INTRODUCTION

There is increasing demand for talents in the computer science (CS) field. However, the field of CS has always faced a dilemma of talent shortage. For example, relevant industries like information technology (IT) and Artificial intelligence (AI) have been constantly recruiting new programmers and software developers (Costa, 2014). These fields are growing is so quickly that the demand for human resources cannot be met. This phenomenon is especially popular in California in the United States because a big number of giant companies in the CS field are located in Silicon Valley. 

Bergin and Reilly (2005) pointed out that low graduation rate of CS major in U.S. universities was one of the main reasons that caused the lack of talent. According to (Dolgopolovas, Jevsikova & Dagiene, 2018), “the researchers found that although there were ¼ million computing jobs opened in the U.S between 2008 and 2018, only 64,405 students received computer science degrees in the year of 2015 - 2016 according to the data from the U.S. Department of Labor and the National Center for Education Statistics” (p. 78).

In order to solve this problem, in early 2000s, many scholars proposed a variety of ways to help college students learn CS. Curriculum and learning activities by (Lepper, Corpus, & Iyengar, 2005) and Vallerand et al. (2008) were designed to extrinsically motivate U.S. undergraduate students to learn Python, a programming language commonly set in introductory courses by universities. Nevertheless, students’ learning outcomes indicated that pedagogical approaches that only focused on extrinsic motivation didn’t work well (Glogger-Frey et al., 2015; Gopalan, Bakar, Zulkifli, Alwi, & Mat, 2017).

After several decades’ study and discussion, self-determination theory (SDT), which can transfer students’ learning from being extrinsically motivated to intrinsically motivated, has continuously gained support from scholars (Ryan, 2000; Jenkins, 2001; Bergin, 2005; Gressmann, Weilemann, Meyer, & Bergande, 2019; Serrano Corkin, Ekmekci, & Fisher, 2020). Moreover, research by (Wang, Liang, Liu, & Liu, 2016), (Hug, Thiry, & Tedford, 2011) and (Srimadhaven et al., 2020) claimed that gamification was able to benefit U.S. college students’ CS learning through intrinsically motivating them to complete assignments.

Given that SDT can improve students’ CS learning outcomes, and given that the issue of insufficient human resources, it’s important that constructing theoretical framework based on SDT. Therefore, this proposal aims to design a RPG game for California undergraduate students without programming experiences to learn the knowledge and concepts of Python in order to solve the problem of talent shortage.