How ChatGPT is transforming the postdoc experience

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. Concerning their interaction style, the conversation with chatbots can be chatbot or user-driven (Følstad et al., 2018).

Okonkwo and Ade-Ibijola (2021) discussed challenges and limitations of chatbots including ethical, programming, and maintenance issues. 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). Based on my initial explorations of the current capabilities and limitations of both types of chatbots, I opted for scripted chatbots. 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.

Virtual tutoring with AI chatbots

However, the education perfect bot makes the entire process easier and more engaging with its instant feedback mechanism. Therefore, it was hypothesized that using ECs could improve learning outcomes, and a quasi-experimental design comparing EC and traditional (CT) groups were facilitated, as suggested by Wang et al. (2021), to answer the following research questions. Conversely, it may provide an opportunity to promote mental health (Dekker et al., 2020) as it can be reflected as a ‘safe’ environment to make mistakes and learn (Winkler & Söllner, 2018). Furthermore, ECs can be operated to answer FAQs automatically, manage online assessments (Colace et al., 2018; Sandoval, 2018), and support peer-to-peer assessment (Pereira et al., 2019).

AI-powered chatbots are designed to mimic human conversation using text or voice interaction, providing information in a conversational manner. Chatbots’ history dates back to the 1960s and over the decades chatbots have evolved significantly, driven by advancements in technology and the growing demand for automated communication systems. Created by Joseph Weizenbaum at MIT in 1966, ELIZA was one of the earliest chatbot programs (Weizenbaum, 1966). ELIZA could mimic human-like responses by reflecting user inputs as questions. Another early example of a chatbot was PARRY, implemented in 1972 by psychiatrist Kenneth Colby at Stanford University (Colby, 1981).

Peer agents

We also discussed and clarified all doubts and gray areas after analyzing each selected article. 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. Various design principles, including pedagogical ones, have been used in the selected studies (Table 8, Fig. 8).

This means it is necessary for every institution to always guide their students by giving them timely and accurate information. But with no optimization, it is almost impossible to ensure each student is getting proper support. The authors declare that this research paper did not receive any funding from external organizations. The study was conducted independently and without financial support from any source. The authors have no financial interests or affiliations that could have influenced the design, execution, analysis, or reporting of the research. Guided analysis of how AI can affect your own courses and teaching practice, covering ethical issues, student success issues, and workload balance.

The Peril and Promise of Chatbots in Education

Their interactive and conversational nature enhances student engagement and motivation, making learning more enjoyable and personalized. Also, AI chatbots contribute to skills development by suggesting syntactic and grammatical corrections to enhance writing skills, providing problem-solving guidance, and facilitating group discussions and debates with real-time feedback. Overall, students appreciate the capabilities of AI chatbots and find them helpful for their studies and skill development, recognizing that they complement human intelligence rather than replace it. The latest chatbot models have showcased remarkable capabilities in natural language processing and generation. Additional research is required to investigate the role and potential of these newer chatbots in the field of education. 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.

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