II. Affective Metrics

Metrics of Motivation in Simulations or Game Environments

Simulations, serious games, and game-based learning have become important tools to promote learning outcomes such as acquiring new knowledge, expertise, and content understanding (Hainey ct al., 2016; Konetes, 2010; Mayer, 2019). To date, cognitive aspects of these games and simulations have received the bulk of the attention in terms of both research and theory (Boyle ct al., 2016; Plass et al., 2020). While motivational aspects have not been ignored, the amount of attention has been lower (O’Neil et al., 2005). The emphasis of the present chapter, therefore, is on motivational aspects of serious games and simulations, specifically considerations for their measurement and possible metrics. Rather than providing a compendium of everything that can be assessed, it outlines an approach that begins with well-established motivation theories and research, takes into consideration features of simulations and serious games, and ends with assessment targets that can be examined with a variety of methodologies. The chapter begins with a brief overview of the characteristics of games, with special attention to those features which have motivational consequences. Next, an overview of relevant motivational perspectives is presented, including a discussion of the constructs of motivation, emotion, and engagement and ways that these can be linked and used to frame their assessment within serious games and simulations. Finally, general measurement principles and possible metrics are presented as a means to provide guidance in the development of improved assessment and measurement for research and development purposes, with a goal of promoting increased attention to motivational and affective influences on performance.

Characteristics of Simulations and Serious Games

There are many names for the family of computer-based platforms under consideration here, including game-based learning, serious games, educational games, simulation games, virtual environments, etc. In fact, one of the issues with the research in this area is the lack of consistent and widely agreed-upon terminology. In general, serious games and simulations (hereinafter labeled SGS) differ from games in which the primary purpose is to entertain without an intentional, overt educational or training goal (O’Neil et al., in press;

O’Neil et al., 2005). Wouters and van Oostendorp (2017) and others (Mayer, 2014; Sitzmann, 2011) have noted common characteristics and features of SGSs that include being interactive (the player can make actions), based on a set of agreed rules and constraints (events are bound within a set of rules), directed toward a clear^o«/ that is often set by a challenge (opportunities exist for success and for overcoming difficulties), providing feedback in the form of written or verbal communication with a player, a score, or changes in the game that enable monitoring of progress toward a goal (the SGS is responsive to player actions), and goal-oriented (the player intentionally pursues a goal and can monitor progress along the way). Simulation games in general have a goal of helping one discover causal relationships in a nonlinear fashion and master specific skills and have well-defined achievable goals with predictable outcomes. Thus, the motivation to engage in a simulation is based on the need to learn more about a domain, and is more likely to be required and nonvoluntary. While there are many discrete features of SGSs, two elements especially salient in terms of motivation are the ability to give feedback (Johnson et al., 2017) and the ability to promote interest and engagement of players.

Motivation in SGSs

Early views of motivation emphasized stable and enduring drives needing to be met, reflecting the behavioral view of human functioning. However, contemporary theory focuses on cognitive approaches to motivation, including a learner’s beliefs or interpretations of various aspects of a specific learning situation, task, or domain. A recent overview of motivation defined it as “the processes of initiating and sustaining behavior" (Linnenbrink-Garcia &: Patall, 2016, p. 91). The focus in this chapter is on motivational considerations related to learning tasks and contexts within SGSs, often called achievement motivation (Aiderman, 2008).

Social Cognitive Theory

Even though a cognitive perspective unites contemporary motivational theories, there is no overarching theory of motivation, but rather there are various subtheories that focus on various components and which vary in comprehensiveness in terms of the components represented (for reviews see Karabenick & Urdan, 2014; Schunk et al., 2014; Wentzel & Wigfield, 2009). Bandura’s (1986, 1997, 2001) social cognitive theory has provided a general overall perspective that underlies many motivation theories (Blumberg et al., 2012; Klimmt & Hartmann, 2006; Klimmt et al., 2007). Briefly, Bandura’s triadic reciprocal causation model identifies three variables (internal personal factors, behavioral patterns, and environmental influences) whose bidirectional interactions explain human functioning. Regarding internal personal factors, Bandura (1986, 1997) noted that the beliefs people have about their capability (self-efficacy) serve as better predictors of their behavior and exert an enormous influence on how people engage their skills and knowledge, and these in turn have been shown to predict learning and academic outcomes (Schunk & Pajares, 2009).

Self-Efficacy

Self-efficacy has been defined by Bandura (1986) as “people’s judgments of their capabilities to organize and execute courses of action required to attain designated types of performances” (p. 391). While many motivational constructs appear in the literature, self-efficacy is one of the most investigated. Pajares and Urdan (2006) have indicated that self-efficacy predicts academic achievement across academic areas and different educational levels, and has also been associated with increased engagement, task persistence, effort, learning, self-regulation, positive emotions, and overall achievement (Klassen & Usher, 2010; Schunk &: Pajares, 2005; Usher, 2016) including within SGS environments (Klimmt & Hartmann, 2006).

Bandura (1997) proposed that self-efficacy beliefs are developed and influenced over time based on four both internal and external cues, which are attended to, interpreted, and integrated through a dynamic process that varies depending on the social context (Bandura, 1997). In the context of an SGS, feedback and the organization of success and failure (for example by modifying difficulty levels) may be the most direct influences. Muenks et al. (2018) noted that training studies have indicated that feedback, especially when combined with training of skills to be undertaken, is successful in increasing self-efficacy and control expectations (Schunk, 2003), and feedback can provide information about an individual’s mastery of a task (Zimmerman & Kitsantas, 2002) further contributing to the development of self-efficacy (Johnson et al., 2017).

 
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