Social Learning in Practice at IBM

What is social learning and how can it help drive engagement and develop a culture of learning?

The social learning theory of Bandura emphasizes the importance of observing and modeling the behaviors, attitudes, and emotional reactions of others. Bandura (1977) states: “Learning would be exceedingly laborious, not to mention hazardous, if people had to rely solely on the effects of their own actions to inform them what to do. Fortunately, most human behavior is learned observationally through modeling: from observing others one forms an idea of how new behaviors are performed, and on later occasions this coded information serves as a guide for action.” Basically, Bandura’s theory is that human beings can learn by example.

Why does social learning matter?

Research states that most people only recall 10% of information learned within just 72 hours in typical training environments. Social learning can reverse this curve. In fact, research shows retention rates as high as 70% when social learning approaches are employed. Rather than relying on typical training environments with low recollection rates, social learning allows learning to happen in the working environment. Learners can pull knowledge from experts within the organization rather than have it pushed on them. Learning becomes a part of the organization culture.

An example of social learning at IBM

The Data Analytics Center Of Excellence (COE) at IBM continuously provides Data Science training for our employees and decided to pilot the use of the recently IBM Data Science Professional Certificate on Coursera. They identified 2 different controlled study groups 1) A group of individuals who would have otherwise gone through a 5-day full time face to face bootcamp and 2) A group of instructors who would typically teach this bootcamp. One of the biggest problems of using MOOCs for enablement is the high dropout rate, research shows that approx ONLY 5% of the total learners complete a course. Here are a few ways in which we are keeping this group of learners engaged:

FAQs and Forum

A dedicated SLACK channel has been established with the pilot participants in which employees can pose questions and receive answers from within the group. This promotes collaborative learning as individuals can learn from their peers and also learn from questions posed by others. Apart from the pilot, there is also a large IBM Data Science Community  that hosts events on a regular basis and has plenty of enriching forums with discussions.

Organization Wikis

The participants are encouraged to blog about their experience. Bernard Freund, STSM – Data Analytics CoE writes a blog post at the end of each week as he completes a course. This post not only provides user with a thorough review of the course, but also highlights some issues along with workarounds which has been extremely useful for other learners attempting the course later.

Utilize expert knowledge

Besides the SLACK channel, we have also instituted check-point calls with the Coursera and course development team. Not everyone attends these calls, but it does give the participants an opportunity to get some 1:1 time with the SMEs to overcome any obstacles that may be preventing them from completing the program.

Gamification and rewards

You can’t force people to learn but you can give them the right tools and incentives to make sure they don’t waste opportunities. IBM does this through the Open Badge program. The program awards badges upon the completion of each of the 9 courses and a certificate upon program completion. These badges provide a way for the administrators and users to track their learning progress.

Currently, we are 1 month into the 3 month pilot and the learners seem very engaged and vested in their progress. On an average most participants have completed at least 2 of the 9 courses which does put them on track for completing the certificate within the pilot timeline. Stay tuned as we report further results in the coming months.