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What are some of the best practices and tips for implementing adaptive learning and AI in your organization?

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Adaptive learning and AI are two powerful trends that can transform how you design, deliver, and evaluate learning experiences in your organization. Adaptive learning is the ability to tailor learning content and activities to the individual needs, preferences, and goals of each learner, while AI is the use of algorithms and data to automate, enhance, and personalize learning processes. In this article, you will learn some of the best practices and tips for implementing adaptive learning and AI in your organization, such as:

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1 Define your learning objectives and outcomes

Before you start using adaptive learning and AI, you need to have a clear vision of what you want to achieve and how you will measure it. What are the specific skills, knowledge, and behaviors that you want your learners to develop or improve? How will you align them with your organizational goals and values? How will you assess the progress and impact of your learning interventions? Having a well-defined learning strategy and framework will help you choose the right adaptive learning and AI solutions and tools for your needs.

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Christopher Lind

Bridging Business, Technology & Human Experience | Executive Advisor | Business & Product Transformation | Devoted Husband and Father of 8
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Defining the outcomes is critically important, but you have to do it a little differently when it comes to selecting and implementing adaptive tech. As I mention later, the diversity in capability is extremely diverse, and if you aren’t clear what you’re looking to enhance with the capability, you won’t know what questions to ask. As a result, you may end up buying a platform that is technically “adaptive,” but it’s not adapting the experience in the way you were looking to enhance the experience. I’d also say that you may want to revisit your desired outcomes anyway. While adaptive tech can enhance the experience, if you don’t already know what problem you’re looking to solve, solving “it” better is a waste.

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Nuwan Dishan

Client Relationship Manager @ Cambridge Judge | Global Executive Education
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Any learning strategy should start with business strategy, most organisations fail to align learning strategy for business strategy. When learning strategy is defined and aligned to business strategy it is relatively easier to analyse how learning technology could help in creating better learning experiences. Therefore it is important invest in technologies that fit for purpose rather than investing modern technology for the sake of investing. AI is powerful tool that any learning professional can leverage if the technology is used in right context for right purpose.

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2 Choose the right level and type of adaptivity and AI

Adaptive learning and AI are not one-size-fits-all solutions. They can vary in terms of the level and type of adaptivity and AI that they offer. For example, some adaptive learning systems may only adjust the difficulty or pace of the learning content, while others may also provide feedback, guidance, recommendations, or personalization. Similarly, some AI applications may only automate or augment certain tasks, such as content creation, analysis, or curation, while others may also generate insights, predictions, or recommendations. You need to consider the complexity, diversity, and context of your learning content and audience, and choose the level and type of adaptivity and AI that best suit your learning objectives and outcomes.

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Christopher Lind

Bridging Business, Technology & Human Experience | Executive Advisor | Business & Product Transformation | Devoted Husband and Father of 8
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This is a really important thing to dig into if you’re considering any tech that claims to have “adaptive” capability. The diversity in adaptive tech is extremely diverse, and there are lots of vendors that add that claim to their tool very loosely. That’s not necessarily a bad thing, but you have to make sure you ask specific questions about how it adapts the learning experience and what responsibility you have in making it happen. As an example, there’s full adaptive authoring tools that completely and dynamically change the experience based on the user’s knowledge and skill. Conversely, there are platforms that require you to manually tag metadata and recommend content based on that data. Those are two very different capabilities.

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3 Ensure data quality and security

Adaptive learning and AI rely heavily on data to function effectively and efficiently. Data is the fuel that powers the algorithms and models that enable adaptivity and AI. Therefore, you need to ensure that the data you use and collect is accurate, relevant, reliable, and secure. You need to follow the best practices and standards for data collection, storage, processing, and analysis, and comply with the relevant laws and regulations regarding data privacy and protection. You also need to ensure that the data you use and collect is ethical, transparent, and fair, and that it does not introduce any biases or discrimination in your learning outcomes.

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Bill Sodeman, Ph.D.

Award-winning Learning & Development executive | Consultant | Business professor
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For example, organizations that have employees or customers in the EU must comply with the General Data Protection Regulation (GDPR). This regulation, implemented in 2018, strictly controls trans-border data flow, the use of cookies, and other issues. User privacy is a primary focus of GDPR. While the regulation is not by itself binding to EU member states, it is best practice to treat any user in the EU as being from a state that has put the regulation into effect. Organizations that have employees or customers in the state of California face a regulation called the California Consumer Privacy Act (CCPA). This act has a lower threshold than the GDPR in terms of organization revenue size. CCPA is also less prescriptive than GDPR.

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4 Involve and empower your learners

Adaptive learning and AI are not meant to replace or undermine the role of your learners in the learning process. On the contrary, they are meant to enhance and support their learning experience and outcomes. Therefore, you need to involve and empower your learners in the design, implementation, and evaluation of adaptive learning and AI. You need to communicate the benefits and expectations of adaptive learning and AI to your learners, and provide them with the necessary information, guidance, and support. You also need to give them the opportunity to provide feedback, input, and preferences, and to control their own learning pace, path, and goals.

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5 Evaluate and improve your adaptive learning and AI

Adaptive learning and AI are not static or fixed solutions. They are dynamic and evolving solutions that require constant monitoring, evaluation, and improvement. You need to collect and analyze data on the performance, effectiveness, and efficiency of your adaptive learning and AI interventions, and use the insights and findings to inform your decisions and actions. You need to identify the strengths and weaknesses of your adaptive learning and AI solutions and tools, and address any issues or gaps that may arise. You also need to keep up with the latest trends and developments in adaptive learning and AI, and explore new opportunities and possibilities for enhancing your learning outcomes.

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6 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?

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What are some of the best practices and tips for implementing adaptive learning and AI in your organization?

1

2

3

4

5

6

1 Define your learning objectives and outcomes

2 Choose the right level and type of adaptivity and AI

3 Ensure data quality and security

4 Involve and empower your learners

5 Evaluate and improve your adaptive learning and AI

6 Here’s what else to consider

Digital Learning

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What are some of the best practices and tips for implementing adaptive learning and AI in your organization?

1

2

3

4

5

6

1 Define your learning objectives and outcomes

2 Choose the right level and type of adaptivity and AI

3 Ensure data quality and security

4 Involve and empower your learners

5 Evaluate and improve your adaptive learning and AI

6 Here’s what else to consider

Digital Learning

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