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This essay stages an encounter between surveillance studies and the sociology of price and price formation. I argue that surveillance is integral to the calculative operations of retail price strategies, especially during periods of high inflation, and that these calculative operations hinge on the human infrastructure of a precarious data-collecting workforce. I present my argument through a case study of competitor price monitoring, a corporate surveillance practice in which commercial actors record, process, and transmit information on competitors’ pricing, inventory, and display strategies. While pricing intelligence services like web-scraping and dynamic pricing algorithms are typically applied in e-commerce settings, I focus here on a firm that specializes in the collection of brick-and-mortar retail price data, with special attention to the labor practices involved in the manual (in-person, device-aided) production of retail price information at the national-industrial scale. Building on auto-ethnographic observations as a price data collector as well as analysis of employee reviews of the firm on sites like Indeed and Glassdoor, I argue that surveillance studies can contribute in significant ways to our understanding of the material practices, and politics, of price and price formation.

Keywords: calculating price, intelligence services, price data collector, Indeed, Glassdoor

Many post-secondary institutions are developing policies and programs aimed at improving responses to sexual assault experienced by students. In some areas, such as Ontario, Canada, the government has mandated post-secondary institutions to do so. However significant these initiatives, they are predicated on the assumption that students trust, and want to engage with, the university following sexual violence. This study explores students’ perceptions of sexual assault policies and services on one mid-size university campus focusing specifically on how trust factors into reporting sexual victimization and using services. Findings show that students believe that sexual assault policies and programs exist, but this does not meanstudents are willing to use such resources or that they even trust that their university has students’ needs and interests at the fore. This paper discusses policy and programmatic considerations for building student trust in their post-secondary institutions to encourage student use of campus support.

In education, the integration of artificial intelligence (AI) has presented opportunities to transform the dynamics of online learning. This study investigated the impact of an AI-powered application, namely ChatGPT, on the autonomy of Saudi Arabian primary students participating in online classes. It also explored how the implementation of Chat GPT influenced Saudi Arabian primary students’ autonomy. In this mixed-methods study, a quasi-experimental design assessed the impact of ChatGPT on learner autonomy among 250 Saudi Arabian primary students from six primary schools in Riyadh, Saudi Arabia. The quantitative analysis employed descriptive statistics and t-tests, while the qualitative data underwent interpretative phenomenological analysis. To ensure coding reliability, 20% of the codes were independently reviewed by an external coder, with a 94% inter-coder agreement coefficient reached through consensus. Findings revealed that ChatGPT significantly affected the participants’ perceptions of autonomy and its different dimensions. Qualitative data showed that AI-powered applications contributed to the students’ autonomy in 10 different ways. Participants also mentioned that AI-powered apps might have some negative consequences. This study has theoretical implications for redefining learner autonomy in the digital age and calls for the exploration of many facets of autonomy. Practical applications from this study include strategic integration of AI into online education, data security, and the need for orientation programs.

Keywords: AI-powered applications, ChatGPT, students' autonomy, online classes, students' perceptions

The transformative impact of advancements in educational technology, particularly those powered by artificial intelligence (AI), on the landscape of education and the teaching profession has been substantial. This study explores the repercussions of AI-powered technologies on teachers’ autonomous behavior, digital burnout, and professional development. The study involved a cohort of 320 high school teachers in China segregated into control and experimental groups. The experimental group received instructions on AI-integrated applications and how they might be used in education. However, the teachers assigned to the control group did not receive information on the use of AI educational applications. Three distinct questionnaires probing autonomous behaviors, digital burnout, and online professional development were administered, and the ensuing data were analyzed using independent sample t-tests. The findings elucidate a discernible positive impact of AI-integrated technology intervention on teachers’ professional development and autonomous behaviors. The incorporation of AI-enhanced tools facilitated an augmentation in teachers’ professional growth and bolstered their independent and self-directed instructional practices. Notably, using AI-integrated technology significantly reduced teachers’ susceptibility to digital burnout, signifying a potential alleviation of stressors associated with technology-mediated teaching. This research provides valuable insights into the multifaceted effects of AI-powered technologies on educators, shedding light on enhancing professional competencies and mitigating digital burnout. The implications extend beyond the confines of this study, resonating with the broader discourse on leveraging technology to augment the teaching profession and optimize the learning environment.

