TY - GEN
T1 - Secure Education and Learning Research at Scale with OpenStax Kinetic
AU - Basu Mallick, Debshila
AU - Bradford, Brittany C.
AU - Baraniuk, Richard
N1 - Funding Information:
The research reported here was supported by the Institute of Education Sciences, U.S. Department of Education, through Grant
Publisher Copyright:
© 2023 ACM.
PY - 2023/7/20
Y1 - 2023/7/20
N2 - OpenStax Kinetic is an innovative research infrastructure that aims to transform education and learning research in the digital age. With its access to large sample sizes, authentic learning environments, experimental control, scalability, security and privacy protection, Kinetic provides an unparalleled opportunity for researchers to study the complex interactions between different factors in digital learning environments. This versatile platform utilizes Qualtrics and can support various research designs, including correlational, longitudinal, and interventional studies. Kinetic's unique privacy-by-design implementation via secure enclaves ensures that researchers can analyze fully-identified data without compromising data security and privacy as well as affords greater analytical reproducibility. The findings from Kinetic can inform educational interventions and strategies to enhance student success in digital learning environments. Kinetic has the potential to significantly advance education and learning research by improving pedagogies, practices, and policies in education and learning sciences. In this demo of Kinetic, researchers will be able to interact with the test instance of the Kinetic system online and view the learner experience. All researchers will be able to engage in the experience of creating a study, releasing a study, and interacting with our implementation of secure enclaves for data analysis.
AB - OpenStax Kinetic is an innovative research infrastructure that aims to transform education and learning research in the digital age. With its access to large sample sizes, authentic learning environments, experimental control, scalability, security and privacy protection, Kinetic provides an unparalleled opportunity for researchers to study the complex interactions between different factors in digital learning environments. This versatile platform utilizes Qualtrics and can support various research designs, including correlational, longitudinal, and interventional studies. Kinetic's unique privacy-by-design implementation via secure enclaves ensures that researchers can analyze fully-identified data without compromising data security and privacy as well as affords greater analytical reproducibility. The findings from Kinetic can inform educational interventions and strategies to enhance student success in digital learning environments. Kinetic has the potential to significantly advance education and learning research by improving pedagogies, practices, and policies in education and learning sciences. In this demo of Kinetic, researchers will be able to interact with the test instance of the Kinetic system online and view the learner experience. All researchers will be able to engage in the experience of creating a study, releasing a study, and interacting with our implementation of secure enclaves for data analysis.
KW - adult learning
KW - digital learning platform
KW - digital learning research
KW - education R&D
KW - research methods at scale
UR - http://www.scopus.com/inward/record.url?scp=85167864516&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85167864516&partnerID=8YFLogxK
U2 - 10.1145/3573051.3596187
DO - 10.1145/3573051.3596187
M3 - Conference contribution
AN - SCOPUS:85167864516
T3 - L@S 2023 - Proceedings of the 10th ACM Conference on Learning @ Scale
SP - 360
EP - 362
BT - L@S 2023 - Proceedings of the 10th ACM Conference on Learning @ Scale
PB - Association for Computing Machinery, Inc
T2 - 10th ACM Conference on Learning @ Scale, L@S 2023
Y2 - 20 July 2023 through 22 July 2023
ER -