University students often face challenges in managing academic demands and difficulties like time management, task prioritization, and effective study strategies. This scoping review investigates the application of Deep Learning (DL) and Reinforcement Learning (RL) in evaluating and enhancing academic performance, focusing on their practical applications, limitations, and future potential. Using PRISMA guidelines, 27 empirical studies published between 2014 and 2024 were analyzed. These studies utilized advanced DL and RL technologies, including neural networks and adaptive algorithms, to support personalized learning and performance prediction across diverse university contexts. Key findings highlight DL’s ability to accurately predict academic outcomes and identify at-risk students, with models achieving high accuracy in areas like dropout prediction and language proficiency assessments. RL proved effective in optimizing learning pathways and tailoring interventions, dynamically adapting to individual student needs. The review emphasizes significant improvements in grades, engagement, and learning efficiency enabled by AI-driven systems. However, challenges persist, including scalability, resource demands, and the need for transparent and interpretable models. Future research could focus on diverse datasets, multimodal inputs, and long-term evaluations to enhance the applicability of these technologies. By integrating DL and RL, higher education can foster personalized, adaptive learning environments, improving academic outcomes and inclusivity.

Autism spectrum disorder (ASD) often presents significant challenges for adolescents in developing social interaction skills. Emerging technologies such as Serious Games (SGs) and Virtual Reality (VR) offer promising solutions by providing immersive, interactive learning environments. This scoping review evaluates the potential of VR-based SGs to enhance social skills in adolescents with ASD by identifying current applications, benefits, limitations, and research gaps. A systematic search of the literature was conducted on Scopus, focusing on empirical studies published between 2013 and 2024. Studies were included based on their relevance to the use of SGs and VR in promoting social interactions in children and adolescents with ASD. The review highlights that VR-based SGs can effectively support the development of social skills, such as communication and collaboration, by providing structured, safe environments for children and adolescents to practice and refine their abilities. However, challenges remain, including the high cost of VR equipment, the need for greater customization, and the limited scope of long-term efficacy studies. While VR-based SGs show considerable promise, further research is needed to explore their long-term impacts and improve accessibility. Addressing these challenges could solidify VR’s role in ASD interventions, enhancing social skill development and improving the quality of life for children and adolescents with ASD.

Dyscalculia is a specific learning disorder that affects numerical comprehension, arithmetic reasoning, and problem-solving skills, significantly impacting academic performance and daily life activities. Traditional teaching methods often fail to address the unique cognitive challenges faced by students with dyscalculia, highlighting the need for innovative educational approaches. Recent studies suggest that educational robotics and game-based learning can provide engaging and adaptive learning environments, enhancing numerical cognition and motivation in students with mathematical difficulties. The intervention was designed to improve calculation skills, problem-solving strategies, and overall engagement in mathematics. The study involved 73 secondary students, divided into three classes, among whom only a specific group had been diagnosed with dyscalculia. Data were collected through pre- and post-intervention assessment evaluating improvements in numerical accuracy, processing speed, and support motivation. Preliminary findings indicate that robotics and gamification create an interactive, less anxiety-inducing learning experience, facilitating conceptual understanding and retention of mathematical concepts. The results suggest that these tools hold promise as supplementary interventions for children with dyscalculia. Future research should explore long-term effects, optimal implementation strategies, and their integration within formal educational settings.

Rett syndrome (RTT) is a rare neurodevelopmental disorder primarily affecting females, characterized by a spectrum of debilitating symptoms that impact neurological, cognitive, and motor functions. Eye-tracking technology (ETT) has emerged as a prominent tool in Augmentative and Alternative Communication (AAC) systems, particularly for neurological patients with motor and verbal impairments. This narrative review aimed to evaluate studies conducted on the use of ETT to improve cognitive abilities in girls with RTT and to examine its potential application. A review of the most recent empirical evidences was conducted. Some relevant contributions were highlighted and some useful ideas were detailed. Guidelines for research and practice were argued. The analyzed data demonstrated ETT's effectiveness in improving cognitive abilities in girls with RTT. ETT may be helpful in enhancing cognitive functioning in RTT individuals.

Dyscalculia is a specific learning disorder that affects numerical comprehension, arithmetic reasoning, and problem-solving skills, significantly impacting academic performance and daily life activities. Traditional teaching methods often fail to address the unique cognitive challenges faced by students with dyscalculia, highlighting the need for innovative educational approaches. Recent studies suggest that educational robotics and game-based learning can provide engaging and adaptive learning environments, enhancing numerical cognition and motivation in students with mathematical difficulties. The intervention was designed to improve calculation skills, problem-solving strategies, and overall engagement in mathematics. The study involved 73 secondary students, divided into three classes, among whom only a specific group had been diagnosed with dyscalculia. Data were collected through pre- and post-intervention assessment- evaluating improvements in numerical accuracy, processing speed, and support motivation. Preliminary findings indicate that robotics and gamification create an interactive, less anxiety-inducing learning experience, facilitating conceptual understanding and retention of mathematical concepts. The results suggest that these tools hold promise as supplementary interventions for children with dyscalculia. Future research should explore long-term effects, optimal implementation strategies, and their integration within formal educational settings.

The transportation sector stands within a highly competitive environment, continuously seeking for effectiveness and efficiency. In the logic of decision-making processes, optimizationthe selection of the best element, with regard to some criterion, from some set of available alternativesappears central. In addition to traditional decision making, there is the technique of Linear Programming, which is an optimization problem in which the objective function is a linear function subject to linear constraints, which may be equalities and/or inequalities. Many real-life problems can be modeled in terms of Linear Programming, highlighting its strong practical interest. Therefore, Linear Programming can be a useful tool to support management in decision-making activities, helping both to reduce human effort and to provide quantitative results to optimization problems, such as revenue maximization or cost minimization. The aim of this research is to highlight how the combination of qualitative methods and quantitative techniques is an ideal combination for identifying the best solution in the decision-making process, contributing to research in the fields of organizational behavior and management. The chapter analyzes the whole decision-making process in transportation organizations seeking competitive advantage. Through a practical application of Linear Programming, presented using a case study, the chapter results demonstrate the importance of an instrument supporting decision-making process.