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Between 1812 and 1841, Fort Ross was a Russian fur trading outpost and multi-cultural colony located in the Northern California coast. Current Fort Ross is a popular California State Historic Park visited every year by over 100,000 visitors from all over the world. In March 2011, California State Parks and the University of California Merced started the Fort Ross Virtual Warehouse project— a digital scholarship initiative aimed to enhance a pilot serious game on Fort Ross developed by California State Parks Staff in the early 2000s— with the goal to explore novel ways for archiving, disseminating, and teaching cultural and historical information. After twenty-four months of development, Fort Ross Virtual Warehouse serious game is ready to be tested in a user study with elementary school students. This paper exposes key features, design solutions and game mechanics of Fort Ross Virtual Warehouse along with preliminary assessments of the game performed as an expert evaluation by the leader of the Special Interest Group on “serious games for humanities and heritage” of the GALA Network of Excellence (www.galanoe.eu).

Serious games offer the potential to not only entertain and educate, but can also operate as a diagnostic tool. While designing a game with the goal of a diagnostic tool, we faced many challenges. In this paper, we share our experiences in dealing with these challenges in the iterations of designing, implementing, and evaluating such a tool.

In less than three months from now, a lot of us will be in Rome for the fourth edition of the Game and Learning Alliance – Gala Conf 2015 (http://www.galaconf.org). The conference has reached a huge number of submissions and we are sure that the level of the presentations will be further higher than in the previous editions. We will be pleased to have representatives from several continents, if not all, and with very different backgrounds, stressing the importance of different disciplines for the development of a good serious game and the possibility of a variety of application domains.

This paper introduces the integration of the face emotion recognition part and the voice emotion recognition part of our FILTWAM framework that uses webcams and microphones. This framework enables real-time multimodal emotion recognition of learners during game-based learning for triggering feedback towards improved learning. The main goal of this study is to validate the integration of webcam and microphone data for a real-time and adequate interpretation of facial and vocal expressions into emotional states where the software modules are calibrated with end users. This integration aims to improve timely and relevant feedback, which is expected to increase learners' awareness of their own behavior. Twelve test persons received the same computer-based tasks in which they were requested to mimic specific facial and vocal expressions. Each test person mimicked 80 emotions, which led to a dataset of 960 emotions. All sessions were recorded on video. An overall accuracy of Kappa value based on the requested emotions, expert opinions, and the recognized emotions is 0.61, of the face emotion recognition software is 0.76, and of the voice emotion recognition software is 0.58. A multimodal fusion between the software modules can increase the accuracy to 78i¾ź%. In contrast with existing software our software modules allow real-time, continuously and unobtrusively monitoring of learners' face expressions and voice intonations and convert these into emotional states. This inclusion of learner's emotional states paves the way for more effective, efficient and enjoyable game-based learning.