APU Cyber & AI Original

Will AI Teacherbots Ever Replace Online Instructors?

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By Dr. William Oliver Hedgepeth, Dr. Robert Gordon, Dr. Kandis Wyatt, Dr. Wanda Curlee and Dr. Shelly Pumphrey

Faculty Members, Transportation and Logistics Management, School of Business, American Public University

This is the first article in a research study on whether an AI system could ever replace online college professors. Several APU School of Business faculty members are conducting this study.

Artificial intelligence (AI) processes and systems have become a continuous part of our daily lives and working activities. AI is currently used to make decisions for humans. Think about Siri, Alexa and Google. They make lower-level decisions for humans every day.

Start a degree program at American Public University.

Five professors of American Public University System (APUS) are conducting research on whether an AI system could ever replace online college professors. Given the nature of the study, this research effort will stretch into 2021 and beyond. The hypothesis is whether college students will accept the use of AI (teacherbots) as a learning platform compared to a human teacher in an online asynchronous classroom.

During this first year, we will be conducting surveys with APUS military and civilian students. Most of them are working adults seeking a B.A. or M.A. degree to prepare for their next career or for an upcoming promotion opportunity.

What Is AI?

Before we analyze this technology and its relationship to teaching, we must first define Artificial Intelligence. AI started with mathematician John McCarthy in 1955 and discussed at length during the first AI conference at Dartmouth College in 1956.

AI can be confusing to understand. Currently, there are 28 terms used for AI. In alphabetic order, these terms are algorithms, artificial intelligence, artificial neural network (ANN), autonomic computing, chatbots, classification, cluster analysis, clustering, cognitive computing, convolutional neural network (CNN), data mining, data science, decision tree, deep learning, fluent, game AI, genetic algorithm, heuristic search techniques, knowledge engineering, logic programming, machine intelligence, machine learning, machine perception, natural  language processing, recurrent neural network (RNN), supervised learning, swarm behavior and unsupervised learning.

Each of these terms carries with it part of the definition of complex systems in their applications to solving human computer interaction (HCI) problems.

Three distinct terms help focus the definitions of AI in our study of human-computer interactions: artificial narrow intelligence (ANI), artificial general intelligence (AGI) and artificial super intelligence (ASI).

Our study will explore which AI descriptions best represent the application of AI technology to replace or enhance the role of an online college professor and the interaction between online students and online professors.

The Research Approach Will Be Both Quantitative and Qualitative

The research will be both quantitative and qualitative. The team will present the survey findings at conferences as well as through online social media sources.

The research focus is on the ethics of AI in the curriculum design of online college courses and in the application of AI systems — teacherbots — to replace, supplement, or assist human teachers in online classroom activities.

The goal of this project is to establish APUS as a leader among other colleges and universities with a technology trend that has already started in K-12 education and has become commonplace in many homes and workplaces.

The research, which is related to Social Cognitive Learning Theory, will provide further insight from end users’ perspective about the perceived advantages and disadvantages of AI in the learning environment. This insight can also help by identifying areas where faculty will need to train in order to help students prepare for the AI platform and activities.

Research Basis and Hypothesis

Artificial intelligence is all around us. So is it really a stretch to start thinking about how AI can be infused into the classroom? As instructors who have taught online for several decades, we feel this change in practice will mean a total paradigm change from when the first online classrooms were proposed about 30 years ago. The University of Illinois first conceived distance learning in 1960 when classroom students developed an intranet that facilitated distance learning.

Do you shrink at the idea of thinking that, thanks to AI, an online teaching career may soon be a thing of the past? Let’s consider what artificial intelligence would look like in the classroom and how we would structure curricula involving AI.

A discussion about AI in curricula can be seen from two perspectives. The first is the teacher’s perspective of AI in the classroom. Many teachers would love to have a personal assistant to read and critique papers and essays, hold student office hours, and help high-achieving students move faster through the curriculum. Artificial intelligence could also assess teachers’ strong and weak points, and provide timely training to address any deficiencies.

The second perspective is the students’ understanding of AI in the classroom. Students would need to understand what artificial intelligence is, the ways that AI can make learning more relevant and fun, and how AI will enrich their lives in the future.

AI and Ethics Have a Dilemma to Resolve

Should AI have ethical values built into the teacherbot or should the teacherbot learn ethics? The problem about learning ethics is that every culture has different ethics. Nuances in ethics need to be understood. In 2014, the MIT Media Lab conducted the crowdsourced experiment called the Moral Machine.

The experiment was based on the famous trolley problem that examined the moral choice of whether to save one person and let a group of others die, or to save the group and let the individual die. Whose life is more important?