Keywords: artificial intelligence, AI, AI applications, teacher autonomy, online professional development, digital burnout

This study proposes a hypothetical model combining the unified theory of acceptance and use of technology (UTAUT) with self-determination theory (SDT) to explore design professionals’ behavioral intentions to use artificial intelligence (AI) tools. Moreover, it incorporates job replacement (JR) as a moderating role. Chinese-speaking design professionals in regions influenced by Confucian culture were surveyed. An analysis of 565 valid cases with AMOS (Analysis of Moment Structures) supported the structural model hypothesis. The model explains 52.1% of the variance in behavioral intention to use (BIU), proving its effectiveness in explaining these variances. The results further validate the importance of performance expectancy (PE) over effort expectancy (EE) in influencing BIU. Additionally, it has been shown that the impact on intrinsic motivation (IM) and extrinsic motivation (EM) can be either amplified or diminished by anxiety about JR. For individuals experiencing higher levels of JR anxiety, there is a marked increase in IM. They may perceive adopting AI tools as an opportunity to enhance their skills and job security. Conversely, this anxiety also significantly boosts EM, as the potential for improved efficiency and productivity with AI use becomes a compelling incentive. These findings suggest new paths for academic researchers to explore the psychological impacts of AI on design professionals’ roles. For practitioners, especially in human resources and organizational development, understanding these dynamics can guide the creation of training programs that address job replacement anxiety.

Keywords: unified theory of acceptance and use of technology, UTAUT, self-determination theory, generative artificial intelligence, GenAI, job replacement, performance expectancy

Artificial intelligence (AI) revolutionizes education by fundamentally altering the methods of teaching and processes of learning. Given such circumstances, it is essential to take into account the mental and psychological well-being of teachers as the architects of education. This research investigated the links between teacher immunity (TI), work passion (WP), job satisfaction (JS), occupational well-being (OW-B) and psychological well-being (PW-B) in the context of AI-assisted language learning. In order to achieve this objective, 392 Iranian teachers of English as a foreign language (EFL) were given the Language Teacher Immunity Instrument, the Work Passion Scale, the Job Satisfaction Questionnaire, the Occupational Well-Being Scale, and the Psychological Well-Being at Work Scale. By using confirmatory factor analysis and structural equation modeling, the study identified and quantified the impacts of TI, WP, JS, OW-B, and PW-B via data screening. The findings emphasize the crucial role that TI and WP play in providing a balance in teachers’ JS, OW-B, and PW-B while applying AI in their language instruction. The broad ramifications of this research are explored.

Keywords: AI-assisted language teaching, teacher productive immunity, work passion, job satisfaction, occupational success, psychological well-being, EFL teacher

While research has been done to identify the potential implications of biometric technology on marginalized populations’ privacy and autonomy, this paper contributes to existing research by examining these technologies in healthcare settings. Drawing from insights across surveillance studies, rhetoric of health and medicine, and technical communication, we identify how one leading healthcare institution in New York City has employed rhetorics of efficiency, effectiveness, safety, and security regarding its biometric technology system. This employment of biometric technologies often contributes to patients’ marginalization and dismissal. As we explore, interrogating the language used by the healthcare institution to describe biometrics opens opportunities for us—surveillance studies scholars, patients, allies, students, and more—to ensure that innovations within the healthcare system promote equity, agency, and improved outcomes for all.

Keywords: biometric technologies, patient advocacy, informed consent, privacy, health communication

Teaching for social justice is an explicit goal of most teacher education programs. However, this mandate has been criticized by scholars who claim that social justice is an undertheorized and vague concept that is often disconnected from methods courses that focus on content-specific pedagogies. This study seeks to address this disconnect by exploring how an Equity Literature Circles (ELC) framework within a literacy methods course can enhance teacher candidates’ (TCs’) understanding of the relationship between literacy instruction, diversity, and social justice. Drawing on the perceptions of ten TCs enrolled in a teacher education program in western Canada, data for the study was generated from classroom artifacts, an individual survey, and a focus group interview. Upon analysis of the data, the findings suggest that an ELC framework is an effective instructional strategy for enhancing TCs’ understanding of intersecting aspects of diversity, equity-focused literacy instruction, and teaching about and for social justice.

Keywords: Equity Literature Circles, Literacy as Social Practices, social justice education, intersectionality, Diversity, young adult novel, Critical Literacy/Pedagogy, language arts classroom, preservice teacher education