TOJNED - Volume 16 - Issue 1 - January 2026
21ST-CENTURY COMPETENCIES IN THE AGE OF ARTIFICIAL INTELLIGENCE: RECONSTRUCTING EDUCATION SYSTEMS IN THE CONTEXT OF GLOBAL TRANSFORMATIONS Mehmet Çağlar
Abstract:
The rapid technological, economic, and social transformations of the twenty-first century have fundamentally reshaped the competencies required of individuals in education and working life. In particular, the widespread adoption of artificial intelligence technologies has made it necessary to reconsider the goals and structures of education systems. In an era where access to information is increasingly effortless, the primary function of education has shifted from knowledge transmission to fostering individuals who can adapt to change, think critically, and engage in lifelong learning.
The purpose of this study is to examine key twenty-first-century competencies in the age of artificial intelligence and to discuss the role of education systems in developing these competencies. The study draws on recent reports published by the World Economic Forum, the OECD, and the European Union, as well as contemporary international academic literature. Competency is conceptualized as a holistic construct encompassing knowledge, skills, attitudes, and values. The findings indicate that traditional knowledge-based educational models are insufficient in today’s rapidly changing environment. Instead, competencies such as adaptive thinking, problem solving, creativity, ethical judgment, and the ability to formulate meaningful questions are becoming increasingly critical. While artificial intelligence enhances efficiency in information processing, human capacity for interpretation, contextual reasoning, and value-based decision-making remains essential. The study concludes that education systems must be restructured around competency-based approaches to effectively prepare individuals for an uncertain and evolving future.
ARTIFICIAL INTELLIGENCE–BASED APPROACHES TO STRENGTHEN QUALITY IN E-LEARNING ENVIRONMENTS Hüseyin Gökal
Abstract:
With the acceleration of digital transformation in education, e-learning platforms have become a fundamental learning environment for both students and institutions. This development has further increased the need to ensure quality assurance in online learning processes. Artificial intelligence (AI) technologies—particularly adaptive learning systems, predictive analytics, and natural language processing applications—enhance personalization, increase interaction, and improve accuracy in assessment processes. This study aims to examine the contributions of AI-based mechanisms to quality dimensions in e-learning. Based on a systematic review of recent empirical studies and best-practice examples in the literature, it was found that AI-supported quality frameworks provide significant improvements in instructional design, student satisfaction, feedback effectiveness, and performance monitoring. The findings indicate that AI approaches integrated with data-driven evaluation models enable continuous quality enhancement in online learning ecosystems. In conclusion, the study offers recommendations for higher education institutions to develop AI-supported quality assurance strategies aligned with ISO 21001 and ENQA quality standards.
ASSESSMENT OF EDUCATIONAL QUALITY IN SPECIAL EDUCATION: NEW INDICATORS AND MONITORING MECHANISMS FOR INCLUSIVE SCHOOLS Turkan Gurbanova
Abstract:
The assessment of educational quality in special education has become a critical concern within inclusive education systems, where equity, accessibility, and learner-centered outcomes are central priorities. Traditional quality assessment frameworks, which rely predominantly on standardized academic indicators, often fail to capture the multidimensional needs of learners with special educational needs (SEN). This study examines emerging indicators and monitoring mechanisms for assessing educational quality in inclusive schools, with particular attention to pedagogical practices, learning environments, individualized support systems, and student well-being. Using a qualitative, theory-driven approach based on systematic literature review and policy analysis, the study synthesizes international research and inclusive education frameworks. The findings indicate that effective quality assessment in special education requires multidimensional indicators integrating academic progress, social participation, emotional development, and institutional support. The study concludes that inclusive schools benefit from adaptive monitoring systems that emphasize continuous improvement, stakeholder participation, and data-informed decision-making.
AUTHENTIC AND TRANSFORMATIONAL LEADERSHIP IN EDUCATIONAL MANAGEMENT: A COMPARATIVE REVIEW AND SYNTHESIS Taleh Mirzayev
Abstract:
This study examines authentic and transformational leadership in educational settings by integrating systematic literature findings with large-scale trend analyses from Web of Science, Scopus, and Scopus AI. Drawing on conceptual foundations, empirical evidence, and AI-supported semantic mapping, the study analyzes the core dimensions, mechanisms, teacher-related outcomes, and cultural contexts associated with both leadership styles. Results indicate that authentic leadership primarily strengthens teachers’ autonomy, well-being, trust, and ethical climate through mechanisms such as relational transparency, emotional support, and organizational justice. Transformational leadership, meanwhile, exerts a stronger influence on innovation, collective efficacy, job satisfaction, and organizational commitment, driven by inspirational motivation, intellectual stimulation, and shared vision.
