Gesture’s role as a powerful and versatile tool for instruction, especially in STEM domains, is well-established. However, many specific teaching moves accomplished through gesture remain understudied. Using interaction analysis, we examine how an introductory. university physics instructor uses gesture during whole-class discussion of graphical representations of energy conservation to synthesize multiple student groups’ solutions. This embodied, whole-class discussion orchestration move distills and summarizes the key points of the lesson while highlighting student contributions and addressing misunderstandings.

Gestures play a key role for physicists and physics students in representing physics entities, processes, and systems. One affordance of gesture is the ability to laminate or layer together representations of concrete physical features (e.g., objects and their interactions) and symbolic representations (e.g., coordinate systems) to make sense of and model physical scenarios. Using interaction analysis, we illustrate how students can laminate these different layers of abstraction together in gesture to generate complex explanations to solve physics problems. We argue that laminating different layers of abstraction (both the symbolic and concrete) constitute a key form of representational competence in physics.

Social interactions, particularly parent-child conversations, play a critical role in children’s early learning and pre-academic skill development. While these interactions are bidirectional, complex, and dynamic, much of the research in this area tends to separate speakers’ talk and capture the frequency of words or utterances. Beyond the aggregation of talk exists rich information about conversational structures and processes, such as the extent to which speakers are aligned or reciprocate each other’s talk. These measures can be derived using categorical cross-recurrence quantification analysis (CRQA), a method that quantifies the temporal structure and co-visitation of individual and sequential events, e.g., utterances between speakers. In this paper, we present an application of CRQA, following the protocol described in our tutorial paper (Duong et al., 2024, this issue), to describe alignment in parent-child conversations about numbers and math (i.e., number talk). We used the ‘crqa’ package in R and the code used in this application is available in the Supplemental Materials. Further, the CRQA measures derived from this application were compared to traditional frequency measures of talk, i.e., counts of utterances, in the prediction of children’s math skills. Overall, we showed that (1) CRQA can be applied to existing transcription data to uncover theoretically-driven patterns of parent-child talk that are not captured by common frequency measures and (2) these CRQA measures offer additional, rich information about interactions beyond frequencies of talk and can be used to predict individual differences in children’s math skills. (PsycInfo Database Record (c) 2024 APA, all rights reserved)

Social interactions are defined by the dynamic and reciprocal exchange of information in a process referred to as mutual alignment. Statistical methods for characterizing alignment between two interacting partners are emerging. In general, they exploit the temporal organization of dyadic interactions to uncover the effect of one partner on the other and the extent to which partners are aligned. This paper describes and provides a tutorial on one such method, categorical cross recurrence quantification analysis (CRQA), which quantifies the temporal structure and co-visitation of individual and sequential states of interest. CRQA is a useful descriptive technique that can be used to explore the extent, structures, and patterns of partner alignment within dyadic interactions. We provide a brief technical introduction to CRQA and a tutorial on its application to understanding parent-child linguistic interactions using the ‘crqa’ package in R (Coco, Monster, Leonardi, Dale, & Wallot, 2021). (PsycInfo Database Record (c) 2024 APA, all rights reserved)

With the passage of the Chips and Science Act, semiconductor workforce development has become front and center for US universities. Among the many skills needed for undergraduates to enter the semiconductor industry, debugging is an important skill that is rarely taught. As the transistor count and complexity of today’s chips grow, thanks to Moore’s Law, fewer new chips can work perfectly for the first time. Hence, much engineering effort is put into debugging, a process that identifies and fixes any discrepancies between the expected and measured chip behavior. This paper first investigates the need and the economic incentives of debugging in the semiconductor industry. It was estimated that a typical semiconductor project spent 35 to 50 percent of its time in debugging. The need for silicon debugging has led to a new profession called validation engineers. Debugging has also gained the nickname of the Schedule Killer, highlighting its impact on the project schedule and the company’s bottom line. Next, the paper summarizes existing cognitive models of troubleshooting. Early models often failed to capture the role of experience, which was essential for circuit and hardware debugging. Jonassen et al. proposed a troubleshooting learning architecture that includes the contribution of past experiences. This cognitive framework has been successfully applied in computer science and physics education, leading to some of the latest pedagogy innovations, such as collaborative pair debugging. This paper also investigates multiple emotions associated with debugging, such as frustration, fear, and anxiety. These emotions may lead to disengagement and avoidance of the subjects. Debugging may also be related to other non-cognitive factors, such as mindsets. The positive effect of teaching self-theory and a growth mindset has been observed in different age groups. However, studies also found that domain-specific aptitudes were more helpful in changing student’s performance in the subject matter. The takeaway message from this paper is that a genuinely effective debugging education intervention must be holistic and domain-specific. Holistic means that the intervention should address both cognitive and affective components. Domain specificity means that any growth mindset message should be contextually situated within the subject matter materials. How to design such an intervention will be the next million-dollar question, as it not only fills the gap of collegiate debug education in microelectronics but also serves as a critical missing piece toward developing a globally competent semiconductor workforce for generations to come.

The construction industry has been a predominantly White/Caucasian Men community with a very low representation of women and people from traditionally marginalized backgrounds. Even though companies have been implementing Diversity, Equity, and Inclusion (DEI) statements for many years, we still believe it is neither a diverse nor equitable field. To better understand how DEI statements declared by companies have been understood and recognized by employees, a survey was deployed nationwide to understand how professionals in the construction industry perceive their organization's DEI statements or policies. A complete data set was built from 249 participants. 75% identified themselves as men and 25% as women, and nobody identified with other gender identities. More than 80% of participants were White/Caucasian, 4% Black or African American, 4% Hispanic or Latinx, and 6% Asian. Participants are currently working in small (24%), medium (30%), and large (46%) construction and design companies located across The United States. Regarding the number of employees, companies are small, less than 99 employees; medium, between 100 and 499 employees; and large, more than 500 employees. Also, companies were grouped into four main types, building construction companies (67%), transportation construction companies (6%), special trade contractor companies (17%), and design companies (10%). For more than 65% of professionals in the construction industry who participated in this study, DEI was mainly related to proper representation of women and minoritized populations in the workforce; Merit-based transparent recruitment and promotion; equality, social justice, and nondiscrimination policy statement; and equitable payment and compensation. Other factors such as proper representation of women and minoritized populations at the top management level and payment structure transparency did not emerge from the results. We also found that 70% of professionals identified DEI statements in their companies and 30% of professionals did not identify or did not know about DEI statements. Looking at the company size, 85% of professionals in large companies identified DEI statements in their companies, but 71% and 42% of professionals in medium and small companies identified DEI statements in their companies, respectively. According to the company type, more than 80% of professionals working in design companies recognized DEI statements in their companies, but around 60% in construction and special trade companies. We can highlight that large companies have established policies and practices that result in better socialization and recognition of their DEI statements than medium and small companies. Also, construction and special trade companies need to strengthen their DEI statements and increase the representation of women and people from traditionally marginalized backgrounds. Results from this research give an idea about the current state of DEI in the construction industry and would contribute to the current effort to increase the diversity of the nation's construction workforce.