An application called "Productivity Heatmap" was created with this project with the goal of allowing users to track how productive they are over the course of a day and week, input through scheduled prompts separated by 30 minutes to 4 hours, depending on preference. The result is a heat map colored according to a user's productivity at particular times of each day during the week. The aim is to allow a user to have a visualization on when he or she is best able to be productive, given that every individual has different habits and life patterns. This application was made completely in Google's Android Studio environment using Java and XML, with SQLite being used for database management. The application runs on any Android device, and was designed to be a balance of providing useful information to a user while maintaining an attractive and intuitive interface. This thesis explores the creation of a functional mobile application for mass distribution, with a particular set of end users in mind, namely college students. Many challenges in the form of learning a new development environment were encountered and overcome, as explained in the report. The application created is a core functionality proof-of-concept of a much larger personal project in creating a versatile and useful mobile application for student use. The principles covered are the creation of a mobile application, meeting requirements specified by others, and investigating the interest generated by such a concept. Beyond this thesis, testing will be done, and future enhancements will be made for mass-market consumption.

Last Hymn was created by the team of Tyler Pinho, Jefferson Le, and Curtis Spence with the desire to create an eccentric Role Playing Game focused on the exploration of a strange, dying world. Battles in the game are based off of rhythm games like Dance Dance Revolution using a procedural generation algorithm that makes every encounter unique. This is then complemented with the path system where each enemy has unique rhythm patterns to give them different types of combat opportunities. In Last Hymn, the player arrives on a train at the World's End Train Station where they are greeted by a mysterious figure and guided to the Forest where they witness the end of the world and find themselves back at the train station before they left for the Forest. With only a limited amount of time per cycle of the world, the player must constantly weigh the opportunity cost of each decision, and only with careful thought, conviction, and tenacity will the player find a conclusion from the never ending cycle of rebirth. Blending both Shinto architecture and modern elements, Last Hymn used a "fantasy-chic" aesthetic in order to provide memorable locations and dissonant imagery. As the player explores they will struggle against puzzles and dynamic, rhythm based combat while trying to unravel the mystery of the world's looping time. Last Hymn was designed to develop innovative and dynamic new solutions for combat, exploration, and mapping. From this project all three team members were able to grow their software development and game design skills, achieving goals like improved level design, improved asset pipelines while simultaneously aiming to craft an experience that will be unforgettable for players everywhere.

Museum evaluation is an important process that aims to study an exhibit's effectiveness in engaging visitors and in teaching concepts. Imperatives and methods to strengthen museum evaluation have been suggested and implemented in the past, but ultimately faced several challenges including the collection of visitor feedback in an efficient, non-intrusive way. The Ask Dr. Discovery project seeks to address the challenge of conducting efficient, affordable, and large-scale science museum evaluation via an interactive app aimed at collecting direct visitor feedback through use of the app and through questionnaires that also collect demographics. This thesis investigates how the demographics of metro Phoenix science museum visitors as a whole compare to the Hispanic/Latino population of visitors, and makes use of visitor feedback from Ask Dr. Discovery to provide useful data for science museum evaluation. An analysis of responses revealed that the majority of the participants in the study (n=785) were White (Non-Hispanic) (65.59%), were 36-45 years old (36.18%) and hold a graduate degree (27.64%). Most Hispanic/Latino participants in the study were 26-35 years old (36.36%) and completed some college (28.67%). Most participants from both participant groups have never visited the museum before (32.99% of all participants; 33.57% of all Hispanics/Latinos). Further analysis suggest that museum visits may be independent of age and visitor group size. Visitor interest in science museum exhibits may be independent of their use of free time science-related activities. Data suggests that there was no real difference in exhibit interest across two different versions of the app ("modes"). Analysis of negative visitor feedback showed different question types, questions asked, and time spent on the app. Data log questions revealed the difference in time spent on the app and complexity of questions asked between adults and children, as well as the location of participants in the museum. There was no major correlation between mode type and number of questions asked, and length of use and number of questions asked.

