Adaptive Learning Course Redesign Sandbox: Restructuring a Curriculum into Flexible Pathways (with Content Creation time)

Concurrent Session 6
Streamed Session

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Brief Abstract

Adaptive learning systems allow students to experience individualized pathways through a course’s content.  Content needs to be broken apart into small chunks and then mapped to allow for these flexible pathways. This session will guide you through the process with your course, including “sandbox” time with Realizeit’s platform.


Dr. Matthew Vick is a professor of science education from the University of Wisconsin-Whitewater. He has directed/co-directed two grant projects at UW-W: a two-year Wisconsin Elementary and Secondary Education Act Title IIA Improving Teacher Quality Grant entitled "Integrating Science and Literacy Learning with English Proficient and English Language Learners" and a one-year UW System Outreach grant entitled "Collaboratively Implementing the Vision of the Next Generation Science Standards in the Mukwonago Area School District with Pre-service and In-service Teachers". He has published research articles and a book chapter in science education as well as practitioner-based articles. He has presented at the National Science Teachers Association, the Association for Science Teacher Education, the National Association for Research in Science Teaching, and the Wisconsin Society of Science Teachers. He has served as department chair for the department of Curriculum and Instruction and interim associate dean of graduate studies.

Extended Abstract


By the end of the session, participants will be able to

-Analyze a course segment, such as a unit, and break it down into nodes for an adaptive system

-Design course objectives that connect nodes

-Assign prerequisite relationships between nodes that accurately infer future and past mastery in an adaptive system

-Create a template for a sample node that can be ingested into the system

-Create reusable assessment questions such as math problems with variables or multiple choice questions with a bank of correct and incorrect answers


Adaptive learning systems, such as a Realizeit, allow instructors and instructional designers to recreate their courses in flexible formats that allow for greater personalization in the pathways that students take through a course’s content.  Adaptive learning fully utilized allows students to bypass content that they have already mastered in order to focus on newer or more difficult concepts. Additionally, it allows students to spend more time on concepts that they are not mastering quickly.  In some adaptive courses, students may only be exposed to a portion of the content that the instructor has designed for them due to the combination of their background knowledge, speed of mastery, and interest.

    Redesigning a course for adaptive delivery requires adequate time and also a new mindset.  Adaptive learning is most powerful if students are able to discover their own pathways through a course, including pathways that the instructor may not consciously have thought about.  Additionally, multiple opportunities to learn and show mastery are key to an adaptive platform. This presentation will share the process used by one instructor and the designers to conceptualize the creation of an adaptive course for teacher education.  Participants will be encouraged to follow these steps for a small portion (perhaps a unit) of a course they are thinking of redesigning. Realizeit will have “sandbox courses” available for use during the presentation so that the participants can also engage with these steps inside of one possible system.  Realizeit was the partner with the instructor’s institution and hence is the partner for this session, but this session’s outcomes will be applicable to other adaptive learning platforms as well.

    The “chunking” of course content into nodes is an important first step.  The major topics of a course can be diagrammed using a branching tree (like a hierarchical concept map) to move from large topic areas into smaller “chunks” of learning and assessment that are self contained.  Several factors should be taken into account by instructors and designers when deciding whether a “chunk” is an appropriate size for an adaptive learning course. These factors include determining (1) is the knowledge logically unified and self contained? (not too big or too small), (2) are the learning objects like text or video an appropriate length for an individual learning session? (are videos longer than 10 minutes? Can the text be read in about that length of time?), and (3) are sufficient assessment questions possible so that mastery can reasonably be inferred by a subset of the questions asked? (are there between 3 and 10 good assessment questions that can be asked?).  

    Next, the nodes will be grouped into course objectives or milestones.  Seasoned instructors and designers will likely find this to be much easier than the dividing of content into adaptive nodes.  More difficult will be the step of determining prerequisite knowledge to be assumed and inferred by the system between the nodes.  This is different than sequencing nodes as in a traditional course. Prerequisite relationships will actually predict mastery in future and past nodes based upon current performance, therefore instructors should not create prerequisites for which this is not an accurate relationship.  A course can still be designed to have a suggested flow or pathway without this relationship. Examples will be shared of how this predictive relationship works so that participants can make good decisions about the type of relationships in a milestone or objective.

    Finally, this session will engage participants in creating sample content for a single node.  This is to give them a feel for the flexibility and options for designing content in an adaptive system.  They will create their content in a Word template that will be uploaded into the system. The overview will include how to create headings, include text, link to a YouTube video, and create assessment questions.  In order to provide context for how question banks can provide enough variety to move beyond simply memorizing a few questions seen again and again, samples of using variables in math problems and of creating a multiple choice question with a bank of correct and incorrect responses will be demonstrated.


Session Plan (45 minutes)

  1. Overview of adaptive learning (5 minutes)

  2. Dividing course topics into a hierarchy that ends in appropriate sized nodes (10 minutes)

  3. Creating course objectives or milestones with prerequisites relationships (10 minutes)

  4. Content creation for a sample node (20 minutes)

Participant Engagement

Participants will be in a “sandbox” version of Realizeit allowing them to use the tools and to create a sample course map with nodes and to create a sample node.