This thesis is based on bringing together three different components: non-Euclidean geometric worlds, virtual reality, and environmental puzzles in video games. While all three exist in their own right in the world of video games, as well as combined in pairs, there are virtually no examples of all three together. Non-Euclidean environmental puzzle games have existed for around 10 years in various forms, short environmental puzzle games in virtual reality have come into existence in around the past five years, and non-Euclidean virtual reality exists mainly as non-video game short demos from the past few years. This project seeks to be able to bring these components together to create a proof of concept for how a game like this should function, particularly the integration of non-Euclidean virtual reality in the context of a video game. To do this, a Unity package which uses a custom system for creating worlds in a non-Euclidean way rather than Unity’s built-in components such as for transforms, collisions, and rendering was used. This was used in conjunction with the SteamVR implementation with Unity to create a cohesive and immersive player experience.

The Migration Framework and Simulator is a combination of C# framework / library and Unity simulation tool used for studying basic migration patterns across the US. Users interact with the
Unity simulation tool by implementing political policies or adjusting values via sliders, buttons, etc., which will alter the values in the framework. The user can then use the simulation interface to view different estimated population values for categories of people, such as regional differences, education levels, and more.

This project is to design an idle game and evaluate players’ enjoyment corresponding to
different currency rates. In the game, the player can control a group of heroes against another
set of heroes. In this project, two different currency rates are examined. The player can get
money more easily in a lower currency rate. Two groups of players are formed, and there are 5
players in group A and group B respectively. Players in group A are assigned to play the idle
game with a higher currency rate and players in group B are assigned to play the game with a
lower currency rate. The idle game is created by using Unity and C# language. The feedback
from the players is collected by asking them to finish an 11-question survey. The analysis is
based on the game’s currency rate and survey results. It is concluded that a higher currency rate
lowers players’ enjoyment of the idle game.

The purpose of this study was to investigate the impact of immersion on knowledge, cognitive load, and presence in a simulation designed to deliver a lesson on science lab safety training. 108 participants were randomly assigned to one of three conditions: high immersion (played an interactive simulation about lab safety in a VR headset), medium immersion (played the same interactive simulation on the computer), or low immersion (watched a video and read about lab safety procedures). Participants completed a pretest, a science lab safety training, a posttest (same as the pretest), a questionnaire with subjective presence questions, and a questionnaire with subjective cognitive load questions. Participants were again asked to complete a follow-up test (same as the pretest and posttest) a week later.

The results revealed three significant findings:

(a) Participants in the high and medium immersion conditions had significantly higher knowledge scores at posttest and follow-up than their peers in the low immersion condition,

(b) Participants in the high and medium immersion conditions reported higher presence scores than participants in the low immersion conditions.

(c) Correlation coefficients suggested that the higher the immersion and presence, the higher the knowledge scores are at posttest and follow-up.

In addition, multiple hierarchical linear regression models were conducted out of which one was significant.

A recorded tutorial dialogue can produce positive learning gains, when observed and used to promote discussion between a pair of learners; however, this same effect does not typically occur when an leaner observes a tutorial dialogue by himself or herself. One potential approach to enhancing learning in the latter situation is by incorporating self-explanation prompts, a proven technique for encouraging students to engage in active learning and attend to the material in a meaningful way. This study examined whether learning from observing recorded tutorial dialogues could be made more effective by adding self-explanation prompts in computer-based learning environment. The research questions in this two-experiment study were (a) Do self-explanation prompts help support student learning while watching a recorded dialogue? and (b) Does collaboratively observing (in dyads) a tutorial dialogue with self-explanation prompts help support student learning while watching a recorded dialogue? In Experiment 1, 66 participants were randomly assigned as individuals to a physics lesson (a) with self-explanation prompts (Condition 1) or (b) without self-explanation prompts (Condition 2). In Experiment 2, 20 participants were randomly assigned in 10 pairs to the same physics lesson (a) with self-explanation prompts (Condition 1) or (b) without self-explanation prompts (Condition 2). Pretests and posttests were administered, as well as other surveys that measured motivation and system usability. Although supplemental analyses showed some significant differences among individual scale items or factors, neither primary results for Experiment 1 or Experiment 2 were significant for changes in posttest scores from pretest scores for learning, motivation, or system usability assessments.

The purpose of this study was to investigate the effects of static pedagogical agents (included and excluded) and gamification practice (included and excluded) on vocabulary acquisition and perceptions of cognitive load by junior high students who studied Navajo

language via computer-based instructional program. A total of 153 students attending a junior high school in the southwestern United States were the participants for this study. Prior to the beginning of the study, students were randomly assigned to one of four

treatment groups who used a Navajo language computer-based program that contained a combination of static pedagogical agent (included and excluded) and gamification practice (included and excluded). There were two criterion measures in this study, a

vocabulary acquisition posttest and a survey designed both to measure students’ attitudes toward the program and to measure cognitive load. Anecdotal observations of students’ interactions were also examined.

