Digital Transformation in Higher Education, Part A

Digital transformation (DT) has become a top priority for higher education (HE), driven by technological advances such as artificial intelligence (AI), artificial general intelligence (AGI) and Generative Open AI. It serves as a catalyst for the reshaping of mainstream processes in academic institutions, emphasizing teamwork, collaborative projects and critical thinking in research, learning and assessment strategies. In this chapter, the authors contextualize the use of this DT, highlighting its potential to improve learning experiences, business efficiency and upskill students and faculty. The holistic approach to DT as an enabler of excellence in HE is based on four pillars of excellence and impact: Business process reengineering, learning excellence and skill building, research capacity and innovation and partnership and outlook. DT needs the development of efficient, resilient, flexible and adaptable strategies and a strong collaboration between all the actors involved in the process to ensure the coherence, the sustainability and alignment of the objectives, means and targets with the real needs of the learners, tutors, labor market and society as whole. The authors’ bold proposition consists of a model for the strategy design of DT in universities and colleges organized in three dimensions: understand, strategize, deploy and exploit. Each dimension emphasizes different stages of the process: understanding emerging technologies and their impact on HE, collaboration between stakeholders, strategy and priorities formulation, roadmap of implementation, deployment and exploitation of digital technologies, etc. The ongoing DT in HE will continue to create an extensive shift in educational processes – learning, teaching, research and management. Institutions around the world are taking bold initiatives to adapt to this rapidly changing environment, emphasizing the importance of readiness for technological changes, system development, inclusive and sustainable transformation.

As an emerging technology marked by rapid advancements, artificial intelligence (AI) has the potential to profoundly transform higher education, particularly after the emergence of ChatGPT at the end of November 2022. Because of its immense power, it poses greater expectations and challenges than any technological advancement in the past. Thus, this paper aims to identify and discuss the need for AI-driven transformation, its challenges as well as policies and expectations of AI's successful integration into teaching and learning. This study examined recent literature and policy documents mostly published after ChatGPT's launch. This study may assist students and instructors in promoting awareness of the importance of ethical, positive and productive AI applications. Besides, the findings of this paper may aid in developing and adopting appropriate educational policies, improving curricula and training pre-service and in-service instructors in adopting knowledge, competencies and strategies for the efficient integration of AI in the teaching process. Thus, the study may help build a strategy for integrating AI systematically into higher education processes and contributing to the transformation of higher education.

Artificial intelligence (AI) tools, namely ChatGPT, Copilot (Bing) or Gemini (Bard) chatbots, have brought very rapid repercussions at education level in general, especially in higher education. Several challenges are being presented to institutions, teachers and students, highlighting the way teachers teach and students learn, and significant transformations are expected in the short term due to the availability of this type of tools. This chapter aims to analyse and discuss how the new generative AI tools, which are accessible to all, can influence teachers' instructional methods and transform the format and the ways students learn. What are the main challenges, limitations and changes that we can foresee, considering the dangers and constraints of these new tools, regarding the teaching and learning processes of young adults in higher education. A case study was selected, using an exploratory questionnaire survey of undergraduate students, which was analysed using descriptive statistics. This study demonstrated that teachers, in student perspectives, are still far integrating IA in their pedagogical strategies, mainly focussing in the dangers and limitations and little in the potential. The aim was to contribute to assess how these new working tools can be an instrument that enhances critical thinking and active and transformative learning of young adults, when used with the minimisation of risks and errors. Furthermore, it is intended to reflect on appropriate AI educational policies as well as on the development of competences and digital literacy in the training of higher education students as global citizens.

The research explores how artificial intelligence-driven natural language processing can be integrated into digital game-based learning to enhance science education worldwide. It conducted a thorough literature review focusing on electronic bibliographic databases, identifying nine key themes. The chapter discusses the potential of digital games to improve science education, including theoretical frameworks, integration techniques and problem-solving methods. It also examines the impact of gaming on critical thinking and natural language processing. The findings suggest that integrating natural language processing into digital game-based learning shows promise for improving inquiry-based teaching and student performance in science education. Digital platforms can offer personalized feedback, support natural language interactions and customize content for each student. However, addressing pedagogical concerns and technological limitations is crucial for fully realizing these benefits. Practically, the research offers guidance for educators, curriculum developers and policymakers. It emphasizes the importance of educating educators on natural language processing, developing inquiry-driven digital learning platforms and establishing supportive policies. This signifies a move toward student-centered learning and the integration of innovative technologies into education. In terms of originality and value, the study contributes to the existing knowledge by discussing challenges and potential strategies for integrating digital game-based learning with natural language processing globally. It suggests that future research and practical efforts in this area can benefit from a comprehensive understanding of the opportunities and implications of this educational approach, informed by extensive research across various themes.

