Systems and complexity have serious ramifications on the studies and research into effective teaching practices integrating technology in learning environments. The number of inputs that go into forming a learning environment is the foundation of this complexity. For educational technology researchers, they look to measure the impact technology has on learning and specific student outcomes. This complexity limits the implications and generalizations from their research. For instance, Huang and Hong (2015) created a study to measure the effects on learning in a flipped classroom model where one class was the control and the other class was an experimental flipped classroom. In this case, the results for flipped classrooms were promising, but due to the complexity of a learning environment, the implications of the study are extremely limited.
The complexity of the classroom can be broken down into eight entities (Branch, 1999) and teachers learn all about them as they complete teacher education programs and enter the classroom. When learning about students, teachers discuss Maslow’s hierarchy of needs. The fact is every student in the learning space has some combination of needs being met and not being met. That immediately is complex in itself. Therefore, it can be hard to fault the teacher when students’ basic needs are not met, but an effective teacher sure is important (Heck, 2009). So before we even talk about the subject, the standards, the time, the context, the classroom management etc., we have these two extremely complex inputs: students and teachers.
Personally, I have experienced the complexity of both these inputs. One year, every morning, I taught two Algebra 2 classes in a one-to-one environment. It would seem logical to arrange one’s schedule this way; the classes would run more or less identically. Yet, the needs of the students in the two classes did not cater to this logic. Instead, with the encouragement from my coach, I spent the year preparing two different lessons for two different classes learning identical standards. While teaching Geometry that same year, I experienced that two teachers (a fellow math teacher and myself) with the same material, classroom design and resources would have drastically different results on our classes’ standardized assessments.
Surely, the complexity exists, but so do relationships, patterns, and trends. Education technology researchers can no longer oversimplify the classroom and form board generalizations (Xi and Branch, 2008). We cannot simply give educators technology and consistently expect positive results. The entire integration process must be thought out to address each entity of the complex system. Quality research into that integration then unearths the dynamic connections within the system. These relationships are important because the identification of best practices will make learning spaces more effective.
Diffusion of technology and its practices is an important piece to understanding educational technology. New technology is not instantly adopted by new users. Most people follow a select few who lead the way. This bandwagon effect is great when the generalizations made are accurate, but they can be extremely detrimental otherwise. Schools may invest heavily into technology that actually does not solve their needs. School funding is not on-demand. These schools then may find themselves in a difficult situation because they followed bad advice, jumping on the wrong bandwagon.
Research and studies have to be accurate with their implications. School leadership relies on this research to make sound decisions. It is thus the job of researchers to make sure generalizations take into account the complex nature of learning spaces.
Branch, R. (1999). Instructional design: a parallel processor for navigating learning space. In Design Approaches and Tools in Education and Training, edited by J. van den Akker, R. Branch, K. L. Gustafson, N. Nieveen, and T. Plomp, pp. 145–154. Dordrecht: Kluwer.
Heck, R. H. (2009). Teacher effectiveness and student achievement: Investigating a multilevel cross‐classified model. Journal of Educational Administration, 47(2), pp.227-249
Huang, Y.-N., & Hong, Z.-R. (2015). The effects of a flipped English classroom intervention on students’ information and communication technology and English reading comprehension. Educational Technology Research and Development, 64, 2, 175-193.
Ni, X. & Branch, R. M. (2008). Complexity Theory. The Handbook on Research on Educational Communication and Technology. Chapter 3, pp. 29-33.