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Adaptive Learning Market worth $5.3 billion by 2025

The major factors driving the growth of the adaptive learning industry include the rising demand for eLearning solutions, personalized learning, and government initiatives for adaptive learning solutions.

According to a research report Adaptive Learning Market by Component (Platform and Services), Application, Deployment (Cloud and On-premises), End User (Academic (K-12 and Higher Education) and Enterprise (SME and Large Enterprise)), and Region – Global Forecast to 2025″, published by MarketsandMarkets™, the global adaptive learning market size is projected to grow from USD 1.9 billion in 2020 to USD 5.3 billion by 2025, at a Compound Annual Growth Rate (CAGR) of 22.7% during the forecast period. The major factors driving the growth of the adaptive learning industry include rising demand for eLearning solutions, personalized learning, and government initiatives for adaptive learning solutions.

The platform segment to hold a larger market size during the forecast period.

Based on components, the platform segment of the adaptive learning market is projected to hold a larger market size during the forecast period. The adaptive learning platform segment consists of products, solutions, and platforms that help learners study through the internet. Owing to the low entry cost in the adaptive learning market, the number of platform providers has increased considerably in the past few years. The adaptive learning platform is capable of working as a standalone solution and is used by several clients as a standalone platform. However, in several other organizations, the adaptive learning platform is integrated with Learning Management Systems (LMS) that comprises other solutions as well. The adaptive learning platform supports the management of a huge pool of information and allows instructors to create content for the course and design the lesson delivery structure, creating a dynamic learning environment.

By end user, the enterprise segment to record a higher growth rate during the forecast period

Organizations and institutions in business domains, apart from the education sector, have been classified as enterprises in the report. Enterprise users include organizations catering to various verticals, such as retail, government, healthcare, and Banking, Financial Services and Insurance (BFSI). Corporate users implement these solutions as a tool to train and assess employees for providing various instructions and suggestions. Real-time mass notification solutions help enterprise management to deploy faster communication among its employees about new policies and other instructions. This segment is further classified into Small and Medium-sized Enterprises (SME) and large enterprises on the basis of the number of employees in the organization.

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Corporate Learning Engineering

Corporate Tools may include quite different systems such as Change Management, Talent Management, Performance Management, Competency Management, Learning Management, Content Management, Learning Records Stores, Analytics, …

Tools Interoperability represents a real problem. Some solutions are IMS Learning Tools Interoperability (LTI), APIs, and xAPI

xAPI. In general, xAPI reflects an empiric nature of Learning Sciences, shares with them a Bottom-Up approach, and allows recording each learner’s performances (not really holistic experiences).  Performance records (mostly about completion) can be analyzed by instructors manually and/or use Analytic Tools for revealing some relations, generating insights, and making decisions about the improvement of content. Instructors are supposed to become researchers, which is no good (overload, amateurism).

So, xAPI is all about recording and using history of learner’s performance.

iTutorSoft. We develop a real-time Adaptive Instructional Platform. We can use externally available historic xAPI records and Analytics, for example, for evaluation of each learner’s background, but we do not actually need historic records for generating a real-time learning process.

Our approach is quite different. It is a Top-Down approach, the essence of Learning Engineering. We apply general interdisciplinary theories (such as Systems, Control, and Activity Theories, and AI) to derive a unified frame/network of goal-oriented human activity. Instructional Designers can use our authoring tool to fill in this frame/network with learning specifics and construct a formalized holistic model (not just some insights) of Learning Experience (Courseware), which is understandable by humans/instructors and machines/computers. Computers can use that Learning Experience Model for automatic generating of instructional processes. Being added with a computer-readable and updatable Learner Model, computers can generate the most effective Adaptive Personalized Instruction at scale.

Moreover, our unified frame/network can represent not only the Learning Experience but also Professional and Corporate Experiences, as well as integrate them together. Such an integrated Corporate/Professional/Learning Experience Model allows supporting inferences, such as

  • evaluate impact of a learning unit on professional competences and to corporate goals
  • derive necessary learning from desired competencies, jobs, corporate goals and change.

Conclusion. iTutorSoft platform can do the following

  • generate the most effective Adaptive Personalized Instruction at scale targeted on predefined Professional Competencies, Roles, and Corporate Goals,
  • represent a common ground of many Corporate Tools (see above), unify them, integrate, and solve the huge interoperability problem.
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The Billion Dollar EdTech Platform Hole

This is a curated short version of the post in eLiterate website.

