Lutz, Jonas
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Gamification of electronic learning in radiology education to improve diagnostic confidence and reduce error rates
OBJECTIVE. The purpose of this study is to validate an electronic learning, or e-learning, concept featuring gamification elements, rapid case reading, and instant feedback. SUBJECTS AND METHODS. An e-learning concept was devised that offered game levels for the purpose of providing training in the detection of pneumothorax in 195 cases, with questions read in rapid succession and instant feedback provided for each case. The user's task was to locate the pneumothorax on chest radiographs and indicate its presence by clicking a mouse. The game level design included an entry test consisting of 15 cases, training levels with increasing difficulty that involved 150 cases, and a final test that including 30 cases (the 15 cases from the entry test plus 15 new cases). A total of 126 candidates were invited via e-mail to participate and were asked to complete a survey before and after playing the game, which is known as RapRad. The level of diagnostic confidence and the error rate before and after playing the game were compared using a Wilcoxon signed rank test. RESULTS. Fifty-nine of 126 participants (47%) responded to the first survey and finished the game. Of these 59 participants, 29 (49%) responded to the second survey after completing the game. Diagnostic confidence in pneumothorax detection improved significantly, from a mean (± SD) score of 4.3 ± 2.1 on the entry test to a final score of 7.3 ± 2.1 (p < 0.01) after playing RapRad, with the score measured on a 10-point scale, with 10 denoting the highest possible score. Of the participants, 93% indicated that they would use the game for learning purposes again, and 87% indicated that they had fun using RapRad (7% had a neutral response and 6% had a negative response). The error rate (i.e., the number of failed attempts to answer a question correctly) significantly decreased from 39% for the entry test to 22% for the final test (p < 0.01). CONCLUSION. Our e-learning concept is capable of improving diagnostic confidence, reducing error rates in training pneumothorax detection, and offering fun in interaction with the platform.
Technological infrastructure supporting the story network principle of the Atlas of the Ageing Society
Atlases have a long tradition of showing and linking information for the exploration of various mostly spatially related topics. Be Atlas of the Ageing Society is an interactive platform illustrating age related data. It enables individuals to explore facts and information related to age and the ageing society. To support content representation as well as a diverse audience, we developed the “story network principle”, which embeds annotated visualizations into a network of information in order to allow storytelling with data. Enabling the exploration of such a multifaceted and highly interconnected data landscape, however, posed some technical challenges. Bis paper describes and discusses a back-end implementation that meets the requirements of the story network principle from a technical perspective. We detail and exemplify the design and implementation of the atlas infrastructure to enable others to benefit from our developments and approaches to the challenges. Be story network principle is potentially applicable to a range of applications such as other atlases or digital portfolios.
Tourney: A game-based learning approach for the recognition of uncommon pathologies in Radiology
Wearables for integrative performance and tactic analyses: opportunities, challenges, and future directions
Micro-electromechanical systems (MEMS) have reduced drastically in size, cost, and power consumption, while improving accuracy. The combination of different sensor technologies is considered a promising step in the monitoring of athletes. Those “wearables” enable the capturing of relevant physiological and tactical information in individual and team sports and thus replacing subjective, time-consuming and qualitative methods with objective, quantitative ones. Prior studies mainly comprised sports categories such as: targeting sports, batting and fielding games as well as net and wall games, focusing on the detection of individual, non-locomotive movements. The increasing capabilities of wearables allow for more complex and integrative analysis expanding research into the last category: invasion sports. Such holistic approaches allow the derivation of metrics, estimation of physical conditions and the analysis of team strategic behavior, accompanied by integrative knowledge gains in technical, tactical, physical, and mental aspects of a sport. However, prior and current researchers find the precise measurement of the actual movement within highly dynamic and non-linear movement difficult. Thus, the present article showcases an overview of the environments in which the wearables are employed. It elaborates their use in individual as well as team-related performance analyses with a special focus on reliability and validity, challenges, and future directions.
