Personalized Learning: 4 Key Takeaways from SHAPE Education Event

Personalized Learning: 4 Key Takeaways from SHAPE Education Event

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On 1 March 2022, our CEO Vivek Agarwal participated in a session on What do you mean ‘personalised learning’? that explored the value personalization can bring to learning, both in terms of an individual’s learning journey and on education as a whole.

SHAPE Education, a joint initiative from Cambridge University Press and Cambridge Business School, organized it as part of its series of bite-size SHAPE Live events spotlighting key challenges and opportunities in the EdTech sector. Rosina Dorelli, founder and director of DaVinci Life Skills, a Cambridge-based organization, was the other speaker who spoke at this event.

Here’s a quick recap of four key takeaways from this event

1. Extensive data analysis with a combination of data points is key

Advanced and systematic data collection techniques through AI have enabled faster dissemination of insights. However, the biggest challenge is gauging what the learner wants to do, which isn’t always easy. Liqvid uses extensive statistics – deep math, linear equations, clustering – to create forecasting for personalization of the learning paths. Extensive data analysis is going to be the key.

2. Learning has an emotional tangent

Decision-making is not all raw data; it’s also cognitive. Vivek recalled the example of his daughter picking up things quickly when she’s more inclined or in a good mood. Emotions clearly play a big part. The eLearning design must factor in that.

3. Curriculum must be a mix of tech and socio-emotional attributes

The one-size-fits-all model doesn’t work. The question is, does our current education system really prepare students with all the skills that they need in life? DaVinci Life Skills is building a showcase model for the future of education based on Biophilic design, which focuses on educating learners creatively, ethically, and sustainably.

4. Dictatorship in education must go

There is a lot of dictatorship in education right now. The question is, what is enough for personalization – give the learners what we think is best for them or entrust them with a sense of control over their learning? Rosina feels a sense of self-motivation is very important. Vivek gave an interesting example of a project where they are leveraging technology to personalize learning by giving students different sets of automated questions for home assignments based on the assessment done by teachers.

Poll Results and Audience Questions

Earlier in the event, a poll was conducted to ask the attendees which types of data they think are most important for personalizing learning. Just over a quarter of respondents picked previous learning, interests, and preferences, followed by confidence scores/self-evaluation as important data points for personalizing learning.

Vivek and Rosina shared their perspectives on a range of interesting questions. Here are two that stood out to us:

Why are some learners are more engaged than others?

To the question of whether there is evidence of the data suggesting why some learners are more engaged than others, Vivek shared Liqvid’s approach, which is to look at the course usage patterns, create a hypothesis, and test it on data. Once the pilot is successful, we expand the data pool and based on the feedback, deploy solutions at scale. So, there is plenty of evidence for achieving a learning model with a high level of engagement.

Should the learners be given what they prefer, or should it be what they need?

Rosina feels completely democratizing learning for students right now won’t be the right way as it’d create a lot of pressure on students as well as teachers. She believes schools must allow students to fail so and then get back up again to achieve that sense of self-achievement.

Summing up

The event concluded with the question on the problem that both speakers haven’t been able to solve yet and what help they would need in order to do so. Rosina said her priority is the model of teacher training they are pursuing right now to empower students to create their own learning objectives for effective personalized learning while, Vivek says the next big challenge would obviously be ensuring how each learner can leverage technology to learn the way they like!

Watch the complete recording for more insights!

BONUS READ: Why is personalized learning so critical today, and how does AI help create personalized learning experiences.

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How is AI Transforming eLearning Beyond the Usual Suspects – Personalized and Language Learning?

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Artificial intelligence (AI) has become a staple not only in cloud computing but in eLearning, too. The reasons are obvious – it can be trained on several functions, saves time and money, build more efficient learning, and provide a deeper level of personalization for learners. Even the numbers back it – per a research report, the AI market is forecasted to reach $190.61 billion by 2025, out of which the eLearning market will surpass $6 billion by 2024! 

But beyond the usual suspects of personalized learning and language learning, AI has a lot to offer in the eLearning industry. Let’s explore other areas where AI is revolutionizing eLearning.

1. Content Analytics

AI-driven content analytics significantly optimizes learning solutions for off-the-shelf eLearning content providers and digital learning content publishers. Leveraging the “what works and what doesn’t” information, they can proactively build course catalogs to address the market demands and learners’ challenges. For educators and course creators, AI helps not just create and manage their eLearning content, but also gain important insights into learner progress and understanding through powerful data sets and models.

2. Virtual Facilitators

AI will, one day, replace an actual instructor with a robot. We already see virtual human mentors and facilitators that can think and act like humans. AI makes it possible via the “touchless technology” or “gesture recognition technology,” which lends human-like abilities to these virtual facilitators to respond or act naturally on verbal and nonverbal cues. Future smart learning environments and platforms will increasingly use AI to create realistic virtual characters and social interactions through augmented reality. Virtual facilitators could be strategically used to optimize human instructors’ time and involvement in the teaching or training process.

3. Intelligent Tutors

They sound the same as virtual facilitators, but they aren’t. AI is increasingly being used in eLearning to tutor a learner based on their difficulties beyond just condensing a lecture into flashcards and smart study guides. For instance, “SHERLOCK,” an intelligent tutoring system, is being used to teach air force technicians to diagnose electrical system problems in aircraft. UCLA has developed intelligent tutoring systems – avatar-based training modules – to train military personnel. In the future, these tutors will be able to help learners with anything and can also adapt to a wide variety of learning styles.

4. Course Creation

Using AI in eLearning will make the complete course creation process simpler and faster. For instance, AI can help in automatic translation and localization to offer more speed and efficiency by developing multi-language content for global companies, or for remote teams that speak different languages.

