Three studies were conducted to explore machine learning support of novel learning problems. The first was a study of a computer-supported online learning website, which was designed to support teachers improving their pedagogy and this work created a data-first approach for Linguistic pedagogy, and to support improved pedagogy delivery and evaluation; the other two studies are supporting a participatory design project to create more youth-centered applications (i.e. an Android learning application), which is divided into two phases -- the user interface information design phase to ascertain patterns in the data set, and phase two applied these pattern to support user sentiment analysis (i.e. collaborative and content-based filtering) to better support user experience in finding youth-centric content. The main objective of this work was to create frameworks that can be used to design usable applications and the proposed frameworks were evaluated through empirical experiments. We applied a framework for the design of online learning systems. This research will result in user sentiment analysis for generation z and other populations. Our goal was to validate the proposed framework and impact on designing online educational applications for these particular populations. In the field of human-computer interaction, we work to define the process of working with humans to find better solutions to support their computer interactions through technology. HCI as defined "improves the design and uses of computer technology, and focused on the interfaces between people (users) and computers. Researchers in the field of HCI both observe the ways in which humans interact with computers and design technologies that let humans interact with computers in novel ways" (Card, Moran, & Newell, 1980). We have studied and worked with many communities in a process of participatory design and during the course of this work, we have gained a novel perspective on two communities of practice and their usage of computers and problems they may encounter. After studying these communities, we gathered functional requirements, created designs, and developed solutions to satisfy their requirements. In this manuscript, we will discuss work with two communities through three essays to document three studies. Our work was to support educational partners, gather requirements, and develop systems to better support their needs. In study one, we worked with teachers and found that they needed a better mechanism for returning results efficiently to their students. We studied the literature and found that the existing learning management systems are a great support to improve educational practice and provide an effective reinforcement that goes far beyond traditional classroom instruction (Ellis, 2009), but did not provide support for the needs of our teachers in the field of communications disorders. The faculty wanted to provide quicker and more robust feedback, to support an increase in student's confidence in learning in this problem area. Secondly, we aimed to provide support for teachers in this area, we endeavored to develop a smarter way to generate exams to optimize their usage of time to give them more time to devote to other higher-level instructional activities instead of spending great amounts of time on rote activities (i.e. grading by hand and creating exams). Recently there has been a resurgence of interest by academic institutions and companies, in the use of specialized algorithms to better solve problems. Some have emphasized an understanding of machine learning, the scientific study of algorithms and statistical models that computer systems use in order to perform a specific task effectively without using explicit instructions, relying on patterns and inference instead (Bishop, 2016). [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://www.proquest.com/en-US/products/dissertations/individuals.shtml.]