11 Benefits of Using AI Chatbot in the Education Sector

Incorporating AI into the Dx framework provides a pathway for institutional leaders as they explore ways to harness the power of AI across the campus. Example flow diagrams from Textit for the design and development of the chatbot are represented in Fig. The number of choices and possible outputs determine the complexity of the chatbot where some chatbots may have simple interaction that requires them to register their groups (Fig. 2) or much more complex interaction for peer-to-peer assessment (Fig. 3). By looking at other relations in more detail, there is surprisingly no relation between Skill Improvement as the most common implementation objective and Assisting, as the 2nd most common pedagogical role. Furthermore, it can be observed that the Mentoring role has nearly equal relations to all of the objectives for implementing chatbots.

Generative AI (or ‘GenAI’) is an artificial intelligence that can produce text, images, and other media. Have you thought about using AI tools in your classroom, but not sure where to start? In this post, we will share some suggestions for activities and 6 tips for you on using GenAI in the English classroom. The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request. The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.

Do chatbots have special qualities that are suited for out-in-the-world learning?

Chatbots are one of the most prevalent applications in the education sector, as this trend is continually developing. Feature papers are submitted upon individual invitation or recommendation by the scientific editors and must receive
positive feedback from the reviewers. Erica, Bank benefits of chatbots in education of America’s virtual assistant, aids customers with account inquiries, balance checks, transaction history, and setting up alerts, offering quick and accurate banking support. Additionally, it can’t understand user intent, which might limit its effectiveness in specific scenarios.

One of the takeaways is that the emerging field around educational chatbots has seen much activity in the last two years. Based on the experience of this preliminary search, search terms, queries, and filters were constructed for the actual structured literature review. This structured literature review follows the PRISMA framework (Liberati et al., 2009), a guideline for reporting systematic reviews and meta-analyses. The framework consists of an elaborated structure for systematic literature reviews and sets requirements for reporting information about the review process (see section 3.2 to 3.4). Most researchers (25 articles; 69.44%) developed chatbots that operate on the web (Fig. 5).

Evaluation studies

According to Kumar et al. (2021), collaborative learning has a symbiotic relationship with communication skills in project-based learning. This study identifies a need for more active collaboration in the EC group and commitment for the CT group. Overall, it can be observed that the group task performed through ECs contributed towards team building and collaboration, whereas for the CT group, the concept of individuality was more apparent. Interestingly, no feedback from the EC group mentioned difficulties in using the EC nor complexity in interacting with it. It was presumed that students welcomed such interaction as it provided learning support and understood its significance. As for the qualitative findings, firstly, even though the perception of learning did not show much variation statistically, the EC group showed additional weightage that implicates group activities, online feedback, and interaction with the lecturer as impactful.

• In this type of support, the student himself is the focus of the conversation and should be encouraged to plan, reflect or assess his progress on a meta-cognitive level.
• The most essential advantage is that students are required to use these digital platforms for training on a daily basis in order to prepare them for the future.
• Flow XO’s chatbot can be connected to Facebook ads, allowing automated responses to Facebook comments.

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. Automated teaching systems like chatbots can be used to analyze and assess student learning to help teachers identify a student’s level of understanding of a topic (Okonkwo & Ade-Ibijola, 2021).

The Mentoring role is the support in terms of students’ personal development, e.g. by supporting Self-Regulated Learning. From a pedagogical standpoint, all three roles are essential for learners and should therefore be incorporated in chatbots. These pedagogical roles are well aligned with the four implementation objectives reported in RQ1.

• The key difference is that Google Bard is trained on a dataset that includes text from the internet, while ChatGPT is trained on a dataset that includes text from books and articles.
• If you have a small support team, it might sound daunting to expand your presence to other channels.
• In this paper, we investigated the state-of-the-art of chatbots in education according to five research questions.
• While not super-sophisticated, the tool has been well received, at least as a way to get students over that initial hesitance to make some connections.
• Accordingly, chatbots popularized by social media and MIM applications have been widely accepted (Rahman et al., 2018; Smutny & Schreiberova, 2020) and referred to as mobile-based chatbots.

However, AI chatbots are a tool that may be leveraged to improve your time spent online—however, a potent one. According to Adamopoulou and Moussiades (2020), it is impossible to categorize chatbots due to their diversity; nevertheless, specific attributes can be predetermined to guide design and development goals. For example, in this study, the rule-based approach using the if-else technique (Khan et al., 2019) was applied to design the EC. The rule-based chatbot only responds to the rules and keywords programmed (Sandoval, 2018), and therefore designing EC needs anticipation on what the students may inquire about (Chete & Daudu, 2020). Furthermore, a designer should also consider chatbot’s capabilities for natural language conversation and how it can aid instructors, especially in repetitive and low cognitive level tasks such as answering FAQs (Garcia Brustenga et al., 2018).

However, there are potential difficulties in fully replicating the human educator experience with chatbots. While they can provide customized instruction, chatbots may not match human instructors’ emotional support and mentorship. Understanding the importance of human engagement and expertise in education is crucial. They offer students guidance, motivation, and emotional support—elements that AI cannot completely replicate. This study report theoretical and practical contributions in the area of educational chatbots.

Additionally, chatbots can be employed to furnish language learners with supplementary resources and provide immediate assistance such as access to online dictionaries, digital materials, and social media in real-time (Dokukina & Gumanova, 2020; Haristiani & Rifa’i, 2020). AI chatbots offer a multitude of applications in education, transforming the learning experience. They can act as virtual tutors, providing personalized learning paths and assisting students with queries on academic subjects. Additionally, chatbots streamline administrative tasks, such as admissions and enrollment processes, automating repetitive tasks and reducing response times for improved efficiency. With the integration of Conversational AI and Generative AI, chatbots enhance communication, offer 24/7 support, and cater to the unique needs of each student.

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And while chatbots can’t replace the human touch and customer interactions, these bots can take care of simple tasks to allow your teams to be more efficient. Trust us, this increased efficiency is worth the monthly price of chatbot software. Gartner estimates that AI can increase operational efficiency by 25%, specifically around “customer touchpoints [that] can be automated with conversational AI platforms.”