Prototype-based research on immersive virtual reality and on self-replicating robots
This chapter presents our recent research in the field of virtual reality (VR) and self-replicating robots. The unifying approach lies in the research philosophy of using consumer market gadgets, mostly developed for the gaming and entertainment business, in order to design and implement research prototypes. With the prototypes, our research aims to better understand real-world problems and derive practice-oriented solutions for them. In the field of VR, these prototypes are dedicated to identifying new business-relevant use cases in order to provide an additional benefit for business and society. A wide range of examples, such as claustrophobia treatment, financial data analysis, gesture control and voice navigation are discussed. In the field of robotics, the idea of self-replicating robots governs particular research questions. Here, the focus is on using model prototypes enriched with artificial intelligence for indoor navigation, computer vision and machine learning. Finally, the prototype-based research approach using gadgets to produce results is discussed.
A new Retrieval Function for Ontology-Based Complex Case Descriptions
This work focuses on case-based reasoning in domains where cases have complex structures with relationships to an arbitrary number of other (potentially complex and structured) entities and where case characterisations (queries) are potentially incomplete. We summarise the requirements for such domains in terms of case representation and retrieval functions. We then analyse properties of existing similarity measures used in CBR { above all symmetry { and argue that some of these properties are not desirable. By exploiting analogies with retrieval functions in the area of information retrieval { where similar functions have been replaced by new ones not exhibiting the aforementioned undesired properties { we derive a new asymmetric ranking function for case retrieval. On a generated test-bed, we show that indeed the new function results in di erent ranking of cases { and use testbed examples to illustrate why this is desirable from a user's perspective.
Intuitive hand gestures for the interaction with information visualizations in virtual reality
The development of virtual reality provides opportunities for immersive information visualizations and therefore it is expected to facilitate the exploration and understanding of data. Hand gesture control enables intuitive interaction and thus it is suggested to amplify the level of immersion further. This paper conducts and experiment to identify a set of intuitive gestures when interacting with an information visualization. Participants are asked to provide hand gestures to given information seeking tasks in an interactive data visualization application in virtual reality that they did not know in advance. The results are analysed and findings with intuitive gestures are communicated and discussed.
Innovation potential for human computer interaction domains in the digital enterprise
This chapter summarizes a historic overview of some iconic examples of human computer interaction devices and focuses on a human computer interaction paradigm which is based more on human language. Human language is by far the most utilized means of conscious communication between humans whereas the mouse and keyboard are the dominant means to store and process information in computers. This chapter elaborates on the main challenges related to human language, as well as on ideas showing how human language, written or spoken, is embedded in different application scenarios. Built on this premise this chapter presents ideas for today’s digitalized enterprises, which seem to disregard the fact that the latest technological advancements enable different ways of interacting with computerized systems, and that current interaction methods are bound to constraints of half a century ago. Given today’s computational power, the engineers of former decades would not have had to invent intermediary interaction devices such as the mouse, if direct manipulation with touch screen or natural language processing had been possible. The possibilities for modern enterprises to overcome the restrictions of interaction devices from the past are considered.
Where Did I(t) put it? A holistic solution to the automatic construction of topic trees for navigation
Managing information based on hierarchical structures is prevailing, be it by storing documents physically in a file structure like MS explorer or virtually in topic trees as in many web applications. The problem is that the structure evolves over time, created individually and hence reflecting individual opinions of how information objects should be grouped. This leads to time consuming searches and error prone retrieval results since relevant documents might be stored elsewhere. Our approach aims at solving the problem by replacing or complementing the manually created navigation structures by automatically created ones. We consider existing approaches for clustering and labelling and focus on yet unrewarding aspects like having information objects in inner nodes (as it is common in folder hierarchies) and cognitively adequate labelling for textual and non-textual resources. Evaluation was done by knowledge experts based on a comparison of retrieval time for finding given documents in manually and automatic generated information structures and showed the advantage of automatically created topic trees.