Wondering about innovations in digital learning? Curious about emerging trends? Interested in research methods used in big-data analysis? If so, come see what Tanya Joosten, Ph.D., has uncovered through vigorous research of OLC’s past Digital Learning Innovation Award submissions, and resulting plans the Every Learner Everywhere Network has developed.
The Online Learning Consortium, one of 12 partner organizations in the Every Learner Everywhere Network, has been tasked with researching and implementing digital learning innovations as part of the greater network goal; to provide advice, training, and community-vetted resources that support the adoption and implementation of adaptive courseware, with a focus on increasing the success of first-generation students, low-income students, and students of color (www.everylearnereverywhere.org).
In year one the ELE Digital Innovations Working Group led by OLC selected Tanya Joosten, University of Wisconsin-Milwaukee to perform an environmental scan. Tanya Joosten, Ph.D., is a Senior Scientist, the Director of Digital Learning Research and Development, and co-PI and co-Director of the National Research Center for Distance Education and Technological Advancements (DETA) at the University of Wisconsin-Milwaukee. She is nationally recognized in her work in blended and online learning as an Online Learning Consortium (OLC) Fellow and works to guide strategic digital learning efforts on campus, across the UW System, and nationally as an advisor to the Provost, a member of the University of Wisconsin System Learning Technology Executive Council, and a member of several national boards and committees (https://uwm.edu/deta/tanya-joosten/).
The purpose of this cross-institutional, qualitative research study was to better understand the profile of emerging digital learning technologies across postsecondary institutions via an environmental scan of past award submission data; specifically, looking to identify new and emerging trends to enhance educational experience and improve completion rates for high-risk populations through digital and adaptive learning. The scope of this work is to review DLIA submissions historically to identify trends within the digital innovations and adaptive learning technologies areas such as VR/AR, mobile applications, interoperability, embedded formative assessment, analytics innovation, competency credentialing, augmented mobile learning and culturally responsive technologies or other areas of focus as appropriate that can generate white papers/research, webinars, conference presentations, stories and pilot planning.
Data was analyzed throughout data collection using an inductive analytical approach and incorporated many of the procedures of the constant comparative method. More specifically, the data analysis process consisted of six steps. First, applicant identifying information was removed from the text. Second, the data was organized into one document based on area of innovation. Third, the data was coded. Fourth, researchers analyzed the codes to identify themes in each area of impact. Fifth, researchers compared coding to further distill the themes. Sixth, research cross-cut the data and identified themes based on digital learning trends. Quality control measures included member checks and peer reviews (Lincoln & Guba, 1985) to assure the validity of the findings.
The resulting data provided areas of focus for innovative adaptive learning technologies that the Every Learner Everywhere Digital Learning Innovations Working group determined through a polling process. Future work within core trends will follow a multi-phased method to select projects submitted through a peer-reviewed proposal, develop pilot plans, and advance innovative projects through the Every Learner Everywhere Network arms as a project pilot until an asset has been created and can be utilized through the Every Learner Everywhere Network or among institutions.