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Monitoring a Learning Community in a Hybrid Environment: a Sentiment Analysis


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M. Cerrone, I. Merciai, Poster: Monitoring a Learning Community in a Hybrid Environment: A Sentiment Analysis, Eden Annual Conference, Budapest, 2016.

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Monitoring a Learning Community in a Hybrid Environment: a Sentiment Analysis

  1. 1. Monitoring a Learning Community in a Hybrid Environment: A Sentiment Analysis Ilaria Merciai ( Marco Cerrone ( University of Naples Federico II Anderson ,T. (2004), Teaching in an Online Learning Context, in Theory and Prac-tice of Online Learning, Athabasca University. Bogliolo, A., De Rosa R. (2016). Teaching to teachers: A MOOC based Hybrid Approach. Paper presented at the Eden Conference 2016 Cambria, E., Schuller, B., Xia, Y., & Havasi, C. (2013). New Avenues in Opinion Mining and Sentiment Analysis. IEEE Intelligent Systems, 28(2), 15–21. doi:10.1109/MIS.2013.30 De Rosa, R., Kerr, R. (2016) Out of the Fishbowl: Toward the Uberization of Teach-ing. Proceedings of “Wow! Europe embraces MOOCs” Rome 2015 Siemens, G., Downes, S.(2009). Elearnspace. Retrieved from Wen, M., Yang, D., & Rosé, C. P. (2014). Sentiment Analysis in MOOC Discussion Forums: What does it tell us? Paper presented at EDM2014. Retrieved from Tools: Netvizz, and T-lab, As Facebook publishes figures showing that social networks have reduced the degree of separation of people on the planet from 6 to 3.7, it is a platitude to say that they are powerful communication tools. However, the literature on their impact within MOOCs is still emerging, where the learning community already resides within its own space on the MOOC platform and where teaching units are accompanied by a forum for requesting clarification or information. In a recent MOOC on the EMMA platform (, “Coding in your classroom, now”, Facebook was used as an additional learning environment, to post and share information on content related to the course, to comment lessons and assignments, or simply to share a common experience and outcomes. The user-community network that has developed around the course has grown from the 6,000 learners enrolled on the course to reach a population of 100,000. The community started to exchange information about their area, schools and classes, and to use the learning experience on the MOOC to share and build knowledge and even plan meetups in their local area. Sentiment analysis, with keywords, online expressions, concepts, contexts, shows that socials acted as a powerful tool not only for dissemination of the course but also for informing thousands of people about the innovative features the Emma platform was experimenting. Last but most importantly, they became a powerful tool for sharing best teaching practice in the field. This work presents an exploration of the learning community on this course and evidence for some of the observations we make, trying to understand what impact this hybrid model of MOOC delivery has on the creation of the learning community and student engagement. ABSTRACT 3. RESULTS 4. CONCLUSIONS 2. METHODOLOGY The EMMA platform ( launched the MOOC “Coding in your classroom, Now”, created by professor Alessandro Bogliolo to help teachers introduce their classes to computational thinking through coding. The course attracted over 4,000 users in its first 10 days, and they behaved as a community: • exchanging information about their area, schools and classes, • using the learning experience on the MOOC to share and build knowledge, • planning meetups in their local area. This high number of learners on an adaptive course has presented interesting challenges and specific learning experiences in a series of loops at all levels of the MOOC delivery process - for the platform, for the tutors, for the teacher and for the learners. We carried out text analysis on the conversations between Facebook group users to study the way that learners respond to the situation, the course and the learning activities, many of which are completely new. And also to explore the way that teachers and tutors present and respond to situations and learner enquiries and communications. In the analyzed FB group we saw that posts were mainly about sharing links, closely followed by photos of analog situations where teachers are using skills/knowledge they acquired on EMMA with their own classes (see fig. 1). So a combination of sharing of materials which are considered to be of interest to the group, and photos which share their experience (self- congratulatory use of photos, but also useful for the group because they illustrated diverse classroom scenarios which could be copied and implemented by the other teachers. Our analysis refers to contributions from learners in the EMMA virtual classroom and to the Facebook Group “Coding in your Classroom, Now!”. We have considered all posts (3,312) and their related comments (14,348) published in the FB group (with 4,097 members in the analyzed range), from 15 January 2016 (when the MOOC was 5. REFERENCES 1. INTRODUCTION Fig. 1: Posts and comments comparison Fig. 2: Tag Clouds Comments Fig. 3: Users types Fig. 4: Hybrid Environment created) to 21st April 2016 (3 days after the last lesson of the course started). Data were extracted using the Netvizz application, then we cleaned and pre-treated the textual data through T-LAB and analyzed the main keywords related to the comments. The text corpus of comments comprised 14,720 lexical forms. Of these, we selected those occurring at least 10 times. The result was a list of 1,154 keywords that we based our interpretation of data on to try to evaluate learner attitude. We triangulated the data with the variable time, so producing four tag clouds. For each month we identified key events that the group conversations built up around. The tag clouds in fig. 2 show the different combinations of the main keywords for each month and we have associated to each the main contexts we identified for the comments. Combining the text analysis (macro level) with observation of individual comments in which they occurred (micro level) based on our overall corpus database, we were able to identify 5 categories of users which we termed: beginners, self- congratulatory, performers, meetuppers and testers/sharers (see fig. 3). Furthermore, the data set offers us the possibility to classify the FB participants in three main categories: teacher, staff and users, which includes the subcategory peer-reviewers. all the identified categories, with diverse levels of experience and competence, and led to the emergence of new contexts to encourage learning by doing. Analysis of the conversations helped us to highlight how members of the FB group attributed meaning to their learning experience through interaction between human and non-human elements. In fig. 4 we see which links were shared the most in the comments, and that other sites and platforms are recommended to integrate their learning. These platforms/instruments are important elements for building relationships between users and for encouraging interaction with the materials. The combination of these diverse elements resulted in the creation of a hybrid learning environment, where numerous online and offline elements interconnect,creating a dynamic and engaging contextfor learning. The exploration of the learning community on this course led us to understand the impact that this hybrid model of MOOC delivery had on the creation of the learning community and student engagement. Our analysis showed how Facebook helped in responding to diverse needs of such large numbers of learners, in