Timothy J. Nokes‐Malach
Papers
2
Total Citations
10
H-Index
2
About
Timothy J. Nokes-Malach is a leading cognitive scientist whose research lies at the intersection of learning, instruction, and human-robot interaction. His work explores how people learn complex concepts, particularly in STEM domains, and how collaboration—both human-human and human-robot—can enhance that process. A major contribution is his investigation of **collaborative teaching with robot learners**, where he examines how students learn by instructing a teachable robot. His highly cited paper, "Comparison of Lexical Alignment with a Teachable Robot in Human-Robot and Human-Human-Robot Interactions" (2022, 6 citations), reveals how dialogue alignment differs when teaching a robot versus a peer, shedding light on the cognitive mechanisms of interactive learning. Another key study, "It Takes Two: Examining the Effects of Collaborative Teaching of a Robot Learner" (2022, 4 citations), demonstrates that dyadic teaching of a robot can boost learning outcomes. Nokes-Malach’s work has profound implications for designing intelligent tutoring systems and collaborative learning environments. His research is widely recognized for bridging cognitive psychology, education, and artificial intelligence, making him a pivotal figure in the future of adaptive learning technologies.
Research Focus
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Top Papers
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