International Journal of Social Science & Economic Research
Submit Paper

Title:
ARTIFICIAL INTELLIGENCE AND VOICE-POWERED ELECTRONIC TEXTBOOKS AND ELECTRONIC BOOKS
Running head: AI and voice-powered e-textbooks and e-books

Authors:
John Leddo

|| ||

John Leddo, Yihao Guo, Yuwei Liang, Dhanush Banka, Rishabh Chhabra, Cole DiManno, Arjun Erasani, Ben Chen, Gayatri Gopavajhala, Jaehee Kim, Kirthi Kumar, Shaan Luthra, Krish Malik, Sadhana Mallemudi, Siddarth Mallemudi, Kapil Manicka, Abhishri Manukonda, Aditya Menachery, Samanvitha Pulugurta, Kashvi Sarayu Ramani, Thomas Rong, Anshul Samant, Anchita Shukla, Shaunak Sinha, Kevin Tang, Anika Thatavarthy, Ethan Valentine, Chenqin Yang, Sofia Yang, Kathleen Yung
MyEdMaster, LLC, 13750 Sunrise Valley Drive, Herndon, VA, United States of America
John Leddo is director of research at MyEdmaster.

MLA 8
Leddo, John. "ARTIFICIAL INTELLIGENCE AND VOICE-POWERED ELECTRONIC TEXTBOOKS AND ELECTRONIC BOOKS." Int. j. of Social Science and Economic Research, vol. 5, no. 1, Jan. 2020, pp. 190-206, ijsser.org/more2020.php?id=13. Accessed Jan. 2020.
APA(6)
Leddo, J. (2020, January). ARTIFICIAL INTELLIGENCE AND VOICE-POWERED ELECTRONIC TEXTBOOKS AND ELECTRONIC BOOKS. Int. j. of Social Science and Economic Research, 5(1), 190-206. Retrieved from ijsser.org/more2020.php?id=13
Chicago
Leddo, John. "ARTIFICIAL INTELLIGENCE AND VOICE-POWERED ELECTRONIC TEXTBOOKS AND ELECTRONIC BOOKS." Int. j. of Social Science and Economic Research 5, no. 1 (January 2020), 190-206. Accessed January, 2020. ijsser.org/more2020.php?id=13.

References

[1]. Anderson, J.R. (1982). Acquisition of cognitive skill. Psychological Review, 89, 369-405.
[2]. Anderson, J. R. (1990). The adaptive character of thought. Hillsdale, NJ: Erlbaum.
[3]. 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.
[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]. Gunawan, F.E. (2018). A learning recommendation to improve electronic textbook learning experience. ICIC Express Letters, 13(1), 1-10.
[6]. Ivanova, E.O. & Osmolovskaya, I.M. (2016). Electronic textbooks: didactic aspect. SHS Web Conferences, 29, 1-5.
[7]. Laketa, S. & Drakulic, D. (2015). Quality of Lessons in Traditional and Electronic Textbooks. Interdisciplinary Description of Complex Systems 13(1), 117-127
[8]. 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.
[9]. Leddo, J. & Sak, S. Knowledge Assessment: Diagnosing what students really know. Presented at Society for Technology and Teacher Education. March, 1994.
[10]. Leddo, J. Bisht, D., Narla, E., Saranu, R. & 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.
[11]. Lokar, M., Horvat, B., Luksic, P. & Omerza, D. (2011). Baselines for the preparation of electronic textbooks. Organizacija, 44(3), 76-84.
[12]. National Assessment of Educational Progress. (2016). Princeton, NJ: Educational Testing Service.
[13]. Quillian, M.R. (1966). Semantic memory. Camridge, MA: Bolt, Beranek and Newman.
[14]. Schank, R.C. and Abelson, R.P. (1977). Scripts, Plans, Goals, and Understanding. Hillsdale, NJ: Erlbaum.

Abstract:
Reading, whether as an end in itself as in language arts classes or as a means for learning when done through textbooks, has long been an integral part of classroom education. As much of the information world has moved online, so, too, have books followed. Unfortunately, commercially-available electronic textbooks (e-textbooks) and electronic books (e-books) are typically little more than .pdf versions of their paper counterparts, thus not exploiting other technologies that could be used to increase learning. The present paper describes technologies that use artificial intelligence (AI) and voice/natural language technologies to increase student learning in e-textbooks and e-books. As students learn a lesson, they can verbally ask the technology questions about the content and receive answers much the way they can when using personal assistants on smart phones. When students have completed the material, the technology assesses whether they have learned the material by verbally asking questions and allowing students to answer verbally. Any deficiencies are immediately remediated. When students finish the assessment in the e-textbook, they do practice problems as they would in a standard etextbook. The difference is that with the present technology, all work is done step-by-step on an electronic worksheet where the underlying AI technology monitors each step and provides hints when requested and feedback when mistakes are made. The present e-textbook technology was tested experimentally by having students either use it or leading publisher Pearson's Algebra 2 Common Core e-textbook to learn division of complex numbers. Students were then given a post-test to measure their learning. Students using the AI and voice/natural language-powered etextbook scored four times high on the post-test than those using Pearson's e-textbook. The results suggest that AI and voice/natural language technologies can improve educational performance when incorporated into e-textbooks and e-books.