Adaptive Learning

Gaming’s Role in Adaptive Learning

The current US education system is founded on the principle of continuous learning and development during the crucial stages of cognitive and personal growth. It operates on the expectation that to advance to each new level, students must demonstrate proficiency at the previous level (or grade). Each level serves as a foundation for the next, creating a base upon which further learning is built.

Until the COVID-19 pandemic, there was a consistent increase in reading and mathematics scores in the US since the 1990s. This improvement can be attributed to technological advances and a shift in teaching methods to align more closely with the ways children process and access information, namely through multimodal learning (eLearning Industry).

Between 2020 and 2022, there was a significant decline in reading and math aptitude; over this period there was the largest decline in reading scores since 1990 and the first-ever decrease in math scores.

The main factor distinguishing low-performing and high-performing students was access to an internet-connected device. Among lower-performing students (below the 25th percentile), 58% had a computer or tablet, and 26% had occasional access to high-speed internet. In contrast, 83% of higher-performing students (at or above the 75th percentile) had a computer or tablet, and 43% had access to high-speed internet (NCES). While another large factor was access to support from a teacher every day or almost every day, given the social distancing rules at the time, this was realistically only accessible through an internet-enabled device.

We believe that increasing the accessibility of technology and high-speed internet is crucial to reducing educational inequity. As we have highlighted before, gaming has the potential to be a compelling delivery mechanism for education. In addition to being creative, dynamic, and fun, expanding access to one-on-one tutoring can further support educational growth.

Gaming: Bloom’s 2 Sigma Solution

In 1984, Benjamin Bloom published in The Educational Researcher that the average student tutored one-on-one using “mastery learning techniques” outperformed those educated in a traditional classroom environment by two standard deviations (i.e., two sigmas).

Mastery learning encompasses the following elements (Teaching Experiment Academy):

• Baseline or diagnostic testing
• Clear learning objectives, organized into units that typically increase in difficulty
• An educational unit is any organized activity that is assessed and is associated with credits (in practice, these are usually courses, but internships and seminars are also considered to be educational units)
• Participation in educational activities (e.g., deliberate practice of skills, performing calculations, interpreting data, reading) aimed at achieving the objectives
• A defined minimum passing standard (e.g., test score) for each educational unit
• Formative testing to assess completion of a unit at a pre-set minimum passing standard for mastery
• Progression to the following educational unit upon achieving measured performance at or above the mastery standard
• Continued practice or study in an educational unit until the mastery standard is met

The primary challenge in implementing this approach is that one-on-one tutoring faces two primary obstacles: it is cost-prohibitive and difficult to personalize at scale. This challenge is where we see the potential of gaming to play a pivotal role in devising a solution that aligns with Benjamin Bloom's theory.

Adaptive Difficulty in Gaming

As we have theorized in the past, gaming’s strength in education is to be dynamic and personalized to the end user yet scalable in delivery. This concept is already an applied feature in games, called adaptive difficulty, and has been used for decades.

Adaptive difficulty in games refers to a design mechanism where the game automatically adjusts its difficulty level in response to the player's performance. This concept aims to create a more personalized gaming experience that keeps players engaged and challenged optimally. Here's how it works:

• Tracking Player Metrics: The system meticulously records a range of performance indicators for players. These metrics might encompass the frequency of player deaths, the speed of level completion, shooting accuracy, or the achievement of specific goals.
• Dynamic Difficulty Adjustment: Based on the performance metrics collected, the game intelligently modifies its difficulty setting. Should a player encounter difficulties in particular sections or with specific game elements, the difficulty level might be reduced to maintain enjoyment and avert player frustration. On the flip side, for players navigating the game with ease, the difficulty could be ramped up to keep them engaged and presented with a consistent challenge.
• Optimizing Challenge and Engagement: The fundamental aim of implementing adaptive difficulty is to find an optimal balance. The objective is to avoid creating a game experience that is overly challenging and frustrating or too simple and unengaging. By continually adjusting, the game aspires to sustain a player's flow state, characterized by deep immersion and a rewarding sense of joy from game interactions.
• Adaptive Difficulty Techniques: The approach to adaptive difficulty varies across games. Techniques can include modifying the quantity and strength of adversaries, tweaking their health or damage output, altering resource availability, or changing other aspects of game dynamics to align with the player’s demonstrated skill level and progression.

The difference between incremental difficulty and adaptive difficulty is important because adaptive difficulty automatically adjusts to the player as they either struggle or progress. A game with incremental difficulty will only change in difficulty after predefined time intervals.

Adaptive Education

Adaptive difficulty, while a complex process, has proven in different studies to produce higher learning outcomes than educational games with incremental difficulty adjustments. According to a 2013 study, “[A] game incorporating adaptive difficulty adjustment produced significantly higher learning outcomes than the equivalent game with incremental difficulty adjustment and the written activity.” (ScienceDirect)

Adaptive difficulty faces hurdles as the number of players or users grows, necessitating increased personalization rather than relying on pre-set milestones to adjust difficulty. This includes the capability to dial back and revert to easier levels if a user encounters difficulties. Another challenge is pinpointing exactly where a user finds the material challenging, requiring a more deliberate approach to modifications. For instance, if an elementary student excels in addition but has trouble with negative numbers, the system should adjust the difficulty level specifically for positive or negative numbers rather than concentrating on the fundamentals of addition.

Every learner brings a unique set of skills and preferences to the table despite being educated through a uniform curriculum. This discrepancy can lead to some students lagging or being held back from progressing at their natural pace. Implementing an adaptive, game-based learning strategy can provide a tailored educational journey for each student, aligning with their individual learning styles and facilitating a more personalized route to mastery.

Takeaway: Benjamin Bloom's 1984 research published that individualized tutoring using mastery learning far exceeds the efficacy of traditional teaching. This method's key elements - such as diagnostic tests, clear objectives, educational activities, minimum standards, formative testing, and mastery-based progression - face challenges in cost and personalization at scale for the average modern student to best mimic one-on-one tutoring. Gaming represents a transformative force, with its history of adaptive difficulty which can provide personalized, dynamic learning paths. By adjusting to a student's performance to maintain optimal engagement and challenge, this approach offers a scalable, cost-efficient way to personalize education, aligning closely with Bloom's vision.