Ai Chatbot For Elearning

What Is a Chatbot?

Chatbots are rules-driven services, sometimes powered by artificial intelligence (AI), that help individuals communicate in an online environment. In an e-learning context, AI-powered chatbots make learning more intuitive by helping learners choose, consume and understand content. Rather than clicking buttons, selecting drop-down menu items or tapping on a screen, with chatbots, learners can navigate content through gestures and conversational interactions.

Now, using AI, e-learning developers are moving away from the traditional graphical user interface (GUI) and toward conversational user interface (CUI). AI-driven e-learning is set to radically change the face (and voice!) of online learning.

AI-enabled E-Learning Essentials

To successfully embed AI and chatbot technology into the new e-learning paradigm, course developers will need to keep the following four design pillars in mind:

1. Conversation-focused

E-learning designs will pivot from programmed responses to fixed commands to chatbots that converse as naturally as human beings. Using natural language processing (NLP), the AI will first ask learners how they need help and then “learn” from those interactions so the chatbot can assist learners proactively.

2. AI-focused

With AI, chatbots deliver a learning experience based on past interactions. With the help of deep machine learning (DML), chatbots contextualize what a learner wants to accomplish, using context and content to reach data-driven inferences. For example, if a chatbot discovered that a learner consistently performed poorly when performing a specific task in a software program, it would deliver refresher courses or other content to build those skills.

3. Pervasive Learning

When creating AI-based e-learning, designers will need to ensure that the chatbots can function:

• Across devices (laptops, tablets, smartphones and wearable devices).
• At any location (e.g., at work, at home or at the gym), because learning shouldn’t be location-bound.
• In multiple modes (i.e., hand-scripting, speech, keyboard).
• On demand, anytime that an employee wants to learn something.

The pervasive capability of chatbots adds a convenience element to e-learning that is currently lacking.

4. Proactive Learning

Chatbots are more proactive in enabling learners to consume content more effectively and efficiently. Different people like to learn in different ways, and over time, chatbots can learn employees’ preferences. By proactively simplifying, sequencing and recommending content based on an individual learner’s capacity and preferences, chatbots can make e-learning more “freestyle.” You likely won’t have a single curriculum or course outline, because the chatbot will customize a unique one for every learner.

AI-enabled Chatbots Are Here

The use of AI and chatbots isn’t a distant dream. In fact, consumers use chatbots for all kinds of applications, such as weather bots to provide on-demand forecasts, news bots that customize feeds based on personal preferences, and scheduling bots that coordinate meetings based on multiple calendars.

Conversational AI platforms (CAPs) are the future of e-learning. From recruitment and hiring to training and professional development, CAPs provide a uniquely personalized experience for each user.

Getting Started With AI-enabled Chatbots

If you are interested in starting down the path of integrating chatbots into your e-learning environment, start with a simple chatbot application. Then, as you become more familiar with techniques and technologies, you can start incorporating AI and DLP features into your e-learning courses.

How do Chatbots work?

1. In a Rule-based approach, a bot answers questions based on some rules on which it is trained on. The rules defined can be very simple to very complex. The bots can handle simple queries but fail to manage complex ones.
2. Self-learning bots are the ones that use some Machine Learning-based approaches and are definitely more efficient than rule-based bots. These bots can be of further two types: Retrieval Based or Generative

i) In retrieval-based models, a chatbot uses some heuristic to select a response from a library of predefined responses. The chatbot uses the message and context of the conversation for selecting the best response from a predefined list of bot messages. The context can include a current position in the dialogue tree, all previous messages in the conversation, previously saved variables (e.g. username). Heuristics for selecting a response can be engineered in many different ways, from rule-based if-else conditional logic to machine learning classifiers.

ii) Generative bots can generate the answers and not always replies with one of the answers from a set of answers. This makes them more intelligent as they take word by word from the query and generates the answers.

Pre-requisites

Hands-On knowledge of scikit library and NLTK is assumed. However, if you are new to NLP, you can still read the article and then refer back to resources.

NLP

The field of study that focuses on the interactions between human language and computers is called Natural Language Processing, or NLP for short. It sits at the intersection of computer science, artificial intelligence, and computational linguistics[Wikipedia].NLP is a way for computers to analyze, understand, and derive meaning from human language in a smart and useful way. By utilizing NLP, developers can organize and structure knowledge to perform tasks such as automatic summarization, translation, named entity recognition, relationship extraction, sentiment analysis, speech recognition, and topic segmentation.