Benefits and Barriers of Chatbot Use in Education Technology and the Curriculum: Summer 2023

As an example of an evaluation study, the researchers in (Ruan et al., 2019) assessed students’ reactions and behavior while using ‘BookBuddy,’ a chatbot that helps students read books. The researchers recorded the facial expressions of the participants using webcams. It turned out that the students were engaged more Chat GPT than half of the time while using BookBuddy. According to their relevance to our research questions, we evaluated the found articles using the inclusion and exclusion criteria provided in Table 3. The inclusion and exclusion criteria allowed us to reduce the number of articles unrelated to our research questions.

There is also a bias towards empirically evaluated articles as we only selected articles that have an empirical evaluation, such as experiments, evaluation studies, etc. Further, we only analyzed the most recent articles when many articles discussed the same concept by the same researchers. While using questionnaires as an evaluation method, the studies identified high subjective satisfaction, usefulness, and perceived usability.

Conclusion – Chatbot for education

Similarly, the agent’s visual appearance can be human-like or cartoonish, static or animated, two-dimensional or three-dimensional (Dehn & Van Mulken, 2000). 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). PU is the belief that a particular technological system will be beneficial if adopted, such that the more useful a technology is perceived, the more likely it will be used (Davis et al., 1989). PU has been identified in the literature as a factor determining whether teachers and students adopt chatbots (Chocarro et al., 2021; Malik et al., 2021; Mohd Rahim et al., 2022). The usefulness of AI in education is unfamiliar to some teachers (Hrastinski et al., 2019), and many have had negative experiences using chatbots (Kim & Kim, 2022). It is recommended that continuing education programs be made available for in-service and pre-service teachers outlining the benefits and practical applications of chatbot use.

It isn’t just about being available; it’s about ensuring every interaction, whether midnight in New York or noon in Tokyo, is met with an instant, accurate response. The world of Learning Management Systems (LMSs) has been revolutionized by the advent of AI, transforming how organizations deliver training and education. This guide explores the fundamentals of AI-based https://chat.openai.com/ LMS platforms, the benefits they offer, and the future of AI in corporate learning. With current AI tools already making significant strides in transforming admissions and enrollment, the future of AI in education holds even more potential. As AI technologies continue to evolve, their applications will expand, offering more sophisticated tools and capabilities.

This can increase the learner’s sense of agency and their ownership of the learning process. Another interesting study was the one presented in (Law et al., 2020), where the authors explored how fourth and fifth-grade students interacted with a chatbot to teach it about several topics such as science and history. The students appreciated that the robot was attentive, curious, and eager to learn.

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By comprehending student sentiments, these chatbots help educators modify and enhance their teaching practices, creating better learning experiences. Promptly addressing students’ doubts and concerns, chatbots enable teachers to provide immediate clarifications, fostering a more conducive and effective learning environment. Through interactive conversations, thought-provoking questions, and the delivery of intriguing information, chatbots in education captivate students’ attention, making learning an exciting and rewarding adventure. By creating a sense of connection and personalized interaction, these AI chatbots forge stronger bonds between students and their studies. Learners feel more immersed and invested in their educational journey, driven by the desire to explore new topics and uncover intriguing insights. Education chatbots are interactive artificial intelligence (AI) applications utilized by EdTech companies, universities, schools, and other educational institutions.

Assuming so may be the same mistake as thinking that a chatbot understands what it’s saying, instead of merely generating words that statistically follow the previous words. National Science Foundation, my team at California Polytechnic State University is halfway into what we believe is the first study of the effects A.I. Kitchens and robot cooks could have on diverse societies and cultures worldwide. We can help you learn about eligibility for VA home loans and request a VA home loan Certificate of Eligibility (COE).

For example, the authors in (Fryer et al., 2017) used Cleverbot, a chatbot designed to learn from its past conversations with humans. User-driven chatbots fit language learning as students may benefit from an unguided conversation. The authors in (Ruan et al., 2021) used a similar approach where students freely speak a foreign language. The chatbot benefits of chatbots in education assesses the quality of the transcribed text and provides constructive feedback. 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.

• Students and teachers should be educated on the accuracy of the text produced by chatbots and always fact-check the information produced by them.
• Only one study pointed to high usefulness and subjective satisfaction (Lee et al., 2020), while the others reported low to moderate subjective satisfaction (Table 13).
• Subsequently, the assessment of specific topics is presented where the user is expected to fill out values, and the chatbot responds with feedback.
• This sophistication, drawing upon recent advancements in large language models (LLMs), has led to increased customer satisfaction and more versatile chatbot applications.
• An exemplar is Google’s AlphaZero, which refines its strategies by playing millions of self-iterated games, mirroring human learning through repeated experiences.

This means that teachers can develop systems to identify students at risk of failing and offer appropriate guidance and intervention. Chatbots can provide students with immediate feedback, assisting the metacognitive processes of learning (Chang et al., 2022; Cunningham-Nelson et al., 2019; Guo et al., 2022; Okonkwo & Ade-Ibijola, 2021; Wollny et al., 2021). Similar feedback functions are incorporated on a smaller scale into software applications such as Grammarly, Microsoft Word, and Google Docs. Utilizing chatbots, students can make their statements more clear and concise (Cunningham-Nelson et al., 2019) and receive assistance solving difficult problems (Kaur et al., 2021).

