With the emergence of artificial intelligence (AI), machine-learning (ML), and chatbot technologies, the field of education has been transformed drastically. The latest advancements in AI chatbots (such as ChatGPT) have proven to offer several benefits for students and educators. However, these benefits also come with inherent challenges, that can impede students’ learning and create hurdles for educators. The study aims to explore the benefits and challenges of AI chatbots in educational settings, with the goal of identifying how they can address existing barriers to learning. The paper begins by outlining the historical evolution of chatbots along with key elements that encompass the architecture of an AI chatbot. The paper then delves into the challenges and limitations associated with the integration of AI chatbots into education. The research findings from this narrative review reveal several benefits of using AI chatbots in education. AI chatbots like ChatGPT can function as virtual tutoring assistants, fostering an adaptive learning environment by aiding students with various learning activities, such as learning programming languages and foreign languages, understanding complex concepts, assisting with research activities, and providing real-time feedback. Educators can leverage such chatbots to create course content, generate assessments, evaluate student performance, and utilize them for data analysis and research. However, this technology presents significant challenges concerning data security and privacy. Additionally, ethical concerns regarding academic integrity and reliance on technology are some of the key challenges. Ultimately, AI chatbots offer endless opportunities by fostering a dynamic and interactive learning environment. However, to help students and teachers maximize the potential of this robust technology, it is essential to understand the risks, benefits, and ethical use of AI chatbots in education.

Education Technology advances many aspects of learning. More and more learning is taking place online. Learners’ learning behaviors, style, and performance can be easily profiled through learning analytics which collects their online learning footage. It enables and encourages educational research, learning software application development, and online education practices towards personalized and adaptive learning. As we continue to see personalized and adaptive learning progress, we must also pay attention to the negative impacts that feed into our research. In this paper, we will present our introspection of personalized and adaptive learning and argue that it is the social and moral responsibility of educators and institutions to apply personalized and adaptive learning wisely in their education practice. Educators and institutions should also recognize the realistic diversities of individual students’ learning styles and variable learning progress, contextually dependent learning accessibility, and their correspondent support needs for the fine-grained learning activities. We argue that the strategically balanced practices and innovated learning technology are crucial towards an optimized learning experience for the learners.

This chapter presents a novel GenAI tool, called PBL Support Chatbot, designed to support project-based learning (PBL) by integrating retrieval-augmented generation (RAG) and knowledge graphs (KGs). The aim is to address common challenges in PBL, such as project complexity and curriculum alignment. The tool provides students with real-time, adaptive support through a chatbot that assists in navigating PBL tasks. To illustrate its application, the authors introduce a scenario involving an introductory computer programming course where students develop a text-based adventure game. By offering personalized guidance, immediate feedback, and accurate answers to student inquiries, the tool aims to enhance critical thinking, learning outcomes, knowledge application, and student engagement in PBL environments. The initial prototype demonstrates the potential to improve the PBL learning experience. This underscores the capability of using RAG to create a dynamic, interactive learning environment that aligns with students' individual learning paths and educational goals.

Geospatial information plays an important role in environmental modelling, resource management, business operations, and government policy. However, very little or no commonality between formats of various geospatial data has led to difficulties in utilizing the available geospatial information. These disparate data sources must be aggregated before further extraction and analysis may be performed. The objective of this paper is to develop a framework called PlaniSphere, which aggregates various geospatial datasets, synthesizes raw data, and allows for third party customizations of the software. PlaniSphere uses NASA World Wind to access remote data and map servers using Web Map Service (WMS) as the underlying protocol that supports service-oriented architecture (SOA). The results show that PlaniSphere can aggregate and parses files that reside in local storage and conforms to the following formats: GeoTIFF, ESRI shape files, and KML. Spatial data retrieved using WMS from the Internet can create geospatial data sets (map data) from multiple sources, regardless of who the data providers are. The plug-in function of this framework can be expanded for wider uses, such as aggregating and fusing geospatial data from different data sources, by providing customizations to serve future uses, which the capacity of the commercial ESRI ArcGIS software is limited to add libraries and tools due to its closed-source architectures and proprietary data structures. Analysis and increasing availability of geo-referenced data may provide an effective way to manage spatial information by using large-scale storage, multidimensional data management, and Online Analytical Processing (OLAP) capabilities in one system.

With the emergence of Artificial Intelligence (AI) chatbot technologies such as ChatGPT, which utilize AI and Machine Learning (ML) techniques to generate advanced responses to users, the field of education has been transformed drastically. The latest online learning models empowered by AI have proven to have several benefits for students, but these benefits also come with some inherent challenges, which impede students’ learning process and create hurdles for educators. The study aims to identify and analyze the benefits and drawbacks of AI chatbots in educational settings to help overcome existing educational barriers. The paper begins by highlighting the historical evolution of chatbots along with key elements that encompass the architecture of an AI chatbot. The paper also delves into the challenges and limitations associated with the integration of AI chatbots into learning platforms. A systematic literature review methodology has been adopted by dividing the research into several phases, using techniques of inclusion and exclusion criteria to identify appropriate scholarly articles for review. The research findings from this review reveal several benefits of leveraging AI chatbots in learning platforms. AI chatbots like ChatGPT can serve as a virtual tutoring assistant to foster an adaptive learning environment by aiding students with various learning activities, such as learning programming languages, foreign languages, understanding complex concepts, assisting with research activities and providing real-time feedback. Educators can leverage such chatbots to create course content, generate assessments, evaluate students’ performance and use it for data analysis and research. However, this technology possesses significant challenges concerning data security and privacy. In addition, ethical concerns impacting academic integrity and reliance on technology are some of the key concerns. Ultimately, AI chatbots can provide endless opportunities by creating a dynamic interactive learning environment, however, to allow students and teachers to maximize the potential of such a robust technology, it is imperative to first analyze and address the potential risks that AI chatbots pose.