2024 SoLAR Executive Committee Student Member Nominees – Special Election

Interest in Learning Analytics (Research Area, etc.) & Interest in serving on the SoLAR Executive Committee: My current interest in Learning Analytics centers on learner-facing analytics and the effective delivery of feedback through digital game systems. I am particularly passionate about "closing the loop," ensuring that learning insights are communicated directly to learners in accessible and actionable ways, ideally through the strategic use of learning games. My previous research has explored collaboration skills and introduced the concept of "subversive learning analytics." As an active member and volunteer at LAK conferences over the past three years, I am deeply committed to the contributions and vision of the SoLAR community. I am eager to transition from a supportive role to a more strategic position on the Executive Committee to help shape the future of Learning Analytics. I aim to foster a robust community for game-based research within SoLAR, advocating for initiatives that empower students with learning analytics through digital games. My background as a former public school teacher and a first-generation graduate student provides me with a unique perspective beneficial to the Executive Committee. Additionally, serving as a representative and liaison from New York University would allow me to further contribute this perspective.

Biography: Maurice Boothe Jr. is a learning designer, researcher, and former high school teacher. He holds a BA in Spanish Education from the University of Wisconsin-Madison, a Master’s Certificate in Learning Sciences, Media, and Technology from Indiana University, and an MA in Learning Technology Experience Design from New York University. Maurice is currently pursuing a PhD in Educational Communication and Technology at New York University while working full-time as an Instructional Technologist at NYU Meyers College of Nursing. Maurice has made contributions to the field of Learning Analytics in collaboration and games research as well as received the Best Short Paper Award with Wise et al in LAK '21. He has also been a committed volunteer at LAK for several years. Maurice is also recognized as a Gates Millennium Scholar, a UW-Madison Chancellor’s Scholar, and has received the Samuel Eshborn Service Award from NYU. His current research explores the intersection of game-based learning and learning analytics, exploring the ways that feedback can be delivered to learner using games.

Working Group Interests: The groups that interest me most are: Inclusion Working Group, Events Working Group, ECR Research Grant Working Group, and Membership Working Group.

Interest in Learning Analytics (Research Area, etc.) & Interest in serving on the SoLAR Executive Committee: Qinyi Liu's research focuses on learning analytics, particularly on the escalating privacy and data protection issues within the field. Her Ph.D. project aims to promote the trustworthiness of learning analytics systems using advanced privacy-enhancing technologies and generative artificial intelligence, facilitating the continued scalability vision of learning analytics. Moreover, she is dedicated to making privacy solutions in learning analytics more accessible, allowing individuals to utilize these solutions freely and without prior programming knowledge. Qinyi is committed to learning analytics and aspires to contribute as a member of the SOLAR Executive Committee. Qinyi's journey with SOLAR began at the early start of her doctoral career, of which in just two years, she published her first paper at LAK, successfully qualified to participate in the Doctoral Consortium, and won two Best Poster Awards two years in a row. She aims to maintain her active contribution to SOLAR, supporting numerous students who, like her, are newcomers to this community.

Biography: Qinyi Liu is an energetic, motivated PhD candidate based at the Centre for the Science of Learning & Technology (SLATE) at the University of Bergen in Norway. Qinyi’s research is at the forefront of using data-driven approaches to enhance the trustworthiness of learning analytics and education data science, focused more on data-driven approaches. She has received the Best Poster Award twice at the International Conference of Learning Analytics and Knowledge (LAK) and is currently serving as a guest editor for the British Journal of Educational Technology that draws attention towards enhancing learning at scale using generative artificial intelligence. Qinyi's previous professional career includes impactful roles such as serving as a Researcher for the COVID Governance and Data Protection project at the University of Edinburgh, and as a Research Coordinator at the University of North Carolina Chapel Hill. Her past roles have provided her with extensive expertise in both data protection and digital platforms development. In Qinyi's doctoral project, she is dedicated to mapping known learning analytics privacy issues and providing generative artificial intelligence-based solutions that are developed into a free, open-source, and user-friendly platform for the community to use.

Working Group Interests: Events working group, Special Interest Groups working group

Interest in Learning Analytics (Research Area, etc.) & Interest in serving on the SoLAR Executive Committee: I am interested in serving on the SoLAR executive committee, because I see a future in attending the conference regularly as an academic researcher or early career researcher. I am interested in organizing events that facilitate networking nad resarch collaborations as well as improve the overall quality of the conference and other events organized by SoLAR community such as LASI and LAP.

Biography: I am a PhD Student in the Intelligent Systems Program at the University of Pittsburgh. My current research is on developing personalized educational technologies for students in undergraduate computer science. I develop backend ML models for AI based intelligent User interfaces for students to receive feedback on their interactions. Specifically, in the context of introductory programming interfaces. My research is in the topic of applied AI in education, particularly in the topics of data analysis, data mining, machine learning and natural language processing. I also work with developing intelligent textbooks. Our lab website is available at http://adapt2.sis.pitt.edu/wiki/PAWS.

Working Group Interests: I am interested in the Special Interest Group WGs