What I have learned in the Knowledge Management (CMN5550) course.

The course took a different approach than the other courses offered at the University of Ottawa. What I learned in this course and the approach that we took was not expected at all! Professor Pierre Levy surprised me by telling us not to put our smartphones away; utilizing a Facebook group to share the syllabus, agenda, lectures and assignment details; teaching us about the functions of social media; telling us to tweet our class notes; and instructing us to publish our assignments with images and links through blogs!

Twitter and Social Media

In taking class notes via tweets, we utilized #UOKM. This way all classmates were able to share and access the “knowledge” that was acquired during the lectures. We also used the hashtag to share our opinions, thoughts, and summaries of articles that we read weekly for class. These articles touched upon many concepts ranging from blockchain to artificial intelligence, collective intelligence, big data, digitization, data curation, etc. Thus, I have learned a lot about digital technology, its future and implementation. Pierre Levy also taught us how to make lists on twitter to categorize and manage the data on our profile, include threads in our tweets to expand our expression beyond 140 characters, and include other hashtags to increase the tweet’s impression. In discussing social media, Pierre Levy instilled in us that responsible public behaviour is an absolute necessity.

Collaborative Spaces

Pierre Levy’s teaching philosophy derives from collaborative learning. He highly recommends not limiting oneself to one platform but instead jumping between platforms to enhance learning, collaboration, and problem solving. Twitter along with other social media are collaborative spaces where skills can be acquired, questions can be asked, and the learning experience is enhanced. Wikipedia is also a site that uses group collaboration to contribute information on a site enhancing readers’ knowledge.

Today, individuals have the ability to interact and communicate with other individuals through multiple platforms forming a “community of practice” or “collaborative learning networks”. In a community of practice or collaborative learning networks, people with different expertise, diverse skills, and various perspectives gather together to learn about a topic and deepen their knowledge. Pierre Levy taught that such communities and networks are key to knowledge management and are producers of collective intelligence.

Collective Intelligence

Pierre Levy placed great emphasis on collective intelligence. Throughout the semester, it was made clear that collective intelligence is the transformation of individual knowledge into collective knowledge. In an article that we had to read for class, the difference between collected and collaborative collective intelligence was discussed. First, collected collective intelligence refers to the collection of individual data that is aggregated and hands back collective results. For example, Amazon’s recommendation system collects the metadata of millions of users to generate product recommendations. On the other hand, collaborative collective intelligence refers to the deliberate interaction and collaboration of individuals. With this type of collective intelligence, “intelligence emerges from conscious connections, an interest in sharing, giving, receiving, and socializing”. Pierre Levy is most fond of collaborative collective intelligence.

Big Data

In taking a closer look at collective intelligence, the use big data is a primary concern. In the digital world, every click, share, like, etc. is recorded leaving behind a digital footprint. All this creates an abundance of data sets, known as big data, which can be analyzed to reveal information like trends,

patterns, behaviour, etc. Additionally, the information gathered from big data can be turned into knowledge which can facilitate the processing of new information in the future. In class, we learned that big data and data analytics can be used to rally voters during elections through micro-targeting and can identify personality traits, gender, sexuality and political views based on social media activity. Despite the many misuses of big data, it can also be used in a good way, such as understanding climate change. The problem that is most faced with big data is extracting useful and important information from the flows of big data and deciphering it for better understanding. For this, Pierre Levy taught us the importance of curating data.

Data Curation

Curating data refers to management or organization of data through a system of categorization that will facilitate the finding or extraction of information (read this). Pierre Levy explained that professionals in digital humanities, education, knowledge management, etc. practice data curation in a very systemic way. Librarians for example, curate data by categorizing books in terms of authors, topic, theme, alphabetical order, year of publication, etc. However, Pierre Levy also informed us that we curate data all the time on social media by liking, commenting, and posting. Additionally, he showed us how to curate data on Scoop.it, a collaborative repository in the cloud, by using “tags” to categorize and organize information.

This was just a small summary of what I learned in this course, Pierre Levy taught much more. I recommend this course for anybody who is interested in digital technology and wants to keep up-to date on its implementation and future.