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How Deledao AI Helped 1,000 Students Improve in School

Time Frame: March 2022 – May 2022


District: Aggregate data of districts across multiple states in the U.S.


Students: K-12


Total Student Population: 1,000+

The Challenge

Digital distractions are the number one obstacle to effective digital instruction and legacy solutions implemented by schools today fail to solve the digital distraction problem.

The latest National Assessment of Educational Progress (NAEP) confirmed the worst fears of educators and parents across the country. Also known as The Nation's Report Card, NAEP shows widespread and substantial declines post-pandemic in both math and reading test scores. The pandemic has erased 20 years of steady improvement in student achievement¹.

The rapid increase in 1:1 programs and digital devices in schools coincided with decreased academic scores. Overnight, schools shut down and implemented remote learning. 1:1 programs nearly doubled to 90% of middle and high schools during the pandemic².


While public discourse widely attributes these academic declines to pandemic disruptions, the real problem is digital distractions on school-issued devices. Educators named digital distractions the #1 challenge to more effective digital learning (EdWeek, 2022)³.

Graph - Digital Distractions Increase while Academics Decline
The strong association between student engagement and academic performance makes it imperative to solve the problem of digital distractions.

Research shows that it can take students up to 30 minutes to refocus after being digitally distracted (Chen, Nath, Tang, 2020)⁴. When students spend half a class period disengaged from learning, it is no wonder that their student achievement suffers.

Not only are digital distractions detrimental to the individual student, but also they can potentially affect the whole class negatively. According to research, it is highly likely that digitally distracted students negatively impact the learning of students around them (Hall et al., 2020)⁵.






Schools that rely on teaching students digital citizenship to self-regulate and manage their online behavior find that teaching willpower is complex. Academic research reaches the same conclusion. Even when students are presented with evidence that their media multitasking habits negatively affect their academic performance, many still cannot regulate their behavior (Dontre, 2021)⁶.

Since students cannot help themselves, schools mainly rely on technological tools to help them manage their time learning in a digital environment. The importance of an effective technological solution cannot be underestimated. Digital environments that cannot prevent students from accessing digital distractions make learning self-regulation difficult (Bylieva et al., 2021)⁷.


Traditional web filters and digital classroom management solutions fail to solve the problem of digital distractions because they cannot handle today's internet. This is because traditional solutions, also referred to as legacy solutions, depend on outdated technologies to build a database of allowed or blocked websites (domains), webpages (URLs), and keywords. While this approach may have worked for the internet of the 1990s, the sheer size and dynamic nature of the internet today present an insurmountable problem for this antiquated approach taken by traditional solutions.


252,000 new websites go live every day⁸. 500 hours of video are uploaded to YouTube every minute⁹. The social media platform Tumblr has 540 million individual blogs with 10.5 million daily posts¹⁰.

Icons of the world wide web, YouTube, and Tumblr

It is impossible for legacy solutions to constantly screen through every website, every webpage, and every single piece of content on each webpage to build an updated database. It is equally impossible for busy IT staff to compensate for the shortcomings of these legacy solutions.


For example, legacy solutions cannot differentiate between "how to weed your garden" and "how to grow weed in your garden." Schools can use legacy solutions to block the keyword "weed," but that causes over-blocking.

Instructional teams leverage the internet to find and share many educational resources, especially YouTube videos. Bound by legacy solutions' limitations, schools sometimes have no choice but to over-block YouTube by blocking the platform entirely if too many incidents occur. Over-blocking leaves teachers scrambling to find alternative resources.

Under-blocking is an even more common problem than over-blocking. Besides YouTube, teachers often rely on Google Sites that other educators create as valuable resources. However, many enterprising students create their own Google Sites to share for fun. Student-created Google Sites often list new game URLs that have yet to be added to the blocked list by legacy solutions or the district's overloaded IT staff. As a result, students waste hours every week sneaking off to play games instead of focusing on assigned digital lesson content.


IT staff have two options in dealing with Google Sites using legacy solutions.


