Learning Analytics in Serious Gaming: Uncovering the Hidden Treasury of Game Log Files

This paper presents an exploratory analysis of existing log files of the VIBOA environmental policy games at Utrecht University. For reasons of statistical power we’ve combined student cohorts 2008, 2009, 2010, and 2011, which led to a sample size of 118 students. The VIBOA games are inquiry-based games, which offer a lot of freedom of movement. Our premise is that this freedom of movement is accompanied by behavioural variability across individuals, which may influence the efficiency of learning. Descriptive statistics of our sample revealed such variability of diverse game parameters. We have identified “switching behaviour”, defined as the number of game objects (videos, resources, locations) accessed per unit time, as a relevant behavioural pattern. Multiple regression analysis showed that switching rates of videos and locations explain 54 % of the variance of learning efficiency (defined as final score per unit time). Both the model and the model coefficients were significant beyond the 0.001 level. The same switching variables also account for 45% of the variance of total time spent T. Predictive models of final score weren’t found. We conclude the paper by critically evaluating our findings, making explicit the limitations of our study and making suggestions for future research that links learning analytics and serious gaming

The Journey: A Service-Based Adaptive Serious Game on Probability

Serious Games (SGs) have a lot of potential in education, possibly making learning more engaging and satisfying. Adaptive Games strive to keep the challenges presented by the game balanced with the player\u2019s abilities, as to keep the player in the "flow" state. We have used a Service-Oriented Architecture (SOA) approach to develop a simple adaptive SG for teaching basic elements of probability to high school and entry-level university students, called The Journey. The game performs continuously the updating of a user model with the competences of the student and presents the new challenges according to the student\u2019s current level. This paper presents details of the educational aspects of the game, as well as of its implementation. It also presents a preliminary validation study and discusses future work

Comparing two CbKST approaches for adapting learning paths in serious games

International audienceCompetence-based Knowledge Space Theory (CbKST) is considered a well-fitting basis for adapting Serious Games (SGs). CbKST relies on the domain model associated to a given SG to infer the so-called competence structure. However, building such a model can be time-consuming and a tough task for experts. We propose another approach to overcome this issue by considering the Q-Matrix that contains the mapping between the SG activities and the addressed competences. We compare the two approaches, one based on the domain model and the other on the Q-Matrix, in three SGs. We apply both approaches to two SGs, while in a third one, we apply only the Q-Matrix approach since no domain model is available. The main findings when comparing both approaches refer to the issues derived from the generated competence structures and the definition of competences at a suitable granularity level. This exploratory work can provide meaningful insights when applying CbKST for adapting SGs

To tailor or not to tailor gamification? An analysis of the impact of tailored game elements on learners’ behaviours and motivation

International audienceGamification, defined as the use of game elements in non game situations, is a widely used method to foster learner engagement and motivation. It is generally accepted that in order to be effective, gamification should be tailored to users. Currently, most systems adapt by assigning different game elements based on a single learner profile (e.g. dominant player type, personality or gender). However, there is no study yet that analyse the effect of combining several profiles. In this paper, we study the usage data from 258 students who used a gamified learning environment as a part of their mathematics class. By simulating different adaptation techniques, we show that the learner model chosen to tailor gamification has significant effects on learners' motivation and engaged behaviours depending on the profile(s) used in this context. We also show that tailoring to initial motivation to learn mathematics can improve intrinsic motivation. Finally, we show that tailoring to both player type and motivation profiles can improve intrinsic motivation, and decrease amotivation, compared to a single adaptation only based on learner motivation. We discuss the implications of our findings regarding the choice of a learner model for tailoring gamification in educational environments

Teaming Up With Artificial Intelligence: The Human in the Loop of Serious Game Pathfinding Algorithms

Gentile M., Allegra M., & Söbke H. (eds.). (2019). Games and learning alliance. GALA 2018 (Lecture Notes in Computer Science, vol 11385). Springer, Cham, pp. 354-36

Decoupling assessment and serious games to support guided exploratory learning in smart education

This research proposes an enhanced approach of decoupling assessment and serious games to support fire evacuation training in smart education. The proposed assessment approach employs an evidence-based dynamic assessment and feedback to guide players through school’s building evacuation. Experimentation results show the applicability of the proposed assessment approach in enhancing fire evacuation training using serious games. Moreover, students were engaged to the proposed learning scenarios and their overall fire evacuation assessment were enhanced using the guided exploratory game-based training