Newcomer Integration in Online Knowledge Communities: Exploring the Role of Dialogic Textual Complexity

Using online knowledge communities (OKCs) as informal learning environments poses the question how likely these will integrate newcomers as peripheral participants. Previous research has identified surface characteristics of the OKC dialog as integrativity predictors. Yet, little is known about the role of dialogic textual complexity. This contribution proposes a comprehensive approach based on previously validated textual complexity indexes and applies it to predict OKC integrativity. The dialog analysis of N = 14 blogger communities with a total of 1937 participants identified three main components of textual complexity: dialog participation, structure and cohesion. From these, dialog cohesion was higher in integrative OKCs, thus significantly predicting OKC integrativity. This result adds to previous OKC research by uncovering the depth of OKC discourse. For educational practice, the study suggests a way of empowering learners by automatically assessing the integrativity of OKCs in which they may attempt to participate and access community knowledge.

Predicting Student Performance and Differences in Learning Styles based on Textual Complexity Indices applied on Blog and Microblog Posts

Social media tools are increasingly popular in Computer Supported Collaborative Learning and the analysis of students' contributions on these tools is an emerging research direction. Previous studies have mainly focused on examining quantitative behavior indicators on social media tools. In contrast, the approach proposed in this paper relies on the actual content analysis of each student's contributions in a learning environment. More specifically, in this study, textual complexity analysis is applied to investigate how student's writing style on social media tools can be used to predict their academic performance and their learning style. Multiple textual complexity indices are used for analyzing the blog and microblog posts of 27 students engaged in a project-based learning activity. The preliminary results of this pilot study are encouraging, with several indexes predictive of student grades and/or learning styles.

Does digital competence and occupational setting influence MOOC participation? Evidence from a cross-course survey.

While MOOCs are recognized nowadays as a potential format for professional development and lifelong learning, little research has been conducted on the factors that influence MOOC participation of professionals and unemployed in MOOCs. Based on a framework developed earlier, we conducted a study, which focused on the influence of background variables such us digital competence, age, gender and educational level on MOOC participation. Occupational setting was considered as a moderator in the analysis of the impact of digital skills. Results of the study showed that MOOCs were an important tool for unemployed participants who were more likely to enroll in MOOCs than employed learners. MOOCs were also a way for workers who do not received employer support for other training activities to get professional development training. Results of the regression analysis showed that a person’s level of digital competence was an important predictor for enrolment in MOOCs and that specifically interaction skills were more important than information skills for participating in the MOOC context.