The Peril and Promise of Chatbots in Education American Council on Science and Health

If you have any questions, contact us at This guide was created by Stanford Teaching Commons and is licensed under Creative Commons BY-NC-SA 4.0 (attribution, non-commercial, share-alike). While many different chatbots and LLMs exist, we choose to highlight four prominent chatbots currently available for free. Each has some unique characteristics and nuanced differences in how developers built and trained them, though these differences are not significant for our purposes as educators.

For example, Georgia Tech has created an adaptive learning platform for its computer science master’s program. This platform uses AI to personalize the learning experience for each student. Similarly, Stanford has its own AI Laboratory, where researchers work on cutting-edge AI projects. MIT is also heavily invested in AI with its MIT Intelligence Quest (MIT IQ) and MIT-IBM Watson AI Lab initiatives, exploring the potential of AI in various fields. The language learning chatbots use AI algorithms to understand the user context and be able to answer contextually and uniquely.

The benefits of chatbots for education

The comprehensive list of included studies, along with relevant data extracted from these studies, is available from the corresponding author upon request. Begin by telling the chatbot that you would like to develop a fictional short story and that you’d like its assistance in developing your ideas. Try different ways of interacting and responding to the chatbot to get a sense of its capabilities. This could be invaluable help with the so-called summer melt – the motivation of students who’ve been admitted to college waning over the summer.

The inclusion and exclusion criteria allowed us to reduce the number of articles unrelated to our research questions. Further, we excluded tutorials, technical reports, posters, and Ph.D. thesis since they are not peer-reviewed. In terms of the evaluation methods used to establish the validity of the articles, two related studies (Pérez et al., 2020; Smutny & Schreiberova, 2020) discussed the evaluation methods in some detail.

Whether it’s admission-related inquiries or general questions, educational chatbots offer a seamless and time-saving alternative, empowering students with instant and accurate assistance at their fingertips. The traditional education system faces several issues, including overcrowded classrooms, a lack of personalized attention for students, varying learning paces and styles, and the struggle to keep up with the fast-paced evolution of technology and information. As the educational landscape continues to evolve, the rise of AI-powered chatbots emerges as a promising solution to effectively address some of these issues. Some educational institutions are increasingly turning to AI-powered chatbots, recognizing their relevance, while others are more cautious and do not rush to adopt them in modern educational settings. Consequently, a substantial body of academic literature is dedicated to investigating the role of AI chatbots in education, their potential benefits, and threats. They can be used to provide a personalised learning experience for students and assist in developing their learning processes.

What are the benefits of AI chatbots in education?

While chatbots can help to reduce some gaps, they may also exacerbate others. Keep these issues in mind as you and your students work to maximize the potential benefit of using chatbots. Powered by super AI, a unique combination of generative AI and cognitive AI, Juji’s education solution enables the best-in-class chatbots to aid both students and instructors, aiming at delivering superior user experience and learning outcomes. These chatbots are also faster to build and easier to be integrated with other education applications. This has truly helped develop online learning and improved distance learning for all. It would not be wrong to say that with the right technology and support, education will soon turn from a privilege to a basic human right.

63.88% (23) of the selected articles are conference papers, while 36.11% (13) were published in journals. Interestingly, 38.46% (5) of the journal articles were published recently in 2020. Intriguingly, one article was published in Computers in Human Behavior journal. The remaining journal articles were published in several venues such as IEEE Transactions on Affective Computing, Journal of Educational Psychology, International Journal of Human-Computer Studies, ACM Transactions on Interactive Intelligent System.

AI Chatbots for Education: Corporate Training, Higher Education and K-12

Although a lot of innovative technology advancements were made, the industry wasn’t as quick to adopt until a few years back. Many prestigious institutions like Georgia Tech, Stanford, MIT, and the University of Oxford are actively diving into AI-related projects, not just as topics of research but as initiatives to help make learning more effective and easy. An AI chatbot has a knowledge database based on real students’ conversations. However, when a bot doesn’t know an answer, the question is sent to a human team. As a human answers new questions, the AI learns by adding new data to its database. It leads to the chatbot’s capability of handling an increasing array of circumstances and questions without human input.

It’s important to note that some papers raise concerns about excessive reliance on AI-generated information, potentially leading to a negative impact on student’s critical thinking and problem-solving skills (Kasneci et al., 2023). For instance, if students consistently receive solutions or information effortlessly through AI assistance, they might not engage deeply in understanding the topic. Consider asking the chatbot to take on a particular perspective or identity.

The questionnaires elicited feedback from participants and mainly evaluated the effectiveness and usefulness of learning with Rexy. However, a few participants pointed out that it was sufficient for them to learn with a human partner. The remaining articles (13 articles; 36.11%) present chatbot-driven chatbots that used an intent-based approach. The idea is the chatbot matches what the user says with a premade response. The matching could be done using pattern matching as discussed in (Benotti et al., 2017; Clarizia et al., 2018) or simply by relying on a specific conversational tool such as Dialogflow Footnote 9 as in (Mendez et al., 2020; Lee et al., 2020; Ondáš et al., 2019).

