Sentiment Analysis for Therapy Chatbots: A Comparison of Supervised Learning Approaches IEEE Conference Publication

Google Bard seamlessly integrates AI technology with an extensive knowledge repository. As a virtual study partner, it delivers quick answers to questions and provides invaluable research assistance. Google Bard ensures students have access to a vast information database, fostering a thirst for knowledge. With active listening skills, Juji chatbots can help educational organizations engage with their audience (e.g., existing or prospect students) 24×7, answering questions and providing just-in-time assistance.

QnABot on AWS is an all-encompassing educational companion, assisting students with a wide range of tasks. From answering general knowledge questions to providing in-depth explanations and guidance on complex topics, it serves as a valuable resource for students seeking comprehensive educational support and insights. A scripted chatbot, also called a rule-based chatbot, can engage in conversations by following a decision tree that has been mapped out by the chatbot designer, and follow an if/then logic. In contrast, NLP chatbots, which use Artificial Intelligence, make sense of what the person writes and respond accordingly (NLP stands for Natural Language Processing).

The related chatbot was implemented and evaluated in Moroccan public schools with the support of teachers from the Regional Center for Education and Training Professions of Souss Massa. One is a control class group that uses a traditional approach, while the other two are experimental groups that employ digital content and the chatbot-based method. Preliminary findings indicate that employing chatbots can greatly enhance student learning experiences by allowing them to study at their own speed with less stress, saving them time, and keeping them motivated. Furthermore, integrating these AI systems into a smart classroom will not only create a supportive environment by encouraging good interactions with students, it will also allow learners to be more engaged and achieve better academic objectives.

Stanford has academic skills coaches that support students in developing metacognitive and other skills, but you might also integrate metacognitive activities into your courses with the assistance of an AI chatbot. For example, you and your students could use a chatbot to reflect on their experience working on a group project or to reflect on how to improve study habits. We advise that you practice metacognitive routines first, before using a chatbot, so that you can compare results and use the chatbot most effectively. Keep in mind that the tone or style of coaching provided by chatbots may not suit everyone. Enterprise-grade, self-learning generative AI chatbots built on a conversational AI platform are continually and automatically improving. They employ algorithms that automatically learn from past interactions how best to answer questions and improve conversation flow routing.

Chatbot platforms: key feature overview table

For these and other geopolitical reasons, ChatGPT is banned in countries with strict internet censorship policies, like North Korea, Iran, Syria, Russia, and China. Several nations prohibited the usage of the application due to privacy apprehensions. Meanwhile, North Korea, China, and Russia, in particular, contended that the U.S. might employ ChatGPT for disseminating misinformation. Conversely, OpenAI restricts access to ChatGPT in certain countries, such as Afghanistan and Iran, citing geopolitical constraints, legal considerations, data protection regulations, and internet accessibility as the basis for this decision.

None of the studies discussed the platforms on which the chatbots run, while only one study (Wollny et al., 2021) analyzed the educational roles the chatbots are playing. The study used “teaching,” “assisting,” and “mentoring” as categories for educational roles. This study, however, uses different classifications (e.g., “teaching agent”, “peer agent”, “motivational agent”) supported by the literature in Chhibber and Law (2019), Baylor (2011), and Kerlyl et al. (2006). Other studies such as (Okonkwo and Ade-Ibijola, 2021; Pérez et al., 2020) partially covered this dimension by mentioning that chatbots can be teaching or service-oriented. Chatbots have been utilized in education as conversational pedagogical agents since the early 1970s (Laurillard, 2013).

Additionally, Wollny et al. (2021) argued that educational chatbots make education more available and easily accessible. A conversational agent can hold a discussion with students in a variety of ways, ranging from spoken (Wik & Hjalmarsson, 2009) to text-based (Chaudhuri et al., 2009) to nonverbal (Wik & Hjalmarsson, 2009; Ruttkay & Pelachaud, 2006). Similarly, the agent’s visual appearance can be human-like or cartoonish, static or animated, two-dimensional or three-dimensional (Dehn & Van Mulken, 2000).

