An increase in demand for online education has led to the creation of a new technology, machine teachers, or artificial intelligence (AI) teaching assistants. In fact, AI teaching assistants have already been implemented in a small number of courses in the United States. However, little is known about how students will perceive AI teaching assistants. Thus, the present study investigated students' perceptions about AI teaching assistants in higher education by use of an online survey. Primary findings indicate that perceived usefulness of an AI teaching assistant and perceived ease of communication with an AI teaching assistant are key to understanding an eventual adoption of AI teaching assistant-based education. These findings provide support for AI teaching assistant adoption. Based on the present study's findings, more research is needed to better understand the nuances associated with the learning experience one may have from an AI teaching assistant.

Binge watching, or serial viewing of a single program over an extended period of time, is a relatively new norm in television viewing that is becoming more popular than traditional appointment viewing. Previous research has explored various influences on binge watching; however, the current research is unique in exploring theoretically and empirically grounded predictors of both binge watching frequency and duration of binge watching sessions by means of a survey administered to college undergraduates (N = 651). Data show that binge watching frequency and duration are predicted by two non-overlapping sets of variables. Binge watching frequency was predicted by low self-regulation, greater tendency to use binge watching as both a reward and a form of procrastination, and less regret; while binge watching duration was associated with being female and experiencing greater enjoyment while binging. Self-control did not predict either binge watching frequency or duration, suggesting that alternative theoretical models should be explored. Findings also suggest that scholars should reconceptualize binge watching by including both frequency and duration measures in future studies.

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The COVID-19 lockdown has transformed the way of life for many people. One key change is media intake, as many individuals reported an increase in media consumption during the COVID-19 lockdown. Specifically, social media and television usage increased. In this regard, the present study examines social TV viewing, the simultaneous use of watching TV while communicating with others about the TV content on various communication technologies, during the COVID-19 lockdown. An online survey was conducted to collect data from college students in the United States during the COVID-19 lockdown. Primary results indicate that different motives predict different uses of communication platforms for social TV engagement, such as public platforms, text-based private platforms, and video-based private platforms. Specifically, the social motive significantly predicts social TV engagement on most of the platforms. Further, the study finds that social presence of virtual co-viewers mediates the relationship between social TV engagement and social TV enjoyment. Overall, the study's findings provide a meaningful understanding of social TV viewing when physical social gatherings are restricted.

Background The digital divide refers to technological disparities based on demographic characteristics (eg, race and ethnicity). Lack of physical access to the internet inhibits online health information seeking (OHIS) and exacerbates health disparities. Research on the digital divide examines where and how people access the internet, whereas research on OHIS investigates how intersectional identities influence OHIS. We combine these perspectives to explicate how unique context–device access pairings operate differently across intersectional identities—particularly racial and ethnic groups—in the domain of OHIS. Objective This study aims to examine how different types of internet access relate to OHIS for different racial and ethnic groups. We investigate relationships among predisposing characteristics (ie, age, sex, education, and income), internet access (home computer, public computer, work computer, and mobile), health needs, and OHIS. Methods Analysis was conducted using data from the 2019 Health Information National Trends Survey. Our theoretical model of OHIS explicates the roles of internet access and health needs for racial and ethnic minority groups’ OHIS. Participant responses were analyzed using structural equation modeling. Three separate group structural equation modeling models were specified based on Black, Latine, and White self-categorizations. Results Overall, predisposing characteristics (ie, age, sex, education, and income) were associated with internet access, health needs, and OHIS; internet access was associated with OHIS; and health needs were associated with OHIS. Home computer and mobile access were most consistently associated with OHIS. Several notable linkages between predisposing characteristics and internet access differed for Black and Latine individuals. Older racial and ethnic minorities tended to access the internet on home and public computers less frequently; home computer access was a stronger predictor of OHIS for White individuals, and mobile access was a stronger predictor of OHIS for non-White individuals. Conclusions Our findings necessitate a deeper unpacking of how physical internet access, the foundational and multifaceted level of the digital divide, affects specific racial and ethnic groups and their OHIS. We not only find support for prior work on the digital divide but also surface new insights, including distinct impacts of context–device access pairings for OHIS and several relationships that differ between racial and ethnic groups. As such, we propose interventions with an intersectional approach to access to ameliorate the impact of the digital divide.

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