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Thesis
Mixed-methods evaluation of metrics, character speed, and camera FOV: optimizing immersion, navigation, and engagement in first-person level design
Master of Science (M.S.), Drexel University
Jun 2025
DOI:
https://doi.org/10.17918/00010998
Abstract
Establishing precise spatial metrics and player perspective parameters is fundamental to shaping player spatial experience in first-person level design. Yet, industry standards and empirical guidelines for integrating object size, character movement speed, and camera field of view (FOV) remain underdeveloped. This gap leaves level designers reliant on intuition and iterative trial-and-error, often resulting in inefficient workflows and unpredictable player experiences. This thesis investigates how three categories of level objects--navigation objects, visual cue objects, and environmental objects--interact with player movement speed and camera FOV to influence immersion, navigation clarity, and engagement. The research employs a mixed-methods approach, using a custom white-box playtesting level developed in Unity and based on Call of Duty: Warzone's Caldera (Activision, 2024) map. The experimental level features both indoor and outdoor spaces, systematically manipulated across six experimental conditions varying metrics, movement speed, and FOV. Twelve participants completed playtesting tasks under these controlled conditions. Three complementary data sources were collected: (1) objective level completion times, (2) volumetric heatmaps of player routes, and (3) subjective spatial experience ratings via post-play Likert-scale questionnaires. Multiple regression analyses and cross-validation triangulation were employed to examine independent and interactive effects of metrics, speed, and FOV shape multidimensional player spatial experience. Findings demonstrate that each parameter not only exerts distinct influences on spatial experience dimensions but also interacts non additively. Larger object metrics and reduced character speed reliably promote deeper spatial exploration and immersion, while expanded FOV enhances navigation and engagement. Notably, parameter combinations yield non-linear effects, reinforcing the necessity for designers to consider interdependencies among spatial metrics, movement, and perspective. The thesis offers empirically grounded, data-driven recommendations for early-stage white-box level design, providing actionable guidelines for object scaling, movement tuning, and FOV selection. These findings contribute to both game research and practice by establishing a robust, mixed methods framework for evaluating and optimizing player spatial experience. The methodological approach and results support the development of more efficient design workflows and the creation of engaging, navigable, and immersive first-person game environments.
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Details
- Title
- Mixed-methods evaluation of metrics, character speed, and camera FOV
- Creators
- Junfeng Liu
- Contributors
- Tony Allen Rowe (Advisor) - Drexel University, Digital Media
- Awarding Institution
- Drexel University
- Degree Awarded
- Master of Science (M.S.)
- Publisher
- Drexel University; Philadelphia, Pennsylvania
- Number of pages
- x, 57 pages
- Resource Type
- Thesis
- Language
- English
- Academic Unit
- Digital Media; Drexel University; Antoinette Westphal College of Media Arts and Design
- Other Identifier
- 991022059038804721