5. Chatbots and Virtual Assistants

With AI, educators can perform assessments faster and process inquiries in real-time to accelerate the learning process and enhance engagement. The best example is that of a chatbot or a virtual assistant, which can “decide” what question to ask learners based on their previous answers and jump to a higher level when the learners consistently enter the correct answers. Chatbots and virtual assistants can help both learners and instructors by answering questions that might otherwise have been sent directly to the instructor, or by helping students navigate course material in a friendlier way.

6. Accessibility Experiences

It’s perhaps the most important capability of AI, but less talked about. AI is revolutionizing the accessibility experiences for learners. For instance, Microsoft developed a free app called “Seeing AI” to leverage the power of AI to narrate to the blind by reading text, recognizing products, describing scenes, currencies, and the person standing in front of you, including their emotions. When more content creators add such apps to their learning courses, it will automatically increase collaboration and facilitate social learning. And not just blind; AI can also act as a virtual assistant responding to voice commands, to individuals who deal with mobility issues.

Paving New Pathways

The EdTech industry has seen solutions with AI components in the last few years. However, the adoption has been slow and unmatched to its boundless potential. The AI tools used in the education sector positively affect students, teachers, and schools by improving the accessibility of quality education. We will continue to see it gain a foothold in all areas of digital learning.

AI can seem complicated, but it’s more accessible than you think. Liqvid can help you better understand the potential applications of AI within your unique business process and recommend ways to utilize this game-changing feature to ensure your training is engaging and successful. AI-powered learning is the future. Embrace it to make it your competitive advantage. Contact us!

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Deliver Personalized Learning Experience with Artificial Intelligence

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It’s a boom time for personalized learning, which is driven largely by on-job skill development programs featuring real-time competency analysis and online courses. From students to corporate professionals, most of them favor personalized learning. Per an Industry ARC report, the global personalized learning market is estimated to surpass $2 billion by 2024, growing at an estimated rate of around 29% from 2018 to 2024. And artificial intelligence (AI) is a great enabler to this.

What is personalized learning?

Personalized learning is a teaching approach in which the pace of learning and the learning instructions are optimized for each learner. It leverages AI and machine learning to offer interactive content to the learners with real-time performance analysis. This results in modifications to course content and timelines for efficient learning.

Personalized learning challenges traditional teaching practices by implementing a model where learning by doing takes place. The learning progresses at the rate of learners’ learning ability. As a result, it’s beneficial for corporate learning to upskill resources efficiently and for students to enhance their job readiness.

Why is personalized learning so critical today?

Think about how we now shop or watch TV online; it’s all personalized content. It’s only a matter of time before the same principles can be translated into the learning space. Today’s learning institutes face a wide range of challenges – disengaged students, high dropout rates, and the ineffectiveness of a traditional “one-size-fits-all” approach to education. This is a major topic of conversation with constantly evolving technologies and the need to upskill employees even in the enterprise learning space.

AI, when used right, can create effective personalized learning experiences which can help resolve most of these challenges. Let’s see how.

1. Boosts Engagement

AI can predict outcomes, allowing learning providers to offer content specific to a learner’s past performance and individual goals. For example, if there are skill gaps observed when a learner is taking a course, the algorithms can send targeted recommendations to help them build on their knowledge.

2. Real-time information and feedback

With AI, learners get all the information related to online resources needed to fill gaps and feedback in real-time, which equates to less seat time and training payroll hours. Learners get the information they need quickly. Even the L&D admins and support staff spend less time analyzing metrics and reports and can instead focus on producing effective learning content.

3. Automate content scheduling and delivery

AI is designed to handle routine tasks so humans can focus on other priority tasks and look at the big picture. With AI, the learning platform itself can schedule coursework for the learners or deliver resources based on individual learner assessment results or simulations. This can help the learning providers to automatically predict course maps for each of their learners and readjust as needed.

4. Boost ROI

It’s a given – AI helps the learning providers boost their ROI. And why not? After all, less time spent in training combined with personalization results in better learning outcomes. AI-equipped learning platforms can track and forecast every move of each of the learners, allowing learning providers to launch online learning resources wherever and whenever needed.

5. Innovative learning strategies

AI combines data collection and machine learning to bring automated and personalized learning strategies to life. Here’s how:

i) It identifies skills gaps and suggests the best ways to close them.

ii) It helps providers collect better and more accurate data on how learning materials are impacting individual and business performance.

iii) It proactively supports learners by deploying virtual coaches for a proactive response to personalized learning and development.

iv) It can collect and interpret a vast amount of data, enabling learning providers to easily gather key insights.

Is AI the future of personalized learning?

Research is still ongoing; however, most of the data points to AI being touted as the future of personalized learning. Personalized learning involves giving learners control to choose their learning styles and access learning resources at their pace and convenience. So, essentially, through AI, learners get to choose their preferred learning paths.

There are some challenges ahead, though. The most crucial is to help learners understand and prepare for the new technology-based world and the many disruptive technologies that will change the way work is done. Learners must understand that there always will be some tasks that must be automated, paving the way for roles requiring creative, cognitive, and emotional intelligence skills.

A reliable digital learning company can make the personalized learning experience effortless and help organizations and learners adapt to the most recent and relevant digital learning content delivery methodologies and mediums. We at Liqvid have specialized in AI for English language training (ELT). We analyzed the personalized learning paths of over 1 million learners on our platform for developing our AI tools. Our tools for vocabulary building, automated essay scoring, voice recognition for fluency development, and analytics can assign different learning paths based on learning styles. You can learn more about these AI tools by clicking HERE.

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