Since the introduction of AI and smart technology, research gaps are being filled by everyday appliances and tools. The military is investing in AI and robotic technology for battlefield applications, to save soldiers’ lives, to improve their abilities, and to enhance their situational awareness of harmful factors around them.

Smart or AI technology is on your laptop and cell phone, in your vehicle, and inside your home to assist with your tasks or answer questions. Such devices are now part of our daily training and education from kindergarten to retirement.

AI, or teacherbots, exist today. They are being examined as substitutes for human teachers and as assistants in the classroom.

Nevertheless, there remains a gap in pedagogical usage. Some universities and colleges resist pursuing such technology out of fear of displacement and ethical concerns. These fears and concerns were introduced into business and education in the early 1960s, when computers entered the classroom and became part of the educational toolset, replacing the slide rule and calculator.

The Research Method

The research method involves observation and data collection. The tools used will be interviews and surveys. The researchers will form a panel for this survey and interview respondents’ results.

Active variables, as well as attribute variables, will be evaluated. Factor analysis and multiple regression will be used to analyze the data collected. This is nonexperimental research because there will be no direct control or risk over the subjects under study.

The survey will be combined with personal interviews of the subjects. The information gathered will include sex, age, marital status, education, income, political preferences, religious preference, active-duty military, retired military, and civilian with no military experience.

The interviews will be helpful in documenting the subjects’ reasons for believing or not believing in the use of AI teacherbots. NVivo software will assess the qualitative portions of the research.

The survey will be formed as a flow plan or outline to establish objectives based on the initial questions and hypotheses.

General or specific problems may arise from this survey and interview method. These problems should become part of this analysis and resolved as completely as possible.

Where Does the AI Research Lead to?

There is a larger line of research that needs to be put into the historical context to show how far we have come in the area of AI.

Our future interests span the past and what is happening today about AI and its changes and evolution.

The first short story written by a computer was Soft Ions published in Omni magazine in 1981. The stories have not stopped. Our research does not end with this teacher bot focus.

This research is part of the APUS foundation for developing the best experience for our human teachers who are now being linked to AI systems. We do not envision human teachers being replaced by teacherbots; rather, we see human teachers being given a stronger set of technology tools to do their all-important job.

About the Authors

Dr. Oliver Hedgepeth is a full-time professor at American Public University (APU). He was program director of three academic programs: Reverse Logistics Management, Transportation and Logistics Management and Government Contracting. He was Chair of the Logistics Department at the University of Alaska Anchorage. Dr. Hedgepeth was the founding Director of the Army’s Artificial Intelligence Center for Logistics from 1985 to 1990, Fort Lee, Virginia.

Dr. Robert Gordon is a program director at American Public University (APU). He has over 25 years of professional experience in supply chain and human resources. He has earned Doctorate of Management and Organizational Leadership, an M.B.A. and a B.A. in History. Dr. Gordon has also authored more than 100 published articles including five books covering a variety of business topics.

Dr. Kandis Wyatt, PMP, is a full-time professor of Transportation and Logistics Management in the School of Business. Professionally, Dr. Wyatt has implemented process development practices, designed and created instruction, and developed procedures and programs for civilian employees. Dr. Wyatt’s teaching philosophy includes emphasizing the importance of being an information facilitator and content guider to help students apply real life experiences to foundational principles. Online teaching is more than teaching to the test, it is creating an online learning community. The traditional role of the instructor has changed from “the sage on the stage” to the “guide on the side.” Dr. Wyatt’s teaching style includes creating an environment that emphasizes diverse talents and ways of learning, prompt feedback, and active learning. 

Dr. Wanda Curlee is a full-time professor at American Public University. She has over 30 years of consulting and project management experience and has worked at several Fortune 500 companies. She has a Doctorate of Management and Organizational Leadership, an M.B.A., an M.A. and a B.A. in Spanish Studies. Dr. Curlee has published numerous articles and several books on project management.

Dr. Shelly Pumphrey is a full-time professor at American Public University. She has over 35 years in the energy industry and has taught in several universities and colleges. She has a Ph.D. in Information Security.

Dr. Oliver Hedgepeth is a full-time professor at American Public University (APU). He was program director of three academic programs: Reverse Logistics Management, Transportation and Logistics Management and Government Contracting. He was Chair of the Logistics Department at the University of Alaska Anchorage. Dr. Hedgepeth was the founding Director of the Army’s Artificial Intelligence Center for Logistics from 1985 to 1990, Fort Lee, Virginia.

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