Database trends show that research on transformational leadership is substantially more extensive and historically rooted, whereas authentic leadership has emerged more recently and remains less represented, particularly in longitudinal designs. Scopus AI analysis reveals three dominant thematic clusters: authentic leadership, transformational leadership, and comparative or integrative studies. Both leadership styles exhibit significant conceptual overlap, yet they differ in their psychological pathways and contextual sensitivity. Cross-cultural variability highlights the moderating role of educational governance, collectivism, and policy structures.
The study identifies key gaps, including the scarcity of longitudinal and hybrid models, limited cross-cultural comparative work, and measurement challenges due to construct overlap. It concludes that integrating authentic and transformational leadership may offer a more comprehensive framework for fostering sustainable innovation, teacher well-being, and ethical school cultures.
BALANCING GENERAL ENGLISH AND ENGLISH FOR SPECIFIC PURPOSES IN TECHNICAL UNIVERSITIES Gulshan Aliyeva
Abstract:
The role of English instruction in technical universities has become a subject of ongoing debate: should curricula emphasize general language proficiency or specialized professional training? This study investigates the balance between English for General Purposes (EGP) and English for Specific Purposes (ESP) in technical higher education. EGP develops broad communicative competence, while ESP equips students with discipline-specific skills relevant to engineering, information technology, and oil and gas industries. Drawing on international practices from leading universities, the study highlights the value of a sequential, integrated approach: beginning with EGP to build foundational language skills, then introducing ESP to address specialized academic and professional needs. Methodologically, a qualitative document analysis of 12 international technical universities was conducted, including MIT, ETH Zurich, KAIST, and Tokyo Institute of Technology. The findings indicate that a balanced EGP-ESP curriculum enhances students’ academic performance, professional readiness, and intercultural competence. Practical implications include guidance for language policy makers, curriculum designers, and instructors in technical universities, particularly in developing countries.
DIFFERENCE OF PRINCIPLES AND VALUES WITHIN THE ORGANIZATION: AN ARTIFICIAL INTELLIGENCE–SUPPORTED MIND MAP MODEL Buket Karatop, Adem Akcakaya , Kübra Zayim Gedik , Mehmet Kosem , Yasemin Kirmanli
Abstract:
This study proposes an artificial intelligence–supported mind-mapping model designed to enhance organizational learning and improve the internalization of corporate principles and values. Traditional value statements often remain static and fail to transform into actionable behaviors; therefore, organizations require technology-driven mechanisms that support shared understanding and continuous learning. The proposed model integrates four stages. First, existing organizational values are reviewed and redefined through strategic and participatory processes. Second, a Fuzzy Analytical Hierarchy Process (FAHP) is employed to determine value hierarchies and priorities using pairwise comparison matrices, providing a measurable decision-making structure. Third, qualitative and quantitative data from employees are analyzed to generate AI-supported mind maps that visualize how different groups perceive and interpret institutional values. These mind maps serve as a digital learning environment that strengthens awareness, reflection, and alignment. In the fourth stage, FAHP outputs, mind-map data, and employee insights are integrated to evaluate the coherence between value statements and organizational behavior. The findings demonstrate the potential of AI-based visualization tools to facilitate value-driven learning, reinforce organizational culture, and support technology-enhanced professional development. Recommendations for future research and practical applications in educational and organizational contexts are provided.
ECOLOGICAL SOLUTIONS TO ETHICAL DILEMMAS Sevilay Atmaca, Özlenen Özdiyar-Gedik
Abstract:
This study examines the decision-making processes employed by students when addressing ecology-related ethical dilemmas. A descriptive qualitative research design was employed to analyze students’ written, verbal, and visual responses to scenario-based ethical dilemmas with a focus on sustainability, environmental responsibility, and social welfare. Data were collected through video recordings, researcher observations, written justifications, and student drawings produced during the instructional implementation. Descriptive analysis revealed that engagement with ecological ethical scenarios supported students’ ethical reasoning, critical thinking, and perspective-taking skills. The findings further indicated that students demonstrated varying levels of ethical awareness, responsibility, and socio-ecological sensitivity depending on the complexity and contextual demands of the dilemmas presented. The study concludes that ecological ethical dilemmas constitute a meaningful instructional tool for fostering environmental awareness and ethical decision-making skills. Recommendations are provided for the systematic integration of ecological ethics into educational settings.
