論文アブストラクト： Motivation is a fundamental concept in understanding people's experiences and behavior. Yet, motivation to engage with an interactive system has received only limited attention in HCI. We report the development and validation of the User Motivation Inventory (UMI). The UMI is an 18-item multidimensional measure of motivation, rooted in self-determination theory (SDT). It is designed to measure intrinsic motivation, integrated, identified, introjected, and external regulation, as well as amotivation. Results of two studies (total N = 941) confirm the six-factor structure of the UMI with high reliability, as well as convergent and discriminant validity of each subscale. Relationships with core concepts such as need satisfaction, vitality, and usability were studied. Additionally, the UMI was found to detect differences in motivation for people who consider abandoning a technology compared to those who do not question their use. The central role of motivation in users' behavior and experience is discussed.
インタラクティブシステムに対する動機付けを評価するための新たな指標としてUser Motivation Inventoryを提案。アンケート調査により質問項目を選定し、弁別妥当性を確認した。
論文アブストラクト： Self-reflection is a central goal of personal informatics systems, and constructing visualizations from physical tokens has been found to help people reflect on data. However, so far, constructive physicalization has only been studied in lab environments with provided datasets. Our qualitative study investigates the construction of personal physicalizations in people's domestic environments over 2-4 weeks. It contributes an understanding of (1) the process of creating personal physicalizations, (2) the types of personal insights facilitated, (3) the integration of self-reflection in the physicalization process, and (4) its benefits and challenges for self-reflection. We found that in constructive personal physicalization, data collection, construction and self-reflections are deeply intertwined. This extends previous models of visualization creation and data-driven self-reflection. We outline how benefits such as reflection through manual construction, personalization, and presence in everyday life can be transferred to a wider set of digital and physical systems.
論文アブストラクト： A novel eye-tracked measure of the frequency of pupil diameter oscillation is proposed for capturing what is thought to be an indicator of cognitive load. The proposed metric, termed the Index of Pupillary Activity, is shown to discriminate task difficulty vis-a-vis cognitive load (if the implied causality can be assumed) in an experiment where participants performed easy and difficult mental arithmetic tasks while fixating a central target (a requirement for replication of prior work). The paper's contribution is twofold: full documentation is provided for the calculation of the proposed measurement which can be considered as an alternative to the existing proprietary Index of Cognitive Activity (ICA). Thus, it is possible for researchers to replicate the experiment and build their own software which implements this measurement. Second, several aspects of the ICA are approached in a more data-sensitive way with the goal of improving the measurement's performance.
論文アブストラクト： How valuable are certain interface features to their users? How can users' demand for features be quantified? To address these questions, users' demand curve for the sorting feature was elicited in a controlled experiment, using personal finance as the user context. Users made ten rounds of investment allocation across up to 77 possible funds, thus encountering choice overload, typical of many online environments. Users were rewarded for positive investment returns. To overcome choice overload, users could sort the alternatives based on product attributes (fees, category, fund name, past performance). To elicit their demand for sorting, the experimental design enabled users to forgo 0%-9% of their reward in return for activating the sorting feature. The elicited downward sloping demand curve suggests a curvilinear relationship between sorting use and cost. More broadly, the study offers a way to quantify user demand of UI features, and a basis for comparison between features.
実験中の認知負荷を測定するための新たな指標として、アイトラッカを使用した瞳孔振動計測を行うIndex of Pupillary Activityを提案・検証した。タスクの難易度を区別するのに有効であった。