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This chapter focuses on the state-of-the-art modeling approaches used in Intelligent Tutoring Systems (ITSs) and the frameworks for researching and operationalizing individual and group models of performance, knowledge, and interaction. We adapt several ITS methodologies to model team performance as well as individuals’ performance of the team members. We briefly describe the point processes proposed by von Davier and Halpin (2013), and we also introduce the Competency Architecture for Learning in teaMs (CALM) framework, an extension of the Generalized Intelligent Framework for Tutoring (GIFT) (Sottilare, Brawner, Goldberg, & Holden, 2012) to be used for team settings.

Past research has shown that forecast combination typically improves demand forecast accuracy even when only two component forecasts are used; however, systematic bias in the component forecasts can reduce the effectiveness of combination. This study proposes a methodology for combining demand forecasts that are biased. Data from an actual manufacturing shop are used to develop the methodology and compare its accuracy with the accuracy of the standard approach of correcting for bias prior to combination. Results indicate that the proposed methodology outperforms the standard approach.

The vast bulk of the discourse surrounding reproduction is centered on women. Yet, the rate of childlessness in the United Kingdom (and much of the world) is higher among men. Recently, there has been an increased focus on fatherhood and fathering in academia, policy, practice, and the general media. However, data on men who do not become fathers has been excluded and their experiences minimized and dismissed. Infertility research has shown that failure to achieve the high social status of parenthood has the similar effects on mental and physical health as a diagnosis of life-threatening illness. In this chapter, I will draw on two qualitative research studies to show how not achieving the pronatalist ideal of parenthood impacts on men’s identity, sense of self, behaviors, health and well-being and social networks across the life course. The workplace is an arena where people who do not fit socio-cultural norms and expectations are overtly and/or covertly stigmatized and discriminated against through policy, working practices and everyday interaction between groups and individuals. I will argue that failing to acknowledge men’s experience of non-reproduction has a significant impact on both individuals and institutions alike.

The impact of the “Great Recession” on inequality is unclear. Because the crises in the housing and stock markets and mass job loss affect incomes across the entire distribution, the overall impact on inequality is difficult to determine. Early speculation using a variety of narrow measures of earnings, income, and consumption yield contradictory results. In this chapter, we develop new estimates of income inequality based on “more complete income” (MCI), which augments standard income measures with those that are accrued from the ownership of wealth. We use the 1989–2007 Surveys of Consumer Finances, and also construct MCI measures for 2009 based on projections of assets, income, and earnings.

We investigate the level and trend in MCI inequality and compare it to other estimates of overall and “high incomes” in the literature. Compared to standard measures of income, MCI suggests higher levels of inequality and slightly larger increases in inequality over time. Several MCI-based inequality measures peaked in 2007 at their highest levels in 20 years. The combined impact of the Great Recession on the housing, stock, and labor markets after 2007 has reduced some measures of income inequality at the top of the MCI distribution. Despite declining from the 2007 peak, however, inequality remains as high as levels experienced earlier in the decade, and much higher than most points over the last 20 years. In the middle of the income distribution, the declines in income from wealth after 2007 were the result of diminished value of residential real estate; at the top of the distribution, declines in the value of business assets had the greatest impact.

We also assess the level and trend in the functional distribution of income between capital and labor, and find a rising share of income accruing to real capital or wealth from 1989 to 2007. The recent economic crisis has diminished the capital share back to levels from 2004. Contrary to the findings of other researchers, we find that the labor share of income among high-income groups declined between 1992 and 2007.

In this volume, we have studied the cyclical behavior of numerous business cycle indicators from the U.S. transportation sector and studied how they are related to those of the overall economy. Our study began with the conceptualization of what constitutes the transportation services sector, identifying relevant monthly indicators from the private sector and the government, and finally putting them together to construct a monthly measure of output of the transportation services sector. The challenge was to develop an indicator that will be available promptly soon after a month with other widely reported monthly indicators such as the index of industrial production, Institute for Supply Management (ISM) surveys, CPI, index of leading indicators, etc. and is not subject to much data revisions. Since monthly activity measures of major transportation services sectors such as trucking and railroads are produced by private membership organizations, use of these data in the production of official statistics in the public sector needed skillful persuasion of government officials. Bureau of Transportation Statistics (BTS) releases the preliminary number for the latest month and replaces the number for the oldest preliminary month with a revised number. All other revisions are held until an annual comprehensive revision of the transportation services output (TSI). It is gratifying to see that the arrangement of cooperation between the transportation department and these private service organizations are working out seamlessly, and TSI continues to get the media attention.

Self-report questionnaires are the predominant method used in human resource management (HRM) research to assess employees’ work-related psychological constructs (e.g., processes, states, and attributes). However, this method is associated with significant shortcomings, including the introduction of self-serving bias and common method variance when used exclusively. In this chapter, the authors challenge the assumption that individuals themselves are the only accurate source of the self-focused information collected in HRM research. Instead, the authors propose that other-ratings – ratings of a target individual that are provided by a workplace observer, such as a coworker, supervisor, or subordinate – can accurately assess commonly measured work-related psychological constructs. The authors begin by explaining the advantages of other-ratings for HRM research and practice, reviewing the history of other-ratings and how they emerged in the personality and person-perception literature, and outlining how they have been used in HRM research to date. Then, the authors build upon Funder’s (1995) realistic accuracy model to develop a theoretical argument detailing why workplace others should be able to accurately judge how another employee thinks and feels about work. Next, the authors highlight existing evidence in the literature on the accuracy of other-ratings and present the results of a preliminary meta-analysis on the ability of other-ratings to predict self-ratings of work-related psychological constructs. Finally, the authors discuss potential moderators of other-rating accuracy and reflect on a number of practical considerations for researchers looking to use other-ratings in their own work. The authors intend for this chapter to meaningfully contribute to the larger conversation on HRM research methods. Other-ratings are a simple, yet powerful, addition to the methodological toolkit of HRM researchers that can increase flexibility in research design and improve the overall quality of research.

This chapter describes five disciplinary domains of research or lenses that contribute to the design of a team tutor. We focus on four significant challenges in developing Intelligent Team Tutoring Systems (ITTSs), and explore how the five lenses can offer guidance for these challenges. The four challenges arise in the design of team member interactions, performance metrics and skill development, feedback, and tutor authoring. The five lenses or research domains that we apply to these four challenges are Tutor Engineering, Learning Sciences, Science of Teams, Data Analyst, and Human–Computer Interaction. This matrix of applications from each perspective offers a framework to guide designers in creating ITTSs.