Supporting Learning in Educational Games: Promises and Challenges

• In Event: 43.015 - Game-Based Assessment: How Has the Field Matured Over the Past 10 Years?

Abstract

Educational games have many promises (e.g., increasing students’ content knowledge as well as competencies like problem solving, spatial skills, and persistence). However, there are challenges to overcome before using these games more broadly in educational settings. One challenge involves figuring out the best design of effective, theoretically-based learning supports that don’t reduce the fun/engagement inherent in gameplay while maximizing learning. In our paper, we will: (1) briefly review the literature on learning/instructional supports in educational games, (2) define the most common types and effectiveness of these types of support, (3) present recommendations about educational game design, and (4) describe current work involving the design, development, and testing of various types of embedded cognitive learning supports in our game, Physics Playground (PP; Shute & Ventura, 2013), currently being tested with middle- and high school students.

PP originally was designed to dynamically assess students’ understanding of qualitative physics. In the new version of PP, we are focusing on supporting more formal understanding of an expanded set of physics concepts (i.e., force and motion, linear momentum, energy, and torque). Over the past two years, we have designed, developed, and begun testing on eight different learning supports (i.e., game tutorials, animations, worked examples, formulas, interactive definitions, hints, Hewitt videos, and a glossary). We will present the results from two usability studies which yielded uneven results, where students really enjoyed playing the game, but the effectiveness of the different supports varied (e.g., the worked examples type of support was the most frequently used but did not improve learning). The usability study results led to a full redesign of the learning supports. That is, we (1) enhanced the supports to make them more engaging; (2) divided the supports into two areas (i.e., learning and gameplay related); and (3) designed a game dashboard and reward system. In the current version of the game, students access the supports by clicking a “help” button. This triggers a pop-up window showing three options: “Show me the Physics,” “Show me a Solution or Hint,” and “Show me Game Tips”.
We will elaborate on some of the challenges that we, as well as other educators and educational game designers, have faced in the design of optimal supports, and present some of our next steps, which include (1) designing affective supports with our colleagues (e.g., Ryan Baker and Sidney D’Mello) such as motivational messages and attention redirection activities to complement the cognitive supports, and (2) implementing an adaptive algorithm into the game based on the dynamic results of the stealth assessment. We hypothesize that an integrated adaptive system that selects the best levels for each student will further foster learning. We hope to be able to answer questions regarding learning supports relative to what to do or say, when to do or say it, and how this can maximize learning while minimizing the disruption of gameplay. We will also examine the factors that mediate the influence of supports on learning and gameplay.

Authors

• Valerie J. Shute, Florida State University

• Seyedahmad Rahimi, Florida State University

• Xi Lu, Florida State University