Message Design: Reading Reflection W3

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Reflection Week 3       
By: Jennifer Maddrell
Submitted: May 29, 2008       
For: Dr. Gary Morrison, IDT 895

Reflection  1 – Sweller and Chandler


Sweller and Chandler (1994) report on research conducted to examine assumptions of cognitive load theory. There research attempts to forward a cognitive model in which working memory faces constraints, but long-term memory, where information is stored as schemas, is vast and provides opportunities for automation. They suggest that instructional design can improve the efficiency and effectiveness of information encoding if these assumptions are considered during the design of instruction.

Sweller and Chandler (1994) suggest that information can be difficult to process due to the intrinsic structure of the information which they deem unalterable and beyond the scope of their research. Instead, they focus on extraneous cognitive load; specifically, the interaction of elements which they propose can be addressed through proper structuring and presentation of information within the design. They suggest that the structure and presentation of information can be designed to maximize schema acquisition and automation, two areas they deem “major learning mechanisms.” Their presented research focuses on issues of extraneous cognitive load related to a) split attention and b) redundancy which they suggest can be caused by element interactