Adaptive Learning Management System by using chatbot Based on Learner Preferences Project for computer science students.
Project Domain / Category
E-Learning Web Application by using Artificial Intelligence (AI) and Natural Language Processing technique.
Abstract/Introduction
E-learning is considered as the new alternative to the traditional learning environment. In the E-Learning system context, each individual is able to receive a teaching strategy that is more fine-tuned to its learning style. The success of E-learning is based on flexibility and ease of use and diversity in assessments are the major factors having a leading role in E-Learning implementation.
The learning management system is playing a major role in an E-Learning environment. Natural language processing combined with Artificial Intelligence can be used in an E-learning environment.
This conversational chatbot can be used in an E-Learning environment. Chatbots are a form of artificial intelligence associated with natural language processing that interacts with users in a human-like manner.
Often, this technology used as personal assistants and has become accessible to almost anyone thanks to mobile phones. Chatbots are capable of asking a vast number of questions to change how online learning is conducted.
Today, chatbots are the bridge between technology and education. Chatbots create an interactive learning experience, similar to one-on-one training with a teacher. Chatbots now play a vital role in education and can be used in several areas of learning. The machine-learning chatbots are still in the early days; in many cases, it is obvious that the learner is interacting with a chatbot.
Functional Requirements:
Our proposed Adaptive Learning Management System by using Chatbot (ALMSC) offers the learning environment for every user. Learning Management Systems (LMSs) are used in many (educational) institutes to manage the learning process.
Adaptive Learning Environment with the help of chatbot offers support for the learning process through adaptive guidance and provisioned personalized learning material.
The goal of ALMSC is to perform the following activities.
- Learners used the learner ID and password to access the Learning management system. Pop up window should be displayed at the bottom right of our Leaning Management
The system by prompting the user for any kind of guidance.
- Chatbot also used an avatar or an animated character, ensure the chatbot’s appearance that is sync with the audience it addresses.
- Chatbot correctly guesses the most likely gender of a name Gender agreement is important for being able to bind the referent with a correct anaphor. i.e. binding “he” with “Ali”.
- Conversation Flow — When a human talks to a human, he or she rarely plan the entire dialog in advance. When a human talks to a bot, this conversation has to be guided. The thing is, conversation flow is a dialog tree. It visualizes expected user-bot interactions and makes sure every user request is covered by some part of the bot’s logic. To make the conversation flow smooth and efficient, it’s important to apply the best practices and build a chatbot. For this Machine learning algorithms be used by taking into account business objectives and learners’ expectations.
- The chatbot should already be “taught” common questions so that it can Answering learner questions and respond immediately to learners’ questions.
- Quizzing learners—chatbots can quiz learners on vocabulary or other fact-based learning to prepare for quizzes, ensure that learning sticks, or just for fun. An intelligent chatbot can even adopt, personalizing the questions asked or information reviewed to the individual learner, and adjusting to the learner’s responses.
- Assessment—chatbots can administer quizzes or other assessments and collect responses.
- Enrollment—an adaptive chatbot can perform enrollment and course selection activities. Prerequisites and other requirements are already taught to the chatbots. By using the knowledge base chatbots can enroll eligible learners in the correct courses, saving human staff a lot of time.
- Programming language syntax–In case the learner is interested in understanding programming language our chatbot can answer the proper syntax of programming language statements.
- For successful human-like interaction, chatbots need a perfect tone and dialect. To achieve coherence, a character is used to effectively communicate in audio synced with the text.
- Chatbot used a list of Frequently Asked Questions to generate a chatbot’s list of pre-programmed queries and responses.
- In case of user asks some specific topic or research question, chatbot provisioned the appropriate link and provide material to its intended user.
Tools: JSP, SQL server 2008, Dialogflow, IBM Watson, Microsoft Bot Framework, Wit.ai, Api.ai, Chatfuel.
