As the pandemic crisis persists, “Zoom fatigue” continues to pose challenges to the online learning/education industry (Zoom fatigue” is a sense of exhaustion and boredom caused by attending too many meetings, classes, or seminars). As a result, teachers keep facing overworking problems and students increasingly drop out from classes (online, offline or hybrid), adding to the “retention crisis” of the industry.

The pandemic has also widened the inequality and digital divide across different income segments, with those with limited household income/savings dropping out of school altogether. As attested by ErudiFi CEO Naga Tan, many of the edutech firm’s school partners saw a corresponding drop in enrollment rates and an increase in student attrition during the pandemic.

Even before the emergence of the pandemic, online courses consistently recorded higher dropout rates (5 per cent to 35 per cent) than physical classes, research showed. 

To address this, edutech startups, which consider Zoom fatigue a short-term symptom, strive to make the e-learning experience a fun and more engaging journey for educators and learners.

Over the past years, many edutech startups came up with different innovative solutions — such as continuous assessment of individual performance, improved learning management systems, tailored courses to strengthen the knowledge absorption capacity, and gamified interactive learning design. 

Among them, two approaches stood out — data analytics and study-to-earn — evincing interests among educators with their capabilities to cope with the looming “retention crisis”.

Data analytics 

Singapore-based ErudiFi aims to address the 10-15 per cent annual school dropout rates by providing its partner educators with data-driven financing solutions that support student recruitment and retention. The firm helps track tuition fee disbursements and offers real-time analytics for dropped students.

But the approach that mushroomed in the recent past is personalised/adaptive learning, which stands alone as the most buzzworthy data-based method to raise engagement and secure desirable retention rates.

With the support of technology, human intervention, curriculum design, or pathway, and most likely a mixture of these, personalised learning tailors instruction to the skills, understanding, progress, and preferences of an individual learner for the better.

A typical model is to leverage analytics and technology to identify areas where students or teachers are weak and recommend the necessary lessons. 

For example, Singapore-based LingoAce employs multimedia, gamification features and AI-powered tools to assess the teaching quality and finetune the curriculum and learning experience after a lesson is conducted. It later leverages live one-on-one and small-group classes with teachers to provide real-time feedback and interaction.

Noodle Factory, another startup, takes a step ahead and utilises natural language processing (NLP) to automate the creation, preparation, and grading of exams and assessments. It uses AI to provide human-like lessons, creating a personalised learning experience that provides direct instruction and feedback to learners.

While human teachers only teach one way of solving a problem, Noodle Factory’s AI tutors claim to learn and develop different methods and remember new approaches that students may have.

However, industry insiders have questioned these technologies’ true ability to raise the retention rate as they believe human interaction should be the core of a personalised engagement. For instance, Learner Net conducts small group courses with a smaller teacher-student ratio. It enables teachers to use different techniques and methodologies to work on students’ weaknesses in a targeted manner that is supposed to engage students more efficiently. 

In response, Noodle Factory CEO Yvonne Soh still believes that technology helps free up valuable time so that students and educators can spend more time on meaningful interactions instead of being replaced by machines. 

“Technology is great for facts and memorisation,” said Soh. “[With the help of technology], we are actually solving workload challenges for educators.”

Study-to-earn

With cryptocurrencies and blockchain becoming popular, the edutech industry, too, has started adopting the technology. The initial discussions of blockchain in education focus primarily on verifying certifications and accepting crypto for tuition fee payment. 

Another exciting development is happening — a reward system to encourage learning on online platforms and simultaneously raise the retention rate.

“Educators are willing to pay five to ten per cent of revenue for loyalty,” added Quang Mai, Director of Vietnam-based edutech accelerator Topica Founder Institute, adding that most profits in the education come from repeat transactions of loyal users/students.

By giving points for every course purchased or learning activity performed, educators allow students to use these reward points to buy more courses or unlock specific functions. Learner Net, for instance, is working with third-party merchants with whom students can use these reward points.

“We have also looked at NFTs [non-fungible tokens] to reward users,” Learner Net Founder Joe Ngoi told e27. “‘Study-to-earn’ concept is a blockchain take on the traditional gamified learning experience, with open-loop rewards instead of closed-loop rewards.”

However, the first-movers have the disadvantage: they have to invest money in educating the incumbents as blockchain, and its associated technologies are relatively new in the education space.

To break these barriers, Mai and his team are on track to launch MetaStudy; it is a central playground operated as a private blockchain for all educators to do loyalty driven by “study-to-earn” (a concept evolving from the “play-to-earn” frenzy). The mechanism, which Binance founder Changpeng Zhao mentioned in a tweet, helps increase students’ engagement and drive the retention rate up dramatically.

In essence, Meta Study network has a common token named MTS, which is used with all educators and allows them to issue their rewarding tokens backed by MTS to reward users/students. Their students can redeem, swap, exchange tokens in Meta Study’s exchange and a common marketplace for NFTs, products/services, or join Meta Study’s events and challenges to earn more.

“In traditional reward systems, those rewarding points are only usable in that specific education institution and could not be added together from a group of people such as family members who study in different places and levels, not to mention the burden of inventory management of gifts,” said Mai.

Though it is similar to loyalty platforms, such as what Urbox or Society Pass provide, with Meta Study network, educators can keep their brands with their rewarding tokens in the network and incentivise learners for better engagement and flexible learning options throughout their lives.

“Study-to-earn can be an appropriate incentive for learners, with the right tokenomics and as a part of a larger ecosystem,” Ngoi commented.

However, Alex Ng, Managing Director of EduSpaze, a Singapore-based edutech accelerator, is doubtful about the sustainability and long-term effects of “study-to-earn”, especially for younger learners.

“My view is that this can be useful if it’s well designed to encourage and motivate learners and not excessively used,” said Ng.

Students stay longer, but do they learn more effectively? 

Insiders say that current technologies’ data for personalised learning still tend to group students into generic categories. This may impact students’ learning efficiency as it cannot include their unique characters, personalities and traits.

“As competition stiffens, we are likely to see consolidation in this market as the bigger players aim to acquire more data,” said Ngoi.

That is why a sector-specific accelerator like EduSpaze aims to dive a lot deeper into creating the right community and ecosystem, maximising the leverage for these edutech startups.

“If more learning organisations and schools can share relevant, anonymised learning data, that will help the ecosystem move forward faster,” noted Ng.

Fortunately, the ecosystem stakeholders agree on the value of human interaction as the core of any intention to retain students and improve learning quality. For online learning to succeed, it requires not only a reliable platform but also a willing learner and a dedicated teacher.

Technology should help to improve learning outcomes and support teachers’ role as a form of reinforcement and not a replacement. It can help motivate learners with money or rewards, but only students who have an inner passion can do more and make a difference.

“Incentives can have benefits, especially when used to drive certain behaviours, but incentives alone will not help students to learn,” said Soh of Noddle Factory. “I do believe there needs to be intrinsic motivation for a student to perform well truly.” 

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