Programming is quickly becoming as ubiquitous a tool as general mathematics. The technology field is progressing at an exponential rate and driving this constantly evolving field forward requires competent software developers. Elementary and high school educational facilities do not currently express the importance of the computer science field. Computer science is not a required course in high school and nearly impossible to find at a middle school level. This lack of exposure to the field at a young age handicaps aspiring developers by not providing them with a foundation to build on when seeking a degree. This paper revolves around the development of a virtual world that encompasses principles of programming in a video game structure. The use of a virtual world-based game was chosen under the hypothesis that embedding programming instruction into a game through problem-based learning is more likely to engage young students than more traditional forms of instruction. Unlike the traditional method of instruction, a virtual world allows us to "deceive" the player into learning concepts by implicitly educating them through fun gameplay mechanics. In order to make our video game robust and self-sufficient, we have developed a predictive recursive descent parser that will validate any user-generated solutions to pre-defined logical platforming puzzles. Programming topics taught with these problems range from binary numbers to while and for loops.

This thesis investigates students' learning behaviors through their interaction with an educational technology, Web Programming Grading Assistant. The technology was developed to facilitate the grading of paper-based examinations in large lecture-based classrooms and to provide richer and more meaningful feedback to students. A classroom study was designed and data was gathered from an undergraduate computer-programming course in the fall of 2016. Analysis of the data revealed that there was a negative correlation between time lag of first review attempt and performance. A survey was developed and disseminated that gave insight into how students felt about the technology and what they normally do to study for programming exams. In conclusion, the knowledge gained in this study aids in the quest to better educate students in computer programming in large in-person classrooms.

Learning to program is no easy task, and many students experience their first programming during their university education. Unfortunately, programming classes have a large number of students enrolled, so it is nearly impossible for professors to associate with the students at an individual level and provide the personal attention each student needs. This project aims to provide professors with a tool to quickly respond to the current understanding of the students. This web-based application gives professors the control to quickly ask Java programming questions, and the ability to see the aggregate data on how many of the students have successfully completed the assigned questions. With this system, the students are provided with extra programming practice in a controlled environment, and if there is an error in their program, the system will provide feedback describing what the error means and what steps the student can take to fix it.

Keyboard input biometric authentication systems are software systems which record keystroke information and use it to identify a typist. The primary statistics used to determine the accuracy of a keyboard biometric authentication system are the false acceptance rate (FAR) and false rejection rate (FRR), which are aimed to be as low as possible [1]. However, even if a system has a low FAR and FRR, there is nothing stopping an attacker from also monitoring an individual's typing habits in the same way a legitimate authentication system would, and using its knowledge of their habits to recreate virtual keyboard events for typing arbitrary text, with precise timing mimicking those habits, which would theoretically spoof a legitimate keyboard biometric authentication system into thinking it is the intended user doing the typing. A proof of concept of this very attack, called keyboard input biometric authentication spoofing, is the focus of this paper, with the purpose being to show that even if a biometric authentication system is reasonably accurate, with a low FAR and FRR, it can still potentially be very vulnerable to a well-crafted spoofing system. A rudimentary keyboard input biometric authentication system was written in C and C++ which drew influence from already existing methods and attempted new methods of authentication as well. A spoofing system was then built which exploited the authentication system's statistical representation of a user's typing habits to recreate keyboard events as described above. This proof of concept is aimed at raising doubts about the idea of relying too heavily upon keyboard input based biometric authentication systems since the user's typing input can demonstrably be spoofed in this way if an attacker has full access to the system, even if the system itself is accurate. The results are that the authentication system built for this study, when ran on a database of typing event logs recorded from 15 users in 4 sessions, had a 0% FAR and FRR (more detailed analysis of FAR and FRR is also presented), yet it was still very susceptible to being spoofed, with a 44% to 71% spoofing rate in some instances.

