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Webinar Highlights: Demystifying AI for Learning

29 May


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Webinar Highlights: Demystifying AI for Learning

John Kilroy, CEO and Founder of the Digital Learning Institute was joined by our very own head of product, Luana Raggi and instructional designer, Aine Walsh in this months webinar on Artificial Intelligence.

Luana and Aine have been busy experimenting over the last four months with Artificial intelligence and during this webinar session are excited to showcase the Digital Learning Institutes reflections and thoughts. 

There has been a lot of discussion, debate and to a certain extent noise around artificial intelligence over the last 6 months in terms of its impact on how we work and particularly in terms of its application in learning and education. It’s fair to say that now we are in a trial/ experimental phase at the moment, particularly with the amount of technology that’s been released on a daily basis. 

In the Digital Learning Institute we have used the last three months to experiment ourselves with a view to develop our own understanding on Artificial Intelligence but to also help our students take ownership over AI as a tool. 

As Learning professionals and educators it’s really important we don’t stick our head in the sand and we use this time to develop our understanding of artificial intelligence. As part of the webinar, the team explores where learning designers, instructional designers and educators are going to be spending less time doing and more importantly what you will spend more time doing and what those skills are potentially going to look like in the future.

The DLI team have been working hard creating an AI toolkit, At the beginning of the Webinar John gives a quick run through of the contents.

One of the areas that is really exciting about artificial intelligence is the potential role of virtual tutors, DLI have launched our very own virtual tutor as part of our Diploma programme named Bob Bloom. Bob has been named after our two favourite learning theorists, Benjamin Bloom and Robert Gagne. In this new exciting area of AI it’s important to us that we stay connected to learning theory and principles. 

Some of the other features in our AI toolkit is a breakdown of some of the tools that the team have been exploring which have been broken down into different categories such as text, voiceover, video, etc. 

The DLI team have gone a bit further and given case study examples. So we have taken some of those tools and created videos showcasing how you can use them in a real life learning scenario. We have also created a health check questionnaire, one of the really important things if you are looking to see how AI can create efficiency is having strong foundations as a starting point. The toolkit is packed with useful information such as definitions, module details and more! 

Key Components of AI

Artificial intelligence is a component of computer science. It is mainly about using systems to perform tasks that would normally be performed using human intelligence. The key components of AI can be broken down into 5 broad components. 

  1. Machine Learning – analyses and interprets data and makes recommendations of the back of that using algorithms. We use this on a day to day basis in our lives. For example if you’re on Netflix it is analysing your behaviour in order to recommend the right content for you. 

  2. Natural Language Processing (NLP) – This is how AI systems interpret conversation language. That is how we are able to have conversations with the likes of Siri and Alexa. 

  3. Robotics – This is how AI combines with machines to perform complex tasks. 

  4. Computer Vision – This is how AI interprets what it sees. Examples of this is facial recognition and self-driving cars.

  5. Expert systems – This is when AI can perform problematic and complex tasks. 

Now we are seeing all of these components of AI combining together to become a lot more powerful. 

Artificial Intelligence has evolved through several stages over the years. It all began with narrow or weak AI, where AI systems were designed to carry out specific tasks, as previously mentioned with examples like Alexa, Google recommendations, and Netflix.

We have now entered the realm of General or strong AI, which enables AI systems to comprehend and perform a multitude of tasks simultaneously. Within this framework, a significant aspect is generative AI, which involves the creation of outputs such as text, visuals, and 3D models. While generative AI has been in existence for some time, recent months have witnessed a notable increase in its accessibility, particularly with the introduction of ChatGPT by OpenAI.

ChatGPT is an exceptionally user-friendly and accessible chatbot, which has opened up a new frontier in content creation using AI. This development has sparked significant interest and discussions over the past six months.

Beyond General AI lies the realm of Super intelligent AI. This stage holds the potential for artificial intelligence to surpass human performance, and it is a domain where caution is necessary. Many individuals harbor concerns about the direction AI is headed, especially as it approaches super intelligent capabilities.

Learn more about AI in our NEW module in our professional diploma in Digital Learning Design

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Using Artificial Intelligence in ADDIE

As learning professionals and educators, it is crucial for us to recognise the transformative potential of AI in terms of driving efficiency and its impact on our roles as digital learning designers. A helpful perspective is to envision AI as a tool that accelerates our progress from 0 to 40 in record time.

For instance, let’s consider a learning project or course development that would traditionally span 100 days starting from day 0. With the integration of AI, we can now swiftly advance from 0 to 40, reaping the benefits of increased speed and efficiency. This rapid progress in learning design allows us to unlock additional time for various activities, which exemplifies the immense value of leveraging AI in our work.

Here at the Digital Learning Institute, we have been experimenting with AI within the framework of the ADDIE model, particularly focusing on its impact on analysis and design. In the analysis phase, AI plays a pivotal role in problem definition, outcome establishment, audience profiling, persona creation, content mapping, and curriculum training specifications.

Moving into the design phase, AI aids in crafting objectives, developing instructional design plans, storyboarding, ensuring accessibility standards, and facilitating assessment creation. It streamlines these processes and brings efficiency to the forefront.

During the development phase, AI assists in building the course through video production, audio production, image development, and utilizing tools like Articulate Storyline. This phase also emphasizes rigorous testing procedures.

