Autism Spectrum Disorder (ASD) is a neurodevelopmental condition characterized by challenges in social communication and repetitive behaviors. The Picture Exchange Communication System (PECS) has been widely utilized to support communication in children with ASD by using picture cards to convey needs and responses. However, traditional PECS can be limited by its static nature and lack of immediate feedback. Recent technological advances, particularly Augmented Reality (AR), offer new avenues for enhancing these communication strategies. This study explores the integration of AR into PECS and its impact on improving basic communication skills, specifically answering questions and commenting, in children with ASD. The research involved a multiple baseline design with four participants aged 7-12 years, recruited from autism centers in Melaka, Malaysia. Results showed significant improvements in both the frequency and accuracy of responses and relevant commenting skills after the AR-based intervention. Answering skills improved by 83%, and commenting skills increased by 122%, with the average number of relevant comments rising from 3 (SD = 0.89) to 6.67 (SD = 2.25). Statistical analysis (paired t-test) revealed a significant effect (p = 0.00272). Compared to traditional methods, AR-based PECS accelerated the achievement of target communication skills. Future research should focus on larger sample sizes and explore long-term impacts to solidify these promising outcomes.

This study presents a comprehensive bibliometric and content analysis of research on autism and mathematics learning from 2010 to 2024. A total of 131 peer-reviewed articles were retrieved from the Web of Science (WoS) database using keywords such as autism, mathematics, learning, and intervention. Bibliometric analysis was conducted to quantitatively examine publication trends, leading authors, contributing countries, and co-authorship networks, offering a macroscopic overview of the field’s evolution. Visualisations generated using VOSviewer further illustrated keyword co-occurrence and thematic clustering. Complementing this, content analysis provided a qualitative synthesis of research themes and conceptual progressions across the literature. The findings revealed a clear thematic evolution. Early research (2010–2015) predominantly focused on behavioural interventions, structured instructional approaches, and basic numeracy development. Mid-phase studies (2016–2020) introduced inclusive pedagogies, social-emotional considerations, and differentiated instruction. Recent research (2021–2024) has shifted towards personalised, technology-enhanced instruction, Universal Design for Learning (UDL), and the integration of digital tools in mathematics education. Despite this growth, several gaps remain. Research remains limited in addressing cross-cultural diversity, long-term evaluations of digital interventions, and the adaptation of pedagogies in underrepresented regions. This study emphasises the need for future research to explore culturally responsive frameworks, the sustainability of technology uses, and equity in mathematics education for autistic learners.

Autism Spectrum Disorder (ASD) is a neurodevelopmental condition marked by persistent challenges in language acquisition, particularly in the lexical and semantic domains. This study examined the effectiveness of an adapted Applied Behavior Analysis (ABA) intervention in improving lexical and semantic language skills among preschool-aged children with ASD. A total of 3- to 6-year-old children participated, divided into experimental and control groups across two specialized centers. The experimental group received an adapted ABA-based program emphasizing discrete trial teaching, functional communication strategies, visual supports, and targeted reinforcement techniques. Pre- and post-intervention assessments were conducted using a structured methodology that evaluated active and passive vocabulary, semantic categorization, and contextual language use. Results from paired t-tests showed statistically significant improvements in the experimental group compared to the control group (p < .05). Despite these gains, generalization of language skills across social contexts remained limited. These findings highlight the value of individualized behavioral interventions and support their inclusion in early childhood programs for children with ASD.

This systematic review synthesizes research on the application of Augmented Reality (AR) technology in K–12 special education to evaluate its impact on learning outcomes and identify implementation trends, benefits, and challenges. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guidelines, a search of the Scopus, IEEE, Web of Science, and ProQuest databases on 20 March 2024 for English-language peer-reviewed articles published between 2010 and 2024 yielded 16 studies that met the inclusion criteria. The analysis of these studies reveals a growing research interest, particularly after 2019, with a concentration of research in developing nations like Indonesia and Malaysia. The findings consistently show that AR technology interventions, predominantly targeting students with learning disabilities and autism spectrum disorder (ASD) through 3D objects and game-based applications, positively impact academic achievement, motivation, and skill development. Despite these promising outcomes, this review concludes that a significant gap remains between the technology's potential and its current practice, hindered by challenges such as high costs, technical complexity, and a narrow research focus. Therefore, future work should prioritize developing cost-effective, user-friendly AR technology and expanding research to include a wider range of disabilities and educational contexts to ensure equitable and effective access for all students. 

The current study sought to evaluate the impact of programs used to enhance the self-regulation and social interaction for children with Autism Spectrum Disorders (ASD), as perceived by their families. The descriptive approach was used to collect and analyze data and derive conclusions after developing the study instruments. The study sample consisted of 150 families of children with ASD enrolled in special education centers in Amman, Jordan. The study participants were purposefully selected to respond to the two provided measurement scales. To measure the impact of the intervention programs, the researchers developed the Self-Regulation Behavior Scale and the Social Interaction Scale, ensuring the validity and reliability of both scales. The results of the study indicated that from the families’ perspective, programs for children with ASD had a moderate impact on enhancing self-regulation and a high impact on social interaction. Additionally, the findings of the study revealed statistically significant differences in the degree of improvement in self-regulation and social interaction behaviors related to the child’s gender and the severity of their disorder. However, no statistically significant differences were found related to the child’s age and gender in their level of improvement in self-regulation and social interaction behaviors.

This bibliometric analysis examines global trends and scholarly discussions on learning poverty, with a focus on numeracy and literacy skills among young learners over the past decade (2015-2023). All data is retrieved from the Scopus database, and quantitative methods were employed to evaluate the impact and influence of literature in this area. In conducting the bibliometric analysis, the study utilised Microsoft Excel for descriptive statistics, Harzing’s Publish or Perish for citation metrics, and VOSviewer to visualize networks related to the co-occurrence of keywords and co-word analysis. The analysis findings indicate a substantial increase in research output on learning poverty, particularly after 2020, driven by the educational disruptions caused by the COVID-19 pandemic. The key themes identified in the literature include the expansion of educational inequalities, the impact of the digital divide, and the role of educational technologies in addressing learning losses. Co-occurrence and co-word analyses reveal a strong focus on COVID-19, educational inequality, and the integration of advanced learning technologies in recent research. These findings underscore the critical importance of targeted interventions and equity-focused policies to combat learning poverty. The analysis also emphasizes the importance of ensuring that all children, regardless of their socioeconomic background, acquire essential literacy and numeracy skills. Furthermore, the study emphasises the need for resilient and adaptable educational systems to better prepare for future challenges, particularly in the face of global crises such as pandemics. Essentially, the conclusions discuss the sustained efforts to address educational disparities and promote equitable learning opportunities for all.