Presentation on theme: "Artificial Intelligence (AI) Simulation Technologies: Providing Immediate Feedback to Students and Faculty in Online Programs An AI Based Student Retention."— Presentation transcript:
Artificial Intelligence (AI) Simulation Technologies: Providing Immediate Feedback to Students and Faculty in Online Programs An AI Based Student Retention Initiative
Presenters Dale Crowe, PhD - faculty member, School of Advanced Studies at the University of Phoenix Martin La Pierre - Independent consultant at Ferentina, Inc., Doctoral Candidate, University of Phoenix, Col. USMC (Ret). Raquel Pesce, PhD - Mentor and Lead Instructor, Pre-Calculus Department, Florida Virtual School
Agenda 1.Agenda 2.Definition of AI Simulation Technologies 3.Student Retention Issues 4.Online Learning in Numbers 5.Program Description 6.Purpose and Significance 7.Scholarly Writing Simulator Using IBM’s Watson 8.Demo 9.Questions
Definition of AI Simulation Technologies AI is a branch of computer science in which developers attempt to replicate and improve upon the cognitive aspects of human and animal functions using artificial or non- naturally occurring computing devices. AI based Simulation Technologies are computer applications that provide a realistic environment that adapts to the user in order to increase skill or knowledge. Military personnel use AI based Simulation Technologies to hone pilot, vehicle driver, system administrator and infantry skills
Student Retention is at the Forefront of Higher Education Explosive growth in online degree offerings and students taking online courses – Fall 2011 total of 6.7 million students taking at least one online course (Allen & Seaman, 2013) – Online enrollment has steadily increased as a percent of total enrollment each year since 2002 (Allen & Seaman, 2013) – In recent years there has been a significant increase in students enrolling exclusively in distance education courses (Ginder, 2014)
Online Learning in Numbers Source: Allen & Seaman, 2013
Online Learning – Retention Issues Remoteness and isolation from student support systems Transitory nature of military families exacerbate student support issues Applying education specific AI simulation technologies as a mitigation tool in student retention
Program Description Military community represents an increasing population at higher education institutions (Byman, 2007) – Education community must be prepared to meet learning, professional, personal needs – Student retention rates have steadily decreased since the early 1980s (Bean, 1980; Lederman, 2009) – The military community can benefit from new strategies and programs designed for retention (Lascher & Offenstein, 2013; Tinto, ) – Military community members must take initiative and seek out program's designed to help them (O’Herrin, 2011).
Program Description Artificial Intelligence (AI) simulations can be used, by students, to learn skills such as scholarly writing and mathematics Why? – Students may not have mastered required skills (Varol & Varol, 2014) – Instructors may not be available to teach skills to students who are falling behind – Instructors may not have the time to address the shortcomings of small minority of students – Students that fall behind tend to drop out (Kellogg & Raulerson, 2007) – A well-developed AI simulator may assist students so that they can continue their academic courses with a greater degree of success
Purpose and Significance Military community members face unusual challenges affecting the amount time spent in the online classroom – Course work and requirements should be designed around the specific needs of military community members Online courses that provide AI simulation experiences could provide for the needs of military community members – Military community members are familiar with AI simulations from work and recreational activities
Purpose and Significance Educators may have difficulty in instructing students to the importance of addressing topics directly (Jones, 2014) – Aligning a response with a topic may seem like a straight forward proposition for a student but that is hardly ever the case – When writing scholarly papers many students believe that it is necessary to have long and rambling responses – When done on a regular basis it is difficult, because of time constraints, to address each instance individually and provide proper guidance
Purpose and Significance It might be possible to extend the capabilities of a word processor application, or rudimentary expert system programs, to create an AI simulator that can teach the art scholarly writing – A scholarly writing AI simulator can provide constant feedback and assessment – A scholarly writing AI simulator helps students learn but would also provide a sense of preparedness – Students who are prepared and complete their course work successful tend to stay in academic programs longer (Varol & Varol, 2014)
Purpose and Significance Building an AI scholarly writing simulator can be accomplished using the inherent capabilities of IBM’s Watson computer system (Ferrucci, et al., 2010) IBM’s Watson computer bested a pair of champions on the TV game show Jeopardy in 2011(Watson wins on jeopardy, 2011). IBM has built Watson so that third party application developers can use the underlying properties of Watson in their own applications (Barinka, 2013).
