A user’s guide to the evolutionary argument against naturalism

Alvin Plantinga has famously argued that metaphysical naturalism is self-defeating, and cannot be rationally accepted. I distinguish between two different ways of understanding this argument, which I call the "probabilistic inference conception", and the "process characteristic conception". I argue that the former is what critics of the argument usually presuppose, whereas most critical responses fail when one assumes the latter conception. To illustrate this, I examine three standard objections to Plantinga's evolutionary argument against naturalism: the Perspiration Objection, the Tu Quoque Objection, and the "Why Can't the Naturalist Just Add a Little Something?" Objection. I show that Plantinga's own responses to these objections fail, and propose counterexamples to his first two principles of defeat. I then go on to construct more adequate responses to these objections, using the distinctions I develop in the first part of the paper.     

Computer “personalities”: A new approach to understanding user compatibility

While many scholars have looked at computer processes as a means of better understanding how the brain functions, very few have explored the opposite perspective, that computers have personalities which may influence how they interact with people. This article describes a study which compared the personalities of two popular personal computers, then discusses the implications for computer development, documentation, marketing and training.John Penrose is a professor in the Information and Decision Systems Department at San Diego State University. Lawrence M. Seiford is Associate Professor at the Department of Industrial Engineering and Operations Research at the University of Massachusetts.     

What are the factors determining user intentions to use AV while impaired?

In this study, we employ the Integrated Choice Latent Variable (ICLV) framework to model the public’s intention of using Autonomous Vehicles (AVs) while impaired under the influence of alcohol, medicine, or fatigue. We identify five latent constructs from psychometric indicators that define respondent’s perception and attitudes towards AVs which are i) perceived benefits, ii) perceived risks, iii) enjoy driving, iv) wheels public transport attitude, and v) rails public transport attitude. We use these latent variables along with explanatory variables to study user intentions regarding delegation of vehicle control from human driving to autonomous driving. The study uses survey data collected from 1,065 Czech residents between 2017 and 2018. Our findings indicate that user intentions are primarily defined by attitudes rather than socio-demographic attributes. However, the inclusion of both types of variables is crucial in evaluating user intentions. Despite a positive outlook towards AVs, people were found to be reluctant in using AVs while impaired which can be attributed to distrust towards the technology. Our analysis shows that with appropriate efforts from policymakers, the public’s attitude can be changed to promote adoption. The efforts will have to be emphasized towards building positive attitudes (such as perceived benefits) and diminishing existing negative attitudes (such as perceived risks).     

Working memory span tasks: A methodological review and user’s guide

Working memory (WM) span tasks—and in particular, counting span, operation span, and reading span tasks—are widely used measures of WM capacity. Despite their popularity, however, there has never been a comprehensive analysis of the merits of WM span tasks as measurement tools. Here, we review the genesis of these tasks and discuss how and why they came to be so influential. In so doing, we address the reliability and validity of the tasks, and we consider more technical aspects of the tasks, such as optimal administration and scoring procedures. Finally, we discuss statistical and methodological techniques that have commonly been used in conjunction with WM span tasks, such as latent variable analysis and extreme-groups designs.     

Epistemic action: A measure for cognitive support in tangible user interfaces?

The quality of user interfaces is often measured in terms of efficiency, effectiveness, and satisfaction. In the area of tangible user interfaces, epistemic—or exploratory—action has been suggested as a fourth measure of quality. In computer game studies (Kirsh & Maglio, 1992, 1994), players used epistemic actions to modify the environment, which helped them determine the correct position of blocks with less mental effort. There, the researchers found that it might be easier to physically modify the external world and then interpret it than to compute and interpret a new state mentally. Specifically, epistemic action may be a relevant concept when researching tangible user interfaces incorporating physical handles. This article examines the potential relations between the three traditional measures of usability and epistemic actions using three spatial planning tools with different degrees of physicality. The results indicate that epistemic action is a measure that is independent of the three traditional usability measures: efficiency, effectiveness, and satisfaction. However, epistemic action does not increase linearly with the physicality of a user interface, and it probably is a more complex measure that is also related to the reusability of the interface. Further research is needed to fully understand the potential of this measure.     

Analysing user’s reactions in advice-giving dialogues with a socially intelligent ECA

In this paper, we investigate the user’s reactions to received suggestion by an Embodied Conversational Agent playing the role of artificial therapist in the healthy eating domain. Specifically, we analyse the behaviour of people who voluntarily requested to receive information from the agent, and we compare it with the results of a previous evaluation experiment in which subjects were not properly motivated to interact with the agent because they were selected for evaluating the system. This study is part of an ongoing research aimed at developing an intelligent virtual agent that applies natural argumentation techniques to persuade the users to improve their eating habits.     

Understanding user’s travel behavior and city region functions from station-free shared bike usage data

Station-free shared bike (SFSB) is a new travel mode that shared bikes are allowed to park in any proper places. It implies that the users are more likely to park the SFSB as close as their destinations. This advantage makes the SFSB data to be an ideal source to understand the land-use distribution. Inspired by the idea in text mining, this paper proposes a topic-based two-stage SFSB data mining algorithm to understand the SFSB user’s travel behavior and to discover city functional regions. A region, a function and human mobility patterns are treated as a document, a topic and words, respectively. Then, a region is represented by a distribution of functions, and a function is featured by a distribution of mobility patterns. The point-of-interest data is combined to annotate the clustered regions to discover the real functions. At last, the proposed method is tested using 14-day SFSB data in Beijing and the results are estimated by the Satellite Map data. The proposed methods and the results can be applied to infer the individual’s travel purpose through functional regions and to improve land-use planning, etc.     

