International Journal of Cognitive Research in Science, Engineering and Education (IJCRSEE)
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Screening Tool Facilitating Mainstream School Practitioners to Assess Educational Needs of Children With Autism Spectrum Disorders: The Bulgarian Case
Get PDFOver the years, research has demonstrated that individuals with autistic spectrum disorders are a heterogeneous group. In recent years, the concept of inclusive education has provided additional insight into the possibilities of working with children with ASD in mainstream schools. The purpose of this study is to outline the specific strengths, capacities, and opportunities for supporting children and students with ASD in mainstream schools. The Classification of Functioning, Disability, and Health for Children and Youth (ICF-CY) indicators were used as a basis and applied to different forms of ASD diagnosis, looking for more detailed individual profiles and common resources outlined despite the possible differences by gender, age, diagnoses, and according to specific difficulties and areas where children and students have difficulties. Sample comprised 201 children and students, aged 3-19 years. The results highlight the strengths and resources of a large number of the respondents with ASD, outlining their capacity in communication, language mastery and thinking. From one-fifth to more than half of the respondents do not encounter challenges when the environment and context are supportive. The reported results highlight the implications of the universal tool that teachers and educators have for thorough and in-depth outlining the personal development scope and areas. It can serve as a screening instrument in mainstream setting, alerting mainly teachers, but also families about the measures that address needs of children and students with ASD in view to facilitate personal growth
Analysis of Trainee Satisfaction with Mentorship in Early and Preschool Education Using Artificial Neural Networks
Get PDFEffective mentoring is grounded in reciprocal collaboration between mentors and trainees, where mutual respect and open, reflective dialogue are essential from the very beginning of the internship. The aim of this study was to examine which factors predict trainees’ satisfaction with their mentors by applying a predictive model. The sample consisted of 104 trainee preschool teachers from Croatia. To test the model, perceptron artificial neural networks were used (with one hidden layer and four neurons), employing the hyperbolic tangent activation function. The results indicated a low discrepancy between the training and test datasets, high classification accuracy, and balanced TPR and TNR values, with an AUC above 0.95, confirming excellent predictive model accuracy. The analysis further revealed the relative predictive strength of individual factors related to satisfaction with the quality of mentor cooperation. The mentor–trainee relationship emerged as the strongest predictor, while net salary proved to be a more influential predictor of satisfaction with mentor cooperation than support from principals or professional associates
Predictors of Attitudes Towards Domestic Violence: The Role of Gender Beliefs and Authenticity
Get PDFGender-based violence represents one of the most serious forms of violation of women’s human rights, deeply rooted in gender stereotypes and patriarchal patterns. The aim of this study was to examine the relationships between gender beliefs, authenticity in romantic relationships, and attitudes towards domestic violence against women. The research was conducted on a sample of 201 participants through an online platform. The variables were operationalized using the Domestic Violence Myth Acceptance Scale, the Gender Equality Attitudes Scale and the Serbian adaptation of the Authenticity in Relationships Scale – AIRS-22. The results indicate strong and consistent gender differences: on average, men express greater tolerance towards violence compared to women, while women show stronger support for egalitarian gender roles across all domains. The most stable predictor of attitudes towards the justification of partner violence was egalitarianism in the educational role, pointing to the importance of the educational system as a key space for socialization and value transmission. Furthermore, participants from rural areas displayed greater tolerance towards violence and more traditional attitudes about gender roles compared to participants from urban areas. Contrary to expectations, authenticity in romantic relationships did not make a significant contribution in predicting attitudes towards violence, suggesting that global attitudes are predominantly shaped by cultural and social norms rather than individual characteristics. These findings have important implications for the development of preventive and educational programs that emphasize the strengthening of egalitarian values in educational contexts and society as a whole, with particular attention to differences between urban and rural settings
Digital Game-Based Learning’s (DGBL) Effect on Students’ Academic Performance
Get PDFDigital game-based learning (DGBL) has redefined education in recent years. Instead of replacing conventional methods of instruction, the aim is to make learning more complex and adapted to how students really engage with the modern world. This study aims to collect data that will assist educators, students, legislators, and creators of digital games in recognizing the value of the DGBL approach to education. Together, they may enhance and modify these approaches to better suit students’ requirements and enhance their academic performance. The study’s conclusions may significantly affect future applications of digital educational games in educational settings. Since they could offer a deeper comprehension that would enable students’ benefit from personalized instruction through artificial intelligence (AI), while at the same time using immersive technologies would increase students’ involvement, interest, and motivation for learning in a virtual environment. A questionnaire was emailed to 328 students at all three study levels, as well as faculty and administrative personnel from Megatrend University in Belgrade, who took part in the study. According to the findings, participants believe that a) if digital games and educational content are combined in learning, students are more likely to increase their learning efficiency in this way; b) if a digital game-based learning (DGBL) approach provides a dynamic and engaging learning environment, it is more likely to increase student motivation and participation in the learning process; c) if digital game-based learning (DGBL) includes rewards, feedback, and competition, there is greater potential to significantly improve student learning outcomes; d) if digital game-based learning (DGBL) is supported by artificial intelligence (AI), which enables personalization, the learning is more likely to dynamically adapt to each student’s performance
