Chatbots for Education Use Cases & Benefits

Hence, when both classes had the same team-based project task, the homogenous nature of the sampling may have attributed to the similarities in the outcome that overshadowed the effect of the ECs. Equally, for motivational belief, which is the central aspect needed to encourage strategic learning behavior (Yen, 2018). Subsequently, motivational beliefs are reflected by perceived self-efficacy and intrinsic values students have towards their cognitive engagement and academic performance (Pintrich & de Groot, 1990). According to Pintrich et al. (1993), self-efficacy and intrinsic value strongly correlate with task value (Eccles & Wigfield, 2002), such as interest, enjoyment, and usefulness.

Peer agents allowed students to ask for help on demand, for instance, by looking terms up, while teachable agents initiated the conversation with a simple topic, then asked the students questions to learn. Motivational agents reacted to the students’ learning with various emotions, including empathy and approval. The surveyed articles used different types of empirical evaluation to assess the effectiveness of chatbots in educational settings. In some instances, researchers combined multiple evaluation methods, possibly to strengthen the findings. 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.

Limits and future directions

This means that Google Bard is more likely to be up-to-date on current events, while ChatGPT is more likely to be accurate in its responses to factual questions (AlZubi et al., 2022; Rahaman et al., 2023; Rudolph et al., 2023). Additionally, speech technologies emerged as an area requiring substantial https://chat.openai.com/ improvement, in line with previous results (Jeon et al., 2023). With the exception of Buddy.ai, the voice-based interactions provided very low results due to poor speech recognition and dissatisfaction with the synthesized voice, potentially leading to student anxiety and disengagement.

Nonetheless, certain researchers, including Ayedoun et al. (2015) and Fryer et al. (2019), have indicated that the initial enthusiasm and engagement students show towards chatbots may be short-lived, attributing this to the novelty effect of this technology. 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. Such programs gather comments on various subjects like study material, teaching approaches, assignments, and more.

With a one-time investment, educators can leverage a self-improving algorithm to design online courses and study resources that go beyond the one-size-fits-all approach, dismantling the age-old education structures. Chatbots will be virtual assistants that offer instant help and answer questions whenever students get stuck understanding a concept. 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. By addressing these challenges, we believe that chatbots can become effective educational tools capable of supporting learners with informative feedback.

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. You can picture it as a sidekick in your pocket, one that has been trained at the d.school, has “learned” a large number of design methods, and is always available to offer its knowledge to you. 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.

1 Research questions

The remaining articles (13 articles; 36.11%) present chatbot-driven chatbots that used an intent-based approach. 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). Five articles (13.88%) presented desktop-based chatbots, which were utilized for various purposes. For example, one chatbot focused on the students’ learning styles and personality features (Redondo-Hernández & Pérez-Marín, 2011). As another example, the SimStudent chatbot is a teachable agent that students can teach (Matsuda et al., 2013). 63.88% (23) of the selected articles are conference papers, while 36.11% (13) were published in journals.

The fifth question addresses the principles used to design the proposed chatbots. Examples of such principles could be collaborative and personalized learning. The sixth question focuses on the evaluation methods used to prove the effectiveness of the proposed chatbots. Finally, the seventh question discusses the challenges and limitations of the works behind the proposed chatbots and potential solutions to such challenges. Incorporating AI chatbots in education offers several key advantages from students’ perspectives. AI-powered chatbots provide valuable homework and study assistance by offering detailed feedback on assignments, guiding students through complex problems, and providing step-by-step solutions.

Based on a mixed-method quasi-experimental approach, ECs were found to improve learning performance and teamwork with a practical impact. Moreover, it was found that ECs facilitated collaboration among team members that indirectly influenced their ability to perform as a team. Nevertheless, affective-motivational learning outcomes such as perception of learning, need for cognition, motivation, and creative self-efficacy were not influenced by ECs. Henceforth, this study aims to add to the current body of knowledge on the design and development of EC by introducing a new collective design strategy and its pedagogical and practical implications. However, the study also highlights the challenges that need to be addressed, such as the requirement for more sophisticated AI algorithms capable of adjusting to the learner’s proficiency level and the improvement of speech technologies.

They facilitate communication of homework details, schedules, and answer queries. Furthermore, they aid in conducting assessments, even in courses requiring subjective evaluations. These bots offer individualized support to learners, providing guidance, and aiding in workload management for both teachers and educatee. chatbot in education By streamlining routine activities, chatbots help pedagogues focus on delivering high-quality knowledge and monitoring attendees’ progress. These intelligent assistants are capable of answering queries, providing instant feedback, offering study resources, and guiding educatee through academic content.

Ensuing, the researcher also considered creative self-efficacy, defined as the students’ belief in producing creative outcomes (Brockhus et al., 2014). Prior research has not mentioned creativity as a learning outcome in EC studies. However, according to Pan et al. (2020), there is a positive relationship between creativity and the need for cognition as it also reflects individual innovation behavior. Likewise, it was deemed necessary due to the nature of the project, which involves design. Lastly, teamwork perception was defined as students’ perception of how well they performed as a team to achieve their learning goals.