In the implementation phase, AI contributes to seamless course deployment by facilitating platform integration, LMS administration, learning marketing efforts, and providing support to guide students throughout their online learning experience. Localization of content, including translation and contextualization for personalized learning, may also be a focus during this phase.

Lastly, in the evaluation phase, we delve into learner analytics, assess the effectiveness of the course, and in a corporate setting, analyze the return on investment (ROI) to gauge the program’s impact.

By embracing AI in these various stages, we can revolutionize our approach to digital learning design and harness its potential to enhance efficiency, effectiveness, and learner outcomes.

How does AI fit in the ADDIE model

Analysis Phase

By optimizing our data collection and content creation processes, we can maximize our efficiency and dedicate more time to impactful tasks. Rather than being consumed by data gathering and curriculum development, we will emphasize performance consulting, collaboration with stakeholders, and engagement with academic and subject matter experts. This approach ensures a clear understanding of the problem at hand and fosters a collaborative environment for finding innovative solutions. Moreover, this shift allows us to effectively showcase our expertise in learning and development to stakeholders.

Thanks to the integration of AI, the burden of data gathering diminishes significantly, granting us ample time for thorough review, analysis, and the cultivation of data-driven decision-making. AI’s assistance in these initial stages also liberates valuable time that we can invest in experimenting with and enhancing the learning experience. As a result, the streamlining of analysis tasks not only frees up time but also ignites a wave of creativity within our endeavors.

Design Phase

In the design phase, we observe a similar trend. AI enables us to reduce the time spent on designing assessments, particularly basic ones like multiple-choice questions (MCQs). It also streamlines tasks such as storyboarding and working with subject matter experts (SMEs).

The implementation of artificial intelligence in our design process accelerates the prototype development phase significantly. By swiftly reaching the prototype stage, we enhance visibility, fostering greater engagement and creating abundant opportunities for feedback and collaboration.

With the newfound time at our disposal, we can delve into exploring possibilities for scenario-based learning, problem-based learning, and, most importantly, online learning. This shift signifies a move towards leveraging online platforms for skills development. Rather than solely focusing on knowledge acquisition, we now have the opportunity to facilitate interactive experiences, such as role plays conducted through virtual tutors and similar approaches, in the online learning environment.

Development Phase

This phase is poised to experience the most significant impact, thanks to the integration of artificial intelligence. With AI’s assistance, we will spend less time on content creation, including image and visual development. Additionally, for those utilising tools like Articulate Storyline, we anticipate a reduced need for tasks such as triggers, layers, and states, as we foresee a potential shift in this type of development.

Consequently, we will have more freedom to experiment with videos, allowing us to create and test content at a faster pace. AI becomes a valuable tool for exploring and implementing various mediums within the learning experience. Moreover, it provides an opportunity to prioritise universal design, ensuring that our content adheres to accessibility standards.

While AI can support accessibility in design, it remains crucial for us as learning professionals and designers to seize this extra time and invest in upskilling ourselves in universal design and accessibility practices. Likewise, we can dedicate more time to refining the user experience (UX) design, shaping the ideal learning journey for our learners.

Implement Phase

This phase, once again, holds tremendous potential for leveraging artificial intelligence and witnessing its profound impact.

Introducing our virtual tutor, Bob Bloom, does not aim to replace any of our tutors at the Digital Learning Institute. Instead, Bob enables a division of responsibilities. For instance, Eva can now dedicate her attention to the 10% of student emails that require personalised feedback, while Bob assists with the remaining 90% that typically consist of general questions. By leveraging Bob’s support, Eva gains more time to assist students in need of personalised guidance regarding their career paths or projects, ultimately enhancing the overall student experience.

Moreover, this phase opens up greater opportunities for social learning, ensuring a rich and engaging social experience. As learning professionals and tutors, we now have the luxury of dedicating more time and creativity to learning marketing efforts, cultivating an environment conducive to fostering collaboration and interaction among learners.

With the additional time at our disposal, we can unleash our creativity in designing compelling learning campaigns. By harnessing the power of AI and utilizing relevant tools, we can expedite the implementation of these campaigns, resulting in a highly positive impact.

Overall, this phase marks a significant turning point where AI augments our capabilities and empowers us to deliver an enhanced and dynamic learning experience.

Evaluation Phase

In the evaluation phase, the utilization of artificial intelligence presents vast opportunities and potential. Once again, we can expect to spend less time on analysis, assessment delivery, and continuous back-and-forth communication with tutors.

For those engaged in corporate learning, this newfound time allows for a greater emphasis on showcasing the value of the learning initiatives, focusing on desired behaviors, and measuring return on investment. With AI’s support, learning professionals in the corporate setting can effectively demonstrate the impact and effectiveness of their programs.

This analysis, conducted here at the Digital Learning Institute, points towards a transformative shift in the realm of digital learning when artificial intelligence becomes a regular component of our practices. By harnessing the power of AI in the evaluation phase, we can streamline processes, enhance data analysis, and derive valuable insights to drive continuous improvement in the field of learning and development.

In the remaining time of the Webinar, John ran through how you can use some of the tools such as ChatGPT and 7Tapps as a learning professional, questions regarding concerns and what the future with artificial intelligence looks like was also answered at the end of the webinar. View the tutorials and questions in the webinar recording below.

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