Persuasive Play : Extending the Elaboration Likelihood Model to a Game-Based Learning Context

Persuasive Play : Extending the Elaboration Likelihood Model to a Game-Based Learning Context

Steven Malliet (University of Antwerp, Belgium) and Hans Martens (University of Antwerp, Belgium)
DOI: 10.4018/978-1-61520-719-0.ch009
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Little research has examined the underlying psychological mechanisms of persuasive play. The purpose of the current study is to examine the explanatory potential of information processing approaches in a game-based learning context. Starting from the elaboration likelihood model, the authors theoretically develop a three-step model to explain how individual player characteristics (e.g., game preference) influence cognitive learning and attitude change through mediating variables like player motivations (e.g., personal involvement) and player evaluations (e.g., perceived realism). This model is empirically tested through a secondary analysis of survey data collected from Flemish adolescents (N = 538) in the 5th and 6th grade of secondary education. On the whole, the authors’ results emphasize the importance of information processing variables as predictors of cognitive and attitudinal learning outcomes.
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Digital gameplay has been associated with a wide range of behavioral effects, including positive outcomes such as problem-solving capabilities (Cassell & Ryokai, 2001), spatial cognition (McClurg & Chaillé, 1987), mnemonic strategies (Oyen & Bebko, 1996), hand–eye coordination (De Aguilera & Méndiz, 2003), and social/political empowerment (Frasca, 2004), as well as negative outcomes such as aggressive script rehearsal (Anderson & Dill, 2000) or socialization of violent attitudes and behaviors (Bushman & Anderson, 2002). Although early research had a strong focus on empirically investigating these aspects, in recent years, a shift can be observed towards framing these results within a more comprehensive theoretical framework (e.g., Dipietro, Ferdig, Boyer, & Black, 2007; Van Eck, 2007).

Several models have been used to explain the learning processes that take place during digital gameplay, including models derived from social psychology (Bandura, 2002), language acquisition theory (Johnson, Vilhjalmson, & Marsella, 2005), formal design theory (Gunter, Kenny, & Vick, 2006), or experiential learning theory (Egenfeldt-Nielsen, 2005). In this chapter, we argue that the elaboration likelihood model, or ELM (Petty & Cacioppo, 1986a, 1986b), provides a valuable additional point of view. The ELM has proven useful in explaining the effectiveness of persuasive communication in a wide range of applied research domains such as mass media (Petty, Briñol, & Priester, 2008), health communication (Braverman, 2008; Briñol & Petty, 2006; Holt, Lee, & Wright, 2008; Petty, Gleicher, & Jarvis, 1993), risk communication (Rucker & Petty, 2006), environmental communication (Mosler & Martens, 2008), computer-mediated communication (Di Blasio & Milani, 2008), and entertainment education (Slater & Rouner, 2002). As an audience-centered model focusing on message processing, the ELM can become a particularly useful tool for exploring the influence of serious games on knowledge acquisition and attitudes. This approach is in accordance with current tendencies in research on video game effects that put an emphasis on the receiver side in the communication process (e.g., Malliet, 2007). Nevertheless, the motivations and evaluations of video game players are presumably different than those of recipients of explicit persuasive messages about health, risk, or environment. For example, popular video games are able to attract audiences, not necessarily because of their educational or persuasive content, but because they are compelling as games (for a similar line of argument, see Slater & Rouner, 2002). Therefore, in order to explain how video games can elicit both unintended and intended cognitive and attitudinal effects, the main concepts of the ELM should be translated to a video game research context.

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