Scholarly Writing Simulator Using IBM’s Watson Current expert systems technologies at the University of Phoenix include : WritePoint (by Grammarly) - a grammar checking program. It makes revision's to texts and also explains why it made the changes. Turnitin – An originality checker that is used to ensure that a given work is properly cited Furture SWS technologies would incorporate the functionality of both Writepoint and Turinitin but include the ability to understand the text syntactically and semantically SWS will be built to be able to spot machine generated scholarly texts like the type that have plagued the IEEE (Van Noorden,2014).
Scholarly Writing Simulator Using IBM’s Watson What is a Scholarly Writing Simulator (SWS)? The notional SWS is a word processor extension that allows an individual to train to write scholarly texts in a particular format such as APA, MLA or Chicago It provides an evaluation of content while the text is being written looks for additional source material that is relevant It provides suggestions that might help make the text align better with the subject It asks questions while the text is being written to understand the Authors intent.
Scholarly Writing Simulator Using IBM’s Watson The SWS is built on Watson Watson is a cognitive computing system capable of utilizing unstructured natural language to form a hypothesis based on evidence Watson can answer questions and evaluative texts much like a human can Watson is a type of expert system Watson is used in hospitals? IBM Watson's business chief Manoj Saxena says that 90% of nurses who use Watson now follow its guidance (Upbin, 2013) The Mayo clinic is analyzing the medical records of patients with breast, colorectal, and lung cancer to look for factors leading to causation (Strickland, 2014)
Scholarly Writing Simulator Using IBM’s Watson
Further Reading The Era of Cognitive Systems: An Inside Look at IBM Watson and How it Works
References Allen, E. & Seaman, J. (2013). Changing course: Ten years of tracking online education in the United States. San Francisco: Babson Survey Research Group and Quahog Research Group, LLC. Barinka, A. (2013, ). IBM offers watson as cloud tool. Journal - Gazette Retrieved from 262 Bean, J. P. (1980). Dropouts and turnover: The synthesis and test of a causal model of student attrition. Research in Higher Education, 12, doi: /BF Byman, D. (2007). Veterans and colleges have a lot to offer each other. Chronicle of Higher Education, 54(16).
References Ferrucci, D. :. B.,E., Chu-Carroll, J., Fan, D., Gondek, D., Kalyanpur, A., Lally, A.,... Welty, C. (2010). The AI behind watson — the technical article Retrieved 3/23/2014, 2014, Retrieved from Ginder, S. (2014). Enrollment in distance education courses, by State: Fall National Center for Education Statistics. Kellogg, R. T., & Raulerson, B. A.,III. (2007). Improving the writing skills of college students. Psychonomic Bulletin & Review (Pre-2011), 14(2), Retrieved from 03
References Jones, R. (2014). Dissertation writing: The importance of alignment | the refractive thinker Retrieved from importance-of-alignment Lascher, E. L., & Offenstein, J. L. (2013). Campus racial climate and student academic outcomes: A critique of prior research and recommendations for future study. Journal of College Student Retention, Research, Theory & Practice, 14, Retrieved from Lederman, D. (2009). As talk about retention rises, rates drop. Retrieved from O’Herrin, E. (2011). Enhancing veteran success in higher education. Peer Review, 13(1), 15-18
References Strickland, E. (2014). At the mayo clinic, IBM watson takes charge of clinical trials - IEEE spectrum Retrieved from Tinto, V. ( ). Research and practice of student retention: What next? Journal of College Student Retention: Research, Theory & Practice, 8, Retrieved from jcsr Strickland, E. (2014). At the mayo clinic, IBM Watson takes charge of clinical trials - IEEE spectrum Retrieved from talk/robotics/artificial-intelligence/at-the- mayo-clinic-ibm-watson-takes-charge-of-clinical-trials Tinto, V. ( ). Research and practice of student retention: What next? Journal of College Student Retention: Research, Theory & Practice, 8, Retrieved from
References Upbin, B.( ). "IBM's Watson Gets Its First Piece Of Business In Healthcare". Forbes. Van Noorden, R. (2014). Publishers withdraw more than 120 gibberish papers Nature, doi: /nature Varol, H., & Varol, C. (2014). Improving female student retention in computer science during the first programming course. International Journal of Information and Education Technology, 4(5), doi:http://dx.doi.org.ezproxy.apollolibrary.com/ /IJIET.2014.V Watson wins on jeopardy (2011).. Chatham, United States, Chatham: Newstex. Retrieved from 965