Exploring Play-Learners’ Analytics in a Serious Game for Literacy Improvement

Smith, Shamus P.; Hickmott, Daniel; Southgate, Erica; Bille, Ross; Stephens, Liz

doi:10.1007/978-3-319-45841-0_2

Cited by 8 publications

(5 citation statements)

References 13 publications

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“…Baker, Clarke-Midura, and Ocumpaugh 2016), as the achievement system built into games may not be the most informative indicator of learning (Heeter et al 2013). Some papers point out that their best predictors for measuring learning are based on the analysis of the player's exploration strategies (Käser, Hallinen, & Schwartz, 2017;Owen, Anton, and Baker 2016;Horn et al 2016;Smith, Hickmott, Southgate, Bille, & Stephens, 2016;Kang, Liu, and Qu 2017), or on the characteristics of player failures (Halverson and Owen 2014). One study explored the relation between learning and students' facial behavior (Z. Xu and Woodruff 2017).…”

Section: Results On Assessment and Student Profilingmentioning

confidence: 99%

Applications of data science to game learning analytics data: A systematic literature review

Alonso‐Fernández

Calvo-Morata

Freire

et al. 2019

Computers & Education

101

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Data science techniques, nowadays widespread across all fields, can also be applied to the wealth of information derived from student interactions with serious games. Use of data science techniques can greatly improve the evaluation of games, and allow both teachers and institutions to make evidence-based decisions. This can increase both teacher and institutional confidence regarding the use of serious games in formal education, greatly raising their attractiveness. This paper presents a systematic literature review on how authors have applied data science techniques on game analytics data and learning analytics data from serious games to determine: (1) the purposes for which data science has been applied to game learning analytics data, (2) which algorithms or analysis techniques are commonly used, (3) which stakeholders have been chosen to benefit from this information and (4) which results and conclusions have been drawn from these applications. Based on the categories established after the mapping and the findings of the review, we discuss the limitations of the studies analyzed and propose recommendations for future research in this field.

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Section: Results On Assessment and Student Profilingmentioning

confidence: 99%

Applications of data science to game learning analytics data: A systematic literature review

Alonso‐Fernández

Calvo-Morata

Freire

et al. 2019

Computers & Education

101

View full text Add to dashboard Cite

show abstract

“…One important source of data that is currently all too often out of reach of player-focused researchers are logged play data. As demonstrated by Smith, Hickmott, Southgate, Bille, and Stephens (2016), logging play behaviors can provide an additional layer of objective information, showing how long players spend on parts of the game, or the order in which they progress through it. Though these data might typically be seen as control variables in quantitative studies, they can also serve as outcome measures when investigating player persistence.…”

Section: Methodological Considerations For Comprehensive Impact Validationmentioning

confidence: 99%

Winning Over the Players: Investigating the Motivations to Play and Acceptance of Serious Games

Jacobs

2021

MaC

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Serious games are designed to educate, train, or persuade their players on specific topics and issues. While a lot of studies have sought to prove the effects of these games, the overall image and legitimization of serious games has not benefited fully from these efforts. Indicating that the issue stems from the difference between the captive audience exposed to games in effects studies and the contexts in which people come to play serious games in everyday life, the current article sketches out the research that needs to be performed before this gap can be filled. Three theoretical perspectives are offered, in turn looking at serious games as forms of (promotional) communication, personal media experiences, and technological innovations. This analysis results in insights relating to (among others), how the identity of serious games might hinder their diffusion, how expected gratifications could fail to match the intentions of these games, and what could cause someone to ‘adopt’ a serious game. Based on the insights gained by applying these lenses, potential factors are listed and linked to methodologies that could prove or disprove their importance. These methodologies involve quantitative and qualitative investigations to create a deeper picture of how potential players approach serious games. The article concludes with open questions to investigators and industry professionals generated from this process.

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“…Another study (Smith, Hickmott, Southgate, Bille, & Stephens, 2016) used log data to visualize the decisions of players during gameplay. Log data were analysed to identify areas where university students spend the most time in the game environment, gameplay sequences used as well as their use of training videos.…”

Section: Performance-based Assessment With Game Log Datamentioning

confidence: 99%

Exploring Log Data for Behaviour and Solution Pattern Analyses in a Serious Game

Udeozor¹,

Russo²,

Glassey³

2021

Gamification and Social Networks in Education

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Digital games are interactive, which makes them highly engaging for players. The adoption and use of digital games in higher education are on the rise with many researchers and educators developing and deploying these in classrooms. As a relatively new pedagogical tool, some aspects of the use of games for learning such as measurement and assessment of learning are still under research. Although assessment of performance and learning in digital games are commonly done with pre and post-game tests, interest in growing in the use of gameplay log data as an alternative and valid means of measuring the performance of students in digital games. A few studies have utilized log data to measure the performance of students in general knowledge and skills but limited studies exist where game log data were used to measure domain-specific competencies. This empirical study describes the use of game log data for measuring the behaviours and performance of engineering students in the Cosmiclean game, a serious game designed to teach the principles of separation and recycling operations. Using the data from first year engineering students from two European institutions, sequential behaviour pattern analysis and performance assessment of students solutions in the game are presented. The findings of this study highlight the behaviours and gameplay strategies of students in the game environment, and these would be particularly useful to game designers, educators and researchers in the field of game-based learning.

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Exploring Play-Learners’ Analytics in a Serious Game for Literacy Improvement

Cited by 8 publications

References 13 publications

Applications of data science to game learning analytics data: A systematic literature review

Applications of data science to game learning analytics data: A systematic literature review

Winning Over the Players: Investigating the Motivations to Play and Acceptance of Serious Games

Exploring Log Data for Behaviour and Solution Pattern Analyses in a Serious Game

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