Detecting Play and Learning Styles for Adaptive Educational Games Renny S. N. Lindberg and Teemu H. Laine Department of Information and Computer Engineering, Ajou University, Suwon, South Korea Keywords: Learning Styles, Play Styles, Educational Games, Adaptation, Questionnaire. Abstract: Digital games have emerged as promising tools that aim to make learning more fun. As each person has different learning and play styles, educational games can become more effective should they adapt content delivery according to the user’s learning and play styles. To achieve this, models are needed to represent these styles. Several learning and play style models exist today with varying levels of validity and complexity. With the emergence of educational games, the importance of using such models for enhancing the effectiveness of games as viable educational tools increases. However, not many studies have been conducted that simultane- ously consider both style groups. We first analysed existing learning and play models. Based on the analysis results, we created a questionnaire that uses Bartle’s Player Types model and Honey and Mumford’s Learning Style Questionnaire, and tested it with 127 South Korean elementary school children. The results indicated that within the play style model specific styles were clearly more preferred, whereas learning styles were dis- tributed more evenly. There also were some differences between genders. The results can be used to inform us on what sort of stimuli might yield better immersion in educational games and thereby facilitate the learning process. 1 INTRODUCTION ing styles include Kolb’s Learning Style Inventory (LSI) (Kolb, 1984), Honey and Mumford’s Learn- Digital games have risen to new heights as general ing Style Questionnaire (LSQ) (Honey and Mumford, entertainment to most age groups. They also have 1982), and Felder and Silverman’s Learning Style expanded beyond their traditional field of leisure, as Model Felder1988. they have been increasingly utilized as tools to sup- There are several game genres – ranging from first port and provide education (Nygren et al., 2012; Co- person shooters (FPS) to a large scale country govern- enen et al., 2013; Popescu et al., 2011), and as cat- ing simulations, and from role-playing games to sport alysts for people do physical exercise (Morelli et al., games – that cater for and expect vastly different play 2011; Macvean and Robertson, 2012). These types styles. For example, a majority of FPS games expect a of games that have other purpose than pure enter- combination of aggressiveness and cunning, whereas tainment, are generally referred to as serious games. a typical role-playing game might want the player to Within the umbrella of serious games, game-based have more of a strategic mindset. Perhaps due to the learning in particular is a heavily trodden research youth of the gaming research field, there are not many field. It has been shown that utilizing games in ed- validated play style models that tackle the heterogene- ucation can yield positive results in learning and mo- ity in player population. Examples of models that are tivation (Connolly et al., 2012; Popescu et al., 2011; dedicated to categorize play styles are: Bartle’s Player Coenen et al., 2013; Arnab et al., 2013; Nygren et al., Types (BPT) (Bartle, 2015), Bateman’s Demographic 2012; Kim et al., 2009; Ke and Grabowski, 2007). Game Design (DGD1, DGD2) (Bateman and Boon, While researching education and especially learn- 2005), and Lazzaro’s Four Keys (4K) (Gomez et al., ing, it is not uncommon to come across different 2004). In addition, personality models have also been learning style models and discussions for and against suggested for identifying different player types, such them. Researchers have proposed several models for as Keirsey Temperament Sorter (KTS) (Keirsey and mapping out various learning styles with the pur- Bates, 1984). pose of understanding the differences among hetero- The reasoning for adapting educational games to geneous learners and thereby optimizing the learning cater for both play and learning styles of a person is experience for each learning style. Popular learn- threefold. Firstly, adaptive educational games could 181 Lindberg, R. and Laine, T. Detecting Play and Learning Styles for Adaptive Educational Games. In Proceedings of the 8th International Conference on Computer Supported Education (CSEDU 2016) - Volume 1, pages 181-189 ISBN: 978-989-758-179-3 Copyright c 2016 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved CSEDU 2016 - 8th International Conference on Computer Supported Education offer learning materials to the person in a way that and therefore negatively affect the learning experi- the person would be more attuned to receiving and ence. Moreover, as educational games’ main focus is processing. Secondly, by offering a play style more to educate the player on selected topics through game- suitable for the person, the game mechanics would be play, it is important to select appropriate pedagogical easier to