Many companies wish to create a personalized experience for customers using their websites. For many services that might mean changing the icon on a sign in page; however, as computers become more powerful and customers expect more from the services they use, companies are starting to investigate ways of running personalized code for their customers. Sadly, one big problem with this trend is that it is very new. This leads to many problems such as the lack of technologies fit for a certain scenario, the flooding of new technologies in only a specific field, and the overall general confusion in implementing a novel technology like this. This is why I believe that compounding a list of different technologies, each with a list of pros and cons, example implementations to give a feel of the technology, as well as benchmarks of each method to allow for individuals and companies to create better websites and services for their customers. I will also be going through a history of available technologies to give an idea on how this technology used to be used for, how it is used today, and how I believe it will be used in the future.

This project was a look into how a child's education can be strengthened using not only gamification, but also with a more inclusive curriculum to better include and represent students of all backgrounds. Five games were created using Unity, a free game development software, and with regard to the following subjects, reading, math, music, science, and art. When applicable, the games taught about the cultures of Caribbean and African countries, for example, the art history of Jamaica. Testers played through all games and the number of questions missed as well as time spent on each subject were collected.

Research has shown that the learning processes can be enriched and enhanced with the presence of affective interventions. The goal of this dissertation was to design, implement, and evaluate an affective agent that provides affective support in real-time in order to enrich the student’s learning experience and performance by inducing and/or maintaining a productive learning path. This work combined research and best practices from affective computing, intelligent tutoring systems, and educational technology to address the design and implementation of an affective agent and corresponding pedagogical interventions. It included the incorporation of the affective agent into an Exploratory Learning Environment (ELE) adapted for this research.

A gendered, three-dimensional, animated, human-like character accompanied by text- and speech-based dialogue visually represented the proposed affective agent. The agent’s pedagogical interventions considered inputs from the ELE (interface, model building, and performance events) and from the user (emotional and cognitive events). The user’s emotional events captured by biometric sensors and processed by a decision-level fusion algorithm for a multimodal system in combination with the events from the ELE informed the production-rule-based behavior engine to define and trigger pedagogical interventions. The pedagogical interventions were focused on affective dimensions and occurred in the form of affective dialogue prompts and animations.

An experiment was conducted to assess the impact of the affective agent, Hope, on the student’s learning experience and performance. In terms of the student’s learning experience, the effect of the agent was analyzed in four components: perception of the instructional material, perception of the usefulness of the agent, ELE usability, and the affective responses from the agent triggered by the student’s affective states.

Additionally, in terms of the student’s performance, the effect of the agent was analyzed in five components: tasks completed, time spent solving a task, planning time while solving a task, usage of the provided help, and attempts to successfully complete a task. The findings from the experiment did not provide the anticipated results related to the effect of the agent; however, the results provided insights to improve diverse components in the design of affective agents as well as for the design of the behavior engines and algorithms to detect, represent, and handle affective information.