Impact: Over 1,500 middle schoolers have learned from our educational games

We have run many studies with the Decimal Point game, applying various Learning Science principles to improve its effectiveness. Over the past 10 years, over 1,500 students have benefited from the Decimal Point learning game and curriculum materials.

We designed and developed the digital learning game Decimal Point to improve middle school students' mastery of math. 

This work led to... 

  • Improved mastery of decimals. Student test scores indicate that participants who learned with the game significantly improved their understanding of decimals and decimal operations.
  • New research on using erroneous examples for learning. The game introduced erroneous example problems – meaning at least one aspect of the decimal problem is incorrect – and this style of prompting students to identify and fix the error(s) led to significant learning benefits.
  • Another learning game, Angle Jungle. This work expanded to see if the design principles that work on Decimal Point can be transferred to Angle Jungle, a game that teaches geometric principles.
  • New work on gender and learning. Decimal Point is a gender neutral game but post tests showed that girls’ scores increased more than boys’ scores. We are now exploring the effectiveness of design principles and gender-based learning differences.
     

Supported by:

  • National Science Foundation (NSF), EHR Core Research (ECR).  PIs: Bruce M. McLaren, Jessica Hammer (Carnegie Mellon University),  J. Elizabeth Richey, (University of Pittsburgh), Ryan Baker (University of Pennsylvania),  Nicole Else-Quest (University of North Carolina), Jon Star (Harvard University), “Collaborative Research: Investigating Gender Differences in Digital Learning Games with Educational Data Mining,”  (CMU Portion: $1,050,243)   Period:  07/01/22 to 06/30/25.  
  • National Science Foundation (NSF), EHR Core Research (ECR). PIs: Bruce M. McLaren, Ryan Baker (University of Pennsylvania), Jon Star (Harvard University), “Collaborative Research: Using Educational Data Mining Techniques to Uncover How and Why Students Learn from Erroneous Examples,”  (CMU Portion: $914,042)  Period:  06/01/17 to 12/31/22.   (See the NSF Award Announcement;  Read the CMU HCII article about this grant)
  • National Science Foundation (NSF), Transforming STEM Learning (TSL), Award No: DRL-1238619.  PI: Bruce M. McLaren,  Co-PI: Jodi Forlizzi,  “Enhancing Mathematics Education with Educational Games: Can Erroneous Examples Help?”   ($510,518).   Period:  10/01/12 to 03/31/15.  (See the NSF Award Announcement)

Timing:  This work has been going on for over a decade.

Related work: 

Researchers:  Bruce M. McLaren, Jessica Hammer, Jodi Forlizzi 

Research Areas:  Learning Sciences and Educational Technologies, Games & Play 

 

Looking at Additional HCII Impacts...

Nesra sits at a NoRILLA table and reaches for a tower of blocks

NoRILLA Interactive Mixed-Reality Science for Kids

Our novel, mixed-reality intelligent science stations bridge the physical and virtual worlds. Millions of children and families across the US are learning more science and improving their critical thinking skills after predicting, observing and explaining experiments with our patented system at their schools and museums.

screenshot of the game Anti-Phishing Phil, named after an orange fish in an underwater world that helps players to learn more about phishing

Protecting Millions of People from Phishing Scams

We studied the social aspects of phishing attacks and protected millions of people through education and training. This work led to new educational methods to raise awareness, effective anti-phishing warnings, and algorithmic detection of phishing attacks.

PrivacyGrade

Grading Your Smartphone Apps on Their Privacy Practices

We created a model that analyzed over 1 million smartphone apps on their privacy and data collection practices, and then assigned them a public-facing privacy grade. This easy-to-follow grading system raised public awareness and led to improved privacy practices from several app developers.

hands interacting with a black touch screen with labeled inputs of fingernail, knuckle and pad

TapSense Improved Touch Detection on Millions of Smartphones

We trained smartphones to reliably detect four different touchscreen inputs – for example, a tap by a finger pad as compared to a knuckle – which created opportunities for new interactions and features.

screenshot from PAT, a cognitive tutor for algebra

Millions Learned More Math with Our AI Tutor

Millions of middle school and high school students across the US have learned more math as a result of our decades of work with AI-based cognitive tutoring systems.

proposed data label for IoT devices, modeled after a nutritional label

Human-Centered Privacy for the Internet of Things

As more gadgets become “smart” things and the Internet of Things (IoT) expands to tens of billions of connected devices, we want consumers to be aware of what their devices are doing with their personal data.

decimal point game map

Improved Math Mastery with the Decimal Point Game

We explored the learning analytics behind our digital learning game to see how student learning responds to curriculum changes to the game. Over the past 10 years, over 1,500 students have benefited from the Decimal Point game and curriculum materials.

Zensors airport queue screenshot

Zensors Turns Cameras Into Smart Sensors

In one application installed at the Pittsburgh International Airport in 2019, Zensors use existing cameras as powerful general-purpose sensors to provide wait time estimates for the security line, which benefits almost 10M PIT travelers per year.