ENIGMA: A Web Application for Running Online Artificial Grammar Learning Experiments.

Area of Science:

• Cognitive Science
• Psycholinguistics
• Experimental Psychology

Background:

• Artificial grammar learning (AGL) is crucial for understanding linguistic knowledge acquisition.
• Existing methods for AGL experiments can be limited by time, space, and participant diversity.
• Investigating unconscious and conscious learning processes requires flexible experimental tools.

Purpose of the Study:

• Introduce ENIGMA, a free, web-based tool for online AGL experiments.
• Demonstrate ENIGMA's capability to collect diverse data for L1/L2 acquisition research.
• Provide a practical example of experimental design and data quality assessment using ENIGMA.

Main Methods:

• Developed ENIGMA as a lightweight, user-friendly web application.
• ENIGMA supports visual and aural stimuli with reaction time (RT) measures.
• Tested ENIGMA by partially replicating a previous AGL study.

Main Results:

• ENIGMA is optimized for desktop and mobile devices.
• The tool allows for data collection without temporal or spatial constraints.
• An example study demonstrated the feasibility and quality of data collected via ENIGMA.

Conclusions:

• ENIGMA offers a flexible platform for advancing AGL research.
• The tool can accommodate participants with varied backgrounds and cognitive skills.
• ENIGMA facilitates the study of complex factors in language acquisition and learning.