One option is to block the entire Google Site domain so that no Google Sites can be accessed by default. If any teacher wanted to use an educational Google Site in class, that teacher would put in an IT ticket to request certain Google Sites be put on the allowed list temporarily or permanently. No matter the size of the IT department, it is humanly unfeasible for the IT team to manually add all the requested Google Sites to the allowed list in response to over-blocking the Google Sites domain.


Another option is to allow the Google Sites domain by default. This approach causes under-blocking since it allows students and teachers to access all Google Sites unless those Google Sites are added to the blocked list. In this case, the IT team is still overwhelmed with manually adding new URLs and Google Sites to the blocked list.


Legacy solutions that use keyword blocking only help minimally to solve the under-blocking problem. Keyword blocking usually misses Google Sites with embedded games because the keyword "game" likely does not appear anywhere on the webpage.


Even more difficult for legacy solutions to detect are games embedded directly in the Google search engine. The keyword "game" does not need to be part of the search query for embedded games to show up on Google search results. For instance, legacy solutions cannot see the nuance between "play snake," which shows a snake game hosted directly on the search engine results page, and "play with your pet snake," which results in links to caring for an exotic pet.

Comparison of two web search results pages of "play snake" and "play with pet snake"

Hardly any school district will block the Google search engine. Students are encouraged to explore the internet by their teachers. Using the internet is almost synonymous with using search engines. Unlike the YouTube and Google Sites problems, IT staff can only tackle the search engine problem with legacy solutions by under-blocking.

Under-blocking is the reality for most schools, as digital instruction is now integral to the learning process. Students write essays in Google Docs, create research presentations on PowerPoint online, collaborate with teachers using Learning Management Systems, and take assessments directly through their browsers.

Nevertheless, the vast majority of educators need to realize the extent of how digitally distracted their students are or what they are distracted by when students use the schools’ digital devices. Legacy solutions cannot provide visibility into students' engagement levels during digital instruction because legacy solutions can only evaluate content based on the domain, URL, and at best, keywords.


Forward-thinking schools know there is a need to use AI technology in real time to solve the student engagement problem by automatically redirecting students to their digital curriculum.

Real-time artificial intelligence drastically reduces the amount of manual labor required to maintain blocked lists and allowed lists since AI accurately identifies digital distractions and automatically removes them.

Comparison of what legacy filter solutions can and cannot handle.

Finding a solution

There is only one solution that uses real-time AI across its products to defeat digital distractions and improve the effectiveness of digital learning – Deledao ActiveInsights™.


To better understand how real-time AI helps students stay engaged and learn, Deledao embarked on a study of over 1,000 students from multiple school districts that participated in four-week pilots across the country.

Since these schools have never used solutions employing real-time AI technologies, results from the Deledao Pilot Case Study best show the Deledao solution's impact on students. For the first time, schools guided students in digital instruction with the help of patented Deledao AI technologies: InstantAI™, GameChanger™, and MediaMonitor™. The Deledao Pilot Case Study uncovered detailed insights into student engagement in a digital environment.​

Considering the evidence from academic research, it is no surprise that data from the Deledao Case Pilot Study confirms that most students are distracted on their school-issued digital devices – 94% of students struggle to stay focused online!

Students handle digital distractions differently according to their ability to resist temptation. Based on patterns of their online behaviors, three groupings of students emerged:

  • Self-Directed Students

  • Semi-Distracted Students

  • Easily Distracted Students

Types of students using digital devices: Self-Directed, Semi-Distracted, Easily Distracted

The Self-Directed students did not attempt to go off task online at all during the four-week pilot. These students are self-motivated, focused, and do not need help to stay on task.

The Semi-Distracted students attempted to go off task on some weeks but not every week during the pilot. These students need reminders to get back on task but otherwise have some self-control.

The Easily Distracted students attempted to go off task online every week during the four-week pilot. These students will get distracted no matter the circumstances. They likely struggle with self-regulation in an offline environment as well. They may be even more susceptible to distraction in a digital environment due to the myriad of opportunities for distraction.

The Semi-Distracted and Easily Distracted students composed 94% of all digitally distracted students.


What is driving students to go off task on their devices?

