IJSSER

Title: COMPARING THE EFFECTIVENESS OF AI-POWERED EDUCATIONAL SOFTWARE TO HUMAN TEACHERS
Authors: John Leddo and Khushi Garg
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John Leddo1 and Khushi Garg2 1. director of research at MyEdmaster 2. researcher at MyEdMaster. MyEdMaster, LLC, 13750 Sunrise Valley Drive, Herndon, VA, United States of America
MLA 8 Leddo, John, and Khushi Garg. "COMPARING THE EFFECTIVENESS OF AI-POWERED EDUCATIONAL SOFTWARE TO HUMAN TEACHERS." Int. j. of Social Science and Economic Research, vol. 6, no. 3, Mar. 2021, pp. 953-963, doi:10.46609/IJSSER.2021.v06i03.015. Accessed Mar. 2021. APA 6 Leddo, J., & Garg, K. (2021, March). COMPARING THE EFFECTIVENESS OF AI-POWERED EDUCATIONAL SOFTWARE TO HUMAN TEACHERS. Int. j. of Social Science and Economic Research, 6(3), 953-963. doi:10.46609/IJSSER.2021.v06i03.015 Chicago Leddo, John, and Khushi Garg. "COMPARING THE EFFECTIVENESS OF AI-POWERED EDUCATIONAL SOFTWARE TO HUMAN TEACHERS." Int. j. of Social Science and Economic Research 6, no. 3 (March 2021), 953-963. Accessed March, 2021. doi:10.46609/IJSSER.2021.v06i03.015.
References [1]. Anderson, J.R. (1982). Acquisition of cognitive skill. Psychological Review, 89, 369-405. [2]. Aleven, V., McLaren, B.M., Sewall, J., and Koedinger, K.R. (2006). The Cognitive Tutor Authoring Tools (CTAT): Preliminary Evaluation of Efficiency Gains. Human-Computer Interaction Institute. Pittsburgh, PA: Carnegie Mellon University. [3]. Brna, P., Ohlsson, S. and Pain, H. (1993) (Eds.) Artificial Intelligence in Education. Association for the Advancement of Computers in Education, Charlottesville, USA. [4]. de Kleer, J. and Brown, J.S. (1981). Mental models of physical mechanisms and their acquisition. In J.R. Anderson (Ed.), Cognitive skills and their acquisition. Hillsdale, NJ: Erlbaum. [5]. Garcia, E. and Weiss, E. (2020). A Policy Agenda to Address the Teacher Shortage in U.S. Public Schools. Washington, DC: Economic Policy Institute [6]. Greer, J. (1995) (Ed.) Proceeding of Artificial Intelligent in Education ‘95. Charlottesville, VA: Association for the Advancement of Computing in Education. [7]. Leddo, J., Bisht, D., Narla, E., Saranu, R. and Titov, M. (2016). Using Artificial Intelligence to Enhance the Effectiveness of Multimedia-based Instruction. International Journal of Advanced Education and Research, 1(12), 30-36. [8]. Leddo, J., Boddu, B., Krishnamurthy, S., Yuan, K. and Chippala, S. (2017). The Effectiveness of Self-directed Learning vs. Teacher-led Learning on Gifted and Talented vs. Non-gifted and Talented Students. International Journal of Advanced Educational Research, 2(6), 18-21. [9]. Leddo, J., Guo, Y., Liang, Y., Joshi, R., Liang, I., Guo, W. and Bailey, S. (2019). Artificial Intelligence and Voice-powered Electronic Textbooks. International Journal of Advanced Educational Research, 4(6), 44-49. [10]. Leddo, J. (1994). Did they learn anything?: Finding out with a knowledge assessment tool. Presented at the National School Board Association Technology and Learning Conference. October, 1994. [11]. National Assessment of Educational Progress. (2019). Princeton, NJ: Educational Testing Service. [12]. Quillian, M.R. (1966). Semantic memory. Camridge, MA: Bolt, Beranek and Newman. [13]. Schank, R.C. and Abelson, R.P. (1977). Scripts, Plans, Goals, and Understanding. Hillsdale, NJ: Erlbaum.
Abstract: Current educational assessments report that, nationally, the majority of United States students are performing below grade level (National Assessment of Educational Progress, 2019). Because this trend has been ongoing and there is a current teacher shortage, it seems unlikely that this problem will be rectified in the foreseeable future unless a paradigm shift occurs. The present paper explores the question of whether using artificial intelligence (AI)-powered educational software can effectively stand in for human teachers. High school students were taught the difficult Algebra II topic of dividing complex numbers. Half were taught by active high school math teachers while half were taught by AI-powered software that our team created. Results showed that, on a post-test, students using the AI-powered software scored, on average, 37% higher than those taught by teachers. A closer examination of the data reveals that the distribution of scores of students taught by teachers is rectangular with some performing highly, some performing in the average range and some failing, while most students who were taught by the AI software scored in the A range and no one scored below 70%. Results suggest that our AI software could potentially supplement or stand in for teacher-led instruction with an overall improvement in student performance.

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