The traditional “one size fits all” education system has been largely criticized in recent years on the ground of its lacking the capacity to meet individual student needs. Global education systems are leaning towards a more personalized, student-centered approach. Innovations like Big Data, Machine Learning, and Artificial Intelligence (AI) have given the modern-day technology to accommodate the distinctive features of human beings - smart machines and computers have been built to understand individual-specific needs. This opens an avenue for “personalization” in the education sector. From, mushrooming of Education Technology (EdTech) start-ups to government funding in AI research, it is evident that the next generation educational reforms would take a quantum leap forward piloted by Big Data analysis and AI. The objective of this paper is to organize the vast literature on the use of AI for personalization of education and to shed light on the key themes by which an AI-driven approach makes structural modifications to the existing education system. To this effect, the paper employed a systematic review using a Human-In-The-Loop natural language processing model of past two years' literature (2019–2021) in English language from IEEE Xplore on countries China, India and the USA. This process yielded more than 2000 search results at first and these were eventually shortlisted to 353 relevant papers for in-depth analysis. Being the pioneers in EdTech innovations, insights from research done in these three countries provides valuable input for the development of global education systems and research. The findings bring forward AI's success in catering to specific learning requirements, learning habits, and learning abilities of students and guiding them into optimized learning paths across all three countries. Not just that, it is also evident from the literature that AI augments educational content, customizes it for any individual according to their needs, and raises the flag of caution for anticipated learning difficulties. This recalibrates the role of instructors as well as optimizes the teaching-learning environment for a better learning experience. The upward trajectory of educational development with AI opens a new horizon of personalized education for the future generation, but also comes with its challenges. Data privacy issues, availability of digital resources, and affordability constraints have been reported in the recent literature as impediments in the way of promoting such technologies for day-to-day practice. 

Personalized education and Artificial Intelligence in the United States, China, and India: A systematic review using a Human-In-The-Loop model

Customer service plays a crucial role for a company. As an important aspect of e-commerce companies, they would be required to directly interact and try to solve customers’ problems that might occur anywhere and anytime. However, the limitation of human man hours became a barrier to overcome customers’ problems. On one hand, the rapid development of technology was predicted to replace the traditional human customer service with an Artificial Intelligence agent. On the other hand, this replacement affects the customer satisfaction. This paper performed a study literature review to discover the effect of chatbots and its impact towards customer satisfaction. In an e-commerce customer service use case, chatbots could be implemented in a number of methods. The methods implemented by chatbots are avatar-based, verbal-based, text-based, and menu-based. Research showed that text-based chatbot is the most commonly used methodology and has advanced the most, where some are implementing higher level machine learning methods, such as deep learning. The usage of such chatbot in e-commerce customer service systems will lower the cost but might also lower customer satisfaction, due to reasons such as unsatisfying answers and inhuman behavior. Research showed that even a more sophisticated chatbot doesn’t always mean higher customer satisfaction, even with high accuracy ratings. To look into customer satisfaction, this paper has identified 4 aspects of a chatbot that are relevant to customer satisfaction, which are privacy, reliability, personalization, and responsiveness. Chatbots currently excel in some of these quality measures, but require further research to effectively replace human customer service agents.

Study Literature Review: Discovering the Effect of Chatbot Implementation in E-commerce Customer Service System Towards Customer Satisfaction

Nowadays, educators can show case the technology of chatbots in various fields such as teaching and learning. Earlier the resources are almost negligible, in the field of education with the learning design integrated in it. But now with the advancement of technology, chatbot can fill the gap in the teaching landscape too. Using chatbot in the education domain is reassuring, since these bots can point out some of the logistics and diversified issues that a normal class might face. Besides this, with the further advancement of Artificial Intelligence, tech-giants like Apple, Google, and Amazon are providing platforms where building conversation is more focused rather than technicalities of computer programming i.e., to be more specific in natural language processing. In this paper, we have built a rule based chatbot on a platform named Discord, also showcased that how a chatbot can be integrated into other online platforms to counter the challenges faced in teaching. Q/A features are used to get in-depth knowledge about various preinstalled data in chatbot.

Harsh Raj

Papers

Development of Information Technology Telecom Chatbot: An Artificial Intelligence and Machine Learning Approach