In comparison, the authors in (Tegos et al., 2020) rely on a slightly different approach where the students chat together about a specific programming concept. The chatbot intervenes to evoke curiosity or draw students’ attention to an interesting, related idea. This paper will help to better understand how educational chatbots can be effectively utilized to enhance education and address the specific needs and challenges of students and educators. It is evident that chatbot technology has a significant impact on overall learning outcomes. Specifically, chatbots have demonstrated significant enhancements in learning achievement, explicit reasoning, and knowledge retention. The integration of chatbots in education offers benefits such as immediate assistance, quick access to information, enhanced learning outcomes, and improved educational experiences.

Educational institutions specifically use this AI-powered assistance for communication and interaction with their clients and students. This question reflects on providing feedback on one aspect they have learned from their team that they probably would not have learned independently. 6, the illustration describes changes in each group (EC and CT) pre and post-intervention. First, teamwork showed an increasing trend for EC, whereas CT showed slight changes pre and post-intervention. AI-Powered Chatbots Leveraging machine learning and NLP for adaptive and intelligent interactions. Some 56% of the postdocs who report using chatbots in Nature’s survey employ them to generate, edit and troubleshoot code.

Conversational agents have been developed over the last decade to serve a variety of pedagogical roles, such as tutors, coaches, and learning companions (Haake & Gulz, 2009). I borrowed the term “proudly artificial” from Lauren Kunze, the CEO of the chatbot platform Pandorabots. It would be unethical to use a chatbot to interact with students under false pretenses. It is very important that they understand from the beginning that they are not chatting with a human. At the same time, they should also be told who is the teacher who has designed the chatbot and, most importantly, that the information they share with the chatbot will be seen by the teacher. Depending on the activity and the goals, I often design the bot to ask students for a code name instead of their real name (the chatbot refers to the person by that name at different points in the conversation).

Follow this step-to-step guide to enable chatbot Q&A for intended users, e.g., students or instructors. A great benefit to this chatbot use is promoting inclusiveness in education. Not every student learns the same way, and many have learning disabilities requiring one-on-one lessons and extra care. A chatbot tailors learning and lectures by analyzing each student’s needs and subjects or courses that give them the most trouble. In 2019, he released the results of a poll of 700+ of his students about their experience with Ed the chatbot. Ninety-nine percent said they were satisfied with it and 63 percent said they would like to see chatbots integrated into all of their classes.

• For instance, if students consistently receive solutions or information effortlessly through AI assistance, they might not engage deeply in understanding the topic.
• In general, the studies conducting evaluation studies involved asking participants to take a test after being involved in an activity with the chatbot.
• Universities must ensure quality control mechanisms to verify the accuracy and reliability of the AI-generated content.
• With the help of AI (artificial intelligence) and ML(machine learning), evaluating assessments is no longer limited to MCQs and objective questions.
• For example, teams can use a chatbot to synthesize ideas, develop a timeline of action items, or provide differing perspectives or critiques of the team’s ideas.

Berger reckons that most postdocs seek out and try the AI tools on their own. Bretas, Romanowska and Sclocchi were all introduced to chatbots informally, by friends or colleagues. Of the three, only Bretas says that his institution has issued formal guidelines on how staff should use AI chatbots. RIKEN’s policy prohibits employees from putting information into chatbots that isn’t public or that is personal, because there are no guarantees that data entered into ChatGPT, for instance, stay private.

We potentially missed other interesting articles that could be valuable for this study at the date of submission. SPACE10 (IKEA’s research and design lab) published a fascinating survey asking people what characteristics they would like to see in a virtual AI assistant. Beyond gender and form of the bot, the survey reveals many open questions in the growing field of human-robot interaction (HRI).

Exceptionally, a chatbot found in (D’mello & Graesser, 2013) is both a teaching and motivational agent. I believe the most powerful learning moments happen beyond the walls of the classroom and outside of the time boxes of our course schedules. Authentic learning happens when a person is trying to do or figure out something that they care about — much more so than the problem sets or design challenges that we give them as part of their coursework.

• The matching could be done using pattern matching as discussed in (Benotti et al., 2017; Clarizia et al., 2018) or simply by relying on a specific conversational tool such as Dialogflow Footnote 9 as in (Mendez et al., 2020; Lee et al., 2020; Ondáš et al., 2019).
• Only four chatbots (11.11%) used a user-driven style where the user was in control of the conversation.
• We also encourage you to access and use chatbots to complete some provided sample tasks.
• Further, none of the articles discussed or assessed a distinct personality of the chatbots though research shows that chatbot personality affects users’ subjective satisfaction.
• In head-to-head tests, more sophisticated AI language models tended to perform better than simpler recurrent neural network models and statistical models that just tally the frequency of word pairs found on the internet or in online databases.

Read more about https://www.metadialog.com/ here.