Can Computers Outperform Humans in Detecting User Zone-Outs? Implications for Intelligent Interfaces

The ability to identify whether a user is “zoning out” (mind wandering) from video has many HCI (e.g., distance learning, high-stakes vigilance tasks). However, it remains unknown how well humans can perform this task, how they compare to automatic computerized approaches, and how a fusion of the two might improve accuracy. We analyzed videos of users’ faces and upper bodies recorded 10s prior to self-reported mind wandering (i.e., ground truth) while they engaged in a computerized reading task. We found that a state-of-the-art machine learning model had comparable accuracy to aggregated judgments of nine untrained human observers (area under receiver operating characteristic curve [AUC] = .598 versus .589). A fusion of the two (AUC = .644) outperformed each, presumably because each focused on complementary cues. Furthermore, adding more humans beyond 3–4 observers yielded diminishing returns. We discuss implications of human–computer fusion as a means to improve accuracy in complex tasks.

Impact of Personality Traits and Socio-Demographic Factors on Depression among Doctors and Nurses

The workplace is not immune to conflict and stress, specifically when fulfilling people's responsibilities at great personal costs. Doctors and nurses are always on the frontline in hospitals, vaulting from one stressful high-stakes situation to the next. The HEXACO model of personality traits: Honesty-humility, Emotionality, Extraversion, Agreeableness, Conscientiousness, and Openness, has long been hypothesized to be a major predicting factor when determining individuals' responses to stress and susceptibility to experiencing depression. Most research suggests that personality traits resonate with a person's cognitive abilities and how they can deal with stress and depression. However, there is a lack of research on their correlation to depression severity in the Middle East. The current study aimed to investigate the impact of HEXACO personality traits and socio-demographic factors on depression amongst doctors and nurses. A sample of 170 doctors and nurses (62.1% doctors) completed HEXACO-60 and PHQ-9 depression severity questionnaires. The data were analyzed through descriptive statistics, independent samples t-test, ANOVA, correlation, and regression analysis. The findings showed that Honesty-humility was the strongest predictor, while extraversion was the second strongest. Emotionality had the least impact on depression. The relationship between Agreeableness and Openness to Experience with depression was insignificant. However, gender, age, working hours, and work experience were significant predictors of depression. Marital status and level of specialization were insignificant predictors. Thus, it was concluded that not all HEXACO traits and socio-demographics predict depression. Study findings could be utilized in the implementation of employee recruitment, job crafting, positive psychology, and coaching.

Language learning strategies used by Indonesian learners in IELTS

This study investigated the frequently used language learning strategies (LLS) by Indonesian learners in learning English for a high-stakes exam, IELTS. In addition, differences in the LLS use among participants with different proficiency were examined. Using a quantitative approach, data were collected by using an online survey by utilizing Oxford’s Strategy Inventory for Language Learning (SILL) as the instrument. Sixty-one Indonesian adult learners who had taken IELTS were involved in this study. Their IELTS score indicated their proficiency levels. Data analysis was carried out using Statistical Package for Social Science (SPSS). It involved a descriptive analysis to find the frequency and an independent samples t-test to see the LLS use based on proficiency. The findings revealed that the participants used various LLS in learning English for IELTS. The most frequently used strategies were metacognitive, followed by cognitive, compensative, social, affective, and memory strategies. Meanwhile, the independent samples t-test showed that the difference in the LLS use among participants with different proficiency was not noticeable. Reflecting on the results, it is proposed that English teachers in Indonesia may start growing their learners’ awareness of LLS benefits and teach them to use them properly in their learning English for IELTS.

Why postmortems fail

Most high-profile disasters are followed by demands for an investigation into what went wrong. Even before they start, calls for finding the missed warning signs and an explanation for why people did not “connect the dots” will be common. Unfortunately, however, the same combination of political pressures and the failure to adopt good social science methods that contributed to the initial failure usually lead to postmortems that are badly flawed. The high stakes mean that powerful actors will have strong incentives to see that certain conclusions are—and are not—drawn. Most postmortems also are marred by strong psychological biases, especially the assumption that incorrect inferences must have been the product of wrong ways of thinking, premature cognitive closure, the naive use of hindsight, and the neglect of the comparative method. Given this experience, I predict that the forthcoming inquiries into the January 6, 2021, storming of the US Capitol and the abrupt end to the Afghan government will stumble in many ways.

Raising the Bar: Causal Evidence on Gender Differences in Risk-Taking From a Natural Experiment

We investigate the risk-taking behavior of women and men in high-stakes jumping competitions. Results indicated that female and male athletes differ in the timing and extent of their reactions to an increase in the risk of failure. Male competitors increased risk-taking in the more risky environment immediately after the changes. Female athletes, however, increased risk-taking two years after the rule change. Over time, female athletes revert to pre-reform risk-taking levels, and male athletes’ continued to make more risky decisions in the new environment. We attribute our findings to gender differences in competitiveness and risk preferences.

Predictability of IELTS in a high-stakes context: a mixed methods study of Chinese students’ perspectives on test preparation

High-stakes language tests are used around the world as a gatekeeping tool under the internationalization of higher education. However, the predictable aspect of the high-stakes language tests is seldom discussed, especially from students’ perspectives. This study aims to address this gap by aiming to better understand how certain factors and conditions contribute to the predictability issue of IELTS from students’ perspectives within a high-stakes context. This study used a mixed method approach to investigate the views and experiences of students within a Sino-UK joint college. The data collection was in two concurrent strands: online survey and group interviews. Findings suggested that IELTS can impact students negatively by narrowing their English learning scope, driving them into self-isolated way of study, doing repeated test-taking and buying predicted answers. Implications related to language test preparation are discussed in light of the findings.