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How AI-Powered Teaching Assistance in EdTech is Making a Difference

The year 2020 showed us endless possibilities of how things can be looked at anew especially in imparting education. The entire education system revamp got accelerated through technology innovation. For the learners, shifting to a remote, online medium has meant absorbing more multi-media content. As for the educators, to make up for the lack of in-person interaction, I believe the new system demands creating engaging sessions that are content-rich to eventually ensure effective course outcomes.

This positive disruption in education has thrown open many opportunities for innovation, predominantly in technology. And while this is a welcome shift, it needs to provide teachers easy-to-use tools that help them enhance the teaching-learning process. Rather, teachers will be able to focus on their core task using technology tools as enablers.

Enter Artificial Intelligence

Videos are an extremely effective medium to impart education. However, there is a dire need to streamline the vast content. Many of the education videos available (for example, Open Education Resource) are too long and unstructured. These need to be clipped/snipped appropriately to retain only the most relevant learning content visible. Further, there is a need to logically structure these into micro-learning bites for easy information retention. In fact, this holds true for almost every learning content. Additionally, interactivity and gamification could provide better student engagement and outcomes.

I feel technology will play a crucial role in assisting the education sector for these needs. The one that is particularly making waves is Artificial Intelligence (AI). What can intelligence that is artificial do for us? Well, it has proved to be a resource worth investing in, especially to make technology an enabling function.

For instance, examples of AI usage are surfacing rapidly, be it for student selection, course recommendation, interactive and intuitive content modules, nudge learning, adaptive assessments, reinforced learning, and more. The often-quoted Georgia State University is a good case in point for having used AI effectively in making a difference in the overall student learning at the university.

In this blog, we will talk about two specific AI-powered tools that can help teachers make learning more effective: Quillionz and Skimthru.

Quillionz – Leverage the Power of Questions

In the age of information overload, I find that the key to a successful learning experience lies in asking the right questions. Powered by AI and Machine Learning (ML) algorithms, Quillionz is a platform that lets you build a host of quality quizzes and assessments – within seconds.

Quillionz creates a variety of questions from any given content, including multiple-choice questions, recall questions, and short descriptive questions. Once the questions are ready, Quillionz can curate and enhance them. It lets you generate questions and also allows exporting questions into multiple formats, thus enabling you to directly upload questions on Learning Management System (LMS) or print the assessments.

Self-assessments are important and can be fun too for both students and teachers. Students can examine their own level of understanding without any judgment. Using QuilliQuiz, teachers can quickly reinforce key concepts whenever required. Basically, you can take a self-assessment, check your knowledge, identify areas of improvement, and also have fun sharing it with your peers. Creating editable notes is also very easy with Quillionz. It offers a concise and objective view of the original information so you can highlight important parts, summarize main points, and reinforce key concepts.

Additionally, Quillionz offer APIs for easy integration for product companies. It supports REST API and offers custom integration options with systems that use questions, such as EdTech platforms, assessments and quiz platforms, LMS, digital publishing platforms, and more. With multiple integration options designed to handle various OEM business needs, advanced tools and utilities, and custom input/output formats, Quillionz API can be tailored to suit your unique business needs.

Skimthru – AI-powered Video Navigator

This unique tool is equipped with an interactive video browsing feature making use of a patent-pending concept to create a set of Theme Clouds. Words used in a specific text are clubbed together to emphasize either their frequency or importance or even both. This as a Theme Cloud which helps focus on the core topic in a given video.

As an educator, say if you wish to use a particular YouTube video on a subject, then all you need to do is to ensure that the video comes with a transcript and enter the URL on Skimthru. With the help of AI, the Theme Clouds will get generated automatically based on the key words. As learners go through the video by moving along its timeline, Skimthru highlights relevant parts of the video and vice-versa. It is literally like skimming through the video. Such multiple Theme Clouds make up a Skimthru. This enables a better learning process as learners get precise relevant content that is easier to absorb and retain.

What the Future Holds

Artificial Intelligence, which was once just a dream, is now a reality – chatbots, recommendation engines, personalized tutoring, adaptive assessments, smart virtual assistants, and more, are already here. Educators agree that AI is essential for the future of learning and how it can empower both teachers and students and reshape the way we approach education.

We know that teachers have to handle varied tasks such as organizing educational material, evaluating assignments, grading exams, managing paperwork, communicating with the management, students, parents, etc. The good news is that AI can help teachers with all these administrative tasks in addition to providing all the teaching-learning aids.

