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As a nation with a great need to increase its number of graduates in science, technology, engineering, and math (STEM) fields STEM fields (President’s Council of Advisors on Science and Technology (PCAST), 2010), US educators and researchers have been tasked with finding solutions and resources that address academic and career-based barriers. While barriers to learning can exist in any field, certain educational areas are known for having a steep learning curve, like the STEM fields. Within the STEM disciplines underrepresentation of minority populations are most severe (Hill et al., 2010; Congressional Commission on the Advancement of Women and Minorities in Science, 2000). And while much STEM content has the reputation of being tough, students’ beliefs regarding their success or potential to succeed in these areas could be just as tough a barrier to overcome (Pajares, 2004). For example, the phrase “I’m just not a math person” is commonly used to avoid math related tasks—preferring to defer responsibility to someone perceived to be more skilled. This doubt of ability and deference of challenge demonstrates the connection between a person’s belief about their ability to perform a given task and their actual performance (Bandura, 1997). And this trend is common among various fields (Rodgers, et al., 2014), but perhaps most prevalent in STEM (Lauermann et al., 2017; Nosek et al., 2002; Nosek & Smyth, 2011; Patall et al., 2018). So, how is a barrier of self-belief overcome?
Evidence has shown incorporating digital game-based learning can increase student learning outcomes and interpersonal outcomes, such as motivation and positive self-evaluation across content areas (Clark et al., 2016; Mayer, 2020; Sung et al., 2017), including STEM disciplines (Hwa, 2018; Kebritchi et al., 2010; Shute et al., 2021f; Vu & Feinstein, 2017). However, the relationship between students’ beliefs regarding their abilities to perform, performance-based perceived competence, and their performance in STEM across different populations remains unknown. This analysis takes a step towards better understanding how differences between underrepresented populations (i.e., gender and ethnicity) and their reported performance-based perceived competence, may affect their ability to learn from, perform in, and enjoy a digital learning game for physics.