• If you want to jump straight to our detailed reviews, click on the platform you’re interested in on the list above.
• Now we can easily explore all kinds of activities related to our studies, thanks to these friendly AI companions by our side.
• 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%.
• Renowned brands such as Duolingo and Mondly are employing these AI bots creatively, enhancing learner engagement and facilitating faster comprehension of concepts.
• Airlines KLM and Aeroméxico both announced their participation in the testing;[32][33][34][35] both airlines had previously launched customer services on the Facebook Messenger platform.

The authors have no financial interests or affiliations that could have influenced the design, execution, analysis, or reporting of the research. 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.

The integration of chatbots into the education sector is revolutionizing the way students learn and interact with educational institutions. These AI-driven conversational agents offer a multitude of advantages, enhancing the educational experience for both students and educators. From fostering interactive learning experiences to adapting to individual learning styles and offering quick access to information, AI-powered education chatbots are reshaping education into a more personalized, efficient, and engaging journey.

Learning performance for the course

Furthermore, the evaluations of the AICs by both Spanish and Czech cohorts displayed similar results. This analysis led us to conclude that language nativeness and the specific educational settings of the participants were not key factors influencing the results of our study. Regarding gender, 81% of the participants were females, while 19% were male students. The landscape of mobile-application language learning (MALL) has been significantly reshaped in recent years with the incorporation of AICs (Pham et al., 2018). This innovative approach to mobile learning has been positively received by both students and teachers. For example, Chen et al. (2020) highlighted the effectiveness of AICs for Chinese vocabulary learning by comparing chatbot-based tutoring with traditional classroom settings.

A chatbot for education is a specialized type of artificial intelligence (AI) software designed to simulate conversation with users, providing them with automated responses to their inquiries. In the context of the education sector, these chatbots are tailored to meet the specific needs of students, educators, and administrative staff. To summarize, incorporating AI chatbots in education brings personalized learning for students and time efficiency for educators.

However, this situation presents a unique opportunity, accompanied by unprecedented challenges. Consequently, it has prompted a significant surge in research, aiming to explore the impact of chatbots on education. Multilingual chatbots act as friendly language ambassadors, breaking down barriers for students from diverse linguistic backgrounds. Their ability to communicate in various languages fosters inclusivity, ensuring that all students can learn and engage effectively, irrespective of their native language. Through this multilingual support, chatbots promote a more interconnected and enriching educational experience for a globally diverse student body.

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. In conversations with other people, we routinely ask for clarifying details, repeat ideas in different ways, allow a conversation to go in unexpected directions, and guide others back to the topic Chat GPT at hand. For example, if you are using a chatbot to reflect on a recent experience and to think of possible next steps, a conversational tone might yield better results. Try beginning the same way you would begin a chat conversation with a colleague or acquaintance. Bing Chat, an AI chatbot developed by Microsoft, also uses the GPT large language model.

The streamlined evaluation process offers precise evaluations of student performance. This gives transparent and structured assessment outcomes to educatee, faculty, and stakeholders. 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. Students’ perception of institutional support for chatbot integration influences their acceptance.

AI chatbots can be attentive to – and train on – students’ learning habits and areas of difficulty. It has been scientifically proven that not everyone understands and learns in the same way. To cater to the needs of every student in terms of complex topics or subjects, chatbots can customize the learning plan and make sure that students gain maximum knowledge – in the classroom and even outside.

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As such, we mitigated this risk by cross-checking the work done by each reviewer to ensure that no relevant article was erroneously excluded. We also discussed and clarified all doubts and gray areas after analyzing each selected article. Visual cues such as progress bars, checkmarks, or typing indicators can help users understand where they are in the conversation and what to expect next. Predicted to experience substantial growth of approximately $9 billion by 2029, the Edtech industry demonstrates numerous practical applications that highlight the capabilities of AI and ML. Guided analysis of how AI can affect your own courses and teaching practice, covering ethical issues, student success issues, and workload balance.

