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For more than a century, universities have seldom broken in the design of their programs of study, that the time and when learning takes place is fixed, but the learning outcomes achieved are variable.
Many educational institutions are now starting to invest in student personas and corresponding student journey maps, but the associated outcomes are primarily used for management and marketing rather than for learning purposes. Personalized learning can come in many forms, including customized content, progression, education, delivery, and learning support. Unfortunately, by and large it remains ambitious and lacks scale. And educationally successful and commercially viable models are still in their early stages. This could change soon as technology seeks to enable large-scale individualized learning.
Three paths to personalization
Choice, or the P(upil) route as educator Dan Buckley calls it, means learner-driven personalization. It is the fastest growing form of personalized learning. Students not only benefit from a truly omnichannel education, choosing between face-to-face and online, but also independently navigate internet resources and online databases in search of knowledge that will help them achieve their learning goals. To do.
As a result, many students only visit the campus during evaluation hours. This is an area of individualized learning that needs to move from a model based on the production of university-taught content to the orchestration of globally available sources. the purpose.
Dedication, or the T (eacher) root, is a common path in many industries. We have financial advisors, fitness coaches, or GPs who know us well. Universities committed to personalized learning are encouraged to offer learning coaches internally or through third-party providers. Such coaches not only provide additional support to struggling students, but also help optimize individual return on investment in learning. Advice on how to, assess and recommend learning sources, and most importantly, how to succeed in learning and abandon learning, depending on the specific situation (such as international students, parents, or first-generation students) teach students how to
Automation, or A Route, is the new enabler of personalized learning. Education, like personalized healthcare, finance, and entertainment, is using digital technology to unlock new models of customized engagement. For most universities, AI-driven personalized education is not an option as it lacks the necessary capabilities and requires significant investment, but there are various alternative forms of automated and personalized learning. I have. For this, we look to providers outside the sector for inspiration.
The Spotify Model of Personalized Learning
Spotify, a successful music streaming service, is a benchmark for personalization, and similarities between entertainment and educational content make it a good benchmark for personalized learning. Here are some Spotify-inspired ideas that universities ambitious enough to offer personalized learning can explore.
- use the app. It sounds obvious, but it makes a noticeable difference. Personalized entertainment comes with advanced apps based on modern user experience principles. Recognizing that personalized learning occurs primarily outside of the classroom and via Zoom or similar interfaces, learning can take place wherever you personally prefer (often on the move rather than at your desk). It means we need an app-first approach to facilitate learning.
- Curate your content. The vast amount of music content available requires micro-orchestration in the form of playlists curated by staff, algorithms, or users. What if equivalent “learning lists” were available? These could be mood- and context-based (Sunday afternoons) or topic-based (such as retail case studies or content in French). They can be comprehensive, niche, or very modern user-generated lists created at a rate unfeasible in college.
- User Rating Tool. Customers (students in this case) express micro-preferences through ‘likes’. and evaluation functions. It’s a small step for platforms like Spotify, but a giant step for universities. Preference-based and personalized learning can tailor content to individual learning styles and habits. For example, concept-based learning and case-based learning. This allows other learners to follow the habits of people they personally trust and of specific cohorts.
- community spaces and functions. Like Spotify family accounts, shared spaces for learners working as a community facilitate social learning, including the sharing and integration of learning lists.
- Enable Follow. With Spotify, you can follow your favorite artists. Naturally, students also have their favorite teachers. Individualized learning from your preferred instructor is therefore another way universities can replicate Spotify’s practice in the world of ‘streaming tutoring’.
Personalized learning is a long-standing ambition that has become feasible and viable at scale. Some institutions, such as Southern New Hampshire University and Western Governor’s University, tailor learning outcomes to learners over time and duration, rather than requiring all learners to attend over and over again. We are moving towards competency-based education using a pedagogical approach based on achievement. Duration tailored to your learning provider. But broader examples of more substantial personalization are rare. Personalization principles and techniques should therefore be sourced from sectors with highly customized service offerings. Spotify’s example is what steps it takes towards personalized learning and experiences that can provide a competitive advantage in attracting a generation that is accustomed to personalization in all aspects of life and actively seeks it out. It shows you what you can do.
Michael Roseman is Professor of Information Systems at the Center for Future Enterprise and Queensland University of Technology Business SchoolMartin Betts is a higher education consultant and founder of HEDx. This advice is taken from their latest book. new learning economy (Routledge, 2023).
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