Realtime Knowledge Space Skill Assessment for Personalized Digital Educational Games

Conlan, Owen; Hampson, Cormac; Peirce, Neil; Kickmeier-Rust, Michael D.

doi:10.1109/icalt.2009.150

Cited by 16 publications

(8 citation statements)

References 8 publications

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“…In addition, experts or automated systems define an appropriate description for each set of actions. These descriptions are then used to model the learner (Lessard 2012;Conati and Zhao 2004;Manske and Conati 2005;Stathacopoulou et al 2004;Virvou et al 2003;Katsionis and Virvou 2004;Conlan et al 2009). …”

Section: Translating Learner's Actionsmentioning

confidence: 99%

“…The learner model's goal in Conlan et al (2009) was to generate a real-time evaluation of a learner's skills. The skill assessment engine component was responsible for translating each learner's actions within the game into a list of probabilities that showed the likelihood of each relevant skill having been acquired by the learner.…”

Section: Translating Learner's Actionsmentioning

confidence: 99%

“…In this game, the learner has to solve several physics-oriented puzzles. A virtual character (representing the ghost of Galileo) guides, advises and encourages the learner during the game (Conlan et al 2009). The ELEKTRA project is accessible online (ELEKTRA 2015).…”

Section: Action Modelingmentioning

confidence: 99%

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Learner Modeling Using Educational Games: A Review of the Literature

Khenissi

Essalmi

Jemni

et al. 2015

Smart Learn. Environ.

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Recently, there has been growing interest in the use of games in education. Educational games have been found to stimulate learners by increasing their motivation and engagement. In addition, educational games could be used for creating the learner model. In fact, these games provide ample opportunities for learner's interactions with the computer which can be exploited for creating a reliable learner model. This paper a presents a survey of the field of learner modeling using educational games, describing the main methods and proposing taxonomy to better organize them. The paper also enumerates several educational games that are suitable for experimentation. This synthesis is expected to not only help the researchers and developers working in this field but also pedagogues and teachers who plan to integrate these approaches in educational context.

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Section: Translating Learner's Actionsmentioning

confidence: 99%

Section: Translating Learner's Actionsmentioning

confidence: 99%

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Learner Modeling Using Educational Games: A Review of the Literature

Khenissi

Essalmi

Jemni

et al. 2015

Smart Learn. Environ.

View full text Add to dashboard Cite

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“…Using educational games to assist the learning process offers a wide range of possibilities that can be difficult to attain in a traditional classroom; for example, they give players the possibility of going at their own pace and learning through trial and error in a controlled and safe environment. They also offer many options for assessment; using real-time assessment data, a game can be adapted to a learner's needs (Carvalho et al, 2015;Conlan, Hampson, Peirce, & Kickmeier-Rust, 2009;Göbel, Mehm, Radke, & Steinmetz, 2009). Educational games also offer the possibility of formative assessment and feedback according to a player's actions (Jarvis & de Freitas, 2009).…”

Section: Introductionmentioning

confidence: 99%

Specification and evaluation of an assessment engine for educational games: Integrating learning analytics and providing an assessment authoring tool

Chaudy

Connolly

2019

Entertainment Computing

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Educational games are highly engaging, motivating and they offer many advantages as a supplementary tool for education. However, the development of educational games is very complex, essentially because of its multidisciplinary aspect. Fully integrating assessment is challenging and the games created are too often distributed as blackboxes; unmodifiable by the teachers and not providing much insight about the gameplays. We propose an assessment engine, EngAGe, to overcome these issues. EngAGe is used by both developers and educators. It is designed to separate game and assessment. Developers use it to easily integrate assessment into educational games and teachers can then modify the assessment and visualise learning analytics via an online interface. This paper focuses on EngAGe's benefits for games developers. It presents a quantitative evaluation carried out with 36 developers (7 experienced and 29 students). Findings were very positive: every feature of the engine was rated useful and EngAGe received a usability score of 64 using the System Usability Scale. A Mann-Whitney U test showed a significant difference in usability (Z=-3.34, p<0.002) between novice developers (mean=56) and experienced developers (mean=71) but none in terms of usefulness. This paper concludes that developers can use EngAGe effectively to integrate assessment and learning analytics in educational games.

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“…We use it to link game actions to the domain competencies and to represent the equivalence and sub-optimality relations between game actions. Ontologies have been used for the diagnosis of errors in learning systems [14] as well as for knowledge diagnosis in serious games [15].…”

Section: Combining An Expert Petri Net and A Game Action And Domain Omentioning

confidence: 99%