2. The Pros and Cons of LLMs. Terry Ewell presents positive and negative aspects of Large Language Models. An article from Beijing University is discussed and applied to college-level education. BDP 372. www.terryewell.com.  2026 Jan. 02.
<Music: Hummel’s Bassoon Concerto, Second Movement. Terry B. Ewell and Peter Amstutz, Live Recording, Oct. 1997, Kent State University.>

Welcome to this brief introduction to Large Language Models, or LLMs, for my courses. I'm Terry Ewell.

Large Language Models, or LLMs, are changing every day. As I'm making this video on January 2, 2026, some aspects of it may have already changed when you're viewing this video. Although there will be significant advancements in AI and LLMs, I can still draw some important generalizations. These are based upon my four semesters of teaching courses at Towson University. My students are required to use AIN and LLMs in my online and classroom courses. For over five months, I have intensively worked with ChatGPT. I've employed ChatGPT for my academic writing, as a fitness and health coach, for financial tracking, to record my spiritual activities, and for technical translations into Spanish. I've read academic research and recent peer-reviewed publications that give me further insights into AI and LLMs. And last of all, I've gleaned several observations from YouTube videos and other sources.

This study by Yizhou Fan, conducted in Beijing, China, highlights the important benefits and disadvantages of using LLMs. Three dimensions of learning were studied: one, those with human mentors, two, those guided by checklists, and three, those using LLMs. Participants in this study used English, which was their second language. These observations were provided in the study. “ChatGPT's ability to effectively improve learners' writing performance and productivity had been proven in many studies.” “ChatGPT improved writing performance even more than the condition that involved support provided by a very experienced human expert.” I've seen this in my courses with written components. The improvement in writing is most dramatic with students who have weaker language skills. So, in effect, this is a great equalizer in the course.

I have observed these improved written documents to include better spelling, grammar, and sentence formation. The citations are in better form. And overall, the content of the papers is more sophisticated. Well, let's read on in the study. “Learners with ChatGPT had significantly higher post-test scores (knowledge gained in the field of electronic magnetism) than those with human tutors.” A little further down, “these different studies noted the potential of AI-powered chatbots, such as ChatGPT, to improve learners' test scores. knowledge gain and knowledge transfer.”
I've also observed improved test results in my courses. There are even more benefits than this. There are better research results that I've found as people have used these. Much better than even searching online. A more comprehensive presentation of the dilemmas and scenarios has been a result of using these LLMs. It's easier to find information with the LLMs. There's an ease of research.
LLMs also handle data very well. For instance, in the medical research area, the pace of the doubling of data and everything just happened so quickly that no human could possibly keep abreast of all of the test results. and LLMs can summarize it very quickly and provide terrific summaries. So, it's a great time saver. It's a great summarizer of information.

I'm quite excited about how my students can rapidly improve their results in my course and also throughout probably the rest of their lives. Remember, I teach life skills and academic competencies, and as a result, I must teach AI and LLMs in my courses because these are important skills that students will need to carry beyond the course that I teach at Towson University. Employers will be requiring these skills as well in the future. In all these aspects, LLMs serve as a lever, an augmentation of what people can do.

There are, however, disadvantages. Having provided the positive aspects of LLMs, now let's explore the problems as well. First are issues with hallucinations or errors. The LLMs will produce false data, wrong facts, and even quote from articles and books that don't exist.

It is important to realize that LLMs are trained to produce human-like responses, not necessarily ones that are truthful. There's a kind of eagerness to please by providing a plausible response rather than a correct reply.

Next is the issue of cognitive offloading. This means a deterioration of reasoning skills in the users. So let's read further in this study here. “When learners encounter situations that challenge their intuition, they are more likely to engage in deliberate analytical thinking.” “In the context of Gen. AI, if learners rely excessively on AI-generated outputs or facilitation, they may not experience the necessary dysfluency or cognitive difficulty to trigger these deeper metacognitive processes.” So, in other words, it's talking about struggling to understand concepts, struggling to figure something out creates in your brain new neural networks, ways of thinking about things, and processes that are lost if that cognitive challenge is loaded onto ChatGPT, for instance. Then you don't have to struggle with it. So, the danger is that the use of LLMs could lead to surface learning rather than deep learning. There could be an erosion in reading and research skills. Furthermore, students may have greater difficulty assessing the validity of statements and arguments after extensive use of LLMs.

Well, additional problems that emerge with LLMs are plagiarism, which means passing off another's work, including AI as your own. There is also the issue of homogenization of responses and language. If everyone is using LLMs, the results are increasingly similar. There is a loss of individuality and unique expression. Problems with confidentiality emerge as well. Those who share private information with LLMs risk that information being publicized and misused by the company that owns the LLM. There is, furthermore, the problem of humanization, which is emotionally connecting to AI as if it were a person. This is a serious risk for all of us, in particular for those who lack strong and healthy bonds with other people. All of these are very real and serious problems. We need to be constantly vigilant to address these issues.

Now, please see my website, which has useful information on AI and LLMs.
In conclusion, in my courses, we will dive right into the chaotic mix of the good and the bad, the beautiful and the ugly aspects of AI and LLMs. In my courses, I will call upon you to actively engage in our discussions and in our discoveries of how best to use AI and LLMs. The next videos will present advice on leveraging the benefits of these while reducing the harmful effects. Thank you.


<Music: Hummel’s Bassoon Concerto, Second Movement. Terry B. Ewell and Peter Amstutz, Live Recording, Oct. 1997, Kent State University.>