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This study aimed to determine the expectations of students from mathematics teachers in the planning phase of lesson study (LS) in mathematics classrooms.

This study reported only a part of large-scale action research. The participants were Grade 8 students selected by the convenience sampling method. The data were obtained through open-ended questions. The content analysis method was used to analyze the data.

Four categories emerged: connection, technology-supported teaching, use of concrete materials, practice, and teacher behavior and teaching style.

This study reveals how students in a different culture and education system, such as Türkiye, want to learn mathematics in the LS process of Japanese origin. It also gives some important clues for applying LS in a different culture.

This study may attract the attention of educational stakeholders who want to implement LS in mathematics classrooms by considering student perspectives.

Due to the nature of LS, this study may emphasize teacher–student and teacher–teacher interactions. Thus, it can draw attention to the importance of social learning environments where students take responsibility and interact.

This study emphasizes the importance of listening to student voices in LS. Some ideas about mathematics teaching in Turkey should also be given. Finally, it can provide a good basis for understanding and comparing LS practices in different cultures and understandings.

Artificial Intelligence (AI) has revolutionised the tourism industry, offering personalised experiences and streamlining operations. AI provides customised recommendations for travellers through data analysis and machine learning, making their journeys more meaningful. It has also improved efficiency through automated processes, chatbots and enhanced security measures. AI's ability to analyse large volumes of data enables tourism organisations to make data-driven decisions and target their marketing strategies effectively. One of the most notable contributions of AI in tourism is its ability to offer personalised recommendations. By analysing vast travel history, preferences and online behaviour, AI systems can provide tailored suggestions for destinations, accommodations, activities and dining options. This level of customisation enhances the overall travel experience, making it more relevant and satisfying for individual travellers. AI has also greatly improved operational efficiency within the tourism sector. Chatbots, powered by natural language processing, are increasingly being deployed by hotels, airlines and travel agencies to provide instant customer support and assistance. These chatbots can answer queries, offer recommendations and handle booking processes, reducing waiting times and enhancing customer satisfaction. In addition, facial recognition technology allows for quick and accurate identity verification at airports, hotels and other travel-related facilities. This improves security and provides travellers with a seamless and efficient experience. As technology advances, we expect AI to play a more prominent role in augmented reality, voice recognition and virtual assistants, further enhancing the travel experience and facilitating seamless interactions. In conclusion, AI has transformed the tourism industry by providing personalised recommendations, improving operational efficiency, enhancing security measures and enabling data-driven destination management.

The article aims to present the results of adapting the team boosting behaviors (TBB) scale to Polish cultural conditions and validating it.

The research methodology consisted of three steps. In the first step, I translated the TBB scale into Polish using a rigorous back-translation method. Next, to assess content validity, nine domain experts reviewed the initial version of the instrument for clarity and relevance. Finally, I applied the scale to a sample of 532 team members and underwent thorough psychometric testing to assess construct validity. I employed structural equation modeling (SEM) with the partial least squares (PLS) factor-based algorithm technique for confirmatory factor analysis to assess the scale’s reliability and validity.

After development, the Polish version of the TBB scale kept its three sub-scale structures. However, the validation process led to a slight reduction in the number of test items compared to the original scale.

The findings imply that the Polish version of the scale is a valid and reliable tool for assessing TBB. However, I recommend additional studies to confirm this instrument’s structure.

The results confirmed the reliability and relevance of the tool for measuring TBBs in Polish cultural conditions. The tool provides the basis for implementing further research with the TBB construct in Poland and internationally.

This study aims to identify and explore the factors affecting social entrepreneurial intentions considering an educational institution in Portugal. It also intends to determine the relevance of moderating factors in the antecedents and entrepreneurial intention of these students.

A panel of 177 undergraduate students enrolled in a social entrepreneurship course between the academic years 2018 and 2021 is considered. The data is explored quantitatively considering descriptive analysis techniques, correlational analysis and hypothesis testing.

The findings reveal that entrepreneurial intention depends on multiple individual, organizational and contextual dimensions. Students' entrepreneurial intention remains unchanged regardless of the student’s profile. However, students' professional experience is a more relevant factor for the identification of organizational dimensions related to curriculum and critical pedagogy, while previous involvement in volunteer activities contributes to a higher prevalence of individual factors.

To the best of the authors’ knowledge, this study is original in exploring the role of entrepreneurial intention and its antecedents considering a heterogeneous students' profile. It offers theoretical and practical contributions by extending the literature on social entrepreneurial intention that can be used by higher education institutions to offer specific training more focused on the student's profile.

The aim of this paper is to determine the scope and content for a holistic conservation and development strategies in the case of Gaziantep Rumkale. This approach seeks an answer to the question of “How can Rumkale archaeological heritage be preserved with their original values and passed on to future generations?”

The materials of the paper are based on field research and written and visual resource. The paper has been handled with a four-step method setup. The first stage is to examine the spatial and functional background of Rumkale and its immediate surroundings based on the historical development process. The second stage is to evaluate the upper- and lower-scale planning experiences of the heritage site. The third stage of the research methodology is strengths, weaknesses, opportunities, and threats (SWOT) analysis. The fourth stage is the creation of cultural heritage conservation-development strategies that define strategies for the protection and development of archaeological heritage in the context of sustainability.

The paper emphasizes the development of a holistic perspective that theoretically deals with the archaeological heritage sites of Rumkale together with the surrounding rural areas. In this context, the paper suggests ecological, spatial, socio-cultural, economic and institutional protection development strategies for the Rumkale archaeological site together with the surrounding rural areas for their delivery to future generations.

Although the area has an important cultural heritage value for different religions and cultures, it has not been subject to sufficient scientific research. The paper develops a holistic approach by considering Rumkale and its surroundings together.