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Student engagement is a key factor that connects with student achievement and retention. This paper aims to identify individuals' engagement automatically in the classroom with multimodal data for supporting educational research.

The video and electroencephalogram data of 36 undergraduates were collected to represent observable and internal information. Since different modal data have different granularity, this study proposed the Fast–Slow Neural Network (FSNN) to detect engagement through both observable and internal information, with an asynchrony structure to preserve the sequence information of data with different granularity.

Experimental results show that the proposed algorithm can recognize engagement better than the traditional data fusion methods. The results are also analyzed to figure out the reasons for the better performance of the proposed FSNN.

This study combined multimodal data from observable and internal aspects to improve the accuracy of engagement detection in the classroom. The proposed FSNN used the asynchronous process to deal with the problem of remaining sequential information when facing multimodal data with different granularity.

Hazel Kyrk, one of the first women economists at the Economic Department of the University of Chicago and author of A Theory of Consumption (1923), conducted groundbreaking research for the Bureau of Home Economics of the US Department of Agriculture and the Bureau of Labor Statistics. Kyrk made a considerable contribution to the development of standards for a “decent living,” the Consumer Price Index, and the conceptualization of what would later turn into the definition of the poverty line. This chapter evaluates Kyrk’s use of eugenic notions of gender and race that were widely used in Kyrk’s day. This chapter shows that eugenic reasoning impacts Kyrk’s theoretical work only superficially but does structure her research on consumption standards through her focus on the white middle-class family as the unit of analysis for consumer behavior. This chapter also makes clear that the American Institutionalist approach to consumer behavior, rather than marginalized and side-tracked due to a lack of theoretical progress, was relegated to the margins of economics science together with the research of women economists into Home Economics departments and policy research at government institutions.

This study aims to identify the origins, mechanisms and outcomes of applying behavioral insight in public policy research.

The authors conducted a systematic literature review to answer three research questions. The authors identified 387 primary studies, dated from January 2000 to April 2021 and coded them through a thematic analysis. Related studies were obtained through searching in Emerald, ScienceDirect, Sage, Springer, Wiley and Routledge.

The results identified eight themes for origins, 16 themes for mechanisms/techniques and 13 outcome-related themes. Through the thematic analysis, the major mechanisms of behavioral approach were found to be social marketing, information provision, social norms, incentives, affect, regulation design, framing, salience, defaults, simplification, networking, environment design, scheduled announcements, commitments, attitude-preference-behavior manifestation and combining behavioral and nonbehavioral mechanisms.

The findings of this review help policymakers to design or redesign policy elements.

This review provides the first systematic exploration of the existing literature on behavioral public policy.

This paper aims to challenge the fashion of ubiquitous artificial intelligence (AI) and the effects which it will have upon society. In doing so it argues that the effects of AI will be minimal but important.

This argument is based upon the Socratic method and explores the Utilitarian background in which AI is based while drawing upon classical literature and other examples to illustrate the argument.

The findings are encompassed in the argument and show that we need to be more open and careful when considering AI and its effects. We also need to be more realistic when considering potential benefits.

This argument has significant implications for the adoption of AI.

The social implications are equally profound and will impact upon our application of AI solutions to current problems and upon humanity more generally.

This is the first paper which relates AI to human successes.