ENHANCING LEARNING FOR STUDENTS WITH DOWN SYNDROME THROUGH ASSISTIVE TECHNOLOGIES Gunay Badalzade
Abstract:
This study explores the transformative potential of assistive technologies (AT) in improving learning outcomes for students with Down syndrome (DS). Rapid advancements in digital innovation—ranging from speech-generating devices to adaptive educational applications—are creating more inclusive learning environments for students with intellectual disabilities. This research integrates international experiences and local perspectives from Azerbaijan to investigate the impact of AT on communication, cognitive engagement, and emotional development. Drawing on the resources of the Down Syndrome Association of Greater St. Louis (DSAGSL, 2024), the paper highlights practical examples of AT use in supporting literacy, numeracy, and self-expression. A qualitative-descriptive methodology was used, involving interviews with teachers and parents, classroom observations, and analysis of AT-supported interventions.
The findings suggest that tablet-based software, interactive whiteboards, and communication-focused apps such as Speech Blubs, Proloquo2Go, and TouchChat HD significantly enhance students’ verbal skills, attention span, and motivation. In addition, visual scheduling systems, audiobooks, and task-sequencing tools reduce behavioral anxiety and support independent task completion. Teachers and parents reported that consistent AT usage promotes greater inclusion, autonomy, and participation in daily educational routines. However, the study also identified barriers such as limited training opportunities for educators, insufficient funding, and the lack of localized Azerbaijani-language AT resources.
The paper concludes that assistive technologies can bridge the gap between students’ cognitive potential and academic demands when implemented through a systemic approach that involves training, collaboration, and policy support. To achieve sustainable inclusion, Azerbaijan’s education system must foster digital equity, strengthen teacher competencies, and promote culturally adapted AT solutions tailored to students’ linguistic and social contexts.
IMPACTS OF WAR ON CHILDREN AND ADOLESCENTS Münevver Mertoğlu
Abstract:
Many children have lost their lives in wars in recent years. Those who survived witnessed extraordinary violence.
Many children lost their parents and relatives, and almost all their homes and buildings were destroyed. Children
and their families are denied safe access to food, water, electricity, medicine, and hospitals. Hospitals and schools
were bombed. Especially children and adolescents are psychologically affected by all these negativities. The
degree of impact varies depending on the degree of violence experienced in the war, the age of the children, their
upbringing, their financial situation, and whether similar vulnerabilities have been experienced before. Another
important issue is that the problems of children and adolescents do not end with the end of the war and emerge as
post-traumatic syndrome later in life. One of the impacts of war on children and adolescents is that the violence
applied by the authorities becomes legitimized for children. For these reasons, the necessary treatment and psychosocial
support should be provided to children and adolescents, as well as to those responsible for the care of
children and teachers.
KNOWLEDGE MAPPING OF ARTIFICIAL INTELLIGENCE FOR QUALITY ASSURANCE AND ACCREDITATION IN HIGHER EDUCATION: A BIBLIOMETRIC ANALYSIS (2015–2025) Ahmet Adalier, Damla Karagozlu, Kian Jazayeri, Japheth Ahmed Nuhu
Abstract:
Artificial intelligence (AI), machine learning, natural language processing, and predictive analytics are increasingly used to enhance quality assurance, measurement, assessment, and accreditation processes. Despite this growing adoption, research on AI applications for quality assurance and accreditation remains fragmented across disciplines, including education, information science, and management. A sample of 362 papers from the Scopus database was subjected to bibliometric analysis using the VOSviewer program. Using a dataset of 362 documents, co-authorship and country-level analyses reveal highly interconnected networks, with leading contributors including Al-Ali, Maytha and Almourad, Mohamed Basel, and prominent collaboration hubs in China, the United States, and the United Kingdom. Keyword co-occurrence mapping identifies three major thematic clusters: AI and machine learning technologies, higher education and pedagogy, and quality-focused research, highlighting the interdisciplinary nature of the field. Co-citation and author citation analyses identify foundational sources, such as Assessment and Evaluation in Higher Education, and influential authors, including Apostolou, demonstrating the intellectual structure of the domain. The findings advance theoretical understanding of the integration between technological innovation, pedagogical practices, and institutional quality frameworks. Practically, the study provides guidance for institutions to leverage AI for quality assurance, enhance curriculum design, and foster international research collaborations. Future research should explore emerging AI applications in accreditation, examine evolving collaboration networks, and empirically assess the impact of AI-driven interventions on student outcomes and institutional performance.
