Center on in Pantone7473c/7462c/7542c Thank you for downloading Choose Your Level: Using Games and Gamification to Create Personalized Instruction Karl M. Kapp from the Center on Innovations in Learning website www.centeril.org This report is in the public domain. While permission to reprint this publication is not necessary, it should be cited as: Kapp, K. M. (2016). Choose your level: Using games and gamification to create personalized instruction. In M. Murphy, S. Redding, & J. Twyman (Eds.), Handbook on personalized learning for states, districts, and schools (pp. 131–143). Philadelphia, PA: Temple University, Center on Innovations in Learning. Retrieved from www.centeril. org The Center is funded by the U.S. Department of Education, Office of Elementary and Secondary Education (OESE), under the comprehensive centers program, Award # S283B120052-12A. Choose Your Level: Using Games and Gamification to Create Personalized Instruction Karl M. Kapp Maria, an eighth-grade student, arrives to science class early, walks over to a cabinet, and chooses a tablet computer. She then sits down quietly and begins learning with the tablet. Other students slowly file in and do the same. Maria is learning about velocity as part of a unit introduced by her teacher last week. After Maria’s teacher introduced the concept of velocity and how it is calculated, he assigned a learning game to reinforce what he had taught, and that is what Maria and her classmates are engaged in now. Maria looks over and waves to her friend Juan who has just retrieved his tablet from the cabinet. Today, the first thing Maria does is choose a level. She is feeling smug but not super smart, so she decides to play Level 1 over again before proceeding to the newly unlocked and substantially more difficult Level 2. After quickly playing the first level of the game again and only having to start over once, losing only a couple of points, she proceeds to Level 2 and its terminal learning objective related to the calculation of veloc- ity. Of course, to Maria, it’s not a “terminal learning objective”; rather, it’s the next level of the ROV Commander game she’s been playing for the past few days (Figure 1). Figure 1. The ROV Commander Screenshot 131 Handbook on Personalized Learning In the game, she is the “commander” of a remotely operated vehicle (ROV). The ROV looks like a sphere with an antenna on top. Maria’s challenge is to maneuver the ROV through an obstacle course without running into anything. Her goals are to find a half dozen “hidden” waypoints and to accurately record information about distance, time, and rate and then make calculations based on the recorded information (see Figure 2). The waypoints aren’t really hidden, and if she records information and performs her calcula- tions properly, she can find them quickly. Maria maneuvers the ROV within the confines of the game’s landscape and then records data for each waypoint she locates. With the recorded data, the game can “check” to see that Maria is performing the velocity calcu- lations correctly. If she is not, the game provides corrective feedback, and Maria must recalculate the data for the waypoint. If she does hit an obstacle, the ROV loses speed and energy points. These are both undesirable outcomes to Maria, who is striving to be the first student in her class to get to Level 3 and win the game. If she loses speed, she can’t get to the next level as quickly; if she sustains too much damage, her ROV will need to start over. Maria has heard that Level 3 is “cool,” that the ROV uses boosters to fly. She wants to check that out, but first she will have to do some calculations. Unknown to Maria, but part of why her teacher has chosen ROV Commander as a learning game, is that each level introduces a new concept. This structure provides a scaffolded approach to content enabling Maria and her classmates to progress in both the knowledge and appli- cation of formulas for average velocity, final velocity, distance traveled, and acceleration. Finally, Maria completes her last calculation and finds the last waypoint. She is pleased and lets out a screech. As she reflects on finding this last waypoint, it occurs to her that Juan must have missed it. Otherwise, he wouldn’t be stuck driving around the ROV on Level 2, which is where he started today. Maria suspects it might be because he needs to spend some time calculating distances or travel time from one waypoint to another. Maria mentally makes a note to herself to give Juan a hint of where to look for the last way- point. But that will have to wait, because Maria wants to make it to Level 3 and win the game before Juan does. She is feeling confident that today is the day she’ll make it and win the game. Figure 2. Calculating Speed With Distance and Time 132 Choose Your Level: Using Games and Gamification For decades, educators have been forced to choose between providing each student with personalized instruction or covering required state or locally mandated content. In many