The global pandemic will obviously result in a significant acceleration of adoption of what has been a relatively long and drawn out adoption of technology-enabled teaching and learning. Many of the specific objections and barriers that persisted are moot in the face of the alternative (insolvency of the institution). As those issues are reconciled, it is clear that a key driver is the (re?)realization that organizing around the needs of learners is job one.

In today’s reality, teaching is a rather disconnected from the needs of learners. In the spirit of academic freedom, an individual teaching faculty improvises and curates the materials and tools for their courses. And since it is the very rare case for a single provider to deliver an end-to-end personalized experience – it is up to students to fill the gaps, navigate multiple, disparate systems, jump through multiple authentication sequences, and experience jarring differences in user experience and content fidelity.

In the background, industry technology interoperability standards have evolved tremendously but are implemented in asymmetrical, unpredictable, and sometimes proprietary ways. The use of instructional designers by institutions is growing, but there are still only 10,000 or so instructional designers or roughly 1 per 100 teaching faculty members. These and other efforts can help but are really band-aids covering bigger issues.

Billions of dollars spent to develop EdTech products that are not pedagogically justified and hard to use because of massive market inefficiencies, competitive dynamics and other challenges in the broader education ecosystem.

The question is how higher education institutions and the companies that serve them will react to preserve (or not) academic freedom. Certainly, there is a bifurcation within the market and even within institutions for more (unified) top-down course design and development – but a significant percentage of the overall enrolments are based in institutions with far more complex academic freedom (improvisation) cultures.

Looks like this bifurcation will widen. More and more courses will be built to “scale” with super clean instructional design, careful consideration of student needs, engagement models, insightful use of data to drive outcomes, and “hands on” training for instructors who will deliver using proven pedagogical principles, best practices, their own skills and experiences, but little academic freedom.

On the other hand, institutions for which academic freedom is a key tenet in their institutional mission will strive to build the capacities necessary to preserve their brands and the uniqueness of their teaching culture, while delivering high quality, differentiated learner experiences in technology-enabled environments. For these institutions, highly flexible and customizable technology solutions will be required.

And those are not the only big changes looming: those institutions will become far more demanding of the companies seeking to provide them with content, technologies, and services to ensure those offerings are not locked into proprietary platforms and business models.

So, what is required for accelerated adoption to fill in the billion-dollar EdTech hole? The answer is something like unified, yet flexible, general pedagogy-based Adaptive Learning/Authoring Platforms for Personalized Education targeted on learner’s dynamic needs, success, desired job, and contribution to business outcome. That is exactly what CLARITY is and it is ready for your adoption.

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Why You Get Personalized Learning Wrong And How To Fix It With …

This post is my comment to the post “Why You Get Personalized Learning Wrong And How To Fix It With Learning Analytics” published in eLearning Industry. I am just not sure that the “Personalized Learning Pathway” by itself is a good idea that can be fixed with Learning Analytics.

The biggest mistake with Personalized Learning is trying to develop a Personalized Learning Pathway for each particular learner. It is a Sisyphean Task, endless and ineffective.

Each learner will deviate from any (best) predefined Pathway just because each learner is ever-changing, a learning process is not observable, controllable, and predictable.

Meanwhile, the simple, practical, and effective strategy are (1) using short assessment(s) to narrow down the learner’s possible states before they changed, then (2) choosing learning intervention(s) to push the learner’s state(s) to the objective one, and (3) continuing this process (1-2) up to success.

Believe me, it looks like an interplay of Loops, not a Pathway at all.

The best Personalized Learning is Off-Road Learning generated by that interplay of Loops.

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Pandemic Spike In AI Learning–and What It Means For Schools

Dear reader,

I hope you are well and curious. Let me share with you some trends I found in the Forbes post with the same title. Below is my quote from the post linked above. I emphasized the part of the text in Italic as the most important for my message to you.

“Lessons for High Schools and Community Colleges 

The tech learning space is shifting fast with big implications for high schools and colleges. 

An introduction to coding and computer science can be valuable for all learners. Going beyond an introduction to building pathways that reliably result in high wage employment is a dynamic challenge—both in identifying locally relevant skills and in staffing courses. Relying on a curriculum vendor for current content and staffing in traditional ways are no longer adequate solutions in many cases. 

Tech pathways are shifting to employer-down (back mapped from open jobs) rather than bottom-up (pick a degree and look for a job). They are increasingly inexpensive or debt-free, modular, asynchronous, and credentialed. The pathways may include degrees but that is becoming less important than verified skills and work product. 

