroom and school environment on academic achievement especially in the primary schooling and possible precise contributions from studies utilizing multilevel modelling, the main aim of this systematic review of the existing multilevel modelling studies is to derive and thematize the characteristics of the classroom and school settings impacting academic achievement in primary schooling, by applying strong methodologically-conceptually driven selection criteria.