Implementing a student-centered stroke intervention and prevention education program; evaluating motivation, cognitive load, and performance among middle school students.

Background: In this study, we investigated the association between motivation, cognitive load, difficulty, and performance in a stroke education outreach program implemented for middle school students. Methods: Various interactive instructional activities were developed to engage students throughout the program to assess cognitive and intrinsic load arising from learner implementation of various tasks in a stroke education program for middle school kids. Performance was measured using a post-test to assess knowledge gained by the 6th, 7th, and 8th-grade middle school students. A short questionnaire was also administered to collect data on students' motivation using the ARCS model to asses attention, relevance, confidence, and satisfaction. In addition, we evaluated difficulty level and cognitive load. The relationship between performance and motivation was assessed using Pearson's correlation. Results: In our results, there was no significant difference (p > 0.05) in performance between the 6th, 7th, and 8th-grade students. The difference in performance, cognitive load (mental effort and difficulty), or motivation between the 6th, 7th, and 8 t-grade students was not significant (p > 0.05). The correlation between motivation and performance was significant (r = 0.87, p = 0.001), while the correlation between mental effort and performance was not significant (r = 0.34, p = 0.270). Also, the correlation between difficulty and performance was not significant (r = 0.38, p = 0.361). In the ARCS motivation model, attention, and confidence received the lowest mean scores (3.9), while relevance received the highest score (4.3). Conclusion: Our findings reveal the importance of implementing novel activities to enhance students' motivation to improve performance in the implementation of stroke education outreach programs for middle school students.

Combining partial information from speech and text.

The current study investigated how partial speech and text information, distributed at various interruption rates, is combined to support sentence recognition in quiet. Speech and text stimuli were interrupted by silence and presented unimodally or combined in multimodal conditions. Across all conditions, performance was best at the highest interruption rates. Listeners were able to gain benefit from most multimodal presentations, even when the rate of interruption was mismatched between modalities. Supplementing partial speech with incomplete visual cues can improve sentence intelligibility and compensate for degraded speech in adverse listening conditions. However, individual variability in benefit depends on unimodal performance.