Conference Agenda

Inclusive education has been a central objective of international educational policy for several decades. Commitments such as the UNESCO Salamanca Statement (1994) and the United Nations Convention on the Rights of Persons with Disabilities (UNCRPD, 2006) emphasize the right of all children to participate fully in education systems that value diversity and promote equity. Despite these long-standing international frameworks, the implementation of inclusive education remains uneven, particularly in social-emotional dimensions such as social participation and sense of belonging. In many educational contexts, marginalized students continue to experience social exclusion, limited classroom participation, and weak peer relationships.

Research indicates that the quality of inclusion in schools is strongly shaped by students’ subjective experiences of belonging and social acceptance. According to Prince and Hadwin (2013), the development of a sense of belonging in inclusive educational experiences for students with special educational needs constitutes a key determinant for understanding both the effectiveness and the overall quality of inclusive practices. Empirical studies further demonstrate that children with behavioral difficulties are more likely to be excluded from peer interactions and perceived as contributors to a negative classroom climate. In contrast, children with learning difficulties may experience relatively better social integration (Krull et al., 2014). Moreover, a strong sense of belonging is consistently associated with positive educational outcomes, including higher school engagement, improved well-being, and a reduced risk of early school leaving (Walton & Cohen, 2011).

In the Turkish context, these challenges are particularly salient. Although inclusive education policies are in place, empirical research examining how inclusive practices are enacted at the classroom level, especially through technology-supported interventions, remains limited (İşcen-Karasu & Kayahan-Yüksel, 2023). In particular, studies focusing on social participation and sense of belonging as central outcomes of inclusive education are scarce, pointing to a significant research gap.

Against this backdrop, educational robotics has emerged as a promising yet underexplored approach to inclusive education. Existing research on educational robotics has largely emphasized technical skill development or rehabilitative perspectives, with comparatively limited attention given to its social-emotional and inclusive potential. Drawing on competence-oriented inclusive education frameworks (DIPF, 2019; Müller & Schumann, 2020), inclusion is conceptualized not only as access to learning but also as the interconnected development of technical, social, and emotional competencies. From this perspective, technical learning processes and social-emotional development are understood as mutually dependent, particularly within collaborative learning environments. When embedded in cooperative classroom activities, educational robots may support interaction and participation among diverse learners.

The present study is situated within the Erasmus+ Project Robot4Inclusion (Robots4Inclusion, 2024), a transnational initiative involving six European countries (Germany, Spain, Türkiye, Lithuania, Ireland, and Finland). While the broader project adopts a comparative European framework, the current study focuses exclusively on the Turkish implementation. The study aims to explore how inclusive-oriented child–robot interactions are perceived to relate to social participation and sense of belonging among marginalized primary school students in Türkiye, based on teachers’ classroom observations. The research question guiding the study is: How are changes in social participation and sense of belonging associated with inclusive-oriented child–robot interactions, as perceived by classroom teachers working with marginalized children, including those with special educational needs, low socio-economic status, and immigrant backgrounds?

By presenting qualitative findings derived from teacher interviews conducted before and after a robot-supported classroom intervention, this study contributes to the limited body of research on inclusive educational robotics in the Turkish context. In this respect, the findings suggest that technology-supported, socio-emotional learning-oriented intervention programs may represent a promising approach to addressing the low levels of student belonging reported in PISA data across Europe, while highlighting the importance of teacher perspectives in understanding inclusive classroom processes.

The learning process of students has always been and remains a very complex and individualized process. There are many definitions of the concept of the learning process based on the expected results. In recent years, research has defined learning as a complex combination of inclinations, experiences, social relationships, values, approaches, and beliefs that collectively shape the nature of a person's use of specific opportunities to gain knowledge. In this case, the student is considered as the subject of learning.: how he feels about being a trainee and how he interacts with other trainees.

The learning process, whatever it may be, requires students to overcome certain obstacles, which allows them to move on and deeper. Some people can easily cope with them (due to their natural inclinations and personal qualities), while others need support in all respects.

How can we help students overcome learning barriers? What should be the support system in a modern school? We will try to answer these questions based on the results of the conducted research.

The purpose of the study: To develop a comprehensive support system for students with learning barriers

Research objectives:

• Analysis of motivational, affective, socio-cultural theories of learning;
• Identification of the main types of barriers to learning in theory and practice;
• Analysis of the experimental group's student input data to identify learning barriers;
• Creation of a comprehensive support model for the learner;
• Creation and implementation of an algorithm for all members of the school community to work with this category of students;
• The development of the MAD (My academic diary) for the participants of the Experimental group and the selection of appropriate learning strategies in the classroom;
• Conducting coaching sessions for teachers, parents, and psychologists on algorithm-based systematic student support.