These features include the ability to customize avatars (age, gender, voice, etc.) similar to intelligent conversational agents such as Replika. For example, incorporating familiar characters from cartoons or video games into chatbots can enhance engagement, particularly for children who are learning English by interacting with their favorite characters. Furthermore, by incorporating Augmented Reality (AR) technology, avatars can be launched and video calls can be enabled on social platforms such as Kuki.ai, thereby adding a layer of personal interaction.

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The Design Experience dimension (DEX) underscored the importance of user-friendly interfaces and engaging multimedia content in fostering user engagement and satisfaction. The findings uncovered the necessity for enhancements in adaptive user interfaces, as well as the incorporation of social media and emerging technologies, to simulate the human-student interaction and enrich the language learning experience. The User Experience dimension (UEX) revealed that while some AICs were able to provide a moderate level of enjoyment and engagement, overall satisfaction levels were not as positive as expected. This indicates the need for AICs to offer a more personalized learning experience to sustain learner engagement and interest. Expanding on the necessity for improved customization in AICs, the integration of different features can be proposed to enhance chatbot-human personalization (Belda-Medina et al., 2022).

According to Hadjielias et al. (2021), the cognitive state of teams involved in digital innovations is usually affected by the task involved within the innovation stages. Nevertheless, enhancing such skills is often time-consuming, and teachers are usually not mentally prepared to take up a designer’s (Kim, 2021) or programmer’s role. The solution may be situated in developing code-free chatbots (Luo & Gonda, 2019), especially via MIM (Smutny & Schreiberova, 2020).

• These programs have one or a few functionalities that tackle specific problems.
• Effective tutors may use questioning techniques, collaborative problem-solving, and personalized instruction to support their students.
• Now we can easily explore all kinds of activities related to our studies, thanks to these friendly AI companions by our side.

Ivy Tech Community College in Indiana developed a machine learning algorithm to identify at-risk students. Their experiment aided 3,000 participants, and 98% of those who received support achieved a grade of C or higher. Digital assistants address queries and exchange information regarding lectures, assignments, or events. Furthermore, institutions leveraging chatbots witness higher conversion rates, thereby contributing to overall success. Conversational AI is revolutionizing the way businesses communicate with their customers and everyone is loving this new way. Businesses are adopting artificial intelligence and investing more and more in it for automating different business processes like customer support, marketing, sales, customer engagement and overall customer experience.

Limitations of Educational Chatbots and Why It’s Vital to Address Them

From one day to the next, instructors had to figure out how to teach in a distributed and chimeric space, in which their home office — or kitchen, or living room — was connected to the many home spaces (or coffee shops) where the students could find access to Wi-Fi. You can foun additiona information about ai customer service and artificial intelligence and NLP. It was a great opportunity to be creative and figure out how to activate in-context learning, taking advantage of the unique spaces where the students were, and the wide world out there. For example, when using a chatbot to practice providing supportive language as an instructor, you might ask a chatbot “Please act as an anxious first-year college student from an under-represented minority coming into office hours for the first time” (Chen, 2023).

Furthermore, in regard to problems faced, it was observed that in the EC group, the perception transformed from collaboration issues towards communicative issues, whereas it was the opposite for the CT group. 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.

The ability to transfer skills and knowledge that you learned to a new situation involves abstract thinking, problem-solving, and self-awareness. Deliberate practice, such as role-playing, can help you develop these transfer skills. AI chatbots can help with developing scenarios, role-playing a situation, and providing feedback. For example, you might prompt the chatbot to create a realistic ethical dilemma that applies to the discipline or to role-play as a patient or client in a relevant scenario. As you begin to explore, think about what you already know and the opinions you may already hold about the educational aspects of AI chatbots.

Roleplay enables users to hone their conversational abilities by engaging with virtual characters. Lerners get the opportunity to simulate diverse scenarios, such as planning future vacations, ordering coffee at a Parisian café, shopping for furniture, or inviting a friend for a hike. Pounce provides various essential functions, including sending reminders, furnishing relevant enrollment details, gathering survey data, and delivering round-the-clock support. The primary objective behind Pounce’s introduction was to streamline the admission process. Chatbots ease administrative processes, serving as an efficient interface between students and departments.

Answer to Research Questions

This suggests that while these tools have made strides in providing language-related features, there is still room for improvement, particularly in terms of maintaining contextually relevant dialogues and varying sentence complexity based on the learner’s level. The first one delves into the effects of AICs on language competence and skills. These studies showed how AICs can manage personal queries, correct language mistakes, and offer linguistic support in real-time. 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). As Conversational AI and Generative AI continue to advance, chatbots in education will become even more intuitive and interactive.

