Adaptive Learning Management System by using chatbot Based on Learner Prefrences

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 for the traditional learning environment. In E- Learning system context
each individual is able to receive teaching strategy that is more fine- tuned to its learning style. Success of E-learning is
based on flexibility and ease of use and diversity in assessments are the major factors having leading role in E-Learning
implementation. Learning management system are playing major role in E-Learning environment. Natural language
processing combined with Artifical Intelligences can be used in E-learning environment. For this conversational
chatbot can be used in 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 becoming 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 a 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 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 following activities.
 Learner used the learnerID and password to access the Learning management system. Pop up window should
be displayed at the bottom right of our Leaning Management 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 guess 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 plans the entire dialog in advance.
When a human talksto a bot, this conversation hasto 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 logics. To make conversation flow smooth and efficient, it’s important to apply the best practices and
build chatbot. For this Machine learning algorithms be used by taking into account business objectives and
learners’ expectations.
 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 adapt, 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—adaptive chatbot can perform the 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 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 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.