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Learning Object Context Ontologies

A solid explanation of learning in a connectivist mindset.

A data analysis service for the learning science community

Along with about 400 or so others world-wide, I've signed up for the LAK11 (Learning and Knowledge Analytics) MOOC run by George Siemens and colleagues at the Technology Enhanced Knowledge Research Institute (TEKRI) at Athabasca University. We're now into week 2, and I think I'm just about getting into the swing of things.

As the integration of community-centred teaching practices intensifies, an understanding of the types of relationships that manifest in this network and the associated impact on student learning is required. This paper explores the relationship between a student's position in a classroom social network and their reported level of sense of community. Quantitative methods, such as Rovai's (2002b) Classroom Community Scale and social network centrality measures, were incorporated to evaluate an individual's level of sense of community and their position within the classroom social network. Qualitative methods such as discussion forum content analysis and student interviews were adopted to clarify and further inform this relationship. The results demonstrate that the centrality measures of  closeness and  degrees are positive predictors of an individual's reported sense of community whereas,  betweenness indicates a negative correlation. Qualitative analyses indicate that an individual's pre-existing external social network influences the type of support and information exchanges an individual requires and therefore, the degree of sense of community ultimately experienced. The paper concludes by discussing future recommendations for teaching practices incorporating computer-mediated communications. 

Presentation slides from the January 25 session with Dragan Gasevic

sharing and communicating

There are plenty of reasons to be skeptical about the BD market. But big data probably deserves a place in overall enterprise IT strategy for generating business insight. Best practices include generating a list of important challenges or questions that the current approach to data does not address. Could big data deliver the answers enterprises are looking for? If so, then it's all about discipline. A disciplined, targeted approach to big data - one focused on answering very specific questions. (my emphasis - I'll get to those later)

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"This study analyzes the outcomes at more than 380 higher education institutions. It looks at what the chosen strategies have accomplished, in what ways institutions use the data they collect, whether institutions are investing more resources in tools that enable them to collect and manipulate management information, and the degree to which information and analysis are being used to support institutional decision making."