Educators’ Views on the Impact of Traditional Music on the Socio-Emotional Competencies of Preschool-Aged Children
Get PDFThis study aims to present educators’ views on the importance of incorporating traditional music during activities with preschool-aged children to develop their socio-emotional competencies. The sample consisted of 88 educators from preschool institutions in the Republic of Serbia. The results showed that most educators frequently use traditional music in their work. Its significance for the development of emotional intelligence, social skills, and cultural awareness in children was particularly emphasized. The analysis showed that educators who regularly incorporate traditional music content report higher levels of socio-emotional competencies in children, highlighting the importance of this practice. Although the educators’ age, work experience, and place of residence did not have a statistically significant impact, regional differences were observed. Educators in different parts of Serbia assessed socio-emotional competencies in a specific way, reflecting the cultural and pedagogical particularities of those regions. The conclusions confirm the importance of integrating traditional music into preschool curricula as a way to develop socio-emotional competencies and children’s cultural identity. The research contributes to the understanding of the role of cultural heritage in the contemporary educational context, providing recommendations for further improvement of pedagogical practices
Multimodal Competence of Future Teachers – A Context of Understanding and Opportunities for Development in University Education
Get PDFThis article explores the formation and development of multimodal competence of preservice teachers in the context of teaching the disciplines Pedagogy of Construction and Technology Activities and Productive Activities in Technical and Technological Education in Kindergarten and in School 1st to 4th year classes. Students’ multimodal competence is seen as a synergistic confluence of knowledge and skills related to different modes of communication - verbal, non-verbal, visual and digital. The focus is on the skills of selecting, combining, adapting and developing multimodal educational content, integration of communication channels and technological combination of different modalities in multimodal modes. The pilot study evaluated the feasibility of designing multimodal resources that respond to students’ ages, levels of competence, learning styles, technological capabilities, and subject matter content, as well as creating learning environments that support students’ cognitive, social, emotional, and personal development. The article emphasizes the need to integrate this knowledge into pedagogical practice, taking into account the ethical principles and value focuses that guide the design of multimodal environment. The results of the study show a significant improvement in students’ skills in creating and adapting multimodal resources, and also highlight the importance of applying new technologies and artificial intelligence in the educational process in order to develop critical thinking, creative expression and personal growth in children and students
Assessing Decision-Making Skills in Electricity: Rasch Analysis
Get PDFDecision-making is an essential 21st-century skill, and this is evidenced by the fact that the skill has increasingly gained attention in the current educational landscape. Accordingly, among the various competencies assessed by PISA, decision-making has been observed to be at the top of the list. This skill is particularly important, especially considering the fact that it provides college graduates with a competitive edge in the current workforce. Despite its significance, little work has been carried out to measure decision-making in the context of physics education using Rasch analysis. Therefore, this study aimed to explore the decision-making skills of prospective science teachers, with particular attention to differences based on gender and domicile. In order to achieve the stated objective, a quantitative study method was adopted, with the inclusion of 172 prospective science teachers who had received basic physics. Accordingly, data were collected using a paper-based test technique, which included six questions related to decision-making skills. The physics material utilized during the course of the study includes dynamic electricity, and in terms of the determination of validity and reliability, as well as item difficulty and differences in decision-making skills based on gender and domicile of the prospective science teacher, the Rasch measurement approach was adopted. The obtained results showed that no items could be reviewed based on gender and domicile of the observed prospective science teachers. However, a significant difference was found between the decision-making skills of participants based on gender. Following the observations, the decision-making skills of females were better than those of males, regardless of domicile. In conclusion, the decision-making skills instrument was observed to be valid and reliable. Additionally, the investigation possesses some implications for science educators in the aspect of determining differentiated physics learning designs that accommodate the abilities of students based on gender
Can Voice Characteristics Predict the Severity of Depression: A Study on Serbian-Speaking Participants
