Toward Greater Reproducibility of Undergraduate Behavioral Science Research

Reproducibility crises have arisen in psychology and other behavioral sciences, spurring efforts to ensure research findings are credible and replicable. Although reforms are occurring at professional levels in terms of new publication parameters and open science initiatives, the credibility and reproducibility of undergraduate research deserves attention. Undergraduate behavioral science research projects that rely on small convenience samples of participants, overuse hypothesis testing for drawing meaning from data, and engage in opaque statistical computing are vulnerable to producing nonreproducible findings. These vulnerabilities are reviewed, and practical recommendations for improving the credibility and reproducibility of undergraduate behavioral science research are offered

Modelling Dialogues for Optimal Legislation

International audienceThis paper presents a framework for modelling legislative deliberation in the form of dialogues. Roughly, in legislative dialogues coalitions can dynamically change and propose rule-based theories associated with different utility functions, depending on the legislative theory the coalitions are trying to determine. CCS CONCEPTS • Applied computing → Law, social and behavioral sciences; Law

Non-Equilibrium Social Science and Policy: Introduction and Essays on New and Changing Paradigms in Socio-Economic Thinking

The overall aim of this book, an outcome of the European FP7 FET Open NESS project, is to contribute to the ongoing effort to put the quantitative social sciences on a proper footing for the 21st century. A key focus is economics, and its implications on policy making, where the still dominant traditional approach increasingly struggles to capture the economic realities we observe in the world today - with vested interests getting too often in the way of real advances. Insights into behavioral economics and modern computing techniques have made possible both the integration of larger information sets and the exploration of disequilibrium behavior. The domain-based chapters of this work illustrate how economic theory is the only branch of social sciences which still holds to its old paradigm of an equilibrium science - an assumption that has already been relaxed in all related fields of research in the light of recent advances in complex and dynamical systems theory and related data mining. The other chapters give various takes on policy and decision making in this context. Written in nontechnical style throughout, with a mix of tutorial and essay-like contributions, this book will benefit all researchers, scientists, professionals and practitioners interested in learning about the 'thinking in complexity' to understand how socio-economic systems really work

Distributed and Interactive Simulations Operating at Large Scale for Transcontinental Experimentation

This paper addresses the use of emerging technologies to respond to the increasing needs for larger and more sophisticated agent-based simulations of urban areas. The U.S. Joint Forces Command has found it useful to seek out and apply technologies largely developed for academic research in the physical sciences. The use of these techniques in transcontinentally distributed, interactive experimentation has been shown to be effective and stable and the analyses of the data find parallels in the behavioral sciences. The authors relate their decade and a half experience in implementing high performance computing hardware, software and user inter-face architectures. These have enabled heretofore unachievable results. They focus on three advances: the use of general purpose graphics processing units as computing accelerators, the efficiencies derived from implementing interest managed routers in distributed systems, and the benefits of effective data management for the voluminous information

A technology pathway program in data technology and applications

With an exponential increase in user-generated data, there is a strong and increasing demand for employees possessing both technical skills and knowledge of human behavior. Supported by funds from the National Science Foundation Division of Undergraduate Education, we have begun to address this need by developing a technology pathway program in data technology and applications at a large, minority-serving public university. As part of this program, an interdisciplinary team of faculty created a new minor in Applied Computing for Behavioral and Social Sciences. A large number of diverse students are studying behavioral and social sciences, and the ability to model human behaviors and social interactions is a highly valuable skill set in our increasingly data-driven world. Applied Computing students complete a four-course sequence that focuses on data analytics and includes data structures and algorithms, data cleaning and management, SQL, and a culminating project. Our first full cohort of students completed the Applied Computing minor in Spring 2019. To assess the success of the minor, we conduct student surveys and interviews in each course. Here, we focus on survey data from the beginning and end of the first course, given that it served as a particularly important feedback loop to optimize the course and to inform the design and execution of subsequent courses. The data reflect a significant increase in confidence in programming abilities over time, as well as a shift in attitudes about programming that more closely matches those of experts. The data did not show a significant change in mindset over time, such that students maintained a growth mindset across the semester. Finally, with respect to goals, students placed a greater emphasis on data and tech at the end of the semester, highlighting specific career paths such as user experience and human factors. In the future, we plan to administer this same survey to social science students not involved in the minor to serve as a control group and to begin exploring the large dataset obtained from other courses in the minor. We believe that embedding computing education into the social sciences is a promising means of diversifying the technical workforce and filling the need for interdisciplinary computing professionals, as evidenced by high rates of female and underrepresented minority enrollment in our courses, as well as promising shifts in student confidence, attitudes, and career goals as a result of taking Applied Computing courses

Faculty Internationalization Perceptions: Comparing Disciplines

This project examined faculty internationalization perceptions at a medium-sized public university. In this phase of the project, the researchers focused on the potential differences between distinct faculty groups. The groups under review were based on the university\u27s academic schools of Arts & Letters, Aviation, Business, Computing, Education & Behavioral Sciences, and Health & Natural Sciences. Two sets of data were collected and analyzed. The first collection was exploratory in nature and was collected in the first quarter of 2020. The second dataset was meant to confirmatory and was collected in the fourth quarter of 2020. In hindsight, we now know that the first data gathering period was pre-COVID-19, while the second collection period was mid-COVID-19

TWENTY SOFTWARE REQUIREMENT PATTERNS TO SPECIFY RECOMMENDER SYSTEMS THAT USERS WILL TRUST

Trust has been shown as a crucial factor for the adoption of new technologies. Surprisingly, trust literature offers very little guidance for systematically integrating the vast amount of insights from behavioral research on trust into the development of computing systems. The aim of this article is to translate results from behavioral sciences into software requirement patterns that address user trust in recommender systems. Software requirement patterns are used in requirements engineering to recognize important and recurring issues and reduce the effort of compiling a list of software requirements. We collected antecedents that build trust, and developed software requirement patterns that demand functionality to support these antecedents. This paper contributes by presenting software requirement patterns consisting of the name, the goal and the pre-defined requirement template that can be used to specify trust requirements in recommender system development projects

Machine Understanding of Human Behavior

A widely accepted prediction is that computing will move to the background, weaving itself into the fabric of our everyday living spaces and projecting the human user into the foreground. If this prediction is to come true, then next generation computing, which we will call human computing, should be about anticipatory user interfaces that should be human-centered, built for humans based on human models. They should transcend the traditional keyboard and mouse to include natural, human-like interactive functions including understanding and emulating certain human behaviors such as affective and social signaling. This article discusses a number of components of human behavior, how they might be integrated into computers, and how far we are from realizing the front end of human computing, that is, how far are we from enabling computers to understand human behavior