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Over the past decade, burgeoning concerns with promoting students’ interest in the disciplines of science, technology, engineering, and mathematics (STEM) have prompted many studies and initiatives aimed at understanding and measuring STEM learning (Lam, Srivatsan, Doverspike, Vesalo, & Mawasha, 2005; Machi, 2008; Yang, 2010). In parallel, the growth in the popularity of gaming in education spawned its own share of research (Klabbers, 2003; Wilson, et al., 2008). While these themes pose compelling aims for research, a deeper issue is the science underperformance of high school graduates in the U.S. (AECT, 2010). Despite all innovative approaches, an alarmingly large percentage of middle and high school students continue to forgo science classes (Sanders, 2009).
A shared objective among educators is to inspire in students the desire to learn. Yet it is commonplace to hear students readily express their displeasure with or apprehension about science. If students lack the interest or motivation to learn science; then, the expectation to demonstrate knowledge of complex concepts through assessments that rely on memorization can have a diminishing effect (Yang, 2010). The use of situated assessments using virtual environments brings task relevance, attempts to address the issue of memorization, and aims to engage students in true scientific inquiry (Nelson & Ketellhut, 2007). Situated assessment environments evaluate students’ actual performance while affording them opportunities to strengthen the confidence in their beliefs and abilities.
Some researchers have found that students’ lack of interest in science is not something that can be dichotomized as like or dislike, but rather should be thought of as a range of levels of interest that can vary according to context and topic (Ainley, Hidi, Berndorff, 2002; Kang, Scharmann, Kang, Noh, 2010). These varying levels of interest may be attributed to factors beyond science itself or to a lack of understanding—primarily situational and affective factors. Situational factors include things like students’ workload, priorities, and locus of control. The affective factors include perceived lack of relevance, boredom, and inability to see a practical application (Yang, 2010). Some also believe that it is better to focus on learner competence rather than on motivation, as academic experiences have a significant impact on self-beliefs (Becker & Luthar, 2002). This indicates that initiatives to promote STEM education may need to go beyond the subject matter or the delivery method. Learning environments should include features that support situational and affective factors such as motivation, interest, and beliefs about competence.
Increasing interest is a notion that aligns with the self-determination theory of motivation which refers to an individual’s sense of choice and initiative over their actions (Deci, Vallerand, Pelletier & Ryan, 1991). Wigfield and Eccles (2002) found that a sense of competence influences students’ level of interest. They also posit that expectancy of success (i.e., confidence in one’s competence or likelihood of success) is a strong predictor of performance. Lawanto, Santoso and Liu (2012) also found that interest influences competence beliefs. Competence beliefs refer to students’ perceptions about their academic ability and attitudes towards success.