Results indicated that there were no significant differences in posttest scores among treatment conditions; students were, however, generally successful in learning the Navajo vocabulary terms. Participants also reported positive attitudes toward the Navajo

language content and gamification practice and expressed a desire to see additional content and games during activities of this type. These findings provide evidence of the impact that computer-based training may have in teaching students an indigenous second

language. Furthermore, students seem to enjoy this type of language learning program. Many also indicated that, while static agent was not mentioned, gamification practice may enhance students’ attitudes in such instruction and is an area for future research.

Language learning programs could include a variety of gamification practice activities to assist student to learn new vocabulary. Further research is needed to study motivation and cognitive load in Navajo language computer-based training.

The problem under investigation was to determine if a specific outline-style learning guide, called a Learning Agenda (LA), can improve a college algebra learning environment and if learner control can reduce the cognitive effort associated with note-taking in this instance. The 192 participants were volunteers from 47 different college algebra and pre-calculus classes at a community college in the southwestern United States. The approximate demographics of this college as of the academic year 2016 – 2017 are as follows: 53% women, 47% men; 61% ages 24 and under, 39% 25 and over; 43% Hispanic/Latino, 40% White, 7% other. Participants listened to an approximately 9-minute video lecture on solving a logarithmic equation. There were four dependent variables: encoding as measured by a posttest – pretest difference, perceived cognitive effort, attitude, and notes-quality/quantity. The perceived cognitive effort was measured by a self-reported questionnaire. The attitude was measured by an attitude survey. The note-quality/quantity measure included three sub-measures: expected mathematical expressions, expected phrases, and a total word count. There were two independent factors: note-taking method and learner control. The note-taking method had three levels: the Learning Agenda (LA), unguided note-taking (Usual), and no notes taken. The learner control factor had two levels: pausing allowed and pausing not allowed. The LA resulted in significantly improved notes on all three sub-measures (adjusted R2 = .298). There was a significant main effect of learner control on perceived cognitive effort with higher perceived cognitive effort occurring when pausing was not allowed and notes were taken. There was a significant interaction effect of the two factors on the attitude survey measure. The trend toward an improved attitude in both of the note-taking levels of the note-taking factor when pause was allowed was reversed in the no notes level when pausing was allowed. While significant encoding did occur as measured by the posttest – pretest difference (Cohen’s d = 1.81), this measure did not reliably vary across the levels of either the note-taking method factor or the learner control factor in this study. Interpretations were in terms of cognitive load management, split-attention, instructional design, and note-taking as a sense-making opportunity.

Natural Language Processing and Virtual Reality are hot topics in the present. How can we synthesize these together in order to make a cohesive experience? The game focuses on users using vocal commands, building structures, and memorizing spatial objects. In order to get proper vocal commands, the IBM Watson API for Natural Language Processing was incorporated into our game system. User experience elements like gestures, UI color change, and images were used to help guide users in memorizing and building structures. The process to create these elements were streamlined through the VRTK library in Unity. The game has two segments. The first segment is a tutorial level where the user learns to perform motions and in-game actions. The second segment is a game where the user must correctly create a structure by utilizing vocal commands and spatial recognition. A standardized usability test, System Usability Scale, was used to evaluate the effectiveness of the game. A survey was also created in order to evaluate a more descriptive user opinion. Overall, users gave a positive score on the System Usability Scale and slightly positive reviews in the custom survey.

One of the core components of many video games is their artificial intelligence. Through AI, a game can tell stories, generate challenges, and create encounters for the player to overcome. Even though AI has continued to advance through the implementation of neural networks and machine learning, game AI tends to implement a series of states or decisions instead to give the illusion of intelligence. Despite this limitation, games can still generate a wide range of experiences for the player. The Hybrid Game AI Framework is an AI system that combines the benefits of two commonly used approaches to developing game AI: Behavior Trees and Finite State Machines. Developed in the Unity Game Engine and the C# programming language, this AI Framework represents the research that went into studying modern approaches to game AI and my own attempt at implementing the techniques learned. Object-oriented programming concepts such as inheritance, abstraction, and low coupling are utilized with the intent to create game AI that's easy to implement and expand upon. The final goal was to create a flexible yet structured AI data structure while also minimizing drawbacks by combining Behavior Trees and Finite State Machines.

Can a skill taught in a virtual environment be utilized in the physical world? This idea is explored by creating a Virtual Reality game for the HTC Vive to teach users how to play the drums. The game focuses on developing the user's muscle memory, improving the user's ability to play music as they hear it in their head, and refining the user's sense of rhythm. Several different features were included to achieve this such as a score, different levels, a demo feature, and a metronome. The game was tested for its ability to teach and for its overall enjoyability by using a small sample group. Most participants of the sample group noted that they felt as if their sense of rhythm and drumming skill level would improve by playing the game. Through the findings of this project, it can be concluded that while it should not be considered as a complete replacement for traditional instruction, a virtual environment can be successfully used as a learning aid and practicing tool.