Q1. Discuss and evaluate how collecting data on someone's usage of applications can support understanding their behaviour. In your answer consider the factors related to human-centred design as well as concepts connected to the human and the interaction. An application (or app) is a type of software with a specific purpose, such as a word processor, a web browser, a media player, or a game. Apps collect data from many devices, most commonly on mobile phones (Farrahi & Gatica-Perez, 2008), followed by computers and tablets. Over time, the presence of apps has expanded dramatically; according to the Office for National Statistics (2020), approximately 49% of adults use either apps or virtual assistants. Apps allow for data collection from users, sometimes referred to as third parties. This data can include but is not limited to age, gender, email addresses, location, media such as photos, Wi-Fi, and mobile data usage. With this wide array of data, it can be possible to predict user behaviour with a varied history of experiences and contexts (Wiese et al., 2017) with other applications. Understanding more about a user can help to reduce risks when online and influence offline behaviour. For example, a study by File et al. (2019), attempted to determine the efficacy of a smartphone application compared to controls to reduce participants' alcohol consumption. Data collection reassures users, measures the behavioural intentions of a user (Libaque-Saenz et al., 2016), and examines to what extent how much information they wish to provide. Through this, applications create a sense of trust and control for the user (Libaque-Saenz et al., 2021) and the interaction with the application to provide a positive and secure experience. Real-time usage tracking helps developers understand how technology is part of the user's everyday life. Mobile phones are considered the primary device to measure usage, as more and more people willingly have a phone with them almost all the time (Jalali et al., 2016). Usage data can help explain the effect that using apps have on user's emotions, behaviour, and interactions with other applications or other users, online or in the real world (Bail, 2017). Most applications allow user reviews, a simple but useful method to collect qualitative data on user experience. This helps us understand behaviour as the user is self- reporting their experience willingly; however, this data can be affected by biases such as restrictions to memory and socially desirable responses (Harari et al., 2016) if under observation. Some data is not always accurate, can be misinterpreted, or do not provide enough information (Azam et al., 2012). An example of misinterpreted data can involve cookies, which aim to learn of a user's preferences and provide advertisements across applications they use that target those preferences. However, a user could have chosen something by
accident or no longer feel it applies to them. So, the user would feel bombarded by multiple adverts for a product or service or a recommended application that they have no interest in, resulting in frustration and a less rewarding