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Technology-enhanced learning (TEL), particularly in science, technology, engineering, arts, and math (STEAM), revolutionizes educational approaches by fostering active, transformative learning and expediting the learning process. TEL employs various tools like online courses, artificial intelligence (AI) technologies, virtual reality (VR), simulations, makerspaces, visual learning, and project-based learning, all contributing to accelerated learning in STEAM. A notable TEL innovation is the emergence of Large Language Models (LLMs) and AI chatbots, exemplified by the release of GPT-3 in December 2022. These tools utilize extensive parameters to generate natural language and perform tasks such as classification and prediction, thereby offering personalized and collaborative learning experiences essential for STEAM education. The generative pre-training transformer (GPT), a leading model in natural language processing (NLP), excels in generating human-like text and handling complex tasks like translation, summarization, and question answering. This chapter explores TEL environments that support transformative learning in STEAM, focusing on AI models. It reviews research on TEL’s impact on STEAM education, discussing the constructionism theory and emphasizing TEL’s role in creating engaging, student-centered learning experiences. However, challenges like technology access, instructor training, infrastructure, internet connectivity, and hardware resources are crucial. Additionally, the rise of AI brings ethical concerns regarding privacy, security, and potential biases in AI algorithms. Despite these hurdles, TEL’s potential to enhance STEAM learning experiences and accelerate the educational process is significant. By effectively implementing TEL strategies and leveraging LLMs and AI tools, educators can substantially improve learning outcomes in STEAM education.

Toward the construction of a new paradigm in teacher education in a globalized and digitalized society where it is intended to value knowledge and teacher professional development sustained by collaboration and cooperation, training policies and models based on technology-enhanced active learning will be required. This chapter aims to analyze the dimensions that can affect these training models within a new educational paradigm, at the level of professional development and increase of technological skills, collaborative processes for the creation of communities of practice, and promotion of active learning that contribute to innovative hybrid environments and transformative learning. In the Covid-19 post-pandemic, it is crucial to study and mobilize the experiences developed in the educational field exploring how these can be harnessed to build this new educational paradigm. This work aims to contribute with a reasoned reflection and insights concerning learning models and methodologies in teacher education that contribute to transformative active learning. Focusing on the link between preservice and in-service teacher education, the interrelation among teacher education and evaluation, and the construction of innovative technology-enhanced learning environments, for instance through the active training model.

Healthcare education is a huge industry with a significant social footprint and resilient impact on well-being and on the quality of life. It integrates diverse scientific domains and needs to continuously update its value proposition to reflect the need for preparing top-quality health professionals. It also has to support professional development and to manage effectively the accreditation of programs and the certification of skills and knowledge. In this chapter, the authors expand a theoretical framework about Active and Transformative Learning (ATL) that has introduced in the volume of ATL for STEAM disciplines and also discussed how artificial intelligent (AI) tools, such as OPENAI Chat GPT, can serve as transformers and value carriers for the implementation of ATL activities and use cases in healthcare education.

Active and transformative learning (ATL) challenges the new era of teaching and learning in higher education. In this chapter a systematic approach to ATL theories and methodologies is provided. Authors provide a unique methodological framework for the integration of active learning practices in modern higher education curricula. This chapter also provides an integrated context for the overall discussion of the phenomenon in the volume. The recent arrivals of new disruptive artificial intelligence-enabled technologies such as OpenAI, ChatGPT, DeepAI and others are only few aspects of a new challenging era for the teaching, learning, innovation and sustainability in the higher education.

The impact of education and research skills on the strategic digital transformation of education is straightforward. In this context, the Saudi National Institute of Health plays a pivotal role in the design and implementation of a resilient and robust strategy for the development of skills and competencies to young health professionals. In this chapter, the authors provide a brief overview of the Vision 2030 in Saudi Arabia and its basic priorities in the areas related to the Education and Research in the healthcare domain. The authors also elaborate on the key plans and initiatives undertaken by the education and research skills directory of the Saudi National Institute of Health (SNIH) towards transformative learning with impact on the implementation of the Vision 2030.

Online learning becomes a trendy format for workplace training, particularly during the pandemic. This study aims to examine the effects of a technology-assisted self-adaptive training camp on employees’ learning process and acquired knowledge, and the relationship between employees’ knowledge gained and organisational growth.

The participants were 213 pharmaceutical representatives from a global pharmaceutical business in the Asia-Pacific branch who enrolled in a 21-day professional training camp. Their knowledge gained was calculated by pre-tests and post-test scores captured from an online training system. The company’s profits gained by employees were indicated by individuals’ quarter-over-quarter growth rates. Specifically, the authors applied a series of quantitative analyses to examine the relationship between employees’ knowledge gained, learning quality and organizational growth brought by individuals.

During the online training session, employees obtained increased professional knowledge significantly. The quality of employees’ learning process was a significant predictor of their learning outcomes. In addition, a positive correlation was found between the knowledge obtained by employees and the company’s quarterly growth rates. A followed-up regression analysis indicated that the greater knowledge improvement an individual achieved, the higher quarter-to-quarter growth rate brought by the individual to the organization.

The study provides educational insights for organisations to effectively train employees’ professional competency through online learning. The investigation on the 21-day camp shows that employees received higher-quality training, resulting in increased revenues and greater workplace flexibility. The findings have implications for supporting the integration of educational technology into workplace training to boost the competency development of employees.

Given the persistent receptive skills challenges faced by language learners and the numerous merits of using technologically-enhanced learning in the form of mobile-assisted language learning in language teaching, this study decides to incorporate a context-analysis-practice-exploration lesson-planning framework with mobile learning to improve the receptive skills of learners. This step is necessary on the recommendation by scholarly research that while implementing technology, teacher training, digital literacy and expertise, incorporating good teaching practices and lesson planning frameworks may assist in yielding positive results.

This study decides to utilize a mixed-method research design through an experimental approach to elicit information from 90 EFL students concerning the effectiveness of incorporating the context-analysis-practice-exploration framework in a mobile-leaning mode instructional delivery to improve their reading and listening skills.

After collecting and analyzing data, the study found that while the participants perceived enhanced-mobile learning to make lessons enjoyable, integrating this framework and m-learning improved their reading skills. This study used notable findings to make pedagogical conclusions on the objective of this study.

This study contributes through empirical evidence on the effectiveness of incorporating mobile learning and a responsive lesson planning framework towards improving English as a foreign language learners' learning outcome. Besides, this study is the first to probe and unpack the effectiveness of a responsive lesson-planning framework in language education.

The use of technology in Saudi Arabian higher education is constantly evolving. With the support of the 2030 Saudi vision, many research studies have started covering learning analytics and Big Data in the Saudi Arabian higher education. Examining learning analytics in higher education institutions promise transforming the learning experience to maximize students' learning potential. With the thousands of students' transactions recorded in various learning management systems (LMS) in Saudi educational institutions, the need to explore and research learning analytics in Saudi Arabia has caught the interest of scholars and researchers regionally and internationally. This chapter explores a Saudi private university in Jeddah, Saudi Arabia, and examines its rich learning analytics and discovers the knowledge behind it. More than 300,000 records of LMS analytical data were collected from a consecutive 4-year historic data. Romero, Ventura, and Garcia (2008) educational data mining process was applied to collect and analyze the analytical reports. Statistical and trend analysis were applied to examine and interpret the collected data. The study has also collected lecturers' testimonies to support the collected analytical data. The study revealed a transformative pedagogy that impact course instructional design and students' engagement.