Equally, for motivational belief, which is the central aspect needed to encourage strategic learning behavior (Yen, 2018). A well-functioning team can leverage individual team members’ skills, provide social support, and allow for different perspectives. This can lead to better performance and enhance the learning experience (Hackman, 2011). 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. Remember to take the lead when using chatbots for team projects, making your own choices while incorporating the helpful and discarding what is not. Metacognitive skills can help students understand how learning works, increase awareness of gaps in their learning, and lead them to develop study techniques (Santascoy, 2021).

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. Exploring the long-term effects, optimal integration strategies, and addressing ethical considerations should take the forefront in research initiatives. Yellow.ai is an excellent conversational AI platform vendor that can help you automate your business processes and deliver a world-class customer experience.

AI chatbots equipped with sentiment analysis capabilities can play a pivotal role in assisting teachers. 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.

The is one of the top chatbot platforms that was awarded the Loebner Prize five times, more than any other program. It offers a live chat, chatbots, and email marketing solution, as well as a video communication tool. You can create multiple inboxes, add internal notes to conversations, and use saved replies for frequently asked questions.

Such a streamlined approach will assist learning centers in reducing manual efforts required for materials update, thereby fostering convenient resource utilization. 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. Overloaded due to tight scheduling and plenty of daily duties, educators often face challenges. Invaluable teaching assistants can give a hand with automation tasks like tests, assessments, and assignment tracking.

Another example is the study presented in (Ondáš et al., 2019), where the authors evaluated various aspects of a chatbot used in the education process, including helpfulness, whether users wanted more features in the chatbot, and subjective satisfaction. The students found the tool helpful and efficient, albeit they wanted more features such as more information about courses and departments. In comparison, 88% of the students in (Daud et al., 2020) found the tool highly useful. Shows that ten (27.77%) articles presented general-purpose educational chatbots that were used in various educational contexts such as online courses (Song et al., 2017; Benedetto & Cremonesi, 2019; Tegos et al., 2020). The approach authors use often relies on a general knowledge base not tied to a specific field. Most importantly, chatbots played a critical role in the education field, in which most researchers (12 articles; 33.33%) developed chatbots used to teach computer science topics (Fig. 4).

With our AI chatbots in education, schools can engage with prospective students right from the point of admission to making learning fun for them.If your educational institution is looking for an AI chatbot, schedule a demo and have a conversation with our experts. They can guide you through the process of deploying an educational chatbot and using it to its full potential. Chatbots in education offer unparalleled accessibility, functioning as reliable virtual assistants that remain accessible around the clock. Much like a dedicated support system, they tirelessly cater to the needs of both students and teachers, providing prompt responses and assistance at any time, day or night.

During the 1-month intervention period in each educational setting, participants independently completed the assessment reports. They were instructed to provide personal feedback on their interaction with each AIC, using the template to note both positive and negative aspects. Additionally, they were asked to attach 12 screenshots illustrating their interaction, three with each AIC, to support their assessment. QDA Miner Software was used for textual analysis of students’ written evaluations on each AIC, adhering to a provided template.

Nevertheless, Hobert (2019) claims that the main issue with EC assessment is the narrow view used to evaluate outcomes based on specific fields rather than a multidisciplinary approach. Furthermore, there is a need for understanding how users experience chatbots (Brandtzaeg & Følstad, 2018), especially when they are not familiar with such intervention (Smutny & Schreiberova, 2020). Conversely, due to the novelty of ECs, the author has not found any studies pertaining to ECs in design education, project-based learning, and focusing on teamwork outcomes. Bii (2013) defined educational chatbots as chatbots conceived for explicit learning objectives, whereas Riel (2020) defined it as a program that aids in achieving educational and pedagogical goals but within the parameters of a traditional chatbot. Empirical studies have positioned ECs as a personalized teaching assistant or learning partner (Chen et al., 2020; Garcia Brustenga et al., 2018) that provides scaffolding (Tutor Support) through practice activities (Garcia Brustenga et al., 2018). They also support personalized learning, multimodal content (Schmulian & Coetzee, 2019), and instant interaction without time limits (Chocarro et al., 2021).

