Integrating Learning Analytics into a Game Authoring Tool

Pérez-Colado, Iván José; Pérez-Colado, Víctor M.; Martínez‐Ortiz, Iván; Fernández‐Manjón, Baltasar

doi:10.1007/978-3-319-66733-1_6

Cited by 8 publications

(5 citation statements)

References 8 publications

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“…However, considerable research is still required. Implementing game-learning analytics in the classroom for instructional decision making will also require additional support and technological resources, such as a dashboard to illustrate data visualizations for sense making that are currently unavailable to most teachers (Perez-Colado et al, 2017;Cloude, Dever, Wiedbusch, & Azevedo, 2020;Wiedbusch et al, 2021;Roll & Winne, 2015).…”

Section: Discussionmentioning

confidence: 99%

“…games for learning may be defined as games with specific learning goals" (p. 3); thus, the influence of goals on problem-solving actions and learning information is evident. Significant gaps exist in the literature-this model has not been used in game-based learning or learning analytics research (Kovanović et al, 2018;Scheffel, Drachsler, Stoyanov, & Specht, 2014;Carpenter et al, 2020;Geden et al, 2020;Perez-Colado, Perez-Colado, Freire-Moran, Martinez-Ortiz, & Fernandez-Manjon, 2017;. We address this gap by examining the role of the quantity and quality of reflection as they relate to learning goals structured within Crystal Island to advance our understanding of reflection during game-based learning.…”

Section: Model Of Reflectionmentioning

confidence: 99%

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Game-Based Learning Analytics for Supporting Adolescents’ Reflection

Cloude

Carpenter

Dever

et al. 2021

JLA

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Reflection is critical for adolescents’ problem solving and learning in game-based learning environments (GBLEs). Yet challenges exist in the literature because most studies lack a theoretical perspective and clear operational definition to inform how and when reflection should be scaffolded during game-based learning. In this paper, we address these issues by studying the quantity and quality of 120 adolescents’ written reflections and their relation to their learning and problem solving with Crystal Island, a GBLE. Specifically, we (1) define reflection and how it relates to skill and knowledge acquisition; (2) review studies examining reflection and its relation to problem solving and learning with emerging technologies; and (3) provide direction for building reflection prompts into GBLEs that are aligned with the learning goals built into the learning session (e.g., learn about microbiology versus successfully solve a problem) to maximize adolescents’ reflection, learning, and performance. Overall, our findings emphasize how important it is to examine not only the quantity of reflection but also the depth of written reflection as it relates to specific learning goals. We discuss the implications of using game-learning analytics to guide instructional decision making in the classroom.

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Section: Discussionmentioning

confidence: 99%

Section: Model Of Reflectionmentioning

confidence: 99%

Game-Based Learning Analytics for Supporting Adolescents’ Reflection

Cloude

Carpenter

Dever

et al. 2021

JLA

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“…Game Learning Analytics (GLA) is the combination of both Game Analytics (GA) and Learning Analytics (LA), allowing both game designers and educators to design serious games in a collaborative way (Perez-Colado et al, 2017). GLA analyses player/learner interactions to evaluate player behaviour, categorise players and define player models (Reardon et al, 2022), provides insight on players' prior domain knowledge (Liu et al, 2013) and improves the use of the games in the education aspects (Freire et al, 2016).…”

Section: Game Learning Analytics Frameworkmentioning

confidence: 99%

Personalised Learning through Context-Based Adaptation in the Serious Games with Gating Mechanism

et al. 2023

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When the traditional "one size fits all" approach is used in designing educational games, the game context is usually arranged in a fixed sequence. However, the designated content may not effectively support the diversity of players. The player's ability and characteristics should be considered and supported with an appropriate learning context embedded in the game to facilitate personalised experiences. Adapting game scenarios to a player's characteristics can boost motivation and ultimately improve learning outcomes. This research applies a context-aware design approach and the Learner-Centered Design approach to establish a personalised adaptation framework for designing educational serious games and enhancing personalised knowledge delivery. The proposed framework decouples the game logic implementation and adaptation mechanism. It dynamically adapts the designed game objects and activities to personal learning objectives, learning levels and learning progress to achieve a non-linear learning sequence. Through synchronous real-time xAPI message exchange mechanisms, system components and learning content adaptation are enabled. The adaptation aims to fit personal learning objectives and provide a non-linear learning sequence in a game environment. The framework provides students with personalised learning experiences. A game named GhostCoder is implemented and used to evaluate the framework. Based on the externalised adaptive mechanism, the game content is adapted to the player's performance by adjusting the difficulty of the learning content within the game. Testing of the game in the lab environment has been performed. At the next stage, an evaluation will be conducted with the target groups of students.

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“…For instance, entering an enemy limit could start a battle with the enemy. In cases where crossing the limits changes the game-state, xAPI SGs extensions are used to indicate the consequences of this crossing, such as changes in variables [16].…”

Section: ) Entering and Exitingmentioning

confidence: 99%

Learning analytics for location-based serious games

Pérez-Colado

Rotaru

Martínez‐Ortiz

et al. 2018

2018 IEEE Global Engineering Education Conference (EDUCON)

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Pervasive gaming has experimented a huge commercial growth with location-based game successes such as Pokémon GO or Ingress. The serious game industry has an opportunity to take advantage of location-based mechanics to better connect games with the real world, creating more authentic immersive learning environments. Games such as historical tours, story-based exploration, laboratories, or flora explorations can greatly benefit from location-based mechanics. Location-based games usually include an augmented map to provide game context, which combines both traditional game-dependent elements such as avatars, and location-based elements such as areas or points of interest. For players, interacting with location-based elements may involve entering or exiting specific areas; or reaching a certain location and looking in a specific direction. To include standardsbased learning analytics for location-based serious games (SGs), we have added support for player movement and location-based interactions to the pre-existing xAPI serious game profile. We have validated this approach through a case-study example that guided players through different sports-related facilities within a large outdoor area. This work have been carried out and it is available as part of the analytics infrastructure used in EU H2020 RAGE and BEACONING serious game projects.

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Integrating Learning Analytics into a Game Authoring Tool

Cited by 8 publications

References 8 publications

Game-Based Learning Analytics for Supporting Adolescents’ Reflection

Game-Based Learning Analytics for Supporting Adolescents’ Reflection

Personalised Learning through Context-Based Adaptation in the Serious Games with Gating Mechanism

Learning analytics for location-based serious games

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