Mehmet Başaran

In this study, a Multi-Complementary Approach (MCA) was employed to assess the effectiveness of Artificial Intelligence-Supported Mind Maps Applications (AISMMA) in a life science course, with the experimental component conducted in a public primary school in Gaziantep, Türkiye. The approach comprised three interconnected stages. In the initial stage, results from the literature were comprehensively analyzed. The analyses revealed that the outcomes of 41 experimental studies produced a strong, positive effect on academic achievement (g = 0.86). In this stage of the research (“post-complementary knowledge”), a pre-test–post-test design was implemented with experimental and control groups comprising 78 primary school students. As a result of this stage, which targeted the identified methodological and contextual gaps, the post-test scores of the AISMMA experimental group were statistically significantly higher (t = 2.85, p < .05, g = 0.68). Finally, in the “complementary knowledge” stage, the outcomes of the first two stages were synthesized, providing a comprehensive examination of AISMMA’s effectiveness in life science instruction. After introducing the MCA and its underlying epistemological rationale, the study’s methodological procedures and findings are presented in a step-by-step manner. A literature review, based on document analysis within the context of “life in our country” in life science curricula, revealed that AISMMA has a positive and significant impact on academic achievement and various supporting variables in life science education. These convergent findings underscore AISMMA’s potential to meet the evolving demands of the digital age, thereby advocating its broader and more systematic integration into life science teaching environments.

This research investigates the psychometric properties of the Early Childhood Engineering Design Test (EDTEC), a tool developed to assess children’s engineering design skills. Within the scope of the study, the cognitive processes underlying engineering design are conceptualised in terms of verbal, numerical, and visual-spatial thinking. The scale development study was conducted with 1,410 children aged 5–7 years attending 15 preschools at various socioeconomic levels. “Early Childhood Engineering Design Test”, “Problem Solving Scale (PST)”, and “Cognitive Ability Test (CAT)” were used as data collection tools in the study. During the scale development process, the validity of the scope was examined within the scope of validity studies. Exploratory and confirmatory factor analyses were performed for construct validity. Age, PST, and CAT measurement tools were used to determine the criterion validity of the scale. The scale’s reliability was determined using Cronbach’s alpha and test-retest methods. As a result of the analysis, the three-factor structure of the scale was confirmed, and it accounted for 39% of the total variance. Reliability coefficients for sub-dimensions. It ranges from 70 to 0.86. As a result of the test-retest, the Pearson correlation coefficient was 0.99 in the sub-dimensions of verbal thinking and numerical thinking; in the visuospatial sub-dimension, it was obtained as 0.98. According to the criteria validity results, it was observed that there was no significant relationship between PST and EDTEC. It has been revealed that the engineering design process differs from general problem-solving. In addition, analyses of the relationship between EDTEC and CAT revealed a partial overlap of cognitive structures between VT and VST, with a weak but positive correlation. This shows that engineering design involves cognitive abilities but has a distinct structure. The findings suggest that the scale is a valid and reliable measurement tool, which can be used effectively to assess children’s engineering design skills. The findings of this study provide an important tool for assessing engineering design skills in early childhood and for integrating these skills into educational programs. It can also guide the development of educational policies to support engineering and design-based learning processes from an early age.

The investigation delves into the impact of implementing STEAM education models, specifically tailored for educators, on their comprehension and conceptualization of STEAM principles and inquiry-based teaching. Qualitative data was gathered through responses to metaphorical inquiries within the study framework. The participant group comprised 43 teachers. Analysis of teachers’ metaphorical perceptions of pre- and post-STEAM education revealed the formation of eight categories from 34 STEAM-related metaphors and six categories from 36 inquiry-based teaching-related metaphors initially. Following the training, the number of categories expanded to eight for STEAM, encompassing 42 metaphors, while the inquiry-based teaching -related categories remained at six, derived from 36 metaphors. The findings suggest that STEAM encompasses orientation, algorithm, and renewal categories, embodying a multidisciplinary and interdisciplinary approach. It entails generating products that harmonize multiple disciplines, fostering active participation, and supporting mutual reinforcement, necessitating skill development and problem-based learning. On the other hand, inquiry-based learning involves perpetually posing questions akin to children, engaging in investigative exploration akin to detective work, and results-oriented inquiry. This educational approach encourages inquiry, critical thinking, and experimentation with diverse problem-solving methodologies, fostering adaptability, providing novel perspectives, empowering individuals, and serving as the foundation for synthesizing varied ideas.