MEDIA REPRESENTATION AND PUBLIC REACTIONS TO AI-BASED TRAFFIC CAMERAS: THE CASE OF NORTHERN CYPRUS Emel Yılmaz
Abstract:
This study examines how AI-supported traffic camera systems are represented in the media and how these representations shape the public’s perceptual and behavioral responses. It is based on the assumption that media content does more than transmit information, it transforms surveillance into a socially learned experience. Within this framework, Emel Yılmaz proposes the Perceptual Surveillance Learning Theory (PSLT), which conceptualizes surveillance not merely as a mechanism of control but as a learning process structuring social perceptions, ethical judgments, and public reactions. The theory integrates Foucault’s notion of the disciplinary society, Castells’ concept of the network society, Bandura’s social learning theory, and Habermas’s idea of the public sphere to explain how surveillance culture is internalized through media discourse. The case study conducted in Northern Cyprus shows that newspapers with differing ideological orientations frame surveillance in contrasting ways: left-leaning media present it as a violation of privacy and personal freedom, while centrist and right-leaning outlets legitimize it as essential for public safety and social order. These representations reveal how compliance, anxiety, resistance, and acceptance toward surveillance are socially learned through mediated discourse. Accordingly, this study conceptualizes surveillance as a social experience shaped by perceptual learning at the individual level and by the formation of behavioral responses within the public sphere, offering an original conceptual and contextual contribution to the literature on surveillance culture.
QUALITY ASSURANCE IN HIGHER EDUCATION: INSIGHTS FROM AZERBAIJAN STATE PEDAGOGICAL UNIVERSITY Bayim Nabiyeva
Abstract:
The paper examines the conceptual bases, institutional practices, and strategic views on quality assurance (QA) in higher education, focusing on the case of Azerbaijan State Pedagogical University (ASPU). The study incorporates a descriptive-analytical methodology, combining literature review, policy document analysis, and evaluation of institutional practices, with particular attention to management frameworks, internal quality assurance systems, and stakeholder engagement.
The findings reveal that ASPU has developed QA mechanisms aligned with international standards (ESG), while adapting them to local needs through three complementary approaches: excellence-oriented management, transformative and adaptive educational services, and accountability-based monitoring. Results from surveys, rating assessments of academic staff, and accreditation reviews demonstrate progress in transparency, institutional reputation, and quality culture. However, challenges remain in achieving a shared institutional vision, overcoming reliance on traditional teaching methods, and inhibiting the formal implementation of quality assurance procedures.
The discussion emphasizes the dual function of QA as both a compliance tool and a driver of institutional development, highlighting the importance of reflexive analysis and integration of organizational values. ASPU’s experience indicates that effective QA fosters internal cultural change, enhances trust among stakeholders, and strengthens the university’s international visibility.
The paper concludes that sustainable quality culture in higher education requires continuous self-assessment, dynamic adaptation to societal changes, and collective participation of all stakeholders. Recommendations emphasize the need to improve methodological coherence among faculty and to establish quality assurance as a transformational institutional approach rather than merely a procedural tool.
QUALITY MANAGEMENT AND QUALITY ASSURANCE IN HIGHER EDUCATION Ayşegül Tümer
Abstract:
This article highlights the importance of quality management and quality assurance in higher education. As global expectations regarding accountability and performance in education rise, universities are pursuing much more systematic strategies to enhance institutional quality. The article addresses both internal and external quality assurance mechanisms, including accreditation, strategic planning, and continuous improvement practices. It also examines the role of international standards, such as European Standards and Directives, in aligning institutions with global norms. Stakeholder engagement, particularly student involvement, is highlighted as a critical component of quality improvement. Ultimately, quality assurance is depicted not merely as compliance with standards, but as a highly dynamic, ongoing effort toward institutional excellence and innovation in education.
TURNING NUMBERS INTO QUALITY: A LEARNING ANALYTICS-BASED ACADEMIC STAFF EVALUATION MODEL IN HIGHER EDUCATION Galib Sharifov
Abstract:
The purpose of this study is to examine the longitudinal stability, structural coherence, and predictive capacity of a learning analytics-based academic staff evaluation model in higher education. Specifically, the study investigates the relationships between student feedback, composite academic staff rating scores, and demographic performance indicators within a digitally institutionalised quality assurance system.
This research adopts a quantitative, correlational, and longitudinal design. The dataset comprises institutional performance records for 565 faculty members, collected over seven years (2018–2024). Data were obtained from the digital academic staff rating system, online student feedback platform, learning management system analytics, and research and institutional service databases. Statistical analyses included descriptive statistics, longitudinal trend analysis, Pearson correlation, regression modelling, inter-year correlation heatmap analysis, and group-based comparisons across gender and age categories.
The findings reveal a consistent upward trend in academic staff performance over time, indicating continuous professional development under digital performance monitoring. A strong, positive, and statistically significant relationship was identified between student feedback scores and composite academic staff ratings, confirming that feedback is a key predictor of academic performance. Female faculty members demonstrate slightly higher average performance, whereas the 30–39 age group exhibits the strongest performance dynamics. Inter-year correlation results show that the evaluation system achieved high institutional stability and predictive reliability after 2021.
