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“Everything that can be digitised will become digital” is a prediction we’re hearing more and more often. And yet in terms of ongoing progress in digitisation, Germany, when compared with other countries, is only an “also-ran”.
Frank Thelen, a well-known startup founder and tech investor, is among the most passionate proponents of digitisation and technologisation. He’s written numerous articles about Germany’s urgent need to catch up – despite the country’s general prosperity and the outstanding reputation of German industry and manufacturers in the fields of artificial intelligence, 5G, quantum computing and blockchain. As Thelen says: “Good is the biggest enemy of great.” He also holds a very specific belief: due to its continuing exponential growth, artificial intelligence will soon be a key issue across all industries. So it is essential for businesses to implement the right strategies for growth, repositioning and smart networking in the very near future.
Digitisation has, of course, been part of the educational landscape for a long time, as reflected in the widespread use and acceptance of blended-learning and online training courses – recently given a further boost by the coronavirus crisis. All modern Learning Management Systems (LMS) use automated analytics and reports on learning processes and pathways to motivate participants and make it easy for them to track their progress. But nowhere near enough is being made of the capability of modern LMS to use the data they collect to further develop learners’ personal skill and knowledge profiles. Instead, LMS are often used simply to deliver study materials and administer course participants; their ability to analyse, evaluate and correlate data and results is only used sporadically. And yet in recent years, LMS have been upgraded to include new functions that make it possible to offer custom courses specifically tailored to each student’s needs and preferences, guiding them down their own personal learning pathways.
Today, big/smart data can be used to analyse digital learning and identify correlations that even human experts are unable to spot, while algorithms can be used to generate (for example) dependencies and pathways. This opens up new opportunities when designing educational frameworks. In much the same way as programmatic advertising, future learning systems will soon be capable of generating accurate profiles that support personalised, adaptive learning strategies.
Based on data analysis, difficulties with understanding can be identified at an early stage, whereupon learners can be given targeted support to improve the overall success of both teaching and learning. According to case studies from higher-education institutions in the UK and USA, users report positive changes in their learning experience when they receive support tailored to their needs or motivating feedback on their learning performance.
Alongside the machine-based component, educational experts should soon be able to play a role in AI-based learning systems by offering advice and support, as well as designing the empathic, motivational, social and collaborative aspects of the learning experience.
Frankfurt School provides support for digital transformation, both internally and in the form of Executive Education programmes covering IT & Digitalisation as well as Strategy & Change Management. As a full-service provider, Frankfurt School is also working with its specialist subsidiary efiport to develop adaptive and modular learning management systems that meet the specific in-house needs of individual companies.
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