For 16-24 year old learners, the support of an instructor and cohort is typically beneficial. But with so many industry provided or sponsored learning pathways, high schools and colleges can rethink delivery with blended competency-based pathways that incorporate instructor, peer and mentor supports. For this age group, successful work experiences can be as valuable as coursework—and some of those can be incorporated into credit and evidence records.     

Pathway partnerships with employers and education providers (which are increasingly the same entity) are critical for high school and colleges to be able to offer relevant learning sequences that are modular, applied, and competency-based. 

Helping young people make informed choices between dynamic pathways, in ways that match interests and local opportunities, is becoming more important but more challenging. An industry advisory board can be helpful in localizing and personalizing guidance.”

The trends I see are as follows.

1. AI Learning is getting and will be very popular

2. It is about direct targeting jobs that are on high demand

3. It is about developing learning pathways to those jobs and their personalization for higher effectiveness of learning

iTutorSoft’s Learning/Authoring platform enforces all those trends.

1. It is AI-based and teaches students how to learn the most effectively. Every Student Succeeds.

2. It supports designers in the systematic analysis of jobs and precision design of required courseware. It is Learning Engineering, dear reader!

3. It automates generating the most effective personal pathways to the targeted jobs in real-time of learning from the courseware.

So, it looks like great timing for iTutorSoft and our partnership!
Would you agree?

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What is a good Learning Management System for people to teach in real-time?

This is my answer to the above question in Quora.

Ideally, real-time Learning Management is a role of a tutor in one-on-one interaction with a student without annoying delays. In classroom practice, teachers working with a class of students cannot do that.

Traditional Learning Management Systems (LMS) are not designed for tutoring students in real-time. They are designed for teachers to enroll the students in their courses (at one time) and get back reports/update grade book (at another time). They are rather Learning Administration Systems.

Real-time Learning Management Systems have to simulate tutors working with an individual student within a course. They are computer applications where each course is (1) manually programmed or (2) automatically generated.

The first case (1) is the most common. Most of the known courses represent sequences of learning and assessment items branching in accordance with student performance. Manual programming of even simple courses requires high qualification and is labor-consuming. That is why practical courses are often oversimplified linear page-turners, which cannot be effective for all so different students.

The second case (2) is not yet common but getting much and growing attention nowadays. It represents Intelligent Tutoring Systems (ITS). The early ITSs have been able to automatically solve well-formalized tasks, monitor a student solving the same task, comparing ITS’s performance against the student’s one, and providing remedial feedback in real-time. The later ITS (a.k.a. Adaptive Learning Systems) are able to automatically plan and personally recommend a learner each next learning or testing item/page, track learner’s performance, provide immediate feedback, evaluate current achievement of learning objectives, target not yet achieved objectives, and do so until each particular learner achieves all the learning objectives in her/his own pace. Such ITS can be very effective for all so different students. The best thing is that teachers do not need to reinvent and program any sequencing anymore. It is all done yet can be tuned. An example of such ITS is iTutorSoft. It is available on the website “adaptive deep learning/authoring platform for personalized education”.

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What Is The Difference Between Adaptive Learning And Personalized Learning?

This post is inspired by the post with the same title published in eLearning Industry. Its conclusive point is “there’s more value in thinking of personalized learning and adaptive learning as fruit on the same vine, than treating them as a separate genre”. It sounds nice but does not clarify “what is the difference” and why it matters. So, let me bring some clarity.

First of all the common term “Adaptive Learning” is confusing. Learning is always adaptive. In general, learning is an adaptation of yourself to an ever-changing environment. So, Adaptive Learning is “Learning Learning”,”Adaptive Adaptation”, or “Learning Adaptation”. Sounds clear? Not really, it is confusing and misleading.

Replace the term Learning with term Instruction. Then instruction can be

· Differentiated, which is Instruction targeted to a specific group of learners (with their specific background, needs, objectives, preferences,…). It is fixed and not flexible. For example, a static playlist/pathway for all learners of the group defined by pre-testing and surveying the learners.

· Personalized, which is Instruction targeted to a particular Learner (with her specific background, needs, objectives, preferences,…). It is fixed and not flexible as well. An example, a static playlist/pathway defined for one particular learner by pre-testing and surveying.

· Adaptive, which is a Personalized Instruction having a moving (and fuzzy) target, ever-changing Learner. So, it is flexible and dynamic. For example, a dynamic pathway automatically generated by an Instructional Engine (such as iTutorSoft) for one particular learner on the fly based on dynamically embedded testing and assessment of learner’s current proficiency and/or deficiency.

