Hybrid teaching, which integrates traditional in-person learning based on students’ perspectives where online learning offers a flexible approach to education, combines the benefits of technology with face-to-face interactions. Moreover, teaching and learning in a hybrid way met several challenges for both teachers and learners, including technological problems, time management, communication difficulties, and assessment complexities. This systematic review investigates six main research questions: (1) What pedagogical frameworks are used in hybrid teaching and learning? (2) How can we enhance students’ engagement in hybrid teaching and learning? (3) What is the impact of technological integration on hybrid learning scenarios, both for students and teachers? (4) How do training and support measures influence the willingness and ability of university teachers to implement hybrid teaching formats? (5) How do formative assessment and feedback methods in hybrid learning environments enable teachers to effectively monitor student progress and provide tailored support? (6) How does the implementation of hybrid learning affect student learning outcomes? This study identifies the following key themes: technological integration, pedagogical innovation, faculty support, student engagement, assessment practices, and learning outcomes. Our contribution of this literature review is related to teaching and learning by showing teachers the most appropriate way to avoid the challenges encountered when teaching in a hybrid way. These include strong technology integration, innovative pedagogical strategies, strong academic development and support, active student engagement, effective assessment practices, and positive learning outcomes.

The integration of multimedia technologies is transforming teaching and learning in higher education, offering innovative ways to improve student engagement and learning outcomes. Although numerous studies investigate the impact of multimedia, there is still a clear need for a synthesis that brings together the latest evidence from a variety of disciplines and contexts. To address this need, this systematic review aims to summarize the empirical evidence and provide a clearer understanding of how multimedia is applied in higher education, to outline how educators can effectively design and the implications for curriculum design. This article focuses on three key research questions: (1) How does the integration of multimedia in higher education classrooms influence student engagement and learning outcomes? (2) How does the use of multimedia affect the development of specific skills? (3) What are the challenges and opportunities to integrate multimedia technologies into higher education? Relevant studies were systematically retrieved and screened from major academic databases, including ScienceDirect, Web of Science, IEEE Xplore, Wiley Online Library, Springer, Taylor & Francis, and Google Scholar. In total, 48 studies were selected from these sources for detailed analysis. The findings showed that multimedia tools enhance student engagement, motivation, and performance when integrated with clear pedagogical strategies. In addition, multimedia helps to develop skills such as creativity, digital literacy, and independent learning. However, challenges such as technical limitations, uneven infrastructure, and the need for ongoing teacher training remain significant difficulties in fully exploiting the benefits in higher education. Addressing these challenges requires coordinated institutional support, investment in professional development, and careful alignment of multimedia tools with pedagogical goals.

Artificial intelligence (AI) and related technologies have become important components of the digital economy and affect core areas of our increasingly technologically networked lives. Specific AI technology can support diverse learners and how AI is used in particular in the context of Adult Education to provide a more inclusive and flexible learning environment. Artificial intelligence has been changing education for a long time now, and it is becoming more pervasive in our lives. The authors analyzed many advantages of using AI as an educational tool, such as increasing student engagement by improving grading accuracy by automatically scoring essays with machine learning algorithms. We present a case on how wireframes can be used in website design. Several existing tools have been examined, and their ability to generate interfaces from sketches has been explored. Creating wireframes, prototypes, design mock-ups, and layouts followed the web development process and is now a significant part of website development in engineering education. The paper aims to give the direct opportunity to observe examples of AI wireframes for engineering education.

The study explores the application of data analytics and machine learning to forecast academic outcomes, with the aim of ensuring effective and sustainable e-learning. Technological study programs in universities often experience high dropout rates, which makes it essential to analyze and predict potential risks to reduce dropout percentages. Student performance prediction (SPP) offers potential benefits, including personalized learning and early interventions. However, challenges such as (1) data quality and availability and (2) incomplete and inconsistent data complicate this process. Moreover, to support the fourth Sustainable Development Goal (SDG), we focus on the quality of education. A case study approach is used using data mining techniques, particularly classification, regression, and clustering, to predict student performance. The case presented aims to predict risks and ensure academic success and quality. The cross-industry standard process for data mining (CRISP-DM) methodology is used to structure and guide the prediction process. The study shows that using data from student learning processes within an academic success prediction model and data mining can identify at-risk students.

Learning environments ensure successful implementation of the learning process but not always the effective design of the e-learning objects (ELOs) and moreover, search and adaptation. A technological solution for the design of the learning objects, repositories, and the semantic web is needed. There are many open educational resources, but not many platforms assure the possibility to adapt learning objects. The existing developed multifunctional platforms do not ensure the effective ELOs adaptation as well as the process of design and adaptation in the multifunctional environment. They do not have an automatic search of ELOs in the semantic web, which is directly targeted to the specific objects in repositories of open educational resources and do not allow for adaptation of the already developed ELO by automatically assigning reusable objects. The structure of the papers consists of the literature review and overview of existing practices, research methodology, research results description and conclusions provided by authors. The objective of the research is to suggest, to teachers, a model for effective e-learning objects design, automatic search and adaptation processes in the multifunctional environment by developing a platform based on semantic technologies for e-learning objects design and adaptation.