The scientific basis of the study is the motivational and affective theories of learning, which are based on humanistic psychology and consider human potential from the perspective of Self-Concept. A. Maslow, who developed a hierarchical model of motivation (1986), believed that learning can be considered as a form of self-expression, which is a specific goal. Developing this idea, Rogers believed that learning should be carried out on the initiative of the student himself, even if it was influenced from the outside, the feeling of understanding and discovering new things comes from the inside. Also interesting is Bandura's approach, which identified 4 factors of self–efficacy: personal experience (success increases self-efficacy), modeling (if they can do it, then I can do it too), social beliefs (positive beliefs increase self-efficacy, negative beliefs decrease), physiological factors (physical sensations in stressful situations affect the level of self-efficacy). For effective work with students who have certain barriers to learning, L. Vygotsky's concept of The zone of Proximal Development is ideally suited because it clearly defines the role of a tutor (mentor) in the learning process. The ideas of scaffolding (Merser, Alexsander, Wells) in the process of student support also formed the basis of tutor support algorithms in the framework of the study.

The study of the theoretical aspects of this problem has shown that there are 4 types of barriers to learning that directly or indirectly affect student learning:

1. Effective field of activity: behavior, emotional development, psychological aspects
2. Social field of activity: communication and interaction
3. Cognition and learning (cognitive, general learning skills, abilities)
4. Physiological barriers (linguistic, auditory, visual, etc.)

Teachers' knowledge of the types of barriers, the ability to interpret them and provide students with support in removing barriers in the immediate development area will help to avoid LAGGING BEHIND IN the PROGRAM MATERIAL.

This study investigates the Mistake Map strategy as a didactic intervention for developing students’ metacognitive skills through systematic analysis of errors in Biology, and Computer Science classrooms. Although contemporary learning theories emphasise the productive role of mistakes, classroom practice often treats them primarily as indicators of low achievement. As a result, students rarely engage in structured reflection on the origins of their errors or on alternative solution strategies.

As part of this activity, the Mistake Map is a recurring learning tool in which students analyze incorrect solutions, classify the type of error (conceptual, procedural, or strategic), explain its causes, and propose corrected solutions. The study used sequential mixed methods with 9th and 12th grade students (N = 94). Quantitative data were collected using conceptual tests in biology and computer science, as well as metacognitive awareness (MAI), which were supplemented by classroom observations, student questionnaires, and semi-structured interviews.

The purpose of the study is to investigate how structured error handling of summative assessment per units affects students' metacognitive regulation (planning, monitoring, evaluating) and their perception of errors as a learning resource.

In contemporary educational research, increasing attention is given to the instructional value of students’ errors. From a constructivist perspective, learning is understood as an active process in which knowledge is reorganised through the resolution of cognitive conflict (Piaget, 1977; Posner et al., 1982). (Piaget, 1977; Posner et al., 1982). Within this view, mistakes are not merely signs of insufficient knowledge but indicators of transitional understanding that can stimulate conceptual change when learners are supported in analysing them (Oser & Spychiger, 2005).

Metacognitive theory also emphasizes that effective learning requires conscious regulation of cognitive activities through planning, monitoring, and evaluation (Flavell, 1979; Schraw & Dennison, 1994; Zimmerman, 2002). However, in classroom practice, there is often a focus on correctness and performance, leaving limited space for structured reflection on why errors occur and how they can contribute to deeper understanding. This discrepancy is particularly noticeable in the biology and computer science subjects, where the use of high-level skills in assignments and dense curricula limit opportunities for systematic error correction.

The strategy is based on a curriculum that is divided into units and learning objective of the subject, and it is implemented after the summative assessment of the units. Instead of immediately correcting the answers, students fill out a table with meta-cognitive prompts as an Mistake Map using a template that includes four steps:

1. Identification – writing down the incorrect solution and the task context;

1. Classification – determining the type of error;
2. Explanation – describing the underlying cause;
3. Reconstruction – proposing and justifying a corrected solution path.

For example, after solving a programming problem involving conditional statements, a student who gets an incorrect result writes down the erroneous code fragmentexplains that the logical condition was reversed, and rewrites the corrected algorithm. In biology classes, they investigate incorrect interpretations of physiological processes, diagrams, and academic terminology.

The study pursues three main aims. First, it explores how systematic error analysis can be embedded within regular teaching practices without disrupting curricular progression. Second, it investigates the extent to which such integration supports students’ conceptual understanding and metacognitive development. Third, it examines students’ perceptions of learning in an instructional environment where errors are openly discussed and analysed.

The research question is: How does the implementation of the Mistake Map strategy influence students’ metacognitive regulation during problem solving?

By transforming mistakes into explicit objects of instruction, the Mistake Map strategy operationalises principles of error‑based learning (Oser & Spychiger, 2005) and metacognitive scaffolding (Schraw, 1998), moving beyond simple correction toward the development of reflective learning routines.