The theta-gamma neural code ensures streamlined information transmission, akin to a postal service efficiently packaging and delivering parcels. This aligns with “neuromorphic computing,” where AI architectures mimic neural processes to achieve higher computational efficiency and lower energy consumption. Learn about how the COVID-19 pandemic rocketed the adoption of virtual agent technology (VAT) into hyperdrive. IBM watsonx Assistant provides customers with fast, consistent and accurate answers across any application, device or channel. By sending questions on various subjects via messaging apps, QuizBot helps students retain information more effectively and prepare for exams in a fun and interactive way. Since different researchers with diverse research experience participated in this study, article classification may have been somewhat inaccurate.

The level of the assessment becomes more challenging as the student makes progress. A slightly different interaction is explained in (Winkler et al., 2020), where the chatbot challenges the students with a question. If they answer incorrectly, they are explained why the answer is incorrect and then get asked a scaffolding question.

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). In terms of the medium of interaction, chatbots can be text-based, voice-based, and embodied. 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.

It has also been observed that some students’ interest dwindled after the initial period of engagement due to repetitive conversation patterns and redundancies, making the interaction less natural compared to student–teacher exchanges (Fryer et al., 2019). This line of research investigates how the interactive nature of some AICs can reduce students’ anxiety and cognitive load (Hsu et al., 2021) and promote an engaging learning environment (Bao, 2019). Furthermore, some authors have examined the ability of chatbots to promote self-directed learning, given their wide availability and capacity for personalized responses (Annamalai et al., 2023). 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.

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Hobert and Meyer von Wolff (2019), Pérez et al. (2020), and Hwang and Chang (2021) examined the evaluation methods used to assess the effectiveness of https://chat.openai.com/. You can foun additiona information about ai customer service and artificial intelligence and NLP. The authors identified that several evaluation methods such as surveys, experiments, and evaluation studies measure acceptance, motivation, and usability. Concerning their interaction style, the conversation with chatbots can be chatbot or user-driven (Følstad et al., 2018). Chatbot-driven conversations are scripted and best represented as linear flows with a limited number of branches that rely upon acceptable user answers (Budiu, 2018).

The ability of AI chatbots to accurately process natural human language and automate personalized service in return creates clear benefits for businesses and customers alike. Usually, weak AI fields employ specialized software or programming languages created specifically for the narrow function required. For example, A.L.I.C.E. uses a markup language called AIML,[3] which is specific to its function as a conversational agent, and has since been adopted by various other developers of, so-called, Alicebots. Nevertheless, A.L.I.C.E. is still purely based on pattern matching techniques without any reasoning capabilities, the same technique ELIZA was using back in 1966. This is not strong AI, which would require sapience and logical reasoning abilities.

• Keep in mind that the tone or style of coaching provided by chatbots may not suit everyone.
• 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.
• However, concerns arise regarding the accuracy of information, fair assessment practices, and ethical considerations.
• Various design principles, including pedagogical ones, have been used in the selected studies (Table 8, Fig. 8).
• Try different ways of interacting and responding to the chatbot to get a sense of its capabilities.
• This allows the teacher to tweak the chatbot’s design to improve the experience.

This can in turn prompt you to give more specific details and instructions that can yield better results. Genesys DX comes with a dynamic search bar, resource management, knowledge base, and smart routing. This can help you use it to its full potential when making, deploying, and utilizing the bot. Installing an AI chatbot on your website is a small step for you, but a giant leap for your customers.

