Background Cognitive deficits are present in several neuropsychiatric disorders, including Alzheimer disease, schizophrenia, and depression. Assessments used to measure cognition in these disorders are time-consuming, burdensome, and have low ecological validity. To address these limitations, we developed a novel virtual reality shopping task—VStore. Objective This study aims to establish the construct validity of VStore in relation to the established computerized cognitive battery, Cogstate, and explore its sensitivity to age-related cognitive decline. Methods A total of 142 healthy volunteers aged 20-79 years participated in the study. The main VStore outcomes included verbal recall of 12 grocery items, time to collect items, time to select items on a self-checkout machine, time to make the payment, time to order coffee, and total completion time. Construct validity was examined through a series of backward elimination regression models to establish which Cogstate tasks, measuring attention, processing speed, verbal and visual learning, working memory, executive function, and paired associate learning, in addition to age and technological familiarity, best predicted VStore performance. In addition, 2 ridge regression and 2 logistic regression models supplemented with receiver operating characteristic curves were built, with VStore outcomes in the first model and Cogstate outcomes in the second model entered as predictors of age and age cohorts, respectively. Results Overall VStore performance, as indexed by the total time spent completing the task, was best explained by Cogstate tasks measuring attention, working memory, paired associate learning, and age and technological familiarity, accounting for 47% of the variance. In addition, with λ=5.16, the ridge regression model selected 5 parameters for VStore when predicting age (mean squared error 185.80, SE 19.34), and with λ=9.49 for Cogstate, the model selected all 8 tasks (mean squared error 226.80, SE 23.48). Finally, VStore was found to be highly sensitive (87%) and specific (91.7%) to age cohorts, with 94.6% of the area under the receiver operating characteristic curve. Conclusions Our findings suggest that VStore is a promising assessment that engages standard cognitive domains and is sensitive to age-related cognitive decline.

This paper describes the development of a set of three video games designed to reduce the high drop-off rates associated with learning to play the piano/keyboard by gamifying rote tasks that require monotonous practice. By defining our own understanding of what musicianship is and creating a custom framework for assessment through the use of existing curriculum, we have chosen specific areas which require the most rote learning and are critical to developing motor skills and to building an understanding of music; these include learning and practicing scales, keeping in time with tempo and the basics of hand coordination and fingering styles. Existing solutions that attempt to resolve the issue of high drop off rates observed with beginner instrument learners use elements of gamification in order to enrich their learning experiences and also help increase motivation. These approaches do work but in most cases they offer short term solutions; a key issue is retaining users over long periods of time and ensuring that they practice consistently and regularly. We developed solutions which offer a way for learners to practice in an engaging and entertaining way, with the intention to reduce the drop-off rates and lower the barrier for entry to learning piano/keyboard.

This paper describes the development of a set of video games designed to reduce the high drop-off rates associated with learning to play the keyboard by gamifying rote tasks that require monotonous practice. By defining our own understanding of what musicianship is and creating a custom framework for assessment through the use of existing curriculums and learning applications, we have chosen specific areas which require the most rote learning, are critical to developing motor skills and to building an understanding of music; these include learning and practicing musical scales, keeping in time with tempo and the basics of hand coordination and fingering styles. We developed solutions which offer a new way for learners to practice in an engaging and entertaining way with the aim to reduce the drop-off rates and lower the barrier for entry to learning keyboard. Developing games requires an iterative process of development, testing, isolating key issues and solving them through further development. Therefore, through a pilot study (using observations, screen recordings and semi-structured interviews as data collection methods), we have observed that whilst this novel method of learning and practicing using video games is positively accepted by learners and teachers alike, the games themselves and the process of validation requires refinement in order to truly gauge each game relating to engagement, motivation and educational benefit. This paper describes the findings of this pilot study regarding the improvements and changes of each developed game as well how to improve future user studies.

Abstract. The Unity 3D engine is used by a large majority of developers to create games. It owns a forty five percent market share and is considered one of the biggest development tools today; this is due to its simple and fast development process which allows for rapid production of game prototypes. However, with over a hundred different options available to develop games, one must ask whether using an engine such as Unity to generate simple 2D mobile games is necessary. This paper aims to discover whether the use of the Unity engine is appropriate for beginner developers who are looking to create 2D mobile games whilst also providing insight into how influential Unity is within education and whether learning more programming orientated applications is beneficial in regards to universal application and longevity. We will define the criteria for selecting a development methodology and create a 2D mobile game within the Unity engine and replicate this game using Corona SDK. The development process for both implementations will be reviewed and compared then the game will be tested using a benchmark application on various devices to help demonstrate which method was the most optimised and therefore appropriate for mobile development.

BackgroundAspects of cognitive function decline with age. This phenomenon is referred to as age-related cognitive decline (ARCD). Improving the understanding of these changes that occur as part of the ageing process can serve to enhance the detection of the more incapacitating neurodegenerative disorders such as Alzheimer’s disease (AD). In this study, we employ novel methods to assess ARCD by exploring the utility of the alpha3/alpha2 electroencephalogram (EEG) power ratio – a marker of AD, and a novel virtual reality (VR) functional cognition task – VStore, in discriminating between young and ageing healthy adults.Materials and methodsTwenty young individuals aged 20–30, and 20 older adults aged 60–70 took part in the study. Participants underwent resting-state EEG and completed VStore and the Cogstate Computerised Cognitive Battery. The difference in alpha3/alpha2 power ratios between the age groups was tested using t-test. In addition, the discriminatory accuracy of VStore and Cogstate were compared using logistic regression and overlying receiver operating characteristic (ROC) curves. Youden’s J statistic was used to establish the optimal threshold for sensitivity and specificity and model performance was evaluated with the DeLong’s test. Finally, alpha3/alpha2 power ratios were correlated with VStote and Cogstate performance.ResultsThe difference in alpha3/alpha2 power ratios between age cohorts was not statistically significant. On the other hand, VStore discriminated between age groups with high sensitivity (94%) and specificity (95%) The Cogstate Pre-clinical Alzheimer’s Battery achieved a sensitivity of 89% and specificity of 60%, and Cogstate Composite Score achieved a sensitivity of 83% and specificity of 85%. The differences between the discriminatory accuracy of VStore and Cogstate models were statistically significant. Finally, high alpha3/alpha2 power ratios correlated strongly with VStore (r = 0.73), the Cogstate Pre-clinical Alzheimer’s Battery (r = -0.67), and Cogstate Composite Score (r = -0.76).ConclusionWhile we did not find evidence that the alpha3/alpha2 power ratio is elevated in healthy ageing individuals compared to young individuals, we demonstrated that VStore can classify age cohorts with high accuracy, supporting its utility in the assessment of ARCD. In addition, we found preliminary evidence that elevated alpha3/alpha2 power ratio may be linked to lower cognitive performance.