Danielle Alexander
Papers
1
Total Citations
1
H-Index
1
About
Danielle Alexander is a pioneering researcher at the intersection of educational technology, human-robot interaction, and STEM pedagogy. Her work centers on understanding how social robots can transform early childhood learning, particularly in vocabulary acquisition and engagement with science, technology, engineering, and math. In her most cited study, “If a Robot was Teaching, Then Everybody Would Definitely Like School Better,” Alexander conducted a qualitative analysis of 20 children in grades 3-5, using semi-structured interviews to capture their perceptions of learning STEM vocabulary with an educational social robot. This work, published in 2024, has already garnered 1 citation, highlighting its emerging impact. Alexander’s major contribution lies in bridging developmental psychology and robotics, demonstrating that social robots can foster positive attitudes toward STEM learning. Her findings offer critical insights for designing inclusive, child-centered educational tools, and her methodological rigor—employing detailed transcription and talk-turn analysis—sets a standard for qualitative research in human-robot interaction. As a rising voice in her field, Alexander’s research promises to shape future curricula and inspire new generations of learners.
Research Focus
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Top Papers
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