Artificial Intelligence (AI) Simulation Technologies: Providing Immediate Feedback to Students and Faculty in Online Programs

Program Description

 

Military members, spouses, and veterans, represent an increasing population at public and private higher education institutions (Byman, 2007).  With the influx of these members, the higher education community must be adequately prepared to meet their learning, professional, personal needs.  Student retention has steadily decreased since the early 1980s, highlighting a growing problem exists in higher education (Bean, 1980; Lederman, 2009).  Higher education institutions use various practices and metrics to assess student retention and graduation rates.  Strategies to improve online student retention are often incorporated in those institutions whose data indicates there are declining rates of students continuing in their education.   (Lascher & Offenstein, 2013; Tinto, 2006-2007).  Service members who are active-duty military, their spouses, and veterans can benefit from new strategies and programs implemented to assist student learning and enhance retention.  One obstacle found among service members is hesitation to find the support and guidance necessary for their academic success and promote retention in online programs (O’Herrin, 2011).

 

Artificial Intelligence (AI) simulations are one tool that can be used to find support for students to learn hands on skills, including the art of scholarly writing, mathematics, and other disciplines. For example, a problem with most higher education institutions offering an online curriculum is that the student is expected to have mastered the required writing skills they need before they even begin introductory academic courses (Varol & Varol, 2014).  This is a problem that is experienced to some degree by students in most every discipline taught in most every university (Kellogg & Raulerson, 2007).  At times it is a matter of luck finding the right instructor who can teach required skills in a timely manner so as not to let students fall behind their peers academically. Those that do fall behind tend to drop out, try again at a later date or never attempt to take that particular course of instruction again (Kellogg & Raulerson, 2007).  A well-developed AI simulator may hold the potential to assist students in real time in the skills they need so that they can continue their academic courses with a greater chance of success and promote retention.

Purpose and Significance

 

Military students and their spouses also face challenges in terms of deployment or frequent moves from place to place which can affect their time in the online classroom.  Online students have special needs that make traditional classroom based learning and corresponding policies difficult.  Higher education institutions should be knowledgeable about the requirements of active duty members, their spouses, and create flexible technologies for these students.  Course work and requirements can be designed around the specific needs of these members with a focus on an individual degree plan.  Online learning has its own unique challenges including, but not limited to, social isolation, the lack of face-to-face academic instruction, and faculty office hours.  Online courses that provide AI simulation experiences can be especially helpful.  Of particular benefit is that military members are exposed to simulation technologies as part of their initial and ongoing training so they are generally comfortable in working within that environment.

 

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 simplistic and straight forward proposition for a student to accomplish.  For example, many students when writing scholarly papers are of the opinion that long and rambling response will somehow serve to address the topic. Some students do this so regularly that it is difficult for faculty members to address each instance individually and provide proper guidance on what is acceptable when writing a scholarly research paper (Jones, 2014). 

 

Using the scholarly writing example, it might be possible to extend the capabilities of a word processor application so that it can act as an AI simulator that allows a student to learn the art of scholarly writing more directly and completely. A scholarly writing simulator that provides constant feedback and assessment would not only help the student learn but would also provide the student with the sense that they are prepared and can complete their course of instruction successfully.  Students who are better prepared and successfully complete their course work tend to stay in academic programs longer than those who are not (Varol & Varol, 2014).

 

Building a scholarly writing simulator and extending the abilities of the common word processor can be accomplished using the natural language and free form text organization AI 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). According to Jennings (2011)

 

The Watson computer system was able to win because it is able to zero in on key words and then can search its memory for clusters of associations that it rigorously checks the top hits against all the contextual information it can muster: the category name; the kind of answer being sought; the time, place, and gender hinted at in the clue; and so on. And when it feels statistically "sure" enough that it has the correct answer it decides to hit the buzzer.

 

IBM Watson had all the rules for Jeopardy programed into it.  It might be a straightforward process to program all the rules of scholarly writing into a word processing application that accesses the backend processes that Watson used to win Jeopardy.  IBM has built Application Programming Interfaces (API’s) that allow for software to be written that can utilize the Watson computers capabilities by connecting via the Internet to the IBM Watson Cloud (Barinka, 2013).  The Watson back end would not only be able to assess how well the student is addressing a particular topic but it could also check the veracity of declarative sentences in real time. If the student is found to be incorrect the Watson computer can make suggestions on references that discuss the topic under consideration by the student through instant feedback. The Watson computer would probably be able to suggest more appropriate uses of “style” (APA, MLA, etc.) by the student as well. With a tool like the IBM Watson enabled word processor, alignment importance might be possible to more students than was previously possible.

 

This session will offer participants an opportunity to learn about the emerging field of AI simulators and how they can be adapted from the defense, business, and health care sectors to online higher education programs, as well as sharing personal accounts of challenges that are faced within the online environment.  Additionally, this session will offer insights from the presenters who have experience in implementing AI simulators and offer guidance to participants who are interested in employing this emerging technology within their own institution.

 

Participant Outcomes

 

1. Participants will gain an understanding of the factors that impact student retention among military members and spouses in online education programs.

2. Participants will gain an understanding of AI Simulation strategies (e.g. IBM
Watson) that are currently being used in the defense, health care, and business sectors.

3. Participants will be able to apply knowledge and skills of how AI Simulation strategies can be developed and incorporated into higher education, and in particular online higher education.   

Abstract: 

Student retention is at the forefront of higher education. There has been explosive growth in online degree offerings.  Online learning can be a challenge due in part to remoteness and isolation from ground based student support systems.  Service members, families, and veterans are especially vulnerable because of change of station or other factors. This session will offer examples of how to support students through the development and use of education specific AI simulation technologies.

This publication has been peer reviewed.
Publication Type: 
Conference Proceedings
Authors: 
Dale Crowe, Marty La Pierre, Raquel Pesce
Year of Publication: 
2015
Journal, Book, Magazine or Other Publication Title: 
Proceedings: CCME Professional Development Symposium
Place Published: 
Anaheim, CA

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