So, what matters is, due to its static inflexibility, Personalized and Differentiated instruction cannot follow any deviation of the ever-changing learner from the predefined Pathway. That is why they lose their learners and cannot be effective. In contrast, due to its dynamic flexibility, Adaptive Personalized Instruction keeps each learner in the loop and can be really effective.

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How To Turn Test Prep Tutoring Into A 7-Figure Business

In the case of one-on-one tutoring, you can have a small number of students and be very busy. Imagine you can cover as many students as you want, share your knowledge with tens of thousands of students and earn equivalent money. Wouldn’t it be amazing? 

Take a look here if you need more details.

The good news is that a software Platform for the best online Tutoring at scale already exists. It is CLARITY by iTutorSoft. It has been heavily tested and implemented for decades in many different disciplines. It supports tutors/teachers in rapid entering of high-quality content, which you used to teach. Then it uses your content for automatic generating of the most effective Adaptive Personalized Tutoring of your learners at scale ensuring a high success rate. So, you may get thousands of electronic assistants tirelessly working for you 7/24.

Our website is www.itutorsoft.com, visit it for introduction, request your registration via itutorsoft1 @ gmail.com, and start your journey into a 7-Figure Business with our support.

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Early Adopter Benefits

Learn why it’s important to stay ahead of the latest technological trends and how to do it as easily as possible. 

Technology is advancing at a faster rate than ever before. Keeping up with this never-ending wave of innovation may seem daunting, but as an eLearning professional, it’s essential. Harvard Business Review made it pretty clear [1]: “Ignoring trends can give rivals the opportunity to transform the industry”. Forbes echoed this sentiment by saying that “if you don’t keep up with technology – and stay one step ahead of the game” you risk falling behind, becoming irrelevant, and missing opportunities [2]. Thankfully, keeping up with the latest tech stories is easier than you might think, and will benefit you greatly in the short- and long-run. By reading leading online tech publications, watching content on YouTube, listening to podcasts, attending conferences, and becoming an early adopter, you’ll be up-to-date and in-the-know in no time.

It’s also important to try out new technology trends on your own. By becoming an “early adopter”, you’ll have an inside look at the behaviors and thought-patterns involved in upcoming technological innovations. Trying out new technology doesn’t have to be expensive either, many apps or software platforms offer free versions and trials. By trying out a new app, you can experiment with new ways to communicate, take notes, or perform tasks you have to do every day. You may even find new workflows that work better than what you’re doing right now! This habit is beneficial not only because you’re getting small tastes of new technology that may become a larger part of your work in the future, but also (and maybe more importantly)because you’re developing the ability to better learn how to use and navigate new programs and platforms. As a result, when you are inevitably asked to use a new system in your work, you won’t have to waste as much time learning the ins and outs of a new program.

The full text of this article is available here. Good luck!

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5 Things You Should Know About Adaptive Learning

When we think about popular software, we picture sites like Amazon, Netflix, and Hulu: the pros of personalization.

As Amazon users shop, they buy everything from toilet paper to college textbooks, dog food, and nutritional supplements depending on lifestyle and AI-generated product recommendations.

As viewers watch Netflix, they stream endless hours of reality television or hard-hitting dramas or true-crime documentaries depending on personal preference and, more often than not, previous search requests.

These sites don’t discriminate based on age, interests, intellect or socioeconomic status, and neither does adaptive learning, an educational model changing the landscape of learning from a one-size-fits-all atmosphere, to a customized tool for students of all ages. Regardless of learning ability and prior knowledge, adaptive learning helps any student willing to learn.

To help you better understand the basics and benefits of adaptive learning, we’re breaking down a few must-knows.

  1. Adaptive learning helps teachers as well as students
  2. Adaptive learning engages the area between a student’s comfort zone and frustration zone
  3. School and Universities across the country have already adopted adaptive learning and personalization techniques:
  4. When it comes to adaptive learning, BE PICKY
  5. The U.S. Department of Education is investing in adaptive learning.

There are endless benefits to adaptive learning technology – students can track improvement and develop a sense of personal responsibility for their academic progress, students who’ve fallen behind on a subject have additional resources to draw from, and teachers can develop lesson plans tailored specifically to the classroom of students before them.

The adaptive learning model even extends beyond binge-watching platforms and educational models. AL has been implemented to improve training techniques within NASA and branches of the U.S. military, boasting revolutionary success and changing the way we approach educational improvement.

Invest in adaptive learning and whip your students in shape – NASA-style.

Here is a full text of the article.

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