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. It’s in those moments that learners could benefit from a timely piece of advice or feedback, or a suggested “move” or method to try. So I’m currently working on what I call a “cobot” — a hybrid between a rule-based and an NLP bot chatbot — that can collaborate with humans when they need it and as they pursue their own goals.

5 RQ5 – What are the principles used to guide the design of the educational chatbots?

Instead of waiting on hold, customers can get answers to their questions in real time. Over time, chatbot algorithms became capable of more complex rules-based programming and even natural language processing, enabling customer queries to be expressed in a conversational way. This gave rise to a new type of chatbot, contextually aware and armed with machine learning to continuously optimize its ability to correctly process and predict queries through exposure to more and more human language. A chatbot is a computer program that simulates human conversation with an end user. Not all chatbots are equipped with artificial intelligence (AI), but modern chatbots increasingly use conversational AI techniques such as natural language processing (NLP) to understand user questions and automate responses to them. AI chatbots equipped with sentiment analysis capabilities can play a pivotal role in assisting teachers.

They act beyond classroom activities as campus guides, providing valuable information on facilities and helping students. Considering this, the University of Murcia in Spain used an AI chat assistant that successfully addressed more than 38,708 inquiries with an accuracy rate of 91%. The success of chatbot implementation depends on how easily educatee perceive and adapt to their use. If they find tools complex or difficult to navigate, it may hinder their acceptance and application in educational settings. Ensuring a user-friendly interface and straightforward interactions is important for everyone’s convenience.

In one study, students used chatbots to provide continuous feedback on their argumentative essays to assist with writing (Guo et al., 2022). Typically, this feedback is received after peer review or first draft submissions rather than concurrently within the writing process. Feedback is critical in any educational system, and chatbots simplify collecting and analyzing this valuable data.

It excels at capturing and retaining contextual information throughout interactions, leading to more coherent and contextually relevant conversations. Unlike some educational chatbots that follow predetermined paths or rely on predefined scripts, ChatGPT is capable of engaging in open-ended dialogue and adapting to various user inputs. AI systems enhance their responses through extensive learning from human interactions, akin to brain synchrony during cooperative tasks. This process creates a form of “computational synchrony,” where AI evolves by accumulating and analyzing human interaction data. Affective Computing, introduced by Rosalind Picard in 1995, exemplifies AI’s adaptive capabilities by detecting and responding to human emotions. These systems interpret facial expressions, voice modulations, and text to gauge emotions, adjusting interactions in real-time to be more empathetic, persuasive, and effective.

This includes health care, case management, supportive services, and other resources. Whether guiding a purchase on Facebook Messenger or answering product queries on WhatsApp, Yellow.ai positions your brand just where your customers want it. It means that regardless of the platform your customers prefer, they’re greeted with consistent and reliable support, enhancing their overall brand experience. Customers hop from one platform to another, expecting your brand to hop along seamlessly. AI-driven chatbots ensure your brand’s voice resonates across these platforms.

These advisors will use natural language processing to offer personalized advice and resources. To get the most from an organization’s existing data, enterprise-grade chatbots can be integrated with critical systems and orchestrate workflows inside and outside of a CRM system. Chatbots can handle real-time actions as routine as a password change, all the way through a complex multi-step workflow spanning multiple applications. In addition, conversational analytics can analyze and extract insights from natural language conversations, typically between customers interacting with businesses through chatbots and virtual assistants. Institutional staff, especially teachers, are often overburdened and exhausted, working beyond their office hours just to deliver excellent learning experiences to their students.

Teaching agents play the role of human teachers and can present instructions, illustrate examples, ask questions (Wambsganss et al., 2020), and provide immediate feedback (Kulik & Fletcher, 2016). On the other hand, peer agents serve as learning mates for students to encourage peer-to-peer interactions. Nevertheless, peer agents can still guide the students along a learning path. Students typically initiate the conversation with peer agents to look up certain definitions or ask for an explanation of a specific topic.

Interacting with educational chatbots: A systematic review

Likewise, bots can collect inputs from all involved participants after each interaction or event. Subsequently, this method offers valuable insights into improving the learning journey. As Conversational AI and Generative AI continue to advance, chatbots in education will become even more intuitive and interactive. They will play an increasingly vital role in personalized learning, adapting to individual student preferences and learning styles.

When using a chatbot, the gathering of data and feedback from the students happens in a way that is organic and integrated into the learning experience — without the need for separate surveys or tests. The data is captured digitally in a format that can be analyzed manually or by using algorithms that can detect themes, patterns, and connections. In effect the teacher can “interact” with and learn from multiple learners at the same time (in theory an infinite number of them). Concerning the evaluation methods used to establish the validity of the approach, slightly more than a third of the chatbots used experiment with mostly significant results. The remaining chatbots were evaluated with evaluation studies (27.77%), questionnaires (27.77%), and focus groups (8.33%).

