The higher education sector is in the eye of the hurricane of the digital revolution, immersed as it is in an ongoing digital transformation (DT) process that is expected to result in significant changes in the current business model. Despite the relevance of this transformation, little remains known about how the business model is innovated (BMI), due to the impact of digital transformation in the context of higher education institutions (HEI). This research explores the impact of DT on the HEI business model, through analyzing the case of a traditional university, conceived non-digitally. The results present the HEI understanding of DT, the main tensions arising from the DT process for each of the business model dimensions, and the anticipated solutions for solving these tensions. Additionally, the results uncover the existence of an emergent (non-formalized) envisioned business model, which is a visualization of how the current business model is expected to be innovated, due to the impact of DT. The main originality of this paper is in addressing a research gap at the intersection of DT and BMI in the HEI context.

Microlearning is gaining ground in the higher education domain. Despite this trend, there is a lack of evidence of effectiveness when a large number of microlearning units are grouped to form a macrolearning programme. The purpose of this paper is to explore how and why a macrolearning affects students’ self-efficacy. The originality of this paper is its in-depth analysis of an EdTech startup named MLMaster, which has built a portfolio of several business programmes, each consisting of over one hundred microlearning units, forming macrolearning programmes. The main contribution of this paper is to uncover critical insights into how self-efficacy is built in practice, driven by two main factors: participants’ affective states, which are the positive feelings after taking part in the programme, and mastery experiences, which is the application of learning at work.

Led by artificial intelligence (AI), digital technologies are acting as a lever for significant change in higher education. Innovative formats such as macrolearning, the concatenation of a significant number of microlearning units, are consequently emerging. The purpose of this paper is to explore students' preferences for macrolearning programmes from a multidimensional perspective, identifying areas of improvement and how AI can be instrumental in enhancing the student experience. We contribute with evidence-based research to the exploration of how to design and implement an effective macrolearning. Results show that the most preferred dimensions of the macrolearning are those with a technical profile, first the technological platform, then the interface design, followed by institutional aspects, pedagogical aspects, and student support. We also explore the potential of AI to enhance multiple dimensions of macrolearning in the direction of the drawbacks identified, and we discuss how this can accommodate personalisation of training.

The future of higher education depends significantly on the ability of these institutions to envision and manage the digital transformation process and navigate the new competitive landscape. The value of this chapter is in its review of the emerging trends in higher education, reflecting on the opportunities and threats and identifying potentially winning strategies that higher education institutions can implement to create, deliver, and capture value from microlearning strategies. The methodological approach of this research is based on a review of extant academic literature, including both conceptual and applied research that identifies illustrative good practices by means of case studies. To this end, the chapter contributes to the ongoing debate on how the higher education sector should adopt a business mentality and embrace business model innovation as a key driver to sustain the competitiveness of higher education organisations in the future, and to fulfil their mission.