Designing a learning quality model based on Siemens Connectionism theory in universities executing distance Education

The aim of this study was to designing a learning quality model based on Siemens Connectionism theory in universities executing distance Education.
This was an applied research in terms of purpose and descriptive in terms of method and was survey type. The study population consist of all faculty members of distance education universities around the country that counts to 3380 members. The sampling method in the qualitative phase was purposive sampling method (convenient), consist of 10experts in the field of distance Education and in quantitative phase, include stratified random sampling. The number of samples is 380. To gather data, researchers used analytical documents method for non-interactive and self-made questionnaire was used in survey method. Validity was assessed by using confirmatory factor analysis. For data analysis Lisrel v 8.8 and for model fitting AMOS software were used.
There is a significant difference between the theoretical and empirical Average indicators of the effectiveness of Siemens Connectionism Theory indicators on the quality of learning in distance education. Difference between the theoretical and empirical Average was More than middle. The highest ranking belongs to the indicators of Ecosystem Learning and other indicators in order of importance and influence are learning network, interact, learn the elements of pressure and formation of learning nodes.
To keep pace with global developments in the field of distance Education, there is a need to apply the Siemens Connectionism theory. And if this is done well, it can change into very useful elements in universities.