The digital age, characterized by readily available information and social media's prevalence as a news source (Agarwal & Dixit, 2020; Kemp, 2019; Velichety & Shrivastava, 2022), presents challenges like the spread of misinformation (Hern, 2017; Allcott & Gentzkow, 2017). Developing information literacy skills is crucial to combat this (Aydin, 2021). E-learning offers a solution, but engaging students remains a challenge (Poondej & Lerdpornkulrat, 2019). Serious games, particularly personalized ones, offer potential for increased engagement and learning (Chen et al., 2019). This research explores the effectiveness of a personalized serious game designed to improve information literacy skills, focusing on the differences between introverted and extraverted individuals and employing suitable game elements to address the issue of fake news.
Literature Review
The study defines and categorizes fake news, focusing on misinformation (Wang, 2020; Park et al., 2020; Pennycook & Rand, 2019; Lewandowsky, Ecker, & Cook, 2017; Vosoughi et al., 2018; Tandoc, 2021). Information literacy is presented as a crucial skill to combat fake news (Guo & Huang, 2020; Pinto et al., 2020; Reddy et al., 2020; White, 2019; Banik & Kumar, 2019). The role of serious games in education is highlighted, emphasizing their interactive nature and ability to improve learning outcomes (Chen & Michael, 2005; Landers, 2014; Vidakis et al., 2019; Connolly et al., 2012; Romero et al., 2015; Ketamo et al., 2018). The concept of personalized educational games, adapting to individual learners' needs and preferences, is discussed, along with frameworks like the Personalized Learning Environment (PLE) (Hwang & Tsai, 2011) and LearnFit (Tlili et al., 2019). The literature explores the impact of personality traits, particularly introversion and extraversion, on learning styles and preferences (McCrae & Costa, 1987; Mount et al., 2005; Cohen & Baruth, 2017; Denden et al., 2018; Schimmenti et al., 2017; Anderson et al., 2018; Poropat, 2009; Chen et al., 2016; Jung & Baynes, 1923; Costa & McCrae, 2008; Paradilla et al., 2021; Dossey, 2016; Grimes et al., 2011; Blevins et al., 2022; Felder & Silverman, 1988; Borg & Shapiro, 1996; Gray et al., 2005; Eysenck, 1967; Nuckcheddy, 2018; Herzberg, 2008). The influence of game elements on different personality types is reviewed (Jia et al., 2016; Codish & Ravid, 2014a; Codish & Ravid, 2014b; Smiderle et al., 2020; Baker et al., 2021).
Methodology
A quasi-experimental design was employed, comparing a non-personalized serious game (control group) with a personalized version (experimental group) tailored for introverts and extraverts. Participants (N=58 undergraduate students) completed the Big Five Inventory (BFI) (Zhao & Seibert, 2006) to determine personality types. Pre- and post-tests assessed knowledge acquisition and retention of information literacy concepts, specifically source evaluation using the CRAAP test (Liu, 2021). The short Intrinsic Motivation Inventory (IMI) (Vos et al., 2011; Leenaraj et al., 2023; Ryan & Deci, 2000) measured intrinsic motivation (perceived competence, interest, and effort). Login data from the online game provided user behavior data (total and average playtime, number of logins). Data analysis included Shapiro-Wilk tests for normality, paired samples t-tests and Welch's t-tests for comparisons, and Cohen's d for effect sizes. The experiment involved four steps: 1) Consent, pre-test, pre-IMI; 2) Two-week game play; 3) Post-test, post-IMI, data collection; and 4) Delayed post-test (two months later) for knowledge retention. Participants received 200 baht compensation.
Key Findings
Pre/post-test results showed significant knowledge acquisition in both groups (control: M=16.68, SD=4.04; experimental: M=17.34, SD=4.62), but no significant difference between groups (p=0.711, d=0.296). Two-month retention also showed no significant difference (p=0.619, d=0.272). The IMI questionnaire revealed that the personalized game significantly improved all three dimensions of intrinsic motivation (perceived competence, interest, effort) in the experimental group, while the control group only showed significant improvement in interest. A Welch's t-test comparing the two groups showed a significant difference only in perceived competence (p=0.035). Analysis of login data indicated a 37% increase in total playtime for introverts in the personalized game group compared to the control group (Welch's t-test: p<0.001). Extraverts showed no significant difference in playtime between groups (p=0.053).
Discussion
The study's findings suggest that while personalized serious games can significantly enhance intrinsic motivation, particularly perceived competence, they do not necessarily lead to greater knowledge acquisition or retention compared to non-personalized games. The significant increase in engagement among introverted participants in the personalized game highlights the importance of tailoring game elements to specific personality traits. The lack of significant impact on extraverted participants may suggest that the chosen game elements were not optimally suited to their preferences or that other factors influenced their engagement. These results contribute to the understanding of personalized game design and the complex interplay between personality, game mechanics, and learning outcomes.
Conclusion
This study demonstrates that personalized serious games, while effective in boosting intrinsic motivation (especially perceived competence), do not necessarily improve knowledge acquisition or retention over non-personalized versions. A significant improvement in engagement was observed among introverts using personalized games. Future research should explore a wider range of game elements and personality dimensions, and examine diverse participant groups.
Limitations
The study's generalizability may be limited by its specific sample (undergraduate students at Chiang Mai University). Technological access and individual differences in device usage could have influenced results. The complex interaction between game elements and personality traits requires further investigation to identify optimal combinations.
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