Playing an Educational Game Featuring Procedural Content Generation: Which Attributes Impact Players’ Curiosity?

Abstract

Understanding which and how attributes impact player experience can contribute to designing more tailored tools, providing concerns on how to improve these. However, there is a gap in the understanding of what impacts learners’ experience when interacting with Educational Games (EG) featuring Procedural Content generation (PCG) as these have been scantly used together. This article presents an empirical study on which attributes impact both math’s and game’s curiosity of players when interacting with an EG that uses PCG. The results show the attributes that led to higher or lower curiosity, as well aswhich of them are associated with it. Hence, advancing the understanding of what drives players’ curiosity, contributing to the design of EG that feature PCG.

Thinking Inside the Box: How to Tailor Gamified Educational Systems Based on Learning Activities Types

“…As users' demographic data might impact their opinions [Rodrigues and Brancher 2019a], many personalized GES are developed thinking in collecting users' demographic profile and giving them a reasonable group of game elements [Santos et al 2018a;Lavoue et al 2018;Monterrat et al 2017]. Although, recent studies on personalization demonstrate that these tailored game elements might not impact positively on aspects related to the students' learning process [Santos et al 2018a;Monterrat et al 2017].…”

Automatic Game Experience Identification in Educational Games

“…In order to obtain the student's data logs with their game experience, we used the the game SpaceMath Brancher 2018, Rodrigues andBrancher 2019]. It was chosen by convenience because access to in game data log were granted by the game developer.…”

Procedural Level Generation to Improve a Digital Math Game's Development: Does it Impact Player Experience?

“…We compared groups based on six PX metrics, considering their opinions (four) and ingame behavior (two). Players reported their opinions through an adapted version of the questionnaire for rapid assessment by [Moser et al 2012] after playing 20 levels, which captured PX in terms of curiosity (composed of seven statements, referred to as C1, C2, up to C7) [Rodrigues and Brancher 2019], fun, returnance, and experience description. The threshold was 20 because this is the number of human-created levels available, hence, guaranteeing players of both versions completed the questionnaire after playing the same number of levels.…”

“…To enable this research, we developed SpaceMath 1 [Rodrigues and Brancher 2019, Oliveira et al 2019, Rodrigues and Brancher 2018, a DMG that fosters the practice of basic mathematical operations (summation, subtraction, multiplication, and division) and uses PCG to create both its levels and math puzzles. In this game, players control an astronaut towards exploring multiples parallel universes (levels) and solving math puzzles, as shown in Figure 2.…”