First I must explain that there is a difference between empirical research findings and the theoretical formulations that human researchers create to explain their findings. To reiterate, we have:
- research findings (data)
- theoretical explanations (rationales that researchers invent)
The data can be true, while the theoretical explanations can be wrong.
Academic researchers are paid the big bucks—and gain the highest psychic rewards—for developing theories.
As you know if you’ve followed my work for any length of time, I put much more faith in data than in theories.
So, while I am about to share criticisms of a theory, I think the research findings are still sound.
Here are some recent criticisms of Cognitive Load Theory:
Ton de Jong says:
What has cognitive load theory brought to the field of
educational design? The three main recommendations that come from cognitive
load theory are: present material that aligns with the prior knowledge of the
learner (intrinsic load), avoid non-essential and confusing information
(extraneous load), and stimulate processes that lead to conceptually rich and
deep knowledge (germane load). These design principles have been around in educational
design for a long time (see e.g., Dick and Carey 1990; Gagne´ et al. 1988; Reigeluth
1983). Work in cognitive load theory often denies the existence of this earlier
research, as illustrated in the following quote by Ayres (2006a, p. 288):
‘‘Whereas strategies to lower extraneous load are well documented…methods to
lower intrinsic load have only more recently been investigated’’ (p. 288). In
his study, Ayres introduces part-tasks as one of the initial approaches to
lower cognitive load. Describing this as a ‘‘recent’’ approach denies much of
the history of instructional design.
de Jong, T. (2010). Cognitive load theory, educational
research, and instructional design: Some food for thought. Instructional
Science, 38(2), 105-134.
Roxana Moreno says:
Under the light of CLT’s [Cognitive Load Theory’s]
fundamental limitations, I will make the argument that continuing to use the theory
to frame instructional design research is instilling the idea that educational
research cannot aspire to have the same scientific value as that of the hard sciences
(Diamond 1987). The following are some reasons why this might be the case. When
educational researchers are not able to demonstrate that they are making
progress, they give further reasons to believe that the learning sciences are a
lesser form of knowledge (Labaree 1998). Second, although a strength of CL
research is the use of controlled experimental studies—one of the exemplary
methods of scientifically based research (Eisenhart and Towne 2003)—it has
failed to develop adequate methods that permit direct investigation of the
research questions at stake. Science relies on measurements or observational
methods that provide reliable and valid data across studies by the same or
different investigators (National Research Council 2002).
Third, in any science, researchers construct towers of
knowledge on the foundations of the work of others. de Jong raises a valid
concern about the fact that CL research often ignores the existence of earlier
research and theories that may better account for the findings than CLT. The
dangers of this isolated approach to science are clearly stated by Labaree (1998)
‘‘At the end of long and distinguished careers, senior educational researchers
are likely to find that they are still working on the same questions that
confronted them at the beginning. And the new generation of researchers they
have trained will be taking up these questions as well (p. 9).’’
Lastly, although bias may not be completely avoidable,
scientists are expected to be aware of potential bias sources in their work.
One safeguard against bias in any area of study is to be open to reflection and
scrutiny. It is the professional responsibility of educational researchers to
evaluate the state of current knowledge on a regular basis, identify knowledge
gaps, and lay the scientific principles for future investigation. Engaging in
this ‘effortful’ practice is key in fostering a scientific community and
Moreno, R. (2010). Cognitive load theory: More food for
thought. Instructional Science, 38(2), 135-141.
Schnotz and Kurschner (2007) say:
Numerous empirical studies have demonstrated that
traditional instruction can and should be re-designed according to principles
of cognitive load theory, and that this re-design results in better learning.
However, there are also numerous conceptual problems related to cognitive load
theory, which sometimes make interpretation of empirical findings difficult.
Although the concept of cognitive load has been frequently described in general
terms and although definitions have been provided for different kinds of
cognitive load, a closer look reveals that the exact nature of these different
kinds of load is not sufficiently clear yet. Further clarification is needed
regarding the relations between different kinds of cognitive load and whether
they can and how they should be manipulated to enhance learning. Other open questions
refer to the role of working memory in the process of learning. Although
working memory is a key concept in cognitive load theory, it is not
sufficiently clear to what extent working memory is in fact required for
learning. Finally, further clarification is needed whether and in which way
different kinds of cognitive load constrain each other, how they relate to the
process of learning and, last not least, how they can be measured.
Schnotz, W., & Kurschner, C. (2007). A reconsideration of
cognitive load theory. Educational
Psychology Review, 19, 469–508.
So, the theory is shaky, even though it has generated a slew of great research.
The data is still compelling, so, among other things, we can still use worked examples.
- Worked examples are useful for novice learners.
- Worked examples may hurt more experienced learners. Better to utilize practice problems for more experienced learners.