Education of any skill based subject, such as mathematics or language, involves a significant amount of repetition and pratice. According to the National Survey of Student Engagements, students spend on average 17 hours per week reviewing and practicing material previously learned in a classroom, with higher performing students showing a tendency to spend more time practicing. As such, learning software has emerged in the past several decades focusing on providing a wide range of examples, practice problems, and situations for users to exercise their skills. Notably, math students have benefited from software that procedurally generates a virtually infinite number of practice problems and their corresponding solutions. This allows for instantaneous feedback and automatic generation of tests and quizzes. Of course, this is only possible because software is capable of generating and verifying a virtually endless supply of sample problems across a wide range of topics within mathematics. While English learning software has progressed in a similar manner, it faces a series of hurdles distinctly different from those of mathematics. In particular, there is a wide range of exception cases present in English grammar. Some words have unique spellings for their plural forms, some words have identical spelling for plural forms, and some words are conjugated differently for only one particular tense or person-of-speech. These issues combined make the problem of generating grammatically correct sentences complicated. To compound to this problem, the grammar rules in English are vast, and often depend on the context in which they are used. Verb-tense agreement (e.g. "I eat" vs "he eats"), and conjugation of irregular verbs (e.g. swim -> swam) are common examples. This thesis presents an algorithm designed to randomly generate a virtually infinite number of practice problems for students of English as a second language. This approach differs from other generation approaches by generating based on a context set by educators, so that problems can be generated in the context of what students are currently learning. The algorithm is validated through a study in which over 35 000 sentences generated by the algorithm are verified by multiple grammar checking algorithms, and a subset of the sentences are validated against 3 education standards by a subject matter expert in the field. The study found that this approach has a significantly reduced grammar error ratio compared to other generation algorithms, and shows potential where context specification is concerned.

Human-Robot collaboration can be a challenging exercise especially when both the human and the robot want to work simultaneously on a given task. It becomes difficult for the human to understand the intentions of the robot and vice-versa. To overcome this problem, a novel approach using the concept of Mixed-Reality has been proposed, which uses the surrounding space as the canvas to augment projected information on and around 3D objects. A vision based tracking algorithm precisely detects the pose and state of the 3D objects, and human-skeleton tracking is performed to create a system that is both human-aware as well as context-aware. Additionally, the system can warn humans about the intentions of the robot, thereby creating a safer environment to work in. An easy-to-use and universal visual language has been created which could form the basis for interaction in various human-robot collaborations in manufacturing industries.

An objective and subjective user study was conducted to test the hypothesis, that using this system to execute a human-robot collaborative task would result in higher performance as compared to using other traditional methods like printed instructions and through mobile devices. Multiple measuring tools were devised to analyze the data which finally led to the conclusion that the proposed mixed-reality projection system does improve the human-robot team's efficiency and effectiveness and hence, will be a better alternative in the future.

There is a demanding need to empower students from kindergarten through high school to learn computer science and be equipped with the computational thinking skills that they need in today's technology driven world. However, introducing computer programming to students can be challenging, especially for those who aren't familiar with the nuances of code. Several popular tools are used in curriculum for K-12 students which utilize interactive and visualization approaches to engage young kids in learning computational concepts. Possibilities of using Augmented Reality (AR) in teaching programming to novices are explored in this work.

In this thesis Ogmented, an AR application is designed which includes interactive learning material that covers a range of fundamental Object-Oriented Programming (OOP) concepts. This work aims to exploit the idea to learn abstract concepts via AR by capitalizing the strength of visual-aided and interactive elements. A user study with a group of elementary school students is conducted. It explored how students operated the AR application with the interactive elements and how they wrote codes to solve programming problems. It was observed that students who followed instructions while taking tutorials were successfully able to write fragments of codes in exercise modules. Irrespective of their knowledge about programming, majority of students were able to write executable code snippets for concepts they were taught with use of Ogmented. This shares an initial insight on using AR in classroom to teach abstract programming concepts.