Beyond internal consistency reliability: Rationale and user’s guide for Multitrait Analysis Program on the microcomputer

A methodology for evaluating Likert-type scales is presented. Multitrait scaling is a straightforward approach to scale analysis that focuses on items as the unit of analysis and utilizes the logic of convergent and discriminant validity. Multitrait scaling is illustrated with the Multitrait Analysis Program, using patient satisfaction data from the Medical Outcomes Study.     

Spatio-temporal pattern of vulnerable road user’s collisions hot spots and related risk factors for injury severity in Tunisia

High risk of vulnerable road users (VRUs) injuries and fatalities have received higher interest nowadays in Tunisia. By using VRUs crash record (from January 1, 2001 to December 31, 2013), we describe the spatial pattern of VRUs collisions according to different temporal scales such as (a.m. vs p.m. rush hours VRUs collisions, working days vs non-working days VRUs collisions, daytime vs nighttime VRUs collisions) and investigate the influence of personal and environmental factors for VRUs injuries severity within the Center-East region in Tunisia. The empirical results are of great variety: spatial clustering pattern of each subtype of VRUs collisions according to temporal scale were clearly observed with the exception of daytime VRUs collisions, which shows a random tendency. All time-based subtypes of VRUs collisions also were found to be clustered along the national highways and regional highways especially in the regions of Sousse and Sfax. Results from VRUs severity model suggest that the degree of injury severity is higher for male than for female victim. The Tunisian VRUs are more likely to be involved in severe collision than non-Tunisian VRUs. Among driver contributory factors, the change of direction and hazardous overtaking increase the probability of sustaining fatal accidents compared to other driver contributory factors. The season factor shows that accident severity during the summer season is higher. From a policy view point, this kind of analysis can certainly help Tunisian public authorities to develop appropriate safety measures that can possibly reduce the number of VRUs injuries and fatalities.     

Learning about Probability from Text and Tables: Do Color Coding and Labeling through an Interactive‐user Interface Help?

Learning from visual representations is enhanced when learners appropriately integrate corresponding visual and verbal information. This study examined the effects of two methods of promoting integration, color coding and labeling, on learning about probabilistic reasoning from a table and text. Undergraduate students (N = 98) were randomly assigned to learn about probabilistic reasoning from one of 4 computer‐based lessons generated from a 2 (color coding/no color coding) by 2 (labeling/no labeling) between‐subjects design. Learners added the labels or color coding at their own pace by clicking buttons in a computer‐based lesson. Participants' eye movements were recorded while viewing the lesson. Labeling was beneficial for learning, but color coding was not. In addition, labeling, but not color coding, increased attention to important information in the table and time with the lesson. Both labeling and color coding increased looks between the text and corresponding information in the table. The findings provide support for the multimedia principle, and they suggest that providing labeling enhances learning about probabilistic reasoning from text and tables. Copyright © 2016 John Wiley & Sons, Ltd.     

Please stop now,automated vehicle! – Passengers aim to avoid risk experiences in interactions with a crossing vulnerable road user at an urban junction

The success of highly automated vehicles (HAVs; SAE Level 4) will depend to a large extent on how well they are accepted by their future passengers. This is especially true for the interaction of these vehicles with other human road users in mixed traffic. In future urban traffic, passengers of HAVs will observe from a passive position how the automated system resolves space-sharing conflicts with crossing vulnerable road users (VRUs; e.g., pedestrians and cyclists) at junctions. For one such crossing-paths conflict, we investigated when passengers would want the HAV to start braking and how much perceived risk passengers accept in the interaction of their vehicle with VRUs. To this end, we conducted 1) an online video study (N = 118), 2) a driving simulator study (N = 28), and 3) a human&vehicle-in-the-loop (Hu&ViL) study at a test site (N = 10). We varied the speed of the HAV (30 km/h vs. 50 km/h), the type (cyclist vs. pedestrian), and crossing direction of the VRU (left vs. right). During the approach to the junction, passengers' task was to trigger the HAV's braking maneuver, in a first trial at the point they considered ideal and in a second trial at the last point they still considered safe enough to decelerate and come to a stop at the stop line. For each braking maneuver, we analyzed the HAV’s distance and time-to-arrival (TTA) to the VRU at braking onset, as well as passengers’ perceived risk in the VRU interaction. The results showed that most passengers preferred harmless interactions with VRUs (at the ideal braking onset time), and accepted unpleasant, but not dangerous interactions at most (at the last acceptable braking onset time). Methodologically, the results were very similar in the three different environments (online, driving simulator, real vehicle). These results clearly show that, in addition to the technical considerations of safe automated driving, passengers’ perception and evaluation of HAV driving behavior should also be taken into account to achieve a satisfying level of acceptance of these vehicles.