Quiz Design Customization

via “customizable game settings”

I used to play the Wikipedia Game in high school and had an idea for applying the same mechanic of clicking from concept to concept to LLMs.Will post another version that runs with an LLM entirely in the browser soon, but for now, please enjoy as long as my credits last...Warning: the LLM does not a

Unique: Features a highly flexible modular system that allows for extensive customization, unlike many trivia games that offer only fixed settings.

vs others: More adaptable than competitors that provide limited or no customization options.

via “quiz-design-customization”

via “question-type customization”

via “quiz-customization-and-editing”

via “customizable quiz template system with format flexibility”

Unique: Combines AI-generated content with template-based customization, allowing users to generate questions and then apply them to pre-configured assessment structures without manual formatting

vs others: More flexible than Kahoot's rigid game-show format but less feature-rich than Quizlet's full customization options; bridges gap between speed and control

via “interactive quiz creation and customization”

via “quiz customization and editing”

via “question customization and parameter-driven generation”

Unique: Questgen exposes generation parameters through a UI rather than requiring prompt engineering, making customization accessible to non-technical educators while maintaining flexibility for power users.

vs others: More user-friendly than raw LLM APIs because parameters are pre-defined and validated, but less flexible than programmatic APIs because custom logic requires UI interaction rather than code.

via “customizable game session configuration and rule enforcement”

Unique: Decouples question generation from game rules, allowing hosts to specify difficulty, topic, and pacing independently while the system generates questions matching those constraints — rather than forcing a one-size-fits-all trivia experience.

vs others: More flexible than pre-built trivia templates because it generates questions to match custom rules rather than forcing users to select from pre-curated question sets with fixed difficulty and topic combinations.

via “content personalization based on educator preferences”

Unique: Attempts to offer personalization without requiring complex learner modeling or student data integration, using simple UI parameters to guide content generation

vs others: Simpler to use than adaptive platforms like DreamBox or ALEKS that require extensive student data, but lacks their evidence-based personalization and learning science foundations

via “customizable-quiz-question-templates”

Unique: Allows pre-generation customization of question types and difficulty before AI generation runs, rather than post-hoc filtering — reduces wasted generation cycles and improves relevance to specified assessment goals

vs others: More flexible than fully automated quiz generation (which produces generic questions) but less powerful than manual quiz authoring tools that support complex branching, adaptive logic, and custom scoring rules

via “adaptive-practice-question-generation”

via “difficulty-level customization”

via “customizable-question-count-specification”