Current Projects
STEAM Longitudinal Research - Administration, Instruction and Student Learning
This project is in the 7 th year of study with my co-collaborator, Dr. Cassie Quigley (University of
Pittsburgh) and several science education and learning sciences students assisting with the
project each year. Working in 6 different school districts in 3 states, we have investigated
STEAM professional development, created a research-based instructional model for STEAM,
studied implementation practices of teachers and student’s ability to collaborate in STEAM
problem solving. The most recent phase of this project involves measuring student
learning/achievement after participating in STEAM units and exploring makerspaces and
making during STEAM problem solving.
Computational Thinking and Collaborative Problem Solving
This project explores how students in grades 3-8 in a variety of public and charter schools in the
greater Pittsburgh area participate and collaborate in computer science focused STEAM
curricula aimed at enhancing computational thinking. The work is funded through an 18-month
PA-Smart Grant in partnership with South Fayette County Schools, Digital Promise and the University
of Pittsburgh. Our team includes learning sciences and science education students from the
College of Education at Clemson and the School of Education at University of Pittsburgh. We
have just finished a year of data collection and analysis with publications forthcoming.
THINKER (Technology-Human Integrated Knowledge Education and Research)
This project is funded through a 5-year, $2,900,000 NSF/NRT grant under the direction of Dr.
Laine Mears at Clemson University and the ICAR campus in Greenville, SC. The focus of this
project is on training multi-hierarchical teams of tech school, undergraduates, masters and PhD
students engineering practices through a variety of project-based challenges. I work with a team
of computer and learning scientists to develop measurements which gauge student’s ability to
collaborate in computer-supported collaborative environments. Our team has just completed our
second year of data collection - observing and interviewing students working in face:face and
online environments.
Automating Benchmark Assessment in Elementary Schools – AI and Running Records
In elementary schools nationwide, assessments are used to assess how children process
continuous text by examining the accuracy and rate at which children read as well as the
sources of information used or neglected. These assessments, referred to commonly by
educators as benchmark assessments, include passages of short fiction and non-fiction text
administered, and then manually scored, from one to four times a year or more for children who
are receiving intervention services. For this project, our team, consisting of Dr. CC Bates
(Associate Professor of Literacy, Clemson), Research Associates at the Watt Center
(https://www.clemson.edu/centers-institutes/watt/about/) and Creative Inquiry undergraduate
students, is using the AI Watson features of speech-to-text to automate the process of running
records as part of benchmark assessments. Phase one of this project involved collecting a large
set of audio files for dialect analysis and then mapping a set of rules for student error and self-
correction in order to determine, with precision, how the AI might work. We hope to pilot the AI
with classroom teachers during the 2020-21 school year. Our intent is to leverage AI speech-to-
text to generate a transcript that teachers can quickly review and use to find students’
appropriate reading level - and thus assist students in finding books they can read and enjoy
while continuing to build fluency and comprehension.
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