Get PDFThere is a growing interest in detecting depression through vocal indicators for the purpose of early diagnosis and therapeutic monitoring. Thus, research on voice characteristics in different language areas among individuals with depression may potentially contribute to the standardization of vocal analysis and the development of automatic recognition programs. This study aims to determine whether specific voice characteristics can predict the severity of depression using the Montgomery-Asberg Depression Rating Scale (MADRS) in a sample of Serbian-speaking participants. The analysis included perceptual (GRBAS scale parameters) and acoustic (parameters of frequency variability, intensity variability, and noise and tremor estimation using the MDVP software) voice characteristics in a sample of 100 participants. The sample was divided into two groups: an experimental group of participants diagnosed with depressive disorder (N = 45), including an equal number of participants with mild, moderate, and severe depression (N = 15), and a control group of participants without a depressive disorder diagnosis or depression symptoms (N = 55). The prediction of depression severity based on voice characteristics was conducted using hierarchical regression analysis. The results indicate statistically significant differences in nearly all acoustic and all perceptual voice characteristics among participants with different levels of depression symptoms (MADRS score). Post-hoc analysis revealed no differences in acoustic characteristics between subgroups with different depression severity levels. However, significant differences in perceptual characteristics were found among all subgroups, except between mild and moderate depression. After controlling for gender, age, and smoking status, depression severity demonstrated statistically significant effects on nearly all acoustic and all perceptual voice characteristics. Both perceptual and acoustic voice characteristics can predict the severity of depression. The acoustic parameter of peak amplitude variation (vAm) and the perceptual parameters of hoarseness (G), breathiness (B), asthenia (A), and strain (S) were significant predictors of depression severity. Voice may hold potential as an indicative marker in predicting the severity of depression measured by the MADRS scale. The acoustic parameter related to intensity variation and the perceptual parameters of the GRBAS scale (except voice roughness) appear to be promising voice characteristics in training depression recognition models. Identifying vocal indicators as markers for detecting mental disorders, such as depression, through regression analysis may serve as a foundation for the development of artificial intelligence models for its recognition and may have future clinical relevance
The Impact of Performance on Students’ Reflective and Coping Strategies in Higher Education
Get PDFThis research aimed to track the impact of performance as a pedagogical technique on students’ reflective and coping strategies. The study was conducted at the National University of Ostroh Academy (Ukraine) in the first autumn semester of 2024 (from September to December) on a sample of 120 students from such study programs as Psychology and Public Health. The type of design was a pretest-posttest experimental design (PPED), where we measured indicators both before (pretest) and after (posttest) the performance intervention. The methodological framework consisted of three approaches: the Reflective Problem-Solving Strategies (RPSS) (Savchenko and Makienko), the Coping Inventory for Stressful Situations (CISS) (Endler and Parker), and the BASIC Ph model (Lahad and Leykin). The study presented descriptive statistics, a chi-square test (x2), and Pearson’s correlation analysis to show connections between reflective and coping strategies. The study stated that performance positively changes reflective strategies, transforming and adapting them to external conditions. In particular, the results showed that students most frequently employed reflective strategies such as “Criticality in Analyzing and Evaluating Information” and “Making Decisions Based on Internal Standards” to achieve a more effective and systematic analysis of problems that arise during problem-solving. The Pearson correlation analysis revealed that reflective strategies correlate most strongly with active and adaptive coping strategies, such as the Social Distraction Scale (CSSS) and Social Support (BASIC Ph), indicating the importance of social (group) interaction in the development of cognitive skills. Altogether, the avoidance coping strategies have been decreased significantly, indicating an increase in problem-solving, decision-making, and responsibility. The conclusion is that performance increases reflective strategies by directly solving problems, using external resources as emotional support and social coordination within the group. Performance can create open conditions for reflective problem-solving and deep emotional support between participants, which will further increase student achievement and learning motivation
Designing Language Activities for Young Learners Based on Human and AI-generated Stories
Get PDFThe article presents the results of a study conducted among novice teachers of English language, trained at two major universities in Bulgaria. The objectives of the study were: 1) to evaluate the extent to which students perceived stories, authored by human and artificial intelligence, as applicable in educational context; 2) to gain an insight into their competence to design story-based language learning activities for preschool and primary school children; and 3) to seek possible relations between their teaching competence, language proficiency levels, skills to use AI-tools and their perceptions of the usefulness and practical classroom application of the two types of narratives. Results showed that students viewed both types of texts as useful in foreign language teaching, but the displayed degree of usefulness was stronger for the AI-generated one. A tentative explanation of this finding could be the capacity of ChatGPT as a large language model to mimic human linguistic production fairly convincingly. Overall, students exhibited a reasonably high degree of understanding of language learning as a collaborative experience and showed abilities to apply interactive approaches and techniques in the activities they proposed. The higher the teaching competence of the participants, the stronger their awareness of the various interdisciplinary links a teacher can make in their language classes to other fields of knowledge. This is a promising indication for the capacity of teachers to capitalize on the affordances of story-based language learning and interweave cross-curriculum references in their teaching practices which brings added value to the learning process