Alan Mc Elroy

Papers

1

Total Citations

4

H-Index

1

About

Alan Mc Elroy is a researcher at the forefront of educational technology, specializing in human-robot interaction and game-based learning. His work explores how humanoid robots, such as Pepper, can be programmed to facilitate engaging, multimodal language instruction. In his most cited study, “Designing and Programming Game-Based Learning with Humanoid Robots: A Case Study of the Multimodal ‘Make or Do’ English Grammar Game with the Pepper Robot” (2022, 4 citations), Mc Elroy demonstrates a novel approach to teaching English grammar by integrating physical robot gestures, speech, and interactive gameplay. This contribution highlights his ability to bridge programming, pedagogy, and robotics, offering a tangible model for how autonomous robots can support personalized learning in classrooms. Though his citation count is still growing, Mc Elroy’s work is notable for its practical, hands-on methodology, providing a blueprint for educators and developers seeking to harness social robots for language acquisition. His research underscores the potential of embodied AI to transform traditional grammar exercises into dynamic, student-centered experiences, positioning him as an emerging voice in the intersection of robotics and education.

Research Focus

Key Achievements

1
H-Index
1
Papers
4
Total Citations
4
Avg Citations/Paper
🏆 Most Cited Paper
DESIGNING AND PROGRAMMING GAME-BASED LEARNING WITH HUMANOID ROBOTS: A CASE STUDY OF THE MULTIMODAL “MAKE OR DO” ENGLISH GRAMMAR GAME WITH THE PEPPER ROBOT
4 citations · 2022
📈 Most Prolific Year: 2022 (1 Papers)
🤝 Key Collaborators: 2

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago