Validation of the Player Personality and Dynamics Scale

Abstract

Featured Application: The Player Personality and Dynamics Scale (PPDS) can be embedded as an adaptive profiling module in any Learning Management System (LMS). After students complete the brief intake questionnaire (~1 min), the system yields five independent scores, one for each profile (Toxic, Joker, Tryhard, Aesthetic, and Coacher). These continuous scores enable the LMS and its analytics engine to perform the following: 1. Feed AI models that generate or select gamified narratives and mechanics tailored to the specific profile configuration of each learner rather than to a single dominant type. 2. Form student groups on the basis of shared or complementary play-style patterns, thereby fostering cooperation or purposeful competition and mitigating interpersonal conflict. 3. Adapt activity design and learning pathways by dynamically adjusting challenge level, feedback tone, and aesthetic presentation to the profile values of individual students or groups, thus maximizing motivation and engagement. 4. Log profile-linked learning analytics data, providing researchers and instructors with data to rigorously assess the impact of such personalized, narrative-driven gamification on academic performance and retention in forthcoming controlled studies with university cohorts and, subsequently, other educational levels. The psychometric validation reported in this article supplies the empirical foundation required to implement and evaluate these applications in future experimental research. This study presents the validation of the Player Personality and Dynamics Scale (PPDS), designed to identify player profiles in educational gamification contexts with narrative elements. Through a sample of 635 participants, a questionnaire was developed and applied, covering sociodemographic data, lifestyle habits, gaming practices, and a classification system of 40 items on a six-point Likert scale. The results of the factorial analysis confirm a structure of five factors: Toxic Profile, Joker Profile, Tryhard Profile, Aesthetic Profile, and Coacher Profile, with high fit and reliability indices (RMSEA = 0.06; CFI = 0.95; TLI = 0.91). The resulting classification enables the design of personalized gamified experiences that enhance learning and interaction in the classroom, highlighting the importance of understanding players’ motivations to better adapt educational dynamics. Applying this scale fosters meaningful learning through the creation of narratives tailored to students’ individual preferences.