Please use this identifier to cite or link to this item:
https://ptsldigital.ukm.my/jspui/handle/123456789/563482
Title: | Personalized serious games engagement model based on female’s preferences |
Authors: | Shahryan Abdulrahman Alserri |
Supervisor: | Nor Azan Mat Zin, Prof. Dr. |
Keywords: | Universiti Kebangsaan Malaysia -- Dissertations Dissertations, Academic -- Malaysia Serious games Virtual learning |
Issue Date: | 1-Jul-2021 |
Abstract: | Information and Communications Technology (ICT) has an important impact on the economy in many regions. However, in most countries, female involvements in ICT-related jobs are still low despite the availability of many well-paying jobs. Hence there is a need to increase the number of females taking ICT courses. On the other hand, technologies can enhance learning opportunities, and increase learning outcomes. Serious games, an effective tool for learning. However, researchers have found that serious games content does not capture female interest because of its stereotypical design and skewed towards male preferences. Females have their personal preferences in games. Therefore, many researchers suggest using game personalization to design and develop games for females to improve their interest and engagement with games. Moreover, only a few studies created a personalized game for females. Therefore, there is a need to design a personalized serious game for females, which contains their personal preference elements, to capture their attention and interest. Therefore, this study aims to design and develop personalized serious games to motivate female students to study Computer Science (CS). The specific objectives are to identify female preference factors that influence their engagement with serious games, to construct and validate personalized serious game engagement model based on gender, and to evaluate female students engagement with personalized serious game prototype. Usercentered design, which consists of four phases, is used as the research method. In the analysis phase, a study of related literature on personalized females preferences factors for digital games identified nine factors; exploration, fantasy, character customization, storyline, social interaction, challenges, fun, skills, and feedback. These nine factors are used to construct the conceptual model, which comprised of three components: pedagogy, female personalized preferences for digital games and flow state theory component. In the design phase, low fidelity prototype was designed based on the conceptual model and then validated using Heuristic Evaluation (HE) technique. In the development phase, HE results and experts’ comments are used as input in developing a high fidelity prototype. In evaluation phase, the prototype was evaluated using a quantitative approach with 152 undergraduate female students. The data were analysed using Structural Equation Modelling. Results show that all the model’s factors are valid and reliable. Female personalized preferences component’ factors and flow state theory have a positive significant effect on game engagement, but pedagogy is not significant in females’ game engagement. The results of the evaluation indicate that the research model was positively effective in engaging females to play serious games. Moreover, the contributions of the study are the females personalized preferences factors that affect female engagement in serious games, personalize engagement model for females in serious game to teach CS. The model can be used to guide the development of serious games for females which could help educate female students towards reducing the gap of female involvements with ICT. Another contribution of this study is the interface design of the game prototype based on the model. |
Description: | Fullpage |
Notes: | P80713 |
Pages: | 297 p. |
Publisher: | UKM, Bangi |
Appears in Collections: | Faculty of Information Science and Technology / Fakulti Teknologi dan Sains Maklumat |
Files in This Item:
File | Description | Size | Format | |
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SHAHRYAN ABD RAHMAN.pdf Restricted Access | Fullpage | 172.64 MB | Adobe PDF | View/Open |
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