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This article presents a simple and easily implementableBayesian approach to model and quantify uncertainty insmall descriptive social networks. While statistical methodsfor analyzing networks have seen burgeoning activity overthe last decade or so, ranging from social sciences to genetics,such methods usually involve sophisticated stochasticmodels whose estimation requires substantial structure andinformation in the networks. At the other end of the analyticspectrum, there are purely descriptive methods based uponquantities and axioms in computational graph theory. In socialnetworks, popular descriptive measures include, but arenot limited to, the so called Krackhardt’s axioms. Anotherapproach, recently gaining attention, is the use of PageRankalgorithms. While these descriptive approaches provide insightinto networks with limited information, including smallnetworks, there is, as yet, little research detailing a statisticalapproach for small networks. This article aims to contributeat the interface of Bayesian statistical inference andsocial network analysis by offering practicing social scientistsa relatively straightforward Bayesian approach to accountfor uncertainty while conducting descriptive social networkanalysis. The emphasis is on computational feasibility andeasy implementation using existing R packages, such as snaand rjags, that are available from the Comprehensive RArchive Network (https://cran.r-project.org/). We analyzea network comprising 18 websites from the US and UK todiscern transnational identities, previously analyzed usingdescriptive graph theory with no uncertainty quantification,using fully Bayesian model-based inference.

This essay challenges conventional understandings of how research methods courses are taught in the social sciences and the humanities. Currently, students in American Universities are trained in techniques on how to conduct and disseminate research. While these skills are essential, we argue that, as educators, we need to teach students to recognize that the research process does not simply entail method, logic and reason. It begins with the self and with the assumption that emotions have a place in higher education. By using what we call Compassionate Research as a model, we contend that our humanity becomes the point of entry into the world of research. This pedagogical model relies on three interconnected principles, namely the abilities to question, self-question, and empathize. Its implementation in the classroom helps to foster culturally sensitive research and to promote self-awareness that translates into meaningful interactions with our communities.

Many studies have examined the effects of technology on education as well as how educators feel about technology; however, this study examined the opinions of 528 students regarding how technology influences their education. In particular, we investigated whether students felt a sense of entitlement to use their technology in the classroom. The results revealed that almost all students owned personal devices, and many used them during class for both course-related and unrelated purposes. In total, 33.1% of the respondents admitted that using technology during class is distracting, but they still felt they had the right to use their devices during lectures.

Technology is both extolled as an amazing educational tool and disliked as a pestilence that severely impairs learning. While in reality the impact of technology probably lies somewhere in between these two extreme views, it is helpful to consider the arguments from both sides to guide incorporation of technology in classrooms of the future. Five debates about the impact of technology in classrooms are discussed: whether technology enhances or diminishes academic performance, whether multi- or mono-tasking is optimal for tech-savvy students, whether technology isolates or brings people together, whether it is better to ban or train students on classroom technology use, and whether or not old teaching practices need to be updated to incorporate technology. [ABSTRACT FROM AUTHOR]