cases, the need to cover required content trumped the idea of providing personal- ized learning for each student. Given those requirements and typical class sizes, it has been impossible to personalize curriculum delivery, pacing, and level of difficulty for each student. As Maria’s game-playing experience indicates, game-based learning provides several advantages over traditional teacher-led instruction—that is, lecture-based instruction with uniform content delivered to all the students at the same pace, with little time for student reflection or self-direction. Game-based learning, on the other hand, enables each student to have a personalized learning experience with the same content at his or her own pace. Students Game-based learning, on the can review content if they wish, speed ahead, other hand, enables each student to have a personalized learning experiment, and experience the game differently experience with the same content than fellow students and still reach the same at his or her own pace. learning outcomes. In addition to individual- ized pacing, games provide for a student to progress in different ways through the game, reviewing levels or content by replaying a level, and making new choices that impact the outcome of the game (Kapp, 2012). Games can instantly provide feedback and help when needed without the student raising his or her hand or interrupting the teacher who is help- ing another student. Well-designed game-based learning provides levels of personalization that “scaffold each student’s learning and foster self-direction to help each individual achieve mastery of knowledge and skills” (Redding, 2014, p. 6) Although a similar experience could be had in many classrooms with nondigital interventions, many constraints preclude the use of those interventions in achieving personalized learning. Aspects of nondigital strate- gies—such as paper-based programmed instruction and personalized tutoring by the teacher providing carefully scaffolded lessons based on each student’s past performance and rate of understanding—conflict with basic instructional limitations, including the available time and materials and maintaining good classroom management. Digital games, then, offer an ideal tool for delivering what the U.S. Department of Education defines as personalized learning, which is “instruction that is paced to learn- ing needs (i.e., individualized), tailored to learning preferences (i.e., differentiated), and tailored to the specific interests of different learners” (2010, p. 12). Games offer many of the elements of personalization as well as the ability to provide personalized instruction on a scalable level. A teacher can provide all 30 students in her classroom with a tablet, and each can then begin engaging in personalized learning (Guillén-Nieto & Aleson- Carbonell, 2012). Although all of these features of game-based learning reflect advantages associated with personalized learning, research comparing game-based learning with traditional classroom instruction has not consistently shown one method to be superior to the other. Game-based research for education is “vast but not conclusive” (Schifter, 2013, p. 149). Game-based research has been centered on comparison-based studies and discussions of which is better, traditional instruction or game-based learning (Kapp, 2013; Liao, 2010; Randel, Morris, Wetzel, & Whitehill, 1992; Sigurdardottir, 2012). There has not 133 Handbook on Personalized Learning been a conclusive answer to this question. In some studies, games have proven more effective than traditional teacher-led instruction, and, in some cases, they have not. The lack of a definite winner between games and traditional instruction has led to confusion about the effective use of games in the classroom among policymakers, administrators, teachers, and parents, who have little practical or actionable advice to guide them. It has even caused some to ask, “Are games effective for teaching at all?” (Clark, 2013). The answer to that question is a resounding “yes.” Evidence strongly supports the conclusion that games are capable of being effective and efficient tools for teaching—stu- dents can and do learn from games (Hays, 2005; Ke, 2009; Randel et al., 1992; Schifter, 2013; Sitzmann, 2011; Vogel et al., 2006; Wolfe, 1997; Wouters, van Nimwegen, van Oostendorp, & van der Spek, 2013). So the question should not be “Are games capable of teaching?” because they are. Instead, stakeholders should be asking several other questions: “What features of games lead to learning and when?” “What classroom conditions support using games?” “How should a game be integrated into the classroom to ensure positive learning outcomes?” To answer these questions, we need to delve into the rich history of game research and not look only at the comparison with other types of instruction but also review the studies which determine what elements were present in the game or classroom condition when the games led to positive learning outcomes.