I was recently a part of a Point of View session on 'AI-Powered Teaching Assistance in EdTech' where together with my colleagues, we have explained how EdTech stands to benefit from AI. Unfortunately, there is a notion that with the rise of AI technologies in education teachers may become obsolete. In reality, this is highly unlikely to happen as AI will instead become a reliable assistant for the teachers, helping them fulfil their responsibilities with higher efficiency. After all, while AI can be of great help, students will still need a teacher to connect with personally, and more importantly, to guide and inspire them in a way that no machine ever will.

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Tech Trends in HRTech to Look Out For in 2021

It is the time of the year when we start looking at the predominant technology trends that can govern the coming year and beyond. As we see it, these trends develop upon the existing technology. Let’s see how the trends for 2021 are set to enhance the overall HRTech operations and experiences.

Total Experience (TX)

With the onslaught of the COVID pandemic, 2020 enforced remote availability on almost all businesses. Digital transformation became the buzzword where work culture was supported via video conferencing, efficient communication tools, and central availability of data and information through the cloud. In short, multiple modalities of communication supporting various devices towards a multi-experience, dominated this year.

Going a step further, we are now looking at a more unified and cohesive experience for all stakeholders – employees, customers, and end-users via these multiple communication channels. This seamless experience calls for a unified communication strategy where the entire business is analyzed from a communications point of view. Unified communication will also lend itself to an analysis of communication. This should provide us important behavioral insights to enhance operational efficiency.

At Harbinger, we see this trend greatly followed by our customers. In one case, a business created a candidate selection platform, a job marketplace, and corresponding mobile applications for candidates and employers for interviews and interactions, all connected together with communication channels where vendors, employers, and candidates could interact together. The experience so designed helps the business to not just enhance customer experience and satisfaction, but also brings in insights on the communication methods and behaviors, internally and externally. Collaboration and productivity tools like MS Teams, in such scenarios, are enabling the total experience through different interaction mechanisms like conversational interface, custom apps, and Tab views along with support for integration.

AI Engineering

Artificial Intelligence (AI) and Machine Learning (ML) are helping businesses gain valuable insights from accumulated structured and unstructured data. However, till now, the AI component was built on top of the existing offering, something that was planned after stabilizing the intended business offering. Going forward, AI needs to be engineered right from conceptualizing the business solution. Data gathering, storage, and analysis will now need to be baked into requirement definitions to have the maximum impact of the AI solutions and insights.

At Harbinger, we encourage businesses to enable AI and ML capabilities early on. As an example, when architecting a technology rehaul for a client, we designed the data warehouse complete with data visualization and analysis not only for the data to be gathered in the future but also from the perspective of migrating legacy data.

We also feel that more and more AI-based DevOps will help teams to test, code, release, and monitor software more efficiently. Augmented analysis where ML and Natural Language Processing (NLP) is coupled together with AI to automate repetitive tasks as well as for data gathering and insights is also going to be a major trend.

An interesting aspect of AI engineering is Ethical AI. As AI gets applied to the work environment, the value proposition is the removal of human bias due to the use of ML. However, it is frequently observed that the training data and subsequent data model may carry the geographical/ethnic/gender bias that the underlying data displays. It seems like the coming year will show initiatives defined and implemented towards removing such a bias.

Hyper Automation

Business process automation for operational efficiency has been around for a while now. Businesses are looking for more and more ways to automate various tasks – be it processing files, answering emails, providing customer support, etc. They are doing this using various technical capabilities like event-driven software, robotic process automation as well as AI and ML.

Till now, automation was done as and when needed, using multiple tools, where these automated processes did not necessarily talk to one another. Hyper automation will be the next step which considers end-to-end automation with processes exchanging information through integrations and connectors. Such integration will also enable easy access to data and superior analytical insights.

This will be particularly important for HRTech. By design, almost every application has a workflow engine at its core, which essentially helps HR in automating different applicable workflows. But in the current ecosystem, a typical hiring process in the ATS stops after releasing the offer to a candidate. Subsequent workflows for onboarding, HRIS updates, etc. are executed independently. In the future, we will see the use of Hyper Automation to enable the connection between workflows across different HR applications.

