QLens: Visual analytics of multi-step problem-solving behaviors for improving question design

With the rapid development of online education in recent years, there has been an increasing number of learning platforms that provide students with multi-step questions to cultivate their problem-solving skills. To guarantee the high quality of such learning materials, question designers need to inspect how students' problem-solving processes unfold step by step to infer whether students' problem-solving logic matches their design intent. They also need to compare the behaviors of different groups (e.g., students from different grades) to distribute questions to students with the right level of knowledge. The availability of fine-grained interaction data, such as mouse movement trajectories from the online platforms, provides the opportunity to analyze problem-solving behaviors. However, it is still challenging to interpret, summarize, and compare the high dimensional problem-solving sequence data. In this paper, we present a visual analytics system, QLens, to help question designers inspect detailed problem-solving trajectories, compare different student groups, distill insights for design improvements. In particular, QLens models problem-solving behavior as a hybrid state transition graph and visualizes it through a novel glyph-embedded Sankey diagram, which reflects students' problem-solving logic, engagement, and encountered difficulties. We conduct three case studies and three expert interviews to demonstrate the usefulness of QLens on real-world datasets that consist of thousands of problem-solving traces

Automated iterative game design

Computational systems to model aspects of iterative game design were proposed, encompassing: game generation, sampling behaviors in a game, analyzing game behaviors for patterns, and iteratively altering a game design. Explicit models of the actions in games as planning operators allowed an intelligent system to reason about how actions and action sequences affect gameplay and to create new mechanics. Metrics to analyze differences in player strategies were presented and were able to identify flaws in game designs. An intelligent system learned design knowledge about gameplay and was able to reduce the number of design iterations needed during playtesting a game to achieve a design goal. Implications for how intelligent systems augment and automate human game design practices are discussed.Ph.D

Expanding evidence approaches for learning in a digital world

Executive Summary: Relatively low-cost digital technology is ubiquitous in daily life and work. The Web is a vast source of information, communication, and connection opportunities available to anyone with Internet access. Most professionals and many students have a mobile device in their pocket with more computing power than early supercomputers. These technological advances hold great potential for improving educational outcomes, but by themselves hardware and networks will not improve learning. Decades of research show that high-quality learning resources and sound implementations are needed as well.The learning sciences have found that today’s technologies offer powerful capabilities for creating high-quality learning resources, such as capabilities for visualization, simulation, games, interactivity, intelligent tutoring, collaboration, assessment, and feedback. Further, digital learning resources enable rapid cycles of iterative improvement, and improvements to resources can be instantly distributed over the Internet. In addition, digital technologies are attracting exciting new talent, both from other industries and from the teacher workforce itself, into the production of digital learning resources. Yet even with so many reasons to expect dramatic progress, something more—better use of evidence— is needed to support the creation, implementation, and continuous enhancement of high-quality learning resources in ways that improve student outcomes

Le suivi de l'apprenant dans le cadre du serious gaming

"Serious gaming" is a recent approach, using the techniques implemented in video games, to conduct "serious" activities such as communication, awareness and learning. Serious games have now become an essential element of online training. This thesis takes place in the context of serious games for training. Indeed, whatever the preferred meaning, many research questions arise. In particular, how can we assess the knowledge acquired by the player / learner through the game? We have focused on case study type games used especially in management or medicine. We propose a method based on Evidence Centered Design to plan the monitoring of the learner for diagnostic purposes to the teacher and the learner. Actions in case studies are very close to business actions and resort to specific rules. We have chosen to represent them using Petri nets. To bring semantics to the Petri net analysis, we have added a domain and game action ontology. The ontology provides a significant complementarity to Petri net that has a purely procedural dimension. We have combined Petri nets and ontologies to produce performance indicators for this particular category of serious games. The study of errors led us to propose a particular taxonomy for serious games based on the work done in the field of security.Le " serious gaming " est une approche récente pour mener des activités " sérieuses " telles que communiquer, sensibiliser ou apprendre, en utilisant les techniques mises en œuvre dans les jeux vidéo. Les jeux sérieux sont devenus aujourd'hui un élément incontournable de la formation en ligne. C'est dans ce cadre du serious gaming pour la formation que se situe ce sujet de thèse. En effet, quelle que soit l'acception privilégiée, de nombreuses questions de recherche se posent. En particulier, comment peut-on évaluer les connaissances acquises par le joueur/apprenant à travers le jeu ? Nous sommes concentrés sur les jeux de type étude de cas utilisés notamment en gestion ou en médecine et proposons une méthode basée sur l'Evidence Centered Design pour concevoir le suivi de l'apprenant à des fins de diagnostic à destination de l'enseignant et de l'apprenant. Les actions liées aux études de cas sont très proches des actions métiers et recourent à des règles bien précises. Nous avons fait le choix de les représenter à l'aide de réseaux de Petri. Pour apporter de la sémantique à l'analyse par réseau de Petri, nous l'avons adossé à une ontologie du domaine et des actions de jeu. L'ontologie apporte une complémentarité non négligeable au réseau de Petri qui a une dimension purement procédurale. Nous combinons des réseaux de Petri et les ontologies afin de produire des indicateurs de performance pour cette catégorie particulière de jeux sérieux. L'étude des erreurs nous a conduits à proposer une taxinomie particulière pour les jeux sérieux en nous inspirant notamment des travaux réalisés dans le domaine de la sécurité