Characterizing HCI Research in China: Streams, Methodologies and Future Directions

This position paper takes the first step to attempt to present the initial characterization of HCI research in China. We discuss the current streams and methodologies of Chinese HCI research based on two well-known HCI theories: Micro/Marco-HCI and the Three Paradigms of HCI. We evaluate the discussion with a survey of Chinese publications at CHI 2019, which shows HCI research in China has less attention to Macro-HCI topics and the third paradigms of HCI (Phenomenologically situated Interaction). We then propose future HCI research directions such as paying more attention to Macro-HCI topics and third paradigm of HCI, combining research methodologies from multiple HCI paradigms, including emergent users who have less access to technology, and addressing the cultural dimensions in order to provide better technical solutions and support

A longitudinal review of Mobile HCI research Methods

This paper revisits a research methods survey from 2003 and contrasts it with a survey from 2010. The motivation is to gain insight about how mobile HCI research has evolved over the last decade in terms of approaches and focus. The paper classifies 144 publications from 2009 published in 10 prominent outlets by their research methods and purpose. Comparing this to the survey for 2000-02 show that mobile HCI research has changed methodologically. From being almost exclusively driven by engineering and applied research, current mobile HCI is primarily empirically driven, involves a high number of field studies, and focus on evaluating and understanding, as well as engineering. It has also become increasingly multi-methodological, combining and diversifying methods from different disciplines. At the same time, new opportunities and challenges have emerged

Comparing the cognitive profile of the HCI professional and the HCI educator

Previous research into Human-Computer Interaction (HCI) education has focussed mainly on the curriculum, pedagogy and the gap between education, and little is known about the cognitive profile of the HCI practitioner or educator, or how their individual differences impact upon practice in the field or the classroom. This research intends to address this gap by investigating the cognitive style of HCI practitioners, educators, and those with both roles. 315 professionals responded to a global online survey which captured their individual cognitive style using the Allinson and Hayes Cognitive Style Index (CSI) which tests whether the subject tends more towards an intuitivist or analyst, and the Object-Spatial Imagery and Verbal Questionnaire (OSIVQ) which suggests a three dimensional model of cognitive style – object imagers who prefer to construct pictorial images, spatial imagers who prefer schematic representations and verbalizers who prefer to use verbal-analytical tools. Together, these two instruments provide a profile that matches the skills required to work within the field of HCI. The respondents included practitioners in the field (N=179), educators (N=61), and some who were both practitioner and educator (N=75). A one-way between-groups ANOVA and MANOVA was performed to investigate differences in the role of the professional, and the CSI and OSIVQ profiles respectively, followed by the Welch t-test to compare their OSIVQ scores with the published normative values. The ANOVA comparing the CSI scores for each of the groups revealed a statistically significant difference of F(2, 312) = 3.35, p= 0.38 and post-hoc comparisons using the Tukey HSD test indicated that the mean score for the educators was significantly different from that of the ‘both’ group. The practitioners did not differ significantly from either the educators or ‘both’. This may in some part be explained by the fact that very often HCI is taught by an academic with a computer science background rather than an HCI specialist, but further investigation is needed in this area. The MANOVA used the three constructs of the OSIVQ as dependent variables. No significant difference was found between the groups. However, the t-tests comparing the professional against the normative data revealed that whilst there was no significant difference between the object imager score of the HCI professional and the scientist, there was a difference between the spatial imager score of the HCI professional and the visual artist, perhaps again reflecting the computer science background of many professionals. 24 survey respondents have been interviewed and the resulting data will form the basis of a thematic analysis to extend the cognitive profile, and to identify the predominant technological frames of operation. Applying this concept of technological frames to the domain of HCI, will help to make sense of the adoption and application of knowledge, tools and techniques amongst this community. In order for the curriculum to meet the needs of the market, the educator needs to understand the practitioner in order to produce graduates equipped for the role. Finally, as HCI is delivered in a multidisciplinary environment, should it not also be taught by a multidisciplinary team

Designing and Engineering for Emergence: A Challenge for HCI Practice and Research

This research commentary on Future Directions for HCI Research responds to research commentaries on the same topic by Benbasat (2010) and Lyytinen (2010), and to two articles in Volume 1 of the AIS Transactions on Human- Computer Interaction (Galletta and Zhang, 2009; Zhang et al. 2009). It employs a two-dimensional framework for exploring the scope and challenges of HCI that combines a social/ technical dimension and a behavior dimension that emphasizes differences between engineered and emergent behavior in sociotechnical systems. This framework is used to reflect on possible differences between the scope of a definition of HCI in those articles and the scope of the topics identified in the extensive survey of HCI literature reported by Zhang and colleagues (2009). Implications include the possibility that future HCI research and theorizing may find significant opportunities related to designing for emergence, or even engineering for emergence

Do We Truly Sacrifice Truth for Simplicity: Comparing Complete Individual Randomization and Semi-Randomized Approaches to Survey Administration

Human-computer interaction researchers have long used survey methodologies. However, debate remains about the potential for participants to provide biased responses to subsequent items based on previously viewed items. In this research, we investigate the effects of survey item ordering that researchers have not studied previously. Grounded in previous exploratory item-ordering studies using an HCI online survey, we investigate bias in more detail. In addition, we use an adult sample population so that we can extend our results more broadly as compared to previous research. We employed two distinct randomizing survey approaches: 1) complete item randomization for each respondent (random), which presents items to each respondent in a completely randomized order; and 2) partially individualized item randomization (grouped), which presents constructs in the same order in a survey but randomizes items in each construct for each respondent. Our results suggest researchers should use fully randomized survey instruments in HCI research whenever possible since grouped ordering of any kind increases bias and statistical inflation, which can influence results’ veracity. Additionally, we did not appear to find any significant increase in the participants’ frustration or fatigue to be associated with the random treatment

Challenge in Digital Games: Towards Developing a Measurement Tool

Challenge is arguably the most important experience that players seek in digital games. However, without a measure of how challenged players feel during the act of play, it is hard to design games that are neither too easy nor too hard and, therefore, truly enjoyable. Especially in industry, challenge is dominantly assessed by means of manual play testing in ad-hoc trials. The aim of this research is to create a more systematic, complete, and reliable instrument to evaluate the level of players' experienced challenge in games in the form of a questionnaire. This paper presents the key results from an extensive literature survey which will inform further development. We survey definitions of challenge, challenge types, and their relation to player experience based on the observations of game designers. We furthermore draw from empirical findings in a diverse range of fields such as game studies, human-computer interaction (HCI) and artificial intelligence (AI)

Improving fairness in machine learning systems: What do industry practitioners need?

The potential for machine learning (ML) systems to amplify social inequities and unfairness is receiving increasing popular and academic attention. A surge of recent work has focused on the development of algorithmic tools to assess and mitigate such unfairness. If these tools are to have a positive impact on industry practice, however, it is crucial that their design be informed by an understanding of real-world needs. Through 35 semi-structured interviews and an anonymous survey of 267 ML practitioners, we conduct the first systematic investigation of commercial product teams' challenges and needs for support in developing fairer ML systems. We identify areas of alignment and disconnect between the challenges faced by industry practitioners and solutions proposed in the fair ML research literature. Based on these findings, we highlight directions for future ML and HCI research that will better address industry practitioners' needs.Comment: To appear in the 2019 ACM CHI Conference on Human Factors in Computing Systems (CHI 2019