# Internet Wizard for Enhancing Open-Domain Question-Answering Chatbot Knowledge Base in Education
## 1 Introduction  
Chatbots as an application of human-computer interaction have gained significant importance in the last few years and undergone remarkable developments. The growing interest in chatbots can be attributed to the proliferation of mobile devices over the past decade. As these smart devices, such as smartphones, have become increasingly popular, so too have the applications that run on them, including chatbots. Consequently, chatbots have transformed the ways in which humans interact with technology and have created new opportunities for organizations and businesses to engage with their clients. These programs are designed to perform a wide range of tasks in an automated manner, making them a useful tool in various settings [1]. Chatbots, also called conversational agents, can be defined as conversational or interactive agents that provide an instant response to the user [2, 3]. A computer program or artificial intelligence tool that conducts a conversation using auditory or textual methods. Chatbots, or conversational agents, have been around since the development of the first application in 1960 called ELIZA by [PERSON] at MIT. ELIZA used natural language processing (NLP) to recognize patterns and act as a therapist [4]. Other notable examples include ALICE, developed by [PERSON] in 1995, which uses Artificial Intelligence Markup Language (AIML) for pattern matching to recognize inputs and generate responses [5]. In the past, chatbots were primarily used in the customer service industry, but in recent years, they have become more sophisticated and able to understand and respond to more complex inputs. They are now used in a wide range of industries, such as healthcare [6; 7], finance [8; 9], customer service [10; 11], individualized support via intelligent audio device [12], and education such as using chatbots to learn Computer Programming concepts [3; 13; 14]. Their widespread adoption is anticipated to grow even further in the future [15]. Educational institutions have increasingly adopted chatbots to enhance educational support and provide information to students. They are implemented in various settings, including schools, universities, and online platforms, as mobile web applications. Through chatbots, students can instantly access standardized details, such as course materials [16], practice questions and answers [17; 18], evaluation criteria [19; 20], assignment due dates, advice [21], and study materials. Implementing such systems can enhance student engagement, reduce the administrative burden on lecturers, and allow for more focus on curriculum development [16]. Chatbots not only help students develop their interaction skills but also assist teaching faculty by automating some of their tasks [22]. Integrating chatbots with education improves connectivity, efficiency, and reduces uncertainty in interactions [23; 24], leading to personalized, and result-oriented online learning experiences [16], which are vital for today's educational institutions. Furthermore, chatbots increase the level of support provided to each student, reducing the likelihood of ineffective learning and dropouts [25; 26]. Chatbots, whether domain-specific or open-domain, usually undergo a training process that involves teaching them to understand and respond to user inputs in a natural and human-like manner. This is achieved through the use of machine learning techniques, including natural language processing (NLP) and deep learning. Various natural language processing (NLP) models, including BERT, RoBERTa, GPT-2, and GPT-3, are utilized for developing open-domain chatbots. These models are trained on extensive general-domain text data and fine-tuned on task-specific datasets to adapt them to the chatbot's purpose [27; 28; 29]. Commonly used datasets, such as pushshift.io Reddit [30] and Empathetic Dialogues [31], are used to train the weights of a Transformer encoder-decoder, as seen in state-of-the-art chatbots such as Meena [32] and BlenderBot [33].