Figure it Out!: Develop Data Literacy Skills through Use of an Interactive Multimedia Learning Object (MMLO) to Evaluate Figures and Tables
Concurrent Session 3
Evaluating published figures and tables for informational visual quality is a vital skill across many fields, yet students often struggle with mastery. In this interactive session, we will demonstrate a multimedia learning object developed for biomedical informatics students and share preliminary results from a research study evaluating its effectiveness.
A common problem that educators face across all disciplines—and especially in STEM fields—is that students often struggle to evaluate and interpret figures and tables presented in the literature. Moreover, students often do not know where to begin when viewing a figure or a table nor do they know how to assess the quality of the data presented in those figures and tables.
In this session, we will describe the development process of an interactive multimedia learning object (MMLO) used in an online biomedical informatics course at The Ohio State University. After completing this course, students should be able to describe and prepare the major components of an National Institutes of Health F(31) grant proposal. In order to prepare the major components, students must survey the literature and evaluate data contained within to inform their own research plans. However, instructors identified student difficulties with evaluating published figures and tables and, subsequently, creating their own effective figures and tables when writing up their own research. We developed an interactive multimedia learning object (MMLO) in which students have an opportunity to work through multiple examples of figures and tables published in the popular press and scientific journals, to interact directly with those figures and tables through clickable spots, to track their progress through activities, and to receive multiple, immediate rounds of audio and text feedback from instructors. We felt that leading students through this iterative evaluation process would, ultimately, enable them to produce better figures and tables in their own work.
During our presentation, we will briefly demonstrate the MMLO and discuss our process for choosing the tool (Articulate Storyline 360), formulating the workflow of the project, templating the activities within the MMLO, and designing the MMLO to maximize usability and accessibility.
We will also present our research design for a study evaluating the MMLO’s efficacy. In this study, we measure changes in student ability to evaluate and create figures in graduate and undergraduate biology courses using a pre-post, quasi-experimental design. We will describe the different treatment levels for the independent variable (MMLO vs. a static alternative) and our assessment strategies for identifying changes in students’ ability to evaluate and create figures. We will also share preliminary results from our first round of data collection.
During the final portion of our session, we hope to engage with the audience about the importance of teaching data literacy skills in their classes and ways to create engaging, authentic activities to allow students to practice and to develop those skills.
After completion of this session, participants will be able to:
- Recognize the engagement value using an interactive MMLO provides to students.
- Assess the possibilities of adapting an interactive MMLO in their classes to teach data literacy skills.
- Explain the full development process of an MMLO for use in an online and/or face-to-face course.
- Session slides.