Decentralized Group Instruction Per Level/alx

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Decentralized Group Instruction Per Level
Contributors Christian Köppe, Ralph Niels, Robert Holwerda, Lars Tijsma, Niek Van Diepen, Koen Van Turnhout, René Bakker, Stijn Hoppenbrouwers
Last modification May 15, 2017
Source Köppe et al. (2015)[1]; Köppe et al. (2016)[2]
Pattern formats OPR Alexandrian
Learning domain

Your course is running for a while, and differences in the level of concept acquisition start to emerge. Your available time for the in-class meetings is still limited.


A general group instruction does not work anymore if there are student groups with different levels of concept acquisition and there is not enough time to help all individual students.

Giving Individual Support (Individual Support) to many students is scalable to only a limited degree. On the other hand, continuing with giving instructions to the whole group might seem more efficient, but some students won’t be able to follow and the value of the in-class meetings for these students will be low.

On the other end of the spectrum, students who are ahead of schedule or have less trouble with understanding the subject, might get bored.


Therefore: Give adjusted feedback and instructions for smaller groups of students with the same level of concept acquisition, in order to help all students the best possible way.

This adjusted feedback and instructions could be an ad-hoc mini lecture on a concept, a discussion of some additional examples, or a step-by-step execution of a process. This is done with a sub-group of students who all are more or less on the same knowledge level. Such group can be identified when one applies Considerate Lecturer (Considerate Lecturer), Use Student Solutions (Use Student Solutions), and Preparation Status Awareness (Preparation Status Awareness). Make sure that this instruction is open to all students, so that all students can benefit from this extra effort.

Applying this pattern is more efficient than Individual Support (Individual Support), as the feedback and instructions are of value for a larger group of students and not individual ones. Also, students can learn from questions asked by fellow students and by co-operatively working on a (small) assignment.

During execution of the course, but especially in the later phases when the knowledge levels of the students tend to become more varied, one should consciously think about applying Decentralized Group Instruction Per Level (Decentralized Group Instruction Per Level) as part of the Lecture Structuring (Lecture Structuring).

This pattern helps with improving the effectiveness and efficiency of the in-class meetings by providing more value to more students.

However, preparing such group instruction requires extra time for preparation. It also requires that the teacher has a very good grip on the students’ progress, which is a skill that needs to be learned and not often comes natural to beginning teachers.

In the course Structured Program Development at HAN University, at the moment when functions with parameters are introduced, some students grasp it easily, while others struggle with getting the concept of parameters and all issues related with that, such as pass-by-value versus pass-by-reference. At this moment of the course, the lecturer prepared a small extra instruction with some additional examples for the students in the group who still have problems with grasping parameters. As all students in this group were struggling with parameters, they also dared to ask more questions than they would have in the whole group.


  1. Patlet first mentioned in Köppe, C., Niels, R., Holwerda, R., Tijsma, L., Van Diepen, N., Van Turnhout, K., Bakker, R., (2015). Flipped Classroom Patterns - Designing Valuable In-Class Meetings. In Proceedings of the 20th European Conference on Pattern Languages of Programs (EuroPLoP 2015). New York:ACM.
  2. Pattern first published in Köppe, C., Niels, R., Bakker, R., & Hoppenbreuwers, S. (2016). Flipped Classroom Patterns-Controlling the Pace. In Proceedings of the 10th Travelling Conference on Pattern Languages of Programs (VikingPLoP 2016). New York:ACM.