Distributed Cloud

One of the major backbones supporting the trend of ‘anywhere operations’ is a distributed cloud. It allows deployment in physically and geographically distributed cloud infrastructure, allowing management of the cloud in one central location. This enables remote availability in cost-effective ways. Post the pandemic situation of 2020, the HR industry is now going towards distributed control and centralized coordination which again relies on the distributed cloud.

In HRTech, we are also observing that the use of distributed cloud also helps with certain compliances such as GDPR where data separation and access control is a key requirement. As a result, the geographically distributed availability enables saving data in the corresponding location – for example, a distributed cloud allows to have data for a person from Germany be saved in Germany, enabling GDPR compliance implementation.

Personal Analytics

Data-driven HR generated with the data that is gathered from the HR systems, lends itself for analysis, giving us insights about the stakeholders. In today’s times, organizations will need to couple people data with day-to-day operational data as well as location-based data for better predictive analysis and decision making. For example, the use of biometric data along with people data, like facial interactions for productivity analysis, will expand the personal analytics further. Real-time analysis and decision making can be done where daily interactions and behavior of individuals is analyzed by embedding analytics in the business models, instead of having it as a separate module.

In my opinion, these trends are extensions or the next steps of the architecture and technology we are using. The important or the overarching message for everyone here is to be able to define a strategy that will help unify all parts of the HR process, systems, and data. We are now trying to see how all the pieces connect, which will provide us further abilities for better analytics and better operational efficiency.

We will be looking forward to these trends making a mark in the new year. Are there any others that you think should join this space? Do let us know at [email protected].

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5 Key Things to Consider When Designing Your EdTech Product

Like most of the other industries, UX plays a very important role in the EdTech space. As more and more teaching and learning is happening through the digital medium, UX has now taken a centerstage. In one of our earlier blogs, we have spoken about Design Thinking and what it entails. The need of the hour is to merge Design Thinking and digital trends to create educational products. And this is where we need to balance the UX equation.

The question that we need to ask ourselves is – What is the value we are providing for the pain the user is subject to?

UX Equation: Value = Reward – Pain

Below I have listed 5 key things that we should keep in mind when we go about designing an EdTech product.

1. Know Your Audience

You might say that knowing your audience is a basic requirement, and there’s nothing really new about it. Of course, you are right in saying this. But here’s a curve ball. There is a good possibility that the same product might be used by various users to perform different functions. These personas would vary from students to teachers to educational institute administrators to parents. The comfort of doing things in a digital environment would thus vary as well. This is where it is imperative to bring in the opinions and needs of all the stakeholders on the table before you start putting together your design board.

2. Role of the Product

The next key thing to think through is to clearly define the role of your product. Questions should be asked to determine whether the product is being designed to deliver learning, instructions, information, assessment, or entertainment. The design perspective will have to be aligned with the role/s the product is assigned.

3. Triggers for User Motivation

Once we have defined the role, then it is important to identify the triggers for user motivation. The right triggers will keep the users engaged on the product and it will eventually help on the outcomes as well. Learning outcomes can be improved using the right triggers, tools, and outcomes to sustain a user’s interest which helps them gain something intrinsically valuable. For example, an inbuilt performance mechanism which provides continuous feedback will keep the learners motivated and engaged in a learning application.

4. The Ecosystem

Early in the game, it is important for us to figure out if the product will be used as a standalone product or if there are possibilities of integrating it within a bigger ecosystem. If it needs to be a part of a bigger ecosystem then to make sure that the experience is seamless, certain design considerations should be made at the ideation stage itself, rather than coming back to the design board at a later stage.

5. The Stage of Your Product

It is also important to identify what stage your product is at. The questions to be asked are – is it at an ideation stage? Is it an existing product with an active student base or a legacy product with an outdated design? A different design approach would need to be followed depending upon the particular stage.

Very briefly, I have highlighted here the design strategy for the three possible stages of a product:

a) When a product is in the concept/idea level, we can help with concept validation and then apply an iterative user-centric design process (including persona, task flows, information architecture, low + high fidelity prototype, and validation).

b) If the product is already launched and has a stable student/learner base, we can use journey mapping or empathy mapping to enhance the user experience.

c) Finally, legacy product re-designing can be done with a combination of UX research and the UCD (User Centered Design) approach.

It would be interesting to know your thoughts on this. Are there any other key aspects that you would like to add to the list? Also, please do drop us a line at [email protected] for any questions you might have.