Using AI and Customer Personas for Improved Content Development

I firmly believe in working with Generative AI as a copilot to improve existing processes. Here’s an example of a workflow I have developed using ChatGPT-4, in conjunction with virtual customer personas, to improve existing instructional content development. For the proof of concept, I used an e-book I wrote a while back for teachers on how to use Bloom’s Taxonomy in the digital classroom. It was outdated and needed a review and update, but I had been putting it off due to the time it would take. I decided to use an AI workflow to assist with the update, with an editor (me) sitting at the centre of the process, checking and incorporating relevant suggestions by the AI. I developed four personas of potential customers (obviously, you can do less or more) and then set them to suggest updates based on current technology, identify gaps in the content and provide potential extensions to what I had already written. By initiating a continuous feedback loop with these virtual personas representing the target audience, this AI-driven approach improved content substantially. For example, a 564-word sample passage increased to over 1,700 words.

Though initially designed to refine educational materials, this workflow could be used for marketing content enhancement, for example, with simple modifications to the user personas and input prompts. The integration of Grammarly as a final editing tool assures standardization in grammar and style.

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Using Generative AI in Learning Design

Generative AI has been a buzzword in the technology industry for a while now, and it has started to make its way into various fields, including education. Generative AI in learning design uses artificial intelligence to create new content, generate personalized learning paths, and enhance the learning experience.

The potential benefits of using generative AI in learning design are numerous. It can help educators create more engaging and adaptive learning experiences that cater to the individual needs of each student. Generative AI can also automate some of the more time-consuming aspects of designing a course, such as creating assessments and quizzes.

However, there are concerns about the ethical implications of using generative AI in learning design. Some worry that it could dehumanize education, with students being reduced to data points and algorithms. Others are concerned about the potential bias in the algorithms used to generate content. Despite these concerns, the use of generative AI in learning design is on the rise, and it is likely to play an increasingly important role in education in the coming years.

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Diji: Impactful Microcourses for African Language Learners

Here’s an overview of a digital learning platform I am involved with, as an advisor on digital pedagogy and best practice. They’re making a real impact in providing meaningful digital learning to users in African languages.

The digital landscape of education is rapidly evolving, and Diji has a unique approach to microlearning for African language speakers. By intertwining traditional educational values with modern technological tools, Diji offers a platform that resonates with its audience.

Built with adaptability in mind, Diji utilises an omnichannel micro-learning methodology. This allows the platform to deliver content through various tools, such as a WhatsApp Chatbot, the MTN Ayoba app, and an intuitive mobile web learning management system. One of its core strengths is its design, prioritising accessibility in low-data environments and ensuring that quality education reaches even the most remote corners.

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