• Additionally, this will positively impact the brand image, attracting potential applicants and stakeholders.
• Subsequently, motivational beliefs are reflected by perceived self-efficacy and intrinsic values students have towards their cognitive engagement and academic performance (Pintrich & de Groot, 1990).
• In fact, the size of the chatbot market worldwide is expected to be 1.23 billion dollars in 2025 (Kaczorowska-Spychalska, 2019).
• By comprehending student sentiments, these chatbots help educators modify and enhance their teaching practices, creating better learning experiences.

Initially, the total of studies resulting from the databases was 1208 studies. The metadata of the studies containing; title, abstract, type of article (conference, journal, short paper), language, and keywords were extracted in a file format (e.g., bib file format). Subsequently, it was imported into the Rayyan tool Footnote 6, which allowed for reviewing, including, excluding, and filtering the articles collaboratively by the authors. 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.

They help in obtaining information on fee structures, course details, scholarships, and school events. By digitizing enrollment processes and simplifying communication channels, bots reduce the workload for staff. Students’ perception of institutional support for chatbot integration influences their acceptance. If someone feels inadequate support or lacks institutional backing for bot usage in their academic journey, it could result in reluctance or skepticism towards engaging with these tools.

In such a way, institutions commit to academic excellence and foster positive student experiences. For instance, if trainees were absent, the bot could send notes of lectures or essential reminders, to keep them informed while they’re not present. This efficiency contributes to a more enriching learning experience, consequently attracting more students.

Research in this area underscores the importance of understanding users’ viewpoints on chatbots, including their acceptance of these tools in educational settings and their preferences for chatbot-human communication. Similarly, ‘satisfaction’ is described as the degree to which users feel that their needs and expectations are met by the chatbot experience, encompassing both linguistic and design aspects. Studies like those by Chocarro et al. (2023) have delved into students’ enjoyment and engagement with chatbots, highlighting the importance of bot proactiveness and individual user characteristics in shaping students’ satisfaction with chatbots in educational settings. While chatbots serve as valuable educational tools, they cannot replace teachers entirely. Instead, they complement educators by automating administrative tasks, providing instant support, and offering personalized learning experiences.

Additionally, educators can use AI chatbots to create tailored learning materials and activities to accommodate students’ unique interests and learning styles. This study report theoretical and practical contributions in the area of educational chatbots. Firstly, given the novelty of chatbots in educational research, this study enriched the current body of knowledge and literature in EC design characteristics and impact on learning outcomes. Even though the findings are not practically satisfactory with positive outcomes regarding the affective-motivational learning outcomes, ECs as tutor support did facilitate teamwork and cognitive outcomes that support project-based learning in design education.

This subtle intersection of language cues and language identities embeds a message in every dialogical exchange. So, artificial intelligence must embed the power of cultural cues in its communicative pathways. “Second, teachers can use the tool as a way of generating many examples and nonexamples of a form or genre. Often, teachers have the resources and bandwidth to find or create one or two models of a particular kind of writing — say, a personal narrative about a family relationship. As a result, students may come to believe that there is only one way to write such a narrative. ChatGPT allows teachers to offer students many examples of a narrative about family where the basic content remains the same but style, syntax, or grammar differ.

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.

Secondly, we aim to explore the pedagogical roles of chatbots in the existing literature (Goal 2) to understand how chatbots can take over tasks from teachers. (Winkler and Soellner, 2018) and (Pérez-Marín, 2021), identified research gaps for supporting meta-cognitive skills with chatbots such as self-regulation. This requires a chatbot application that takes a mentoring role, as the development of these meta-cognitive skills can not be achieved solely by information delivery. Within our review we incorporate this by reviewing the mentoring role of chatbots as (Goal 3). Another key element for a mentoring chatbot is adaptation to the learners needs.

Using such models, institutions can engage with graduates, fostering a sense of community. According to the survey conducted among 1,000 secondary school attendees, 67% of learners admitted using AI tools. What’s more interesting is that 42% of those surveyed apply this technology in math, while 41% use it for writing essays. 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.

With many examples to compare and analyze, students can begin to see the relationship between form and content. They can develop criteria for what makes a strong piece of writing, or how one verb might affect readers differently than another. For teachers, designing instruction has just become much easier — ChatGPT is essentially a tool for creating contrasting cases, and most teachers will be delighted that ChatGPT is doing a lot of the legwork for them. 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. Moreover, this will provide opportunities for mentorship and collaboration between current attendees and alums.

The streamlined evaluation process offers precise evaluations of student performance. This gives transparent and structured assessment outcomes to educatee, faculty, and stakeholders. While AI models offer numerous benefits, these limitations highlight the importance of continuous improvements. Addressing Chat PG the main restrictions can lead to more robust and efficient chatbot implementations. Admitting hundreds of students with varied fee structures, course details, and specializations can be a task for administrators. Also, with so many variations, there is a scope for human error in the admission process.