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There has been a conscious effort in the past decade to produce a more theoretical account of the use of technology for learning. At the same time, advances in artificial intelligence (AI) are being rapidly incorporated into learning technologies, significantly changing their affordances for teaching and learning. In this article I address the question of whether introduction of AI and associated features such as machine learning is a novel development from a theoretical perspective, and if so, how? I draw on the existing perspective of sociomateriality for learning and argue that the use of AI is indeed different because AI transforms sociomateriality by allowing materiality to take on characteristics previously associated primarily with a human agent, thereby shifting the nature of the sociomaterial assemblage. In this data and algorithm-driven AI-based sociomateriality, affordances for representation and agency change, thereby modifying representational and relational practices that are essential for cognition. The dualities of data/algorithm, representational/agentic augmentation, and relational/participatory practices act in tandem within this new sociomaterial assemblage. If left unchecked, this new assemblage is prone to perpetuate the biases programmed within the technology itself. Therefore, it is important to take ethical and moral implications of using AI-driven learning technologies into account before their use.

The use of social media across the educational landscape is on the rise. Subsequently, the body of research on this topic is vibrant and growing. In this article, we present findings from a review of 103 peer-reviewed scientific studies published over the last decade (2007–2017) that address the use of Twitter for educational purposes across formal and informal settings. The majority of the studies reported in the literature are descriptive case studies carried out with students in North American and European higher education settings. Analysis of these studies signals Twitter as a useful tool for communication due to high accessibility, novelty, and real-time format. Students, teachers, and other stakeholders use it as a pedagogical tool to gain information, interact and engage with each other, participate in their respective communities of interests, and share their insights about specific topics. Moreover, Twitter has the potential to enhance students’ learning capabilities as well as improve their motivation and engagement due to its unique features and non-traditional teaching approach. Finally, our analysis advocates for carrying out further empirical studies focusing on digital trace data and inference, particularly in the developing countries.

The purpose of this study is to provide insights into player experiences and motivations in Pokémon Go, a relatively new phenomenon of location-based augmented reality games. With the increasing usage and adoption of various forms of digital games worldwide, investigating the motivations for playing games has become crucial not only for researchers but for game developers, designers, and policy makers. Using an online survey (N = 1190), the study explores the motivational, usage, and privacy concerns variations among age and gender groups of Pokémon Go players. Most of the players, who are likely to be casual gamers, are persuaded toward the game due to nostalgic association and word of mouth. Females play Pokémon Go to fulfill physical exploration and enjoyment gratifications. On the other hand, males seek to accomplish social interactivity, achievement, coolness, and nostalgia gratifications. Compared to females, males are more concerned about the privacy aspects associated with the game. With regard to age, younger players display strong connotation with most of the studied gratifications and the intensity drops significantly with an increase in age. With the increasing use of online and mobile games worldwide among all cohorts of society, the study sets the way for a deeper analysis of motivation factors with respect to age and gender. Understanding motivations for play can provide researchers with the analytic tools to gain insight into the preferences for and effects of game play for different kinds of users.

PurposeThe current study aims to investigate if different measures related to online psychosocial well-being and online behavior correlate with social media fatigue.Design/methodology/approachTo understand the antecedents and consequences of social media fatigue, the stressor-strain-outcome (SSO) framework is applied. The study consists of two cross-sectional surveys that were organized with young-adult students. Study A was conducted with 1,398 WhatsApp users (aged 19 to 27 years), while Study B was organized with 472 WhatsApp users (aged 18 to 23 years).FindingsIntensity of social media use was the strongest predictor of social media fatigue. Online social comparison and self-disclosure were also significant predictors of social media fatigue. The findings also suggest that social media fatigue further contributes to a decrease in academic performance.Originality/valueThis study builds upon the limited yet growing body of literature on a theme highly relevant for scholars, practitioners as well as social media users. The current study focuses on examining different causes of social media fatigue induced through the use of a highly popular mobile instant messaging app, WhatsApp. The SSO framework is applied to explore and establish empirical links between stressors and social media fatigue.

Johri explains that institutions must carefully consider decisions to give up data and flexibility to digital platforms. After two years of uncertainty, it is starting to look like higher education institutions (HEIs) are entering a post-pandemic reality. Among all their adaptations to get through the pandemic, the increased reliance on technology is one that is certain to endure. It is possible they would have reached this level of technological dependence at some future stage, but the acceleration necessitated by the pandemic has brought changes with a speed and in ways they could not have anticipated. One of the primary drivers of technology adoption across higher education has been the use of digital platforms. Within academia, platform use is now routine for communication and information sharing (Zoom, Microsoft Teams); learning management (Moodle, Blackboard, Sakai); and functions such as HR, financial aid, and alumni engagement (Ellucian, Salesforce, or TargetX).

Although the use of digital information technologies in education has becomecommonplace, there are few, if any, central guiding frameworks or theories thatexplicate the relationship between technology and learning practices. In thispaper, I argue that such a theoretical framework can assist scholars and practitionersalike by working as a conduit to study and design learning technologies.Towards this goal, I propose socio-materiality as a key theoretical construct withvaluable insights and implications for the field of learning technology. Sociomaterialityhelps balance the disproportionate attention given to either the socialimplications of technology use or the material aspects of technology design.Furthermore, I forward ‘socio-material bricolage’ as a useful analytical frameworkto examine and design technology-infused learning environments. I illustratethe value of the framework by applying it to three case studies of formaland informal technology-based learning.

Hate is rising against Asians--Asian Americans, Americans of Asian descent, and Asian immigrants--across the US. Among the broader population of Asians who live here are those, like Johri, who arrived as immigrants and exist in the microcosm of academia and, within that, in engineering schools. It is through this lived experience that he stresses that anti-Asian views leading to the recent spike in violence have also manifested themselves as prejudice, bias, discrimination, and, at best, neutrality in academia for decades. His trajectory, like that of many Asians in engineering, can be traced back to the 1965 removal of the national origin-based quota system for immigration. Post-World War II, US engineering schools had developed an outstanding reputation worldwide and, in combination with a law that allowed non-Western immigrants to enter America, universities were able to attract the brightest minds from Asia through scholarship offers.