The top five digital distractions are ordered below:
  1. Games

  2. Social media

  3. Streaming media (e.g. YouTube)

  4. Shopping

  5. Entertainment

Graph showing the top five digital distractions: Gaming, social media, streaming media, shopping, and entertainment, in that order.

If gaming was not already a top concern for district administrators, it should be. The online games category is the number one digital distraction by far. Data from the study shows that 82% of students are distracted by games.

Not only are the majority of students distracted by games, but also games are the most addictive and distracting of all the categories. In the first week of their pilots, students attempted to access gaming-related activities 10x more often than sneaking off to check social media, the second most popular digital distraction. In the entire four weeks, students attempted to access gaming-related content almost 3x as often as attempting to access social media distractions.

Gaming is the number one category that legacy content filters fail to detect and block. In the Deledao Pilot Case Study, the Deledao solution blocked 159% more game-related distractions than other filters due to the use of AI technologies proprietary to Deledao: InstantAI™, GameChanger™, and MediaMonitor™. For context, the Deledao solution typically removes at least 60% more digital distractions than other leading content filters in head-to-head comparisons.


The overall trend of how digital distractions affect student engagement is primarily determined by student behavior regarding gaming distractions.


Legacy solutions struggle to evaluate Google Sites, the Google search engine, and YouTube due to their reliance on outdated domain, URL, and keyword-blocking techniques. In contrast, Deledao is uniquely positioned to solve gaming distractions on the modern web. Deledao uses InstantAI™, GameChanger™, and MediaMonitor™ technologies across its products to screen online content in real time and steer students back to learning.

InstantAI™ uses AI in real time to review every piece of text, image, and video like a human does. Content is assessed based on context rather than keywords. The previous example of the search queries "play snake" and "play with your pet snake" is handled by InstantAI™ differently.

InstantAI™ recognizes that "play snake" results in the embedded snake game as well as links to the snake game on other websites. In response, InstantAI™ blocks the search engine results for "play snake" according to school policies blocking the gaming category. InstantAI™ understands that "play with your pet snake" shows content related to pet reptiles, which may be for a research project or even curiosity. Consequently, InstantAI™ will allow this search engine results page to be shown.

A student is gaming on his laptop but the Deledao software is stopping his gaming.

The GameChanger™ AI technology tackles the challenge of embedded games on Google Sites while InstantAI™ scans for text, images, and video at the same time. When Deledao detects certain mouse and keyboard movements indicative of gameplay, GameChanger™ activates to block the Google Site webpage that has the embedded game. The rest of the Google Site remains accessible as long as no other games are on the other pages.

The same concept applies to full-screen games. If students start playing previously unblocked full-screen games, that behavior triggers GameChanger™ to shut down the gaming distraction and send students back to work.​

Another layer to the gaming distraction problem is that students love to watch videos of others playing games. Just think of how popular e-sports has become. Students of all ages are captivated by watching YouTube and Twitch personalities play their favorite games.

MediaMonitor™ is the proprietary real-time AI technology Deledao uses to handle social media such as YouTube and Twitch. Working with InstantAI™, MediaMonitor™ catches students distracted by gaming videos and stops them from going down rabbit holes on streaming media.

Deledao MediaMonitor is scanning YouTube comments, the video frame by frame, and the video suggestions.

​​Schools that use legacy solutions are fighting a losing battle against gaming distractions. Student engagement in a digital world depends on real-time AI.


Deledao enables teachers and IT staff to use their time more effectively. IT staff have more important things to do than to tediously update blocked and allowed lists with endless domains, URLs, and keywords. Teachers also regain access to digital resources for their curriculum needs.

More importantly, the Deledao Pilot Case Study revealed positive signs of student engagement. By the end of four weeks, 42% of students completely stopped their attempts to access gaming distractions!


Trends related to gaming distractions generally dictate the trends of overall digital distractions. Changes in gaming distraction trends are significant indicators of student engagement levels in classrooms integrated with digital instruction.


After digging deeper into the data, it turns out that the Deledao ActiveInsights™ solution had more of a positive impact than the data first suggested.


In the context of students distracted by gaming in the Deledao Pilot Case Study, the breakout of the three types of students is as follows:

  • Self-Directed Students: 18%

  • Semi-Distracted Students: 42%

  • Easily Distracted Students: 40%

Donut wheel chart showing the breakout of student behaviors on digital devices.

