Buildup of speaking skills in an online learning community: a network-analytic exploration

Abstract

Studies in learning communities have consistently found evidence that peerinteractions contribute to students' performance outcomes. A particularly important competence in the modern context is the ability to communicate ideas effectively. One metric of this is speaking, which is an important skill in professional and casual settings. In this study, we explore peer-interaction effects in online networks on speaking skill development. In particular, we present an evidence for gradual buildup of skills in a small-group setting that has not been reported in the literature. Evaluating the development of such skills requires studying objective evidence, for which purpose, we introduce a novel dataset of six online communities consisting of 158 participants focusing on improving their speaking skills. They video-record speeches for 5 prompts in 10 days and exchange comments and performanceratings with their peers. We ask (i) whether the participants' ratings are affected by their interaction patterns with peers, and (ii) whether there is any gradual buildup of speaking skills in the communities towards homogeneity. To analyze the data, we employ tools from the emerging field of Graph Signal Processing (GSP). GSP enjoys a distinction from Social Network Analysis in that the latter is concerned primarily with the connection structures of graphs, while the former studies signals on top of graphs. We study the performance ratings of the participants as graph signals atop underlying interaction topologies. Total variation analysis of the graph signals show that the participants' rating differences decrease with time (slope = −0.04, p < 0.01), while average ratings increase (slope = 0.07, p < 0.05)-thereby gradually building up the ratings towards community-wide homogeneity. We provide evidence for peer-influence through a prediction formulation. Our consensus-based prediction model outperforms baseline network-agnostic regression models by about 23% in predicting performance ratings. This in turn shows that participants' ratings are affected by their peers' ratings and the associated interaction patterns, corroborating previous findings. Then, we formulate a consensus-based diffusion model that captures these observations of peerinfluence from our analyses. We anticipate that this study will open up future avenues for a broader exploration of peer-influenced skill development mechanisms, and potentially help design innovative interventions in small-groups to maximize peer-effects.

Creativity in temporal social networks: how divergent thinking is impacted by one’s choice of peers

“…Given an objective, they can choose to make or break ties to update the connectivity patterns around them [10], often in response to the behaviour, performance, prestige, age, gender, popularity, self-similarity and other cues of the social partners [11][12][13]. This dynamic characteristic affords opportunities in human populations that static networks cannot: for example, dynamic networks promote cooperation [14,15], collective intelligence [16], and speaking skills [17], among others.…”

Synchronous Arabic Learning Based on Sociocultural Theory: New Trends in Arabic Learning at University

“…This is also a statement of innovation in Arabic teaching that does not leave efforts to improve each student's competence. In line with (Shafipour et al, 2018) that an essential competency in modern learning is communicating ideas effectively, characterized by developing skills through cognitive maturity.…”

“…This is also a statement of innovation in Arabic teaching that does not leave efforts to improve each student's competence. In line with(Shafipour et al, 2018) that an essential competency in modern learning is communicating ideas effectively, characterized by developing skills through cognitive maturity.The practice of teaching Arabic in sync with video conferencing has shifted the teaching process that is bound by location and time. This practice is a breakthrough in that teaching is easy to implement and develop anywhere, anytime, and throughout life, even without leaving the house and not crossing cities and borders countries(Dubskikh et al, 2019).…”

Creativity in social networks is enhanced by 'Goldilocks' dispersal of ideators' visibility

“…The examples illustrate that despite being an individual strength, creativity benefits strongly from the social stimulation of ideas. Our social embeddings exert a strong influence on the creative inspirations we find, just as it does on the information we receive, the decisions we make, and even the beliefs we hold 3,4 . Question is, in a self-organizing social system, what kind of connection structure can best support the aggregate collection of creative ideas?…”