Soft Systems and Instructional Design for Technical Training

Soft systems methodology (SSM) could easily be used in education as a means to identify learning gaps and make recommendations to fill those gaps.  This is associated with the seven steps to SSM that Zhong (2007) discussed:

  1. Identify the problem or challenge that needs to be addressed.  Zhong (2007) discussed SSM applicable for semi-structured and unstructured problems.

    Applying this to education is to identify the problem that training needs to solve.  For example, a common tech problem is an overload of helpdesk tickets.  Training on a specific application can be added to onboarding or as mandatory to give users the tools needed to resolve their own basic questions.
  2. The identified problem should be described.  Zhong (2007) suggested images as more beneficial than language.  The thought is language could have different meanings depending on the context, where as an image tells a very distinct story and sets a more creative thought process for future steps.

    In education resources can be gathered like error messages, screen shots and emails to identify key pain points.  Then this information can be categorized by level of difficulty.  This organization will help produce training that gets progressively more difficult.  This is important since pain points will likely vary by the type of user.  This step could very likely involve a mindmap which would allow freethinking and interactive movements to get organized.
  3. All systems associated with the problem should be defined.  Zhong (2007) suggests relevant systems should be selected, and defined at the root level, to add insight to the problem.

    Theoretical systems can be associated as appropriate, however all technologies related to the systems need to be identified in order to incorporate them in the right context in the training.
  4. Develop a conceptual model for each associated system.  Zhong (2007) best describes this as “Each root definition consists of six aspects: customer, actor, transformation process, (Weltanschauung) world view, owner and environmental constraints.” (p5733)

    This could be associated with the actual use case development.  Systems are gone through, and level of detail needed for each audience is identified.
  5. The problem that was identified in step two should be compared to the conceptual models developed in step four.

    The initial training challenge is compared to the use case to determine if this will actually resolve key problems.  If it does not adequately train on these issues it is important to go back to step two and walk through the process again to identify where it is wrong.
  6. Identify the change that is expected to happen and if this change is even possible.

    In the educational example this step could happen earlier in the process, or after all problems and systems have been analyzed.  This is where actual learning objectives are created.  Learning objectives must be included in all training since they fill two key roles.  First, they are a self-check for the Instructional Designer to make sure all necessary content was included in the training.  Second, they are used after the training is taken by a user to measure if learning actually happened.  If training was not successful, then the module should again be put through this process.
  7. Finally determine actions that can be taken to resolve the problem.

    Since large technical training modules are best consumed in small bites, this step can be used to match the training back with the problem.  Then additional training can be identified to fill remaining gaps, which would walk us through the process again.

Zhong (2007) discussed how SSM is not the end all solution to a problem, instead it is cyclical, answering certain questions and then identifying new questions.  As in technical training constant improvements are required to accommodate technology innovation, changes in jobs, and to address new challenges that may arise.

Reference:

Zhong, Y. (2007) Soft systems methodology based on decision making knowledge integration,” 2007 International Conference on Wireless Communications, Networking and Mobile Computing, Shanghai, pp. 5733-5736.

This entry was posted in Computer Mediated Discourse Analysis. Bookmark the permalink.

Leave a Reply

Your email address will not be published. Required fields are marked *