Welcome to Synergy! Enhancing classroom collaboration and performance by creating optimized student groups under the UWCSEA 50th anniversary innovation grant. Synergy uses an algorithm to generate well-balanced and diverse groups based on students' personality traits. The project aims to support teachers in fostering a productive and inclusive learning environment for all students.
- Frontend: React.js
- Backend: Node.js, Express
- Database: MongoDB
- UWCSEA CIMS System (REST API)
Synergy uses an innovative algorithm to create optimized groups of students based on their personality traits derived from the Post-Jungian (PJ) personality theory. The PJ personality theory is an extension of Carl Jung's psychological types and consists of four dimensions:
- SN (Sensing vs Intuition)
- TF (Thinking vs Feeling)
- EI (Extroversion vs Introversion)
- PJ (Perception vs Judgment)
Students complete a 20-question personality quiz, with answers ranging from 1 to 4. These answers are then mapped to a four-dimensional vector based on the PJ personality theory dimensions. The personality vectors of all students in a class are used by the algorithm to compute k-sized groups that optimize the utility function.
The algorithm creates groups based on the following principles:
- Cognitive Diversity: Values teams with diverse SN (Sensing vs Intuition) and TF (Thinking vs Feeling) personality dimensions.
- Leadership: Values teams with at least one ETJ agent (the leader).
- Introversion: Values teams with at least one introvert.
- Gender Balance: Values teams with a strong gender balance.
The algorithm computes the optimal partition of a class of students to maximize the product of utility functions of each individual group. Instead of using a brute force method, Synergy employs a greedy algorithm that quickly finds an initial solution and repeatedly improves it through crossover operations. This results in a 99.6% average optimality ratio and a 0.267% average time ratio compared to the brute force method.
Synergy is available as an easy-to-use web application that offers the following features:
- Simple form for teachers to input their class code, teacher code, and desired group size (k).
- Option for teachers to specify students who must or must not be in the same group.
- Integration with the UWCSEA CIMS system for seamless access to student data.
- Built-in form for students to complete the personality quiz based on the Post-Jungian (PJ) personality theory.
- Secure storage of students' personality data in a MongoDB database.
Synergy has been tested in real-world classroom settings and demonstrated significant improvement in group performance compared to self-selected and randomized groups. On average, groups formed by our algorithm performed 35.9% better than self-selected groups.
This project is licensed under the MIT License - see the LICENSE file for details.
We are exploring additional enhancements to Synergy, such as:
- Creating an easy-to-use webapp for teachers to utilise the algorithm
- Incorporating the Five Factor Model (FFM) for personality assessment.
- Enabling students to provide names of preferred team members.
- Taking student grades and other performance metrics into account.
- Momani & Stirk (Diversity Dividend Canada’s Global Advantage)
- Nathan & Lee (Cultural Diversity, Innovation, and Entrepreneurship)
- Tolsma et al. (Who Is Bullying Whom in Ethnically Diverse Primary Schools?)
- Jimerson (Advancing Diversity, Equity, and Inclusion in School Psychology)
- Judge et al. (Personality and Leadership: A Qualitative and Quantitative Review)
- Andrejczuk et al. (Synergistic Team Composition: A Computational Approach to Foster Diversity in Teams)
- Rands & Gansemer-Topf (The Room Itself Is Active: How Classroom Design Impacts Student Engagement)
- Barbuto (A Critique of the Myers-Briggs Type Indicator and Its Operationalization of Carl Jung’s Psychological Types)