Lessons learned applying learning analytics to assess serious games

Alonso‐Fernández, Cristina; Cano, Ana R.; Calvo-Morata, Antonio; Freire, Manuel; Martínez‐Ortiz, Iván; Fernández‐Manjón, Baltasar

doi:10.1016/j.chb.2019.05.036

Cited by 58 publications

(39 citation statements)

References 26 publications

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“…A number of studies have examined knowledge acquisition with game‐based learning environments using a range of data channels such as gameplay behavior traces (eg, Alonso‐Fernández et al ., 2019; Alonso‐Fernández, Martínez‐Ortiz, Caballero, Freire, & Fernández‐Manjón, 2020; Taub et al ., 2017), facial expressions of emotions (eg, Lane & D’Mello, 2019; Taub, Sawyer, Smith, et al ., 2020), performance measures (eg, pre/posttest scores; Dever & Azevedo, 2019), self‐report measures (eg, Cloude, Taub, Lester, & Azevedo, 2019) and eye gaze (eg, Dever, Wiedbusch, & Azevedo, 2019; Gomes, Yassine, Worsley, & Blikstein, 2013; Lee, Donkers, Jarodzka, & van Merriënboer, 2019; Tsai, Huang, Hou, Hsu, & Chiou, 2016). A noteworthy study used gameplay behavior traces to model students’ self‐reported interest during game‐based learning (Sawyer, Rowe, Azevedo, & Lester, 2018).…”

Section: Introductionmentioning

confidence: 99%

Multimodal learning analytics for game‐based learning

Emerson¹,

Cloude²,

Azevedo³

et al. 2020

Brit J Educational Tech

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A distinctive feature of game‐based learning environments is their capacity to create learning experiences that are both effective and engaging. Recent advances in sensor‐based technologies such as facial expression analysis and gaze tracking have introduced the opportunity to leverage multimodal data streams for learning analytics. Learning analytics informed by multimodal data captured during students’ interactions with game‐based learning environments hold significant promise for developing a deeper understanding of game‐based learning, designing game‐based learning environments to detect maladaptive behaviors and informing adaptive scaffolding to support individualized learning. This paper introduces a multimodal learning analytics approach that incorporates student gameplay, eye tracking and facial expression data to predict student posttest performance and interest after interacting with a game‐based learning environment, Crystal Island. We investigated the degree to which separate and combined modalities (ie, gameplay, facial expressions of emotions and eye gaze) captured from students (n = 65) were predictive of student posttest performance and interest after interacting with Crystal Island. Results indicate that when predicting student posttest performance and interest, models utilizing multimodal data either perform equally well or outperform models utilizing unimodal data. We discuss the synergistic effects of combining modalities for predicting both student interest and posttest performance. The findings suggest that multimodal learning analytics can accurately predict students’ posttest performance and interest during game‐based learning and hold significant potential for guiding real‐time adaptive scaffolding.

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Section: Introductionmentioning

confidence: 99%

Multimodal learning analytics for game‐based learning

Emerson¹,

Cloude²,

Azevedo³

et al. 2020

Brit J Educational Tech

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“…Most studies on gamification have shown positive emotions, such as pleasure, fun, and enjoyment, that establish a gameful experience ( Francisco-Aparicio et al, 2013 ). Studies have reported that players of the game enjoy games only when the settings of the game are easy ( Alonso-Fernández et al, 2019 ; Dardis, Schmierbach, Sherrick, & Luckman, 2019 ). According to Klimmt et al (2019) , if the game controls are unreliable, then it impacts negatively on the player’s enjoyment.…”

Section: Hypotheses Formulationmentioning

confidence: 99%

The gamification of in-game advertising: Examining the role of psychological ownership and advertisement intrusiveness

Malhotra

2021

International Journal of Information Management

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Highlights Psychological factors impact gameful experience and the attitudes of online gamers. Gameful experience is positively linked with online gamers’ attitudes. Psychological ownership (PO) and perceived in-game advertisement effectiveness (PAE) positively mediate this path. Online gamers comprehend the effectiveness of in-game advertising. The impact of advertisement intrusiveness can be countered with high PAE and PO.

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“…Alonso‐Fernández et al (2019) introduced three case studies to show various gameplay data collected in game‐based learning context and different ways of analysing these data to examine knowledge acquisition and improve game design. They further suggested that the analyses of gameplay data should be generalized to enhance the use of educational games in different settings.…”

Section: Literature Reviewmentioning

confidence: 99%

Learning immunology in a game: Learning outcomes, the use of player characters, immersion experiences and visual attention distributions

Teng

Chou

Cheng

2020

Computer Assisted Learning

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This study contributed to the current body of literature on game‐based learning by investigating the way playing an educational game, Humunology, affected learning about the immune system and examining further the association between game immersion and visual attention distribution. A total of 79 undergraduate and graduate students participated, and data were collected both in situ and ex situ. The results showed that the students learned through playing Humunology, and the analyses of the use of player characters indicated that the game design facilitated gameplay behaviours that are consistent with the science content. The use of the eye‐tracking method also revealed that students who were more immersed in playing Humunology paid more attention to areas related to player characters. The interpretations and limitations are discussed further.

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Lessons learned applying learning analytics to assess serious games

Cited by 58 publications

References 26 publications

Multimodal learning analytics for game‐based learning

Multimodal learning analytics for game‐based learning

The gamification of in-game advertising: Examining the role of psychological ownership and advertisement intrusiveness

Learning immunology in a game: Learning outcomes, the use of player characters, immersion experiences and visual attention distributions

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