AI's Transformative Effect on Curating Digital Learning Content
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Have you ever wondered how Netflix and Spotify make such spot-on personal viewing and listening recommendations? These are everyday examples of AI-powered content curation at their best. And just like the entertainment world, artificial intelligence is transforming content curation in eLearning. In the digital age, AI is like a lighthouse in the overwhelming sea of information. It draws our attention to credible, relevant and engaging learning resources. And it does so more efficiently and effectively than ever.
This post is the latest in our series, examining the game-changing impact of AI on digital learning. Today, we explore learning curation. We look at how AI adds value to the process and the potential drawbacks. And we finish with a selection of must-have AI tools for optimised learning curation.
Let’s delve deeper into the transformative impact of AI in digital education learning curation.
What is Learning Curation in the Context of Digital Learning?
Learning curation is the process of gathering, organising and presenting educational resources to enhance the learning experience.
This task has never been more critical than in the digital age. Nowadays, we are inundated with an overwhelming amount of information daily. Learning curation helps us navigate this maze of knowledge by identifying trustworthy, relevant resources. It filters all the noise so that learners have exactly what they need to achieve their learning outcomes when they need it.
How Does Learning Curation Work Now?
Before fully appreciating AI’s impact, we must first explore how learning curation works now.
Currently, learning curation is a manual process. Instructional designers, subject matter experts and educators handpick resources and categorise them before presenting them to learners. It’s a time and resource-intensive process.
Here are some of the traditional platforms and tools used for curation that aren’t dependent on AI:
Learning management systems: LMS platforms like Moodle, Blackboard and Canvas allow instructors to curate digital content and create a structured learning pathway.
Educational websites: The likes of Khan Academy, ORLA, Coursera and edX offer curated educational content on a wide range of topics. Instructional designers and subject matter experts often curate content from these platforms and integrate them into their digital programs.
Digital libraries: Libraries such as Project Gutenberg and Google Books provide access to an extensive collection of digitised books, documents and research. These can be curated to supplement eLearning content development.
Blogs, social media, podcasts and webinars: These platforms contain a wealth of industry-specific or expert knowledge that can be categorised for inclusion in digital learning.
Challenges in Current Learning Curation Methods
While the traditional approach ensures human oversight, it requires a lot of time and effort. Currently, curators spend hours sourcing relevant information, sifting through content and determining the most relevant and credible. Although manual curation is effective, there are more efficient uses of time and resources.
Let’s explore some of the other issues with traditional learning curation methods:
Information overload: The sheer vastness of the internet’s data makes it difficult to pinpoint high-quality resources. It’s like searching for the proverbial needle in a haystack.
Timeliness: Another challenge is ensuring curated content remains current and relevant in the fast-changing knowledge landscape.
Diversity and inclusion: Curators also face challenges in catering to today’s learners’ diverse needs, backgrounds and preferences.
Quality control: Filtering out misinformation, outdated content and low-quality resources is another ongoing struggle.
Personalisation: Curators also face issues in ensuring personalised learning experiences for all learners that fit individual styles, preferences and pace of learning.
How Can AI Add Value to Learning Curation?
AI-assisted learning curation offers many benefits to address our outlined challenges. In short, it’s a far more efficient way of getting the job done. Here are five specific ways AI tools enhance learning curation:
Automated filtering: AI algorithms excel at sifting through massive data sets. In the blink of an eye, they can identify high-quality resources and locate impactful, up-to-date information to support learning outcomes. Automating learning curation frees instructors to focus on other critical aspects, like supporting individual learners.
Adaptive learning: Real-time analysis of learner behaviour means AI can customise learning pathways. Digital learning resources are tailored to the student’s unique requirements. Research shows that adaptative learning enhances engagement and understanding, delivering a more effective learning experience.
Trend analysis: As we've seen, staying ahead of the curve is a significant challenge for human curators. AI makes that task much more manageable. What takes humans several hours, AI performs in an instant. AI tools can predict emerging trends and proactively categorise information.
