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.

Assessment is a crucial aspect of any teaching and learning process. Educational games offer promising advantages for assessment; personalised feedback to students and automated assessment process. However, while many teachers agree that educational games increase motivation, learning and retention, few of them are ready to fully trust them as an assessment tool. We believe there are two main reasons for this lack of trust: educators are not given sufficient information about the gameplays, and many educational games are distributed as black-boxes, unmodifiable by teachers. This paper presents an assessment engine designed to separate a game and its assessment. It allows teachers to modify a game's assessment after distribution and visualise gameplay data via a learning analytics dashboard. The engine was evaluated quantitatively by 31 educators. Findings were overall very positive: both the assessment editor and the learning analytics dashboard were rated useful and easy to use. The evaluation also indicates that, having access to EngAGe, educators would be more likely to trust a game's assessment. This paper concludes that EngAGe can be used by educators effectively to modify educational games' assessment and visualise gameplay data, and that it contributes to increasing their trust in educational games as an assessment tool.

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A Clinical Decision Support System (CDSS) is a technology platform that uses medical knowledge with clinical data to provide customised advice for an individual patient's care. CDSSs use rules to encapsulate expert knowledge and rules engines to infer logic by evaluating rules according to a patient's specific information and related medical facts. However, CDSSs are by nature complex with a plethora of different technologies, standards and methods used to implement them and it can be difficult for practitioners to determine an appropriate solution for a specific scenario. This study's main goal is to provide a better understanding of different technical aspects of a CDSS, identify gaps in CDSS development and ultimately provide some guidelines to assist their translation into practice. We focus on issues related to knowledge representation including use of clinical ontologies, interoperability with EHRs, technology standards, CDSS architecture and mobile/cloud access.This study performs a systematic literature review of rule-based CDSSs that discuss the underlying technologies used and have evaluated clinical outcomes. From a search that yielded an initial set of 1731 papers, only 15 included an evaluation of clinical outcomes. This study has found that a large majority of papers did not include any form of evaluation and, for many that did include an evaluation, the methodology was not sufficiently rigorous to provide statistically significant results. From the 15 papers shortlisted, there were no RCT or quasi-experimental studies, only 6 used ontologies to represent domain knowledge, only 2 integrated with an EHR system, only 5 supported mobile use and only 3 used recognised healthcare technology standards (and all these were HL7 standards). Based on these findings, the paper provides some recommendations for future CDSS development.

Serious Games (SG) are developing a reputation with some educationalists as a useful supplementary approach for teaching and learning. Two important issues for SG application developers and educationalists are how the learning is assessed and how assessment is integrated into a SG application. This chapter presents the results of a systematic literature review on assessment integration in SG and highlights the state of the literature in this area by outlining important papers to act as a guide for educationalists tackling this important issue. This chapter defines assessment and discusses formative and summative assessment and embedded and external assessment. A discussion of traditional assessment approaches and assessment approaches in SG are presented along with a discussion of existing frameworks for the integration of assessment into a SG application. The chapter presents a number of examples of assessment in serious games.