AI and chatbots have a huge potential to transform the way students interact with learning. They promise to forever change the learning landscape by offering highly personalized experiences for students through tailored lessons. 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. Institutional staff, especially teachers, are often overburdened and exhausted, working beyond their office hours just to deliver excellent learning experiences to their students. Repetitive tasks can easily be carried out using chatbots as teachers’ assistants.

In this research, the term chatbot (AIC) is used to refer to virtual tutors integrated into mobile applications specifically designed for language learning to provide students with a personalized and interactive experience. These AICs may cover different aspects of language learning, such as grammar, vocabulary, pronunciation, and listening comprehension, and use various techniques to adapt to the user’s level of proficiency and tailor their responses accordingly. educational chatbots For example, students may ask the peer agent in (Janati et al., 2020) how to use a particular technology (e.g., using maps in Oracle Analytics), while the peer agent described in (Tegos et al., 2015; Tegos et al., 2020; Hayashi, 2013) scaffolded a group discussion. Interestingly, the only peer agent that allowed for a free-style conversation was the one described in (Fryer et al., 2017), which could be helpful in the context of learning a language.

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. While AI models offer numerous benefits, these limitations highlight the importance of continuous improvements. Addressing the main restrictions can lead to more robust and efficient chatbot implementations. Chatbots must be designed with strict privacy and security controls to safeguard sensitive information. A strategic plan is essential to organize and present this data through the chatbot without overwhelming the user. We recommend using respond.io, an AI-powered customer conversation management software.

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. Further, we excluded tutorials, technical reports, posters, and Ph.D. thesis since they are not peer-reviewed. Only a few studies partially tackled the principles guiding the design of the chatbots.

This is one of the best AI chatbot platforms that assists the sales and customer support teams. It will give you insights into your customers, their past interactions, orders, etc., so you can make better-informed decisions. Any advantage of a chatbot can be a disadvantage if the wrong platform, programming, or data are used. Traditional AI chatbots can provide quick customer service, but have limitations. Many rely on rule-based systems that automate tasks and provide predefined responses to customer inquiries. Artificial intelligence can also be a powerful tool for developing conversational marketing strategies.

One of the most popular use cases for chatbots in education is helping with homework. These chatbots help students understand complex topics, provide step-by-step solutions, and offer tips for completing assignments. Chatbots have affordances that can take out-in-the-world learning to the next level. The most important of those affordances is that chatbots can respond differently to each learner, depending on what they say or ask, so the experience adapts to the learner. This can increase the learner’s sense of agency and their ownership of the learning process. 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.

Conversational Agents (CAs) are among the most prominent AI systems for assisting teaching and learning processes. Their integration into an e-learning system can provide replies suited to each learner’s specific needs, allowing them to study at their own pace. In this paper, based on recent advancements in Natural Language Processing (NLP) and deep learning techniques, we present an experimental implementation of an educational chatbot intended to instruct secondary school learners Logo, an educational programming language.

Software engineers might want to integrate an AI chatbot directly into their complex product. AI chatbots are commonly used in social media messaging apps, standalone messaging platforms, proprietary websites and apps, and even on phone calls (where they are also known as integrated voice response, or IVR). The terms chatbot, AI chatbot and virtual agent are often used interchangeably, which can cause confusion. While the technologies these terms refer to are closely related, subtle distinctions yield important differences in their respective capabilities.

Master Tidio with in-depth guides and uncover real-world success stories in our case studies. Discover the blueprint for exceptional customer experiences and unlock new pathways for business success. A vivid example has recently made headlines, with OpenAI expressing concern that people may become emotionally reliant on its new ChatGPT voice mode.

We potentially missed other interesting articles that could be valuable for this study at the date of submission. While using questionnaires as an evaluation method, the studies identified high subjective satisfaction, usefulness, and perceived usability. The questionnaires used mostly Likert scale closed-ended questions, but a few questionnaires also used open-ended questions. Pérez et al. (2020) identified various technologies used to implement chatbots such as Dialogflow Footnote 4, FreeLing (Padró and Stanilovsky, 2012), and ChatFuel Footnote 5.