Behavioural Research Technology
Online Problem-Solving Game | Behavioural Research & Data
Executive Summary
Discover how our online problem-solving game tracks decision-making, cognitive biases, and strategy adaptation with real-time data for behavioural research.
A client required a custom-built online problem-solving game to study behavioural strategies in decision-making under rule-based constraints. The objective was to track decision-making processes, adaptation strategies, and problem-solving efficiency in real time. Traditional research methods did not allow for real-time tracking, structured constraints, or precise data collection, making it difficult to analyse problem-solving behaviours with accuracy.
Our team developed a solution that incorporated a real-time data logging system, structured experimental controls, and a customisable framework. This approach ensured scientific accuracy while maintaining participant engagement. The game enforced strict sequential painting rules, introduced adaptive difficulty levels, and provided comprehensive error tracking and analytics. This platform now enables researchers to study problem-solving efficiency, cognitive biases, and decision-making processes in a structured manner.
The Client and Their Challenges
The client wanted to develop an interactive gaming platform to analyse problem-solving strategies within a controlled research environment. Their primary focus involved tracking decision-making approaches rather than conducting cognitive psychology research.
Several challenges required solutions. The platform needed strict rule enforcement and structured constraints to maintain experimental accuracy. The system had to log user actions, response times, and rule violations with millisecond precision. The game had to adapt dynamically, introducing new constraints to measure how users adjusted their strategies. Additionally, researchers needed to balance participant engagement with research integrity to maintain user involvement without compromising scientific validity. The system also had to support between 100 and 300 concurrent users without performance degradation.
Project Details
The project involved the development of a web-based research platform utilising Angular for the front end, Django for the back end, and PostgreSQL as the database. The development process lasted from March 2021 to October 2021, with the budget structured for affordability and scalability.
The client selected our team due to our expertise in behavioural analytics and research-based gaming applications. Our ability to deliver a customisable, structured, and data-driven solution with real-time tracking, rule-based constraints, and dynamic game features played a key role in their decision.
Aspect | Details |
Service | Web-Based Research Platform |
Technology | Frontend: Angular Backend: Django Database: PostgreSQL |
Duration | March 2021 – October 2021 |
Budget | Designed for affordability and scalability |
The Solutions
Our team implemented several key solutions to address the client’s challenges. We introduced a real-time tracking and data logging system to capture every user action, including decision-making patterns, response times, and rule violations. This system logged behavioural data with millisecond precision, enabling in-depth analysis of problem-solving efficiency and strategy shifts. See Our Services
We enforced structured experimental rules and constraints throughout the game. A sequential painting rule ensured that users could only colour cells in a structured order. The game introduced three key constraints: each of the three colours had to be used exactly four times, prime-numbered cells could not be painted yellow, and within groups of four cells, the second and fourth cell had to share a colour.
We incorporated adaptive difficulty levels to enhance the experimental framework. In the second round, the game introduced an additional constraint that prohibited blue on numbers divisible by three. This feature allowed researchers to monitor how users adjusted their problem-solving techniques in response to evolving constraints.
To gather structured participant feedback, we included a post-game survey. Likert-scale questions measured difficulty levels, time constraints, and view preferences. This survey provided insights into how users perceived their strategy success and overall performance.
We designed a scalable and modular system to accommodate between 100 and 300 concurrent users. The system ensured minimal latency, comprehensive error tracking, and real-time feedback, providing researchers with a seamless and reliable experience.
Technology and Stack Benefits
Our team built the front end using Angular, which provided a dynamic and responsive user interface. The back end utilised Django and the Django REST Framework, enabling real-time data collection and processing. PostgreSQL served as the database, efficiently storing and organising large-scale research data for analysis.
We implemented several key features. Real-time rule enforcement prevented invalid moves and ensured that game constraints remained intact. Advanced behavioural data logging tracked errors, response times, and decision-making sequences. Sequential problem-solving mechanics required users to complete the puzzle cell by cell, preventing them from skipping ahead. The game also provided three interactive views, enabling users to switch between one-cell, foursome, and whole-shape perspectives. Post-game analytics and reporting functions allowed researchers to export structured game data for further analysis.
The Results
The system achieved highly accurate data collection, logging all strategy shifts and response times. It captured rule violations and adaptation patterns, providing detailed insights into decision-making processes. Research accuracy improved significantly, as the platform tracked every user interaction with millisecond precision. The structured experimental conditions ensured compliance and prevented deviations.
The user-friendly interface led to increased participant engagement and retention, contributing to higher-quality data collection. The modular design allowed researchers to easily adapt the platform for future studies, supporting cross-disciplinary investigations into behavioural science and problem-solving strategies.
Lessons Learned
Several key lessons emerged from the development process. The user interface played a crucial role in data quality, as a structured and intuitive design helped participants remain engaged and make clear, measurable decisions. Real-time logging significantly enhanced research accuracy, as millisecond-level tracking improved insights into decision-making and behavioural analysis. The modular system design enabled future research, allowing researchers to update and extend study parameters with ease. The choice of technology proved critical for performance, as Django and Angular provided a high-speed, reliable platform capable of supporting hundreds of concurrent users.
Next Steps
Future development plans include implementing AI-driven behavioural insights to analyse decision-making strategies in real time. We also aim to introduce extended adaptive difficulty mechanisms that develop dynamic puzzle challenges to measure long-term learning adaptation. The platform will undergo optimisation for mobile devices, increasing accessibility for participants. Additionally, we plan to expand research on a global scale, enabling participation from diverse demographic groups and broadening the scope of study results.
Conclusion
The Online Problem-Solving Game successfully provided a data-driven experimental platform for studying decision-making strategies under constraints. By integrating real-time tracking, structured constraints, and adaptive difficulty settings, the platform has delivered precise research insights.
With potential applications in education, AI training, UX research, and strategic decision-making, this platform sets a new standard for behavioural science research in problem-solving. Researchers interested in leveraging behavioural analytics for their studies are encouraged to contact us to learn more.
Are you looking to integrate behavioural analytics into your research or develop a custom problem-solving platform? Get in touch with us today to explore how our innovative solutions can support your studies and enhance your insights. Contact us now to discuss your requirements!
WRITTEN BY
March 25, 2025, Product Development Team
Top Categories
- Software Development ................... 6
- AI in Business ................... 5
- Pricing Strategies ................... 3
- Technology ................... 3
- Product Development & AI ................... 3