Content summarisation: AI tools can process extensive resources quickly. These platforms can summarise complex topics, breaking them into easily digestible formats. Highlighting the key points helps learners to grasp the essential concepts without being overwhelmed.
Real-time updates: AI constantly scans the digital landscape for new, relevant content. This proactive approach guarantees that digital learning resources are always up to date.
Watchouts When Using AI in Learning Curation
The integration of AI into learning curation offers many exciting possibilities. However, it also presents some drawbacks that require careful consideration. Here are the top five watchouts when using AI in learning curation.
Over-reliance: Tempting though it is to let AI run its magic, become too dependent, and you risk overlooking valuable resources. There’s a balance to be struck with the nuanced insights only human curators can provide.
Bias: AI algorithms can unintentionally introduce or magnify biases in curated resources if not carefully designed and monitored. This can reinforce pre-existing harmful stereotypes and prejudices.
Loss of human touch: No matter how advanced, AI is no substitute for the human touch. It cannot grasp the subtleties of human experiences and interactions. And it often misses the emotional and cultural elements of learning that people curators understand.
Data privacy: Data is the fuel that drives AI tools. However, with that comes responsibilities. Designers and instructors must ensure that AI platforms comply with educational data privacy standards. There's a duty to safeguard the sensitive information of both educators and learners.
Quality assurance: It’s essential to regularly evaluate and adjust the criteria used by AI for learning curation. Ensuring the curated digital learning resources are of the highest quality and relevance requires careful oversight.
Recommended Tools for AI-Enhanced Learning Curation
Several cutting-edge AI tools are shaping the future of learning curation. Here’s our selection of the must-have tools on the market:
Content Aggregators with AI
These tools help you find better content faster and add value to learners by presenting the most relevant information.
Top picks here include EdCast's content curation tool. Driven by AI, it can suggest relevant course materials by analysing keywords, assessing topic relevance, and more.
Another option is the news aggregator Feebly. This tool uses AI to help you find, organise and share relevant content on your chosen topic.
Adaptive Learning Platforms
Artificial intelligence plays a crucial role in creating adaptive learning experiences. DreamBox Learning is our top pick. It uses AI to analyse learner data and tailor content difficulty to individual needs. Customisation enhances the effectiveness and efficiency of the learning process.
Knewton is also worth checking out. It uses adaptive learning technology to create personalised learning experiences.
AI-driven Search Engines
When it comes to AI-powered search engines, Google still dominates the market. However, Microsoft has upped its game, and Bing is a strong contender when it comes to relevant search results.
Also worth a look is Squirrel AI. Although it’s aimed at school education, it uses AI to provide users with accurate, relevant, trustworthy search results.
Automated Summarisation Tools
These tools can summarise lengthy texts, articles, or research papers, making extracting critical information easier for instructional designers.
Must-haves here include SMMRY and OpenAI's ChatGPT-3. Both platforms extract insights and provide concise summaries, making content curation that bit easier.
Predictive Analytics Tools
Analytics tools help designers and instructors to make data-driven decisions, identify patterns, and optimise learning experiences.
Stand-out options here include IBM Watson Analytics and Tableau. Both platforms provide insights using predictive analytics to analyse learner performance data and identify learning trends.
The use of AI in learning curation has become increasingly common. And for good reason. As we’ve seen, AI’s ability to analyse vast amounts of data, identify patterns and make intelligent, personalised recommendations is unparalleled by any human curator.
However, as we step into this new era and embrace the power of AI, we must tread carefully. A balanced approach to merging AI's efficiencies with human judgement and expertise is vital. People understand the emotional and cultural learning elements that support effective learning. And that’s beyond even the most advanced AI.
We can only achieve the transformative change that AI promises by working alongside AI in a complementary relationship.
Are you ready to harness AI’s power in your practice? Check out our Professional Diploma in Digital Learning Design. This university-accredited, industry-approved program incorporates hands-on project work using the very latest AI-driven tools and platforms.