A Scanpath Analysis of the Risky Decision-Making Process

Analyzing a Cross-Functional Information Technology Project: A Real Application of the Multistage One-Shot Decision-Making Approach

This research applies the multistage one-shot decision-making approach (MOSDMA) to a cross-functional information technology project in Oman. This case study is the first to employ the MOSDMA in actual practice. A group of experts re-evaluate the former decision problem using qualitative and quantitative data. The results show the ease and effectiveness of applying the suggested approach in re-evaluating a former decision problem. In addition, it is well recognized that such a scenario-based approach that involves the decision-maker’s mindset can yield confidence in, satisfaction with, and ownership of the decision, irrespective of the future outcomes.

From eye movements to scanpath networks: A method for studying individual differences in expository text reading

Eye movements have been examined as an index of attention and comprehension during reading in the literature for over 30 years. Although eye-movement measurements are acknowledged as reliable indicators of readers' comprehension skill, few studies have analyzed eye-movement patterns using network science. In this study, we offer a new approach to analyze eye-movement data. Specifically, we recorded visual scanpaths when participants were reading expository science text, and used these to construct scanpath networks that reflect readers' processing of the text. Results showed that low ability and high ability readers' scanpath networks exhibited distinctive properties, which are reflected in different network metrics including density, centrality, small-worldness, transitivity, and global efficiency. Such patterns provide a new way to show how skilled readers, as compared with less skilled readers, process information more efficiently. Implications of our analyses are discussed in light of current theories of reading comprehension.

The effect of visual attention process and thinking styles on environmental aesthetic preference: An eye-tracking study

People often form different aesthetic preferences for natural and built environments, which affects their behavioral intention; however, it remains unknown whether this difference in aesthetic preference is due to differences in thinking styles. However, whether tourists' aesthetic preferences differ when using different visual attention processes has not been studied further. This study used eye-tracking and self-reporting to investigate these questions. The results show that natural environment images are more favored visually because they can evoke in tourists larger pupil diameters and longer scan paths, but we found no significant difference in fixation duration and fixation counts. We also found that the scanning path of tourists who predominantly rely on intuitive thinking is modulated by the bottom-up attention process, while the scanning path of tourists who prefer rational thinking is modulated by the top-down attention process. In the bottom-up process, tourists who prefer rational thinking exhibit more positive aesthetic preferences and emotional arousal. In summary, the present study verified that aesthetic preference is more likely to be influenced by both thinking style and visual attention processing. The results of the present work provide preliminary evidence that the aesthetic preference of the environment is not only related to visual attention but also affected by the individual visual attention process and thinking style.

New Paradigms for the Old Question: Challenging the Expectation Rule Held by Risky Decision-Making Theories

In risky decision making, whether decision makers follow an expectation rule as hypothesised by mainstream theories is a compelling question. To tackle this question and enrich our knowledge of the underlying mechanism of risky decision making, we developed a series of new experimental paradigms that directly examined the computation processes to systematically investigate the process of risky decision making and explore the boundary condition of expectation rule over the course of a decade. In this article, we introduce these methods and review behavioural, eye-tracking, event-related potential, and functional magnetic resonance imaging studies that employed these methods. Results of these studies consistently showed that decision makers in the single-application condition did not perform the weighting and summing process assumed by the expectation rule. Moreover, decision makers were inclined to adopt a non-compensatory strategy, such as a heuristic one, in risky decision making. Furthermore, results indicated that the expectation rule was only applicable for conditions that involved decisions applied to numerous events (multiple applications) or to people (everyone). The findings indicated that using an index based on expected value to prescribe human risk preferences appears to be an artificial or false index of risk preference, and emphasised a new methodological direction for risky decision-making research.

Scanpath Analysis of Student Attention During Problem Solving with Worked Examples

We report on the analysis of scanpath data captured by an eye tracker as students solved problems with access to worked examples. Our work makes two contributions: (1) it reports on scanpath analysis using the MultiMatch tool, (2) it investigates how type of problem-example similarity and assistance influenced attention patterns captured by scanpaths. We show that both problem-example similarity and type of assistance impact scanpaths.

Worth-based choice: giving an offered smaller pear an even greater fictional value

Choices between options represented in a multidimensional space, in which each dimension signifies a distinct attribute describing the objects, are presumably guided by the principle of value maximization. However, the current study assumes that in a real-world setting, those who are able to imagine things that do not actually exist could modify the multidimensional space by self-generating an unoffered but fictional dimension. We define the utility (Uv) assigned by the decision makers to the options on the offered/given dimension as value (v[x]) and the utility (Uw) on the self-generated/fictional dimension as worth (w[xc]). Our series of experiments demonstrated that an option with a greater value established strictly on that given set of dimensions might not necessarily be chosen (which contradicted the principle of value maximization). Choosing an option with less value (i.e. giving away the bigger pear) behavior can be described and explained by the “worth-based choice” approach, as people behave to select the option with the highest worth rather than that with the highest value. We are optimistic that the resulting findings will facilitate our understanding of the beauty of such a “one step further” choice and assist us in understanding the following: the ability to further generate a fictional dimension and to assign a delayed utility (worth) to the options on the fictional dimension, and to make a worth-based choice, which could eventually be taken as the operational definition to measure the degree of “fiction-generating ability”, as proposed by Harari ( 2014 ).

New approaches to the analysis of eye movement behaviour across expertise while viewing brain MRIs

Brain tumour detection and diagnosis requires clinicians to inspect and analyse brain magnetic resonance images. Eye-tracking is commonly used to examine observers' gaze behaviour during such medical image interpretation tasks, but analysis of eye movement sequences is limited. We therefore used ScanMatch, a novel technique that compares saccadic eye movement sequences, to examine the effect of expertise and diagnosis on the similarity of scanning patterns. Diagnostic accuracy was also recorded. Thirty-five participants were classified as Novices, Medics and Experts based on their level of expertise. Participants completed two brain tumour detection tasks. The first was a whole-brain task, which consisted of 60 consecutively presented slices from one patient; the second was an independent-slice detection task, which consisted of 32 independent slices from five different patients. Experts displayed the highest accuracy and sensitivity followed by Medics and then Novices in the independent-slice task. Experts showed the highest level of scanning pattern similarity, with medics engaging in the least similar scanning patterns, for both the whole-brain and independent-slice task. In the independent-slice task, scanning patterns were the least similar for false negatives across all expertise levels and most similar for experts when they responded correctly. These results demonstrate the value of using ScanMatch in the medical image perception literature. Future research adopting this tool could, for example, identify cases that yield low scanning similarity and so provide insight into why diagnostic errors occur and ultimately help in training radiologists.