Micro-credentials have become increasingly popular in the higher education landscape, providing students with the opportunity to obtain specific skillsets and competencies in a shorter timeframe than traditional degree programs. Micro-credentials are typically awarded upon the completion of a short course or programme and are designed to demonstrate a student's knowledge and expertise in a particular area. Global online learning platforms, such as Coursera, Udemy, LinkedIn Learning and Khan Academy, allow for anytime, anywhere learning, providing flexibility, self-directed learning and low-cost options for learners who want to enhance their college degrees or cannot afford college fees. Research has shown that micro-credentials are valuable tools for students, higher education institutions (HEIs) and employers. For students, micro-credentials provide a flexible pathway to learning new skills and can help improve job prospects and career advancement. For HEIs, micro-credentials inform faculty pedagogy and teaching practices, as well as upskill and reskill for future job growth. Regarding employers, micro-credentials assist in identifying and recruiting talent and ensuring that their workforce has the necessary skills to meet the demands of a rapidly changing job market. Despite the evident benefits, uncertainties surround the quality and rigour of micro-credential programs, and some critics argue that they may not carry the same weight as traditional degrees. Additionally, there are concerns about the consistency and standardization of micro-credential programs across different institutions. Nonetheless, the popularity of micro-credentials persists, and many universities and colleges now offer micro-credential programs alongside traditional degrees. As the demand for flexible, targeted learning opportunities further increases, micro-credentials will likely continue to play an important role in the future of higher education.

This chapter proposes that artificial general intelligence (AGI), once fully deployed, will pose existential questions for higher education institutions as they currently operate. Drawing on the theoretical perspectives of the theory of technological determinism and disruptive innovation theory, the authors attempt to project how higher education institutions will be impacted by recent and upcoming developments in AI by juxtaposing current operations against expected future transformations. This chapter comes in four parts. In Part 1, the authors briefly review the advancements in AI technology, focusing on the distinction between artificial narrow intelligence (ANI) and AGI. Part 2 introduces the theory of technological determinism and disruptive innovation theory as a framework for conceptualizing the magnitude of the transformations expected to overtake higher education and their inevitability in some fashion. In Part 3, the authors tentatively juxtapose a series of expected AI-driven disruptions against their current forms. These disruptions will affect the academic infrastructure, instructional practice, curriculum design, grading and assessment, graduation pathways and global accessibility. Finally, the authors consider the implications of these transformations, which, taken together, amount to recasting the university system and constitute an invitation for theorizing these disruptions, assessing their impact and mitigating their effects. This chapter offers a dual contribution to the book. The first is conceptual, and it allows policymakers, educators and stakeholders to use existing theoretical frameworks to understand, imagine and possibly steer the direction of academic institutions so our futures are aided by AGI and not determined by it. The second contribution is practical. Identifying how and where disruptions will occur helps the authors oversee the transition to the new academic landscape with as much foresight and forethought as possible.

Nowadays, the main challenge in the higher education is the daunting task of transforming universities into digital era institutions. Improving HE students' competence to meet the flow of technological innovations through DT has been the focus of many countries. This task has imposed the restraint that HE institutions should implement the most effective strategies of DT. This chapter is focusing on how DT strategies play their role in making the transformation itself become germane and give its fruits. Therefore, this chapter presents the most effective DT strategies that can be implemented by HE institutions in order to prepare their students for the existing professional roles in their societies. A good DT strategy is one that connects the organization's current level of digital maturity with its future ambition. The well-known strategies in the DT field are as follows: the strategy of electronic projects, strategy of smart electronic platforms, integrated training strategy, participatory e-learning strategy, smart learning strategy, pervasive learning strategy, microlearning strategy and e-design thinking strategy, in addition to the strategy in which traditional learning methods are combined with e-learning methods. It is worth noting here that the chapter is not an attempt to favor a strategy over another or compare and contrast them to uncover their differences at any level. On the contrary, the writer will work on displaying how each strategy can be implemented in order to accomplish DT in HE instructional practices. Also, this chapter will show how complementary these strategies can be once they are utilized to reach DT.

This chapter explores the transformative impact of artificial intelligence (AI) on higher education, particularly in the context of accelerating technological and societal changes. As higher education institutions face the need to offer more flexible, adapted and relevant academic programmes, AI presents significant opportunities and challenges. In the first part of this chapter, the authors elaborated on characteristic the evolution of AI including characterizing the emerging AI landscape. One of our contributions in this concluding chapter is to conceptualize the next areas of deployment of AI in higher education considering the novel, innovative services that will disrupt the entire market in the next few years. The strategic proposition for deployment of AI in higher education highlighted six pillars, namely large language models, research.AI, content creation.AI, personalised learning.AI, skill building assistants.AI and education out of the Box.AI. The authors presented opportunities to harness AI to enhance teaching, learning and research under each pillar, along with a detailed list of potential application areas and services. Universities are exploring innovative ways to use AI-driven solutions to improve research, teaching and learning experiences, and the authors also developed indicative scenarios for the use of AI in higher education based on the six pillars. One of the bold contributions in this chapter is the structured framework for understanding the evolution and use of AI in higher education, utilizing a matrix to map the intersection of market penetration and product development. Finally, the authors discuss future directions and strategies for Higher Education 2030 in light of advances in AI technology.