This study investigates the relationship between teacher feedback, assessment for learning (AfL), and students’ learning approaches in Pakistan’s higher education context. Despite a policy emphasis on formative assessment, classroom practices remain largely examination-oriented, limiting the effective use of feedback. Data were collected through a structured questionnaire from 294 students. Descriptive statistics, correlations, mean difference tests, and mediation analysis were employed. The results indicated that feedback types such as verification, directive, scaffolding, and praise were positively associated with AfL, while criticism showed no significant link. AfL strongly predicted students’ adoption of constructive learning approaches, underscoring its role in fostering deep engagement. Gender differences were negligible, although female students reported greater use of constructive learning strategies. Minimal age-related effects were observed, with older students valuing directive feedback more. Mediation analysis revealed that AfL partially mediated the relationship between teacher feedback and learning approaches. These findings highlight the importance of embedding AfL practices in classrooms and strengthening feedback literacy to shift learners beyond rote memorization towards deeper understanding and critical thinking. Overall, the study provides empirical evidence from a developing country context and helps clarify how feedback processes operate within existing assessment practices in higher education settings within contemporary teaching and learning environments in Pakistan.

Contemporary special education research emphasizes artificial intelligence as a tool for automating pedagogical administration and identifying student deficits more efficiently. This paper presents an alternative theoretical framework, Genius Recognition Through AI-Enabled Dialogue (GRAID), which reconceptualizes the role of artificial intelligence in special education. Drawing upon epistemic justice theory, neurodiversity studies, and phenomenological philosophy, this paper argues that current AI implementations, despite beneficial intentions, perpetuate systematic epistemic injustice by automating the diagnostic gaze that renders disabled students' ways of knowing invisible. GRAID proposes a theoretical inversion: rather than using AI to identify deficits, AI should liberate educators from compliance bureaucracy, creating temporal and cognitive space for genuine dialogue with students about their actual thinking processes. This framework articulates four interconnected theoretical dimensions: first, the concept of diagnostic epistemic closure and its displacement through sustained dialogue; second, neurodiversity reconceived not as a disorder but as a cognitive architecture constituting measurable forms of genius—systemic thinking, spatial reasoning, and rapid ideation; third, phenomenological dialogue as a practice of recognition distinct from conventional pedagogical interaction; and fourth, transformative identity formation that repositions disabled students from subjects of deficit discourse to intellectual agents. The paper further develops original conceptual innovations including the Genius-Deficit Paradox, the Epistemic Paradox of Diagnosis, and a relational ontology of disability. This theoretical framework offers philosophical foundations for educational justice without requiring empirical validation, contributing new conceptual architecture for understanding intelligence, recognition, and technology's proper role in transforming special education.

Background: Clinical decision-making is a fundamental competence in nursing practice and directly affects patient safety and quality of care. In recent years, creative thinking has been emphasized as a cognitive skill that enables nursing students to generate flexible, innovative, and effective solutions in complex clinical situations. However, empirical evidence examining the relationship between creative thinking and clinical decision-making among nursing students remains limited.

Aim: This study aimed to examine the effect of creative thinking tendencies on clinical decision-making levels in nursing students and to identify related factors influencing this relationship. Methods: This research was conducted as a descriptive, cross-sectional, and correlational study. The study sample consisted of nursing students enrolled in a health sciences faculty. Data were collected using the Student Information Form, the Marmara Creative Thinking Dispositions Scale, and the Clinical Decision-Making in Nursing Scale. Descriptive statistics, correlation analysis, and appropriate comparative tests were used to analyze the data.

Results: The findings indicated that nursing students demonstrated moderate levels of creative thinking and clinical decision-making. A statistically significant positive relationship was found between creative thinking dispositions and clinical decision-making levels. Students with higher creative thinking scores showed more effective and confident clinical decision-making abilities. Additionally, certain sociodemographic and educational variables were found to influence both creative thinking and clinical decision-making skills.

Conclusion: The results of this study suggest that creative thinking plays an important role in enhancing clinical decision-making skills among nursing students. Integrating educational strategies that promote creative thinking into nursing curricula may contribute to the development of students’ clinical judgment and decision-making competencies. These findings provide valuable evidence for nursing education programs aiming to improve clinical performance and prepare students for complex healthcare environments.

Keywords: Nursing students, creative thinking, clinical decision-making, nursing education

Understanding counting by tens up to 100 is a core component of early numeracy and place-value development in first-grade primary education. This study investigated the effect of tablet-based digital activities on students’ understanding of increasing and decreasing by ten, with particular attention to Special and Inclusive Education. A quasi-experimental design with a control group was implemented. The sample consisted of 82 first-grade students from public primary schools, including students with disabilities and learning difficulties, who formed an integral part of the research sample. The experimental group (n = 41) participated in a four-week instructional intervention using specially designed tablet-based digital activities, while the control group (n = 41) followed conventional instruction based on the standard curriculum.

A researcher-developed assessment tool was administered as both a pre-test and a post-test, allowing for direct comparison of students’ performance before and after the intervention. The assessment measured students’ ability to count forward and backward by tens up to 100 and to recognize numerical patterns related to base-ten structure. The digital activities emphasized visual representations, interactive number lines, immediate feedback, and differentiated task progression, supporting diverse learning needs within the classroom.

The results showed that the experimental group achieved significantly greater improvements in post-test scores compared to the control group. Notably, students with disabilities and learning difficulties demonstrated clear progress in accuracy and conceptual understanding, indicating that the tablet-based intervention functioned as an effective supportive tool within an inclusive instructional context.

The findings suggest that well-designed tablet-based digital activities can enhance early numeracy skills and contribute positively to Special and Inclusive Education practices in first-grade classrooms, supporting meaningful learning outcomes for students with diverse educational needs.

The integration of artificial intelligence (AI) into higher education is accelerating, reshaping teaching practices, learning environments, and institutional decision-making. While AI is often promoted as a solution for personalization and efficiency, its educational value remains uneven and context-dependent. This study critically examines how AI technologies are currently used in higher education and assesses their pedagogical, ethical, and equity-related implications within technology-enhanced education.
The study adopts an analytical literature review methodology, drawing on peer-reviewed publications. Keywords included artificial intelligence, higher education, adaptive learning, academic integrity, and educational equity.
The review identifies four key findings. First, adaptive learning systems and intelligent tutoring tools show consistent improvements in student engagement and performance, particularly in large or heterogeneous classrooms, when supported by instructor involvement. Second, AI-driven assessment and feedback tools enhance efficiency and formative feedback but risk narrowing learning to measurable outputs if poorly aligned with pedagogy. Third, AI applications can improve accessibility for students with disabilities and non-traditional learners; however, unequal access to infrastructure and digital literacy may reinforce existing inequalities. Fourth, concerns occur in unsupervised use of AI especially in terms of data privacy, ethical scholarship and the risk of reduced critical thinking competence.
This study’s contributions have to do with linking specific AI applications to clearly defined educational outcomes and risks, rather than treating AI as a uniform intervention. It concludes that responsible AI integration in higher education requires pedagogically grounded design, institutional governance, and equity-oriented implementation strategies.