Knowledge extraction from pointer movements and its application to detect uncertainty

This work was supported by the Doctoral Program NOVA I4H (Fundacao para a Ciencia e a Tecnologia) [grant PD/BDE/114561/2016].Pointer-tracking methods can capture a real-time trace at high spatio-temporal resolution of users' pointer interactions with a graphical user interface. This trace is potentially valuable for research on human-computer interaction (HCI) and for investigating perceptual, cognitive and affective processes during HCI. However, little research has reported spatio-temporal pointer features for the purpose of tracking pointer movements in on-line surveys. In two studies, we identified a set of pointer features and movement patterns and showed that these can be easily distinguished. In a third study, we explored the feasibility of using patterns of interactive pointer movements, or micro-behaviours, to detect response uncertainty. Using logistic regression and k-fold cross-validation in model training and testing, the uncertainty model achieved an estimated performance accuracy of 81%. These findings suggest that micro-behaviours provide a promising approach toward developing a better understanding of the relationship between the dynamics of pointer movements and underlying perceptual, cognitive and affective psychological mechanisms. Human-computer interaction; Pointer-tracking; Mouse movement dynamics; Decision uncertainty; On-line survey; Spatio-temporal features; Machine learningproofpublishe

Spanish Validation of the Flourishing Scale in the General Population

Well-being research and its measurement have grown in the last two decades. The objective of this study was to adapt and validate the Flourishing Scale in a sample of Spanish adults. This was a cross-sectional study using a non-probabilistic sample of 999 Spanish general adult population participants. The psychometric properties of the scale were analysed from an exploratory and confirmatory perspective. Exploratory factor analysis showed a one-factor solution explaining 42.3% of the variance; an internal consistency of .846; temporal reliability correlation of .749; convergent validity with the Satisfaction with Life Scale of .521 and criterion validity with positive and negative affect (PANAS), pessimism and optimism (LOT-R) ranging from .270 to .488. Confirmatory factor analysis testing the one-factor solution showed a χ2 of 65.57 df = 20; CFI of .982, RMSEA of .06, average variance extracted index of .518 and composite reliability index of .841. Results showed that the Spanish version of the FS is a reliable and valid method for measuring high levels of well-bein

Transparency of CHI Research Artifacts: Results of a Self-Reported Survey

Several fields of science are experiencing a ""replication crisis"" that has negatively impacted their credibility. Assessing the validity of a contribution via replicability of its experimental evidence and reproducibility of its analyses requires access to relevant study materials, data, and code. Failing to share them limits the ability to scrutinize or build-upon the research, ultimately hindering scientific progress.Understanding how the diverse research artifacts in HCI impact sharing can help produce informed recommendations for individual researchers and policy-makers in HCI. Therefore, we surveyed authors of CHI 2018-2019 papers, asking if they share their papers' research materials and data, how they share them, and why they do not. The results (34% response rate) show that sharing is uncommon, partly due to misunderstandings about the purpose of sharing and reliable hosting. We conclude with recommendations for fostering open research practices.This paper and all data and materials are freely available at https://osf.io/3bu6t