Considering that Self-Directed students can already resist gaming distractions without extra help, the efficacy of Deledao can only be measured in terms of its impact on the Semi-Distracted and Easily Distracted students. These distracted students add up to 82% of the total student population.


At first, it seems that Deledao helps Semi-Distracted students and Easily Distracted students in different ways.

Because Semi-Distracted students have more flexible behavior patterns, Deledao helped Semi-Distracted students develop self-regulation skills. At the end of four weeks, the entire group of Semi-Distracted students completely stopped their attempts to go off task due to gaming distractions. Since Semi-Distracted students compose 42% of the overall student population in the study, it is easily seen that 42% of students have learned self-regulation skills to help keep themselves engaged in learning.

Bar graph showing that by week 4, 42% of students completely stopped trying to go off task online.

The Easily Distracted students have more predictable behavior patterns in that they cannot help themselves but give in to digital distractions. They feel compelled to continuously try and go off task even though Deledao prevents them from succeeding.


However, further analysis revealed that the Easily Distracted students also developed self-regulation skills. While they still tried to go off task, Easily Distracted students drastically cut down on trying to play games or watch gaming videos. By the end of the four weeks, they reduced more than half of their attempts to access blocked gaming content!

Graph showing the three types of students and their definitions: Self-Directed, Semi-Distracted, and Easily Distracted.

The Conclusion

The significance of students stopping themselves from accessing distracting content is monumental. It shows a strong signal that students can learn to become self-directed with the right encouragement and conditions (i.e., under the guidance of educators using Deledao ActiveInsights™).

Like how educators aim to teach students how to be critical thinkers instead of what to think, an effective solution to the digital distraction problem helps educators empower students to stay engaged on their own. Once students leave the K-12 education system and become adults, they must learn how to navigate an increasingly digital world as positive, productive digital citizens without any tool or teacher supervising their behavior.


Deledao uniquely enables teachers to employ guided practice or the Gradual Release of Responsibility in digital learning environments. The Deledao ActiveInsights™ solution provides flexible guardrails that facilitate teachers to customize classroom policies to meet students where students are.

Graph showing how teachers and students can use the model of gradual release of responsibility with Deledao to build self-regulation skills.
  1. Teachers do it, and students watch

    • ​Schools use Deledao to block digital distractions automatically.

  2. ​Teachers lead, and students participate

    • ​Teachers use Deledao to assign digital lesson content.

  3. ​Students lead, and teachers guide

    • ​Students choose to engage in digital curriculum over digital distractions.

  4. ​Students do it alone

    • ​Students leave the K-12 system as adults with self-regulation skills.

Classroom management in the age of integrated digital instruction is only as good as the automatic processes set in place to get students back on task. Using patented InstantAI™, GameChanger™, and MediaMonitor™ AI technologies, Deledao ActiveInsights™ enables teachers to focus on teaching instead of policing students.


Deledao offers visibility into student behavior that legacy solutions cannot provide. Along with better data, Deledao enables educators to empower students to take charge of their learning and stay engaged in the modern classroom.


With Deledao assisting instructional teams to improve student engagement in the battle against digital distractions, school districts can look forward to seeing the Nation's Report Card showing academic gains again.

Want to see the results for yourself?

Request a demo and run a free pilot program with us!



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3. Bushweller, Kevin. “What the Massive Shift to 1-to-1 Computing Means for Schools, in Charts.” Education Week, Education Week, 17 May 2022,

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5. Hall, Amanda C.G., et al. “On or off Task: The Negative Influence of Laptops on Neighboring Students’ Learning Depends on How They Are Used.” Computers & Education, vol. 153, 2020, p. 103901.,

6. Dontre, Alexander J. “The Influence of Technology on Academic Distraction: A Review.” Human Behavior and Emerging Technologies, vol. 3, no. 3, 2020, pp. 379–390.,

7. Bylieva, Daria, et al. “Self-Regulation in e-Learning Environment.” Education Sciences, vol. 11, no. 12, 2021, p. 785.,

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