Welcome to Realizeit labs

This site is where we'll share some of the inner workings of the Realizeit Research and Development team: the projects we're working on, meetings we're attending, collaborations we're involved in, papers we're publishing. Make sure to follow us to stay up to date on what is happening.

If you are interested in using the Realizeit platform, please visit www.realizeitlearning.com.

We are always interested in hearing new ideas and discussing potential research collaborations. If you are interested in working with us, or one of our partner institutions on a research project then let us know.

Adaptive Learning: A Stabilizing Influence
Oct 22, 2018  • Colm Howlin

Recently we had a paper Adaptive Learning: A Stabilizing Influence Across Disciplines and Universities published in the Online Learning Journal based on some of the collaborative research that we have...

Read post

Principal Component Analysis - A Primer
Oct 22, 2018  • Colm Howlin  Resource Post

This is a resource post that gives a very brief overview of Principal Components Analysis (PCA). We create these resource posts to provide a basic introduction to some techniques and...

Read post

Boosting Self-Regulated Learning
Oct 3, 2018  • Eoin Gubbins

As an adaptive learning system, Realizeit provides tremendous flexibility for students, allowing them to learn in their own way, at their own pace, and at times that are most convenient...

Read post

  • The University of North Carolina System - Digitial Learning Initiative 2019 Symposium - Raleigh, NC

    Opening Keynote: Multi-context Adaptive Learning at Scale

    Patsy Moskal (University of Central Florida), Chuck Dziuban (University of Central Florida), Colm Howlin (Realizeit), Connie Johnson (Colorado Technical University)

    Mar 27, 2019 - 9:15 AM to 10:30 AM - Carolina Club


  • The 126th American Society for Engineering Education Annual Conference - Tampa, FL

    Pathways of students’ progress through an on-demand online curriculum

    Colm Howlin (Realizeit), Maartje van den Bogaard (Delft University of Technology), Euan Lindsay (Charles Sturt University), Jim Morgan (Charles Sturt University)

    Date: TBD - Time: TBD - Room: TBD


  • 1.
    Charles Dziuban, Colm Howlin, Patsy Moskal, Connie Johnson, Mitchell Eid and Brandon Kmetz (2019)
    Adaptive Learning: Context and Complexity
    E-Mentor 5(77), 7-39. doi:10.15219/em77.1384
    Go to paper

    This article describes a research partnership between the University of Central Florida and Colorado Technical University, with their common adaptive learning platform provider, Realizeit. The study examines component scores at the two institutions in mathematics and nursing based on a number of Realizeit system metrics. Although the principal components across disciplines and universities remained constant, student scores on those dimensions varied considerably. This indicates that adaptive learning is influenced by context and complexity. The context aspect helps frame student learning regarding knowledge, engagement, communication, and growth as they experience variability from faculty approaches to instruction. Complexity indicates a nonlinear learning pattern for the adaptive process in which the emergent property shows that interactions among the individual elements result in a more realistic model for explaining how students function in contemporary higher education. The authors raise a number of implementation issues for adaptive learning.
    Hinkle, Julie F. and Moskal, Patsy (2018)
    A Preliminary Examination of Adaptive Case Studies in Nursing Pathophysiology
    Current Issues in Emerging eLearning: Vol. 5 : Iss. 1 , Article 3
    Go to paper

    Case studies are a valuable instructional tool frequently used in nursing to allow students to analyze clinical problems based on real-world scenarios. This study examines the use of the Realizeit adaptive platform to create case study scenarios for pathophysiology, a course required in the undergraduate nursing curriculum.

    The data gathered as students progressed through the adaptive content--time on task, number of times cases accessed, and scores on each case--provided valuable information on student behavior and engagement with the three case studies. Results of this preliminary study indicate that adaptive case studies are promising for pathophysiology and system analytics confirmed that all but one of the 1,544 simulations presented to students were unique. This provides a benefit over what would typically be a limited number of distinct options when using instructional case studies without the adaptive learning system. Future research is suggested to examine additional uses of case studies and their impact on students’ knowledge acquisition and engagement when part of a course’s graded assignments.
    Johnson, Constance and Zone, Emma (2018)
    Achieving a Scaled Implementation of Adaptive Learning through Faculty Engagement: A Case Study
    Current Issues in Emerging eLearning: Vol. 5 : Iss. 1 , Article 7
    Go to paper

    This paper presents a case study describing the implementation of adaptive learning at Colorado Technical University (CTU) with a focus on faculty adoption. A number of barriers to the adoption of technology will be discussed and more importantly, how CTU overcame these barriers. A description of the key elements of faculty support including training will be outlined as well as the information about the adoption of faculty using data to inform teaching strategies.

    The authors argue that if given the choice, faculty at CTU would prefer adaptive learning technology in their courses and welcome the use of technology and data to enhance the classroom experience.