Text-based agents allow users to interact by simply typing via a keyboard, whereas voice-based agents allow talking via a mic. Voice-based chatbots are more accessible to older adults and some special-need people (Brewer et al., 2018). An embodied chatbot has a physical body, usually in the form of a human, or a cartoon animal (Serenko et al., 2007), allowing them to exhibit facial expressions and emotions. Facilitating conditions refer to the degree to which an individual believes that there will be technological support from their system or organization (Chan et al., 2010).

One of the significant advantages of chatbots in education industry is their ability to offer immediate feedback. This quick response mechanism is capable of asking about specific aspects of the session or course. You can foun additiona information about ai customer service and artificial intelligence and NLP. Such programs gather comments on various subjects like study material, teaching approaches, assignments, and more.

Repetitive tasks can easily be carried out using chatbots as teachers’ assistants. With artificial intelligence, chatbots can assist teachers in justifying their work without exhausting them too much. This, in turn, allows teachers to devote more time and attention to designing exciting lessons and providing learners with the personalized attention they deserve.

This way educational chatbots are becoming indispensable tools in modern education. Integrating AI in wealth management is a transformative shift in the financial industry. Its diverse use case displays a wide range of applications of this technology. AI enables wealth management firms to provide high-quality services at cost-effective rates while enhancing risk management, CX, and customization. Contact our financial domain experts to learn more about the business benefits of testing AI-based solutions before integrating with wealth management services. Brain-Computer Interfaces (BCIs) represent the cutting edge of human-AI integration, translating thoughts into digital commands.

• The integration of artificial intelligence (AI) chatbots in education has the potential to revolutionize how students learn and interact with information.
• Therefore, our paper focuses on reviewing and discussing the findings of these new-generation chatbots‘ use in education, including their benefits and challenges from the perspectives of both educators and students.
• This new content can include high-quality text, images and sound based on the LLMs they are trained on.
• A revolutionized admissions funnel for both graduate and undergraduate programs, positioning your institution at the forefront of innovations in higher education.
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The findings emphasize the need to establish guidelines and regulations ensuring the ethical development and deployment of AI chatbots in education. Policies should specifically focus on data privacy, accuracy, and transparency to mitigate potential risks and build trust within the educational community. Additionally, investing in research and development to enhance AI chatbot capabilities and address identified concerns is crucial for a seamless integration into educational systems. Researchers are strongly encouraged to fill the identified research gaps through rigorous studies that delve deeper into the impact of chatbots on education.

Through simulations, quizzes, and problem-solving exercises, chatbots make learning active rather than passive. Education bots are influencing how institutions engage with students by enhancing learning and administrative processes. In recent years, chatbots have become a crucial component in the digital strategy of educational institutions. Businesses can leverage data-driven insights and recommendations to improve the quality of their wealth management decisions. This leads to informed and accurate choices, maximizing ROI and minimizing wealth management risks. AI algorithms analyze clients’ data to select the relevant insurance products and coverage levels.

RL facilitates adaptive learning from interactions, enabling AI systems to learn optimal sequences of actions to achieve desired outcomes while LLMs contribute powerful pattern recognition abilities. This combination enables AI systems to exhibit behavioral synchrony and predict human behavior with high accuracy. Continual learning from each user engagement allows chatbots to enhance and refine their responses and strategies, embodying a commitment to an ever-improving customer experience. Thus, every customer input becomes a building block, progressively elevating service quality and precision over time. Adopting AI in admissions and enrollment is crucial for higher education institutions to stay ahead of challenges and opportunities.

Any software simulating human conversation, whether powered by traditional, rigid decision tree-style menu navigation or cutting-edge conversational AI, is a chatbot. Chatbots can be found across nearly any communication channel, from phone trees to social media to specific apps and websites. Suggestions, stories, and resources come from conversations with students and instructors based on their experience, as well as from external research. Specific sources listed are only for reference and will evolve with the evidence base. All conversations are anonymous so no data is tracked to the user and the database only logs the timestamp of each conversation.

The Explain My Answer option provides learners with an opportunity to delve deeper into their responses. By selecting a button following specific exercise types, users engage in a chat with Duo, receiving a concise explanation about their answers. The e-learning showed the need for exceptional support, especially in the wake of COVID-19. Supplying robust aid through digital tools enhances the institution’s reputation, especially in the rapidly growing e-learning market. These programs may struggle to offer innovative or creative solutions to complex problems. This limits their ability to stimulate critical thinking or problem-solving skills.

Addressing these gaps in the existing literature would significantly benefit the field of education. Firstly, further research on the impacts of integrating chatbots can shed light on their long-term sustainability and how their advantages persist over time. This knowledge is crucial for educators and policymakers to make informed decisions about the continued integration of chatbots into educational systems.

Finally, the chatbot discussed by (Verleger & Pembridge, 2018) was built upon a Q&A database related to a programming course. Nevertheless, because the tool did not produce answers to some questions, some students decided to abandon it and instead use standard search engines to find answers. Six (16.66%) articles presented educational chatbots that exclusively operate on a mobile platform (e.g., phone, tablet). Examples include Rexy (Benedetto & Cremonesi, 2019), which helps students enroll in courses, shows exam results, and gives feedback.