The COVID‐19 pandemic has forced higher education institutions to implement online learning activities based on virtual platforms, allowing little time to prepare and train faculty members to familiarize students with digital technologies. While previous studies have looked at how students engaged with digital technologies in their learning activities, the characteristics of the student engagement in online learning remain underexplored. Therefore, a systematic review of the literature on student engagement in online learning in higher education is much needed. This article synthesizes the findings on student engagement in Latin American higher education institutions during the COVID‐19 pandemic. After reviewing the studies on online learning activities, this review examines student engagement from behavioural, cognitive and affective dimensions and identifies the main characteristics of student engagement from these tripartite dimensions. The implications of the findings for online learning in Latin American higher education are as follows: (a) to transform higher education, (b) to provide adequate professional training, (c) to improve Internet connectivity, (d) to ensure quality online learning in higher education and (e) to provide emotional support. These findings will provide valuable guidance for teachers, educational authorities and policy makers and help them make informed decisions to use effective strategies to support online learning in higher education institutions. Practitioner notes: What is already known about this topic The COVID‐19 pandemic has disrupted the normal operation of higher education institutions across Latin America, impelling a shift from face‐to‐face instruction to online teaching and learning. Research on online learning in Latin American higher education has been conducted, but the findings and their implications are yet to be widely disseminated among researchers, practitioners and decision‐makers. What this paper adds Providing a systematic review of research on student engagement in online learning in Latin American higher education institutions. Analyzing the construct of student engagement in online learning from tripartite dimensions—behavioral, cognitive and affective—in the Latin American higher education context. Identifying the characteristics associated to each dimension of student engagement in online learning. Implications for practice and/or policy The need to transform the higher education system in Latin America and beyond, at two levels: to improve Internet connectivity at the technological level and to ensure the quality of online education at the pedagogical level. The urgency to offer an adequate professional training regarding the use of new technologies in online learning environments. The significance for higher education institutions to provide emotional support for students during the COVID‐10 pandemic.

Over the last decade, there has been great research interest in the application of artificial intelligence (AI) in various fields, such as medicine, finance, and law. Recently, there has been a research focus on the application of AI in education, where it has great potential. Therefore, a systematic review of the literature on AI in education is therefore necessary. This article considers its usage and applications in Latin American higher education institutions. After identifying the studies dedicated to educational innovations brought about by the application of AI techniques, this review examines AI applications in three educational processes: learning, teaching, and administration. Each study is analyzed for the AI techniques used, such as machine learning, deep learning, and natural language processing, the AI tools and algorithms that are applied, and the main education topic. The results reveal that the main AI applications in education are: predictive modelling, intelligent analytics, assistive technology, automatic content analysis, and image analytics. It is further demonstrated that AI applications help to address important education issues (e.g., detecting students at risk of dropping out) and thereby contribute to ensuring quality education. Finally, the article presents the lessons learned from the review concerning the application of AI technologies in higher education in the Latin American context.

In recent years, artificial intelligence (AI) and learning analytics (LA) have been introduced into the field of education, where their use has great potential to enhance the teaching and learning processes. Researchers have focused on applying these technologies to teacher education, as they see the value of technology for educating. Therefore, a systematic review of the literature on AI and LA in teacher education is necessary to understand their impact in the field. Our methodology follows the PRISMA guidelines, and 30 studies related to teacher education were identified. This review analyzes and discusses the several ways in which AI and LA are being integrated in teacher education based on the studies’ goals, participants, data sources, and the tools used to enhance teaching and learning activities. The findings indicate that (a) there is a focus on studying the behaviors, perceptions, and digital competence of pre- and in-service teachers regarding the use of AI and LA in their teaching practices; (b) the main data sources are behavioral data, discourse data, and statistical data; (c) machine learning algorithms are employed in most of the studies; and (d) the ethical clearance is mentioned by few studies. The implications will be valuable for teachers and educational authorities, informing their decisions regarding the effective use of AI and LA technologies to support teacher education.

Artificial intelligence (AI) and new technologies are having a pervasive impact on modern societies and communities. Given the potential of these new technologies to transform the way things are done, it is important to understand how they can be used to support inclusive education, particularly regarding minority students. This systematic review analyzes the advantages and challenges of using AI and new technologies in different sociocultural contexts, and their impact on minority students. In terms of advantages, this review found that AI and new technologies (a) improved student performance, (b) encouraged student interest in STEM/STEAM, (c) promoted student engagement, and (d) showed other advantages. This review also identifies the main challenges associated with the use of AI and new technologies for inclusive education: (a) technological challenges, (b) pedagogical challenges, (c) dataset limitations, (d) low satisfaction using technology, and (e) cultural differences. This review proposes some solutions to these challenges at the pedagogical, technological, and sociocultural levels, and also explores important aspects of inclusive education that address the students’ sociocultural diversity. The findings and implications will aid teachers, practitioners, and policymakers in making decisions on the effective use of AI and new technologies to support sociocultural inclusiveness in education.

This paper provided a review of 210 studies on AI-enhanced special education from 2013 to 2023. Through bibliometric analysis, this review aimed to explore trends, focus areas, developments, and evolving themes of the field of AI for enhancing special education. Several noteworthy findings emerged from our analysis. The trend analysis of publications and citations revealed distinct phases, including an initial exploratory phase (2013–2016) followed by a period of rapid development (2017–2023). keyword co-occurrence networks and emergent word mapping highlight AI’s transformative potential, especially in autism spectrum disorder interventions and advancements in learning environments. Emerging trends focus on mathematics learning outcomes and educational equity, evolving through phases of understanding AI's support and integrating advanced tools like virtual reality and educational robots. Topic clustering analysis revealed categories including cognitive rehabilitation and ethical AI integration, emphasizing personalized instructional environments. Implications for research stress the need to bolster foundational skills and explore innovative teaching methods, including addressing challenges in gamified learning and integrating AI seamlessly. The review reveals a need for larger sample sizes and longitudinal studies to enhance statistical robustness and real-world relevance. In educational practices, using AI tools like apps, robots, and simulations can boost engagement and support social and academic progress. Tailored interventions for specific learning difficulties, such as dyslexia and dyscalculia, through intelligent tutoring systems, offer promise for positive learning outcomes. Policymakers are crucial in facilitating technology integration by ensuring comprehensive teacher training, increased funding for tech infrastructure, and strong leadership. Initiatives targeting underserved communities aim to promote equity and access to transformative resources. This study highlights AI’s transformative potential in special education, advocating for inclusive and personalized learning environments with ethical Al solutions to address unique challenges faced by special needs students.