This study investigated teachers’ opinions on using artificial intelligence (AI) in education. The aim was to gain insight into teachers’ expectations, desires, and concerns regarding AI applications that will be used more frequently in education shortly. Teachers were consulted about the purposes for which AIs can be used in their lessons and the current level of AI utilization. A qualitative research method was used in the study. Data on the use of AI in education was collected through semi-structured interviews with teachers. The collected data was analyzed using content analysis. According to the findings, teachers believe AIs can be used for language learning, personalized education, and individual student tracking. All teachers participating in the study had a positive view of the use of AI in education. Moreover, most teachers think that AI applications will increase academic success; however, they expect AIs to be suitable for the student level, provide feedback to the student, and evaluate the teaching process. Participants, who stated that teachers also have responsibilities in using AIs, emphasized that teachers need to improve by receiving training on this subject. The study revealed teachers’ concerns about using AI, bringing these reservations to light. In the study’s conclusion, suggestions were made, such as the necessity of using AI in education and considering teachers’ concerns. It also addressed what needs to be done to promote the widespread use of AIs nationwide.

ChatGPT has initiated a new era of inquiry into sources of information within the scientific community. Studies leveraging ChatGPT in the medical field have demonstrated notable performance in academic processes and healthcare applications. This research presents how medical students have benefited from ChatGPT during their educational journey and the challenges they encountered, as reported through their personal experiences. The methodological framework of this study adheres to the stages of qualitative research. An explanatory case study, a qualitative research method, was adopted to determine user experiences with ChatGPT. Content analysis based on student experiences with ChatGPT indicates that it may offer advantages in health education as a resource for scientific research activities. However, adverse reports were also identified, including ethical issues, lack of personal data protection, and potential misuse in scientific research. This study emphasizes the need for comprehensive steps in effectively integrating AI tools like ChatGPT into medical education as a new technology.

The domain of early childhood education has witnessed an increasing emphasis on developing coding and computational thinking (CT) abilities. Scholarly investigations have delved into appropriate approaches for enhancing these proficiencies within early childhood classrooms. The present study aims to investigate the impact of a digital story design program, or Design-Based Digital Story Program (DBDS), on the coding and CT skills of 5-year-old children. Specifically designed for children aged 3–6, the DBDS program aligns with constructivism principles, which promote experiential learning. Employing a case–control quasi-experimental design, the study employed pre-intervention and post-intervention assessments and a follow-up retest after one month. The intervention involved implementing the digital story design program over 11 weeks, with three sessions per week, each lasting between 60 to 90 min, targeting five-year-old participants. The findings reveal that the DBDS program significantly enhances CT and coding skills compared to a control group. Moreover, female participants exhibited more significant improvements in CT skills post-intervention than their male counterparts, while no significant gender-based effects were observed in coding skills. These findings suggest that the DBDS program effectively supports the cultivation of coding and CT abilities among young children, warranting further exploration in diverse educational settings and across various grade levels.

Like any other Western country, Turkiye is becoming an educational destination for many international students, especially Africans. Therefore, Turkiye emphasizes universities' internationalization, which brought rapid success to its political and economic trends. Therefore, this present study investigated the plights of West African students in Turkish universities, specifically focusing on the West African students at Gaziantep University. The study is based on a qualitative research design with a case study approach. This study used interviews and observation to collect data from 12 participants—one participant at least from each of the 10 West African countries presently active at Gaziantep University. The data collected were qualitatively analyzed based on common themes designed for this study. According to the findings of this current study, the language and prejudice of locals against West African students and the country they come from where the enormous challenges they faced while at Gaziantep University. Concerning these findings, the present study recommends addressing the problems mentioned earlier, such as special orientation programs organized by the university and other relevant bodies, which should be delivered by university staff familiar with Africans' socio-cultural heritage and economic and political background. Likewise, scholarships and financial support from the government and other relevant authorities should be given to West African students to overcome the financial problems they encountered during their stay at Gaziantep University