This research investigates the role of force feedback in virtual reality training. By comparing users with and without haptic feedback, it examines effects on brain activity, skill acquisition, and real-world performance. The study aims to improve VR training systems by incorporating sensory input essential for effective motor learning and skill transfer.

This study compares systematic versus exploratory search strategies for locating rare plants. Surprisingly, both methods performed equally, with low detection overall. Challenges such as navigation difficulty and multitasking may explain the results. The findings highlight the need for improved search methods to better identify and protect rare, threatened plant species.

This research shows that pauses in information streams alter decision-making. After a break, the brain increases effort, giving greater weight to subsequent information—a “peak-after-break” effect. A computational model explains this as a performance-effort tradeoff. Findings challenge traditional theories and suggest strategic pauses can shape attention, memory, and judgment.

This research develops a new way to measure mathematical language by integrating words, symbols, and graphs. Through experimental tasks, it shows that these skills predict mathematical performance. The findings highlight the importance of teaching connections between representations, with implications for improving mathematics education and understanding how language shapes learning.