Correlating Formal Assessment with Social Network Activity within a Personal Learning Environment

Correlating Formal Assessment with Social Network Activity within a Personal Learning Environment

Eleni Koulocheri, Michalis Xenos
DOI: 10.4018/IJWLTT.2019010102
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Abstract

Social networks have undoubtedly penetrated into our daily life, in such a degree that educational life could not avoid this effect, as proven by the many education-oriented social networks that have emerged. The education-oriented social network environment named HOU2LEARN, used by the Hellenic Open University, is one of these networks, providing a valuable source of data about students' networking behavior and their tensions. This article aims at contributing to the investigation of possible linkages between social network behavior and student performance as assessed within a formal learning environment. The article is focused on analyzing data and performing statistical correlations from two consecutive and recent academic years in a computer science course, attempting to reach robust conclusions. Although the research question remains the same: Is there a relationship between grades and social activity within the social network? This article is supported by increased sampling and data, providing concrete and intriguing answers, thus setting the pillars for further research goals regarding contemporary and smart learning environments.
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From Learning Analytics To Social Network Analysis

Analytics is a term used in business and science to refer to computational support for capturing digital data to help assist in decision-making, while learning analytics (LA) is a relatively recent term (coined during the 1st International Conference on Learning Analytics and Knowledge, 2011) and refers to the collection and analysis of digital traces that every learner leaves. According to (Buckingham, 2012) LA appropriates the concept of analytics for education: “what should a digital nervous system look like when the focus is on learning outcomes, and to extend the metaphor, what kind of ‘brain’ or collective intelligence is needed to interpret the signals and adapt the system’s behavior accordingly?”

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