understand and thus cut down the learning methods, game mechanics and content modalities to curve at the beginning. Thirdly, a well-aligned play support the player’s personal play and learning styles. and learning styles, through which learning materials Several studies have been conducted in the are provided, could increase the person’s motivation field of game research that focus on either play to continue playing the game and increase the possi- style(McMahon et al., 2012; Orji et al., 2014) or bility for the person to enter the flow state (Mirvis, learning style (Koops and Hoevenaar, 2012; Bontchev 1991). and Vassileva, 2011). We were, however, unable to This work is part of a three-year (2015-2018) Ko- find many studies that would consider both styles si- rean National Research Foundation project, which multaneously. Finally, many models have been pro- aims at developing a learner-aware adaptation frame- posed to organize various play and learning styles. work for developing games for programming educa- Thus, in the following sections we describe and com- tion. In this paper, we presents the results of mul- pare the most well-known and well-tested models to tiple research activities that contribute towards the see how they differ from one another. project’s goals. Firstly, we review existing models for learning and play styles. Secondly, based on the re- 2.2 Learning Styles view, we select one learning style model and one play style model, and develop a questionnaire for identi- Learning styles have been researched by scholars for fying a child’s play and learning styles. Thirdly, we decades. In the following, we present three popular present an analysis of data that were collected from learning style models. 127 South Korean elementary school students using the questionnaire. The purpose of this study is to 2.2.1 Kolb’s Learning Style Inventory see how learning and play styles manifest themselves in a sample population of South Korean elementary One of the best known learning style models was cre- school students. ated by Kolb, who published his Learning Style In- ventory (LSI) in 1984 (Kolb, 1984). In his model, Kolb defined four distinct learning styles as follows: 2 BACKGROUND Accommodator (CE / AE): Prefers practical • hands-on approach to problems. 2.1 Game-based Learning Converger (AC / AE): Prefers hands-on approach • to applying theories. As we briefly stated above, using games to convey ed- Diverger (CE / RO): Prefers discussing and think- ucational content has shown positive results in mul- • ing the problem through. tiple areas. Connolly et al. (Connolly et al., 2012) Assimilator (AC / RO): Prefers reasoning and the- conducted a systematic literature review on 129 pa- • pers of which 82 presented educational games in a oretical approach. range of fields such as business, engineering, ge- Kolb’s learning styles are based on the four-stage ography, health, history, language and mathematics. learning cycle, which consists of: Concrete Expe- The authors discovered that many of the reviewed pa- rience (CE), Reflective Observation (RO), Abstract pers reported that students enjoyed a game-based ap- Conceptualization (AC) and Active Experimentation proach and found it motivating. They also mentioned (AE). Essentially, the four learning styles are com- that the diversity of research on positive impacts and binations of these four stages. For instance, Accom- outcomes associated with playing digital games was modator is a combination of Concrete Experience and noteworthy. Active Experimentation (Kolb, 1984). Since its emer- As shown in Connolly et al’s survey and sev- gence, LSI has been developed further with the lat- eral other studies (Garris et al., 2002; Eastern, 2009; est iteration specifications having been published in Bostan, 2009; Nygren et al., 2012), using games to 2005 (Kolb and Kolb, 2005). convey educational content shows clear results when it comes to raising people’s motivation. However, an educational game that does not respond well to play- ers’ learning and play styles might damage motivation 182 Detecting Play and Learning Styles for Adaptive Educational Games 2.2.2 Honey and Mumford Learning Style Verbal learner: Gets more out of words, both writ- • Questionnaire ten and spoken. Sequential learner: Approaches a problem in a Honey and Mumford (Honey and Mumford, 1982) • stepwise manner, solving one subproblem at a built their Learning Style Questionnaire (LSQ) on top time. of Kolb’s LSI. Their purpose was to use the model in the context of management of workspaces. Honey Global learner: Move forward in large jumps, ab- • and Mumford redefined LSI’s four learner types as: sorbing materials in a seemingly random manner. Activist: Learns by doing; prefers a practical ap- It is worth noting that “Verbal” was “Auditory” in • proach. the original model, and the term “Verbal” was pro- posed by Felder and Solomon in ILS (Oxford, 2003; Theorist: Learns by an analytical approach; needs • Felder and Spurlin, 2005). Furthermore, within one to understand the theory first.