Abstract
ST Math is a visual instructional game-based program that builds a deep conceptual understanding of mathematics through rigorous learning and creative problem solving. It is widely adopted in many elementary schools in the US. In this paper, we describe the exploratory data analysis we conducted on system log data of kindergarten students to discover patterns in students’ interaction with the system, and to examine productivity and engagement of students with different profiles. The findings informed the implementation of the program in schools as well as improvement of individual games in the program to render more effective student learning.
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Bohrnstedt, G., Kitmitto, S., Ogut, B., Sherman, D., Chan, D.: School composition and the black–white achievement gap (NCES 2015-018). U.S. Department of Education. National Center for Education Statistics, Washington, DC (2015). http://nces.ed.gov/pubsearch. Accessed 24 Sept 2015
Campuzano, L., Dynarski, M., Agodini, R., Rall, K.: Effectiveness of reading and mathematics software products: findings from two student cohorts (NCEE 2009-4041). National Center for Education Evaluation and Regional Assistance, Institute of Education Sciences, U.S. Department of Education, Washington, DC (2009)
Pane, J., Griffin, B.A., McCaffrey, D.F., Karam, R.: Effectiveness of cognitive tutor Algebra I at scale. Educ. Eval. Policy Anal. 36(2), 127–144 (2014)
Pape, S.J., et al.: Classroom connectivity in Algebra I classrooms: results of a randomized control trial (2010)
Roschelle, J., et al.: Integration of technology, curriculum, and professional development for advancing middle school mathematics: three large-scale studies. Am. Educ. Res. J. 47(4), 833–878 (2010)
Roschelle, J., Feng, M., Murphy, R., Mason, C.: Online mathematics homework increases student achievement. AERA Open 2(4) (2016). https://doi.org/10.1177/2332858416673968
Rutherford, T., et al.: A randomized trial of an elementary school mathematics software intervention: spatial-temporal (ST) math. J. Res. Educ. Effectiveness 4, 358–383 (2014). https://doi.org/10.1080/19345747.2013.856978
VanLehn, K.: The relative effectiveness of human tutoring, intelligent tutoring systems, and other tutoring systems. Educ. Psychol. 46(4), 197–221 (2011)
What Works Clearinghouse: WWC intervention report: a summary of findings from a systematic review of the evidence—cognitive tutor. Institute of Education Sciences, US Department of Education, Washington, DC (2016). http://ies.ed.gov/ncee/wwc/pdf/intervention_reports/wwc_cognitivetutor_062116.pdf. Accessed 24 June 2016
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Feng, M., Brenner, D., Coulson, A. (2019). Using Exploratory Data Analysis to Support Implementation and Improvement of Education Technology Product. In: Isotani, S., Millán, E., Ogan, A., Hastings, P., McLaren, B., Luckin, R. (eds) Artificial Intelligence in Education. AIED 2019. Lecture Notes in Computer Science(), vol 11626. Springer, Cham. https://doi.org/10.1007/978-3-030-23207-8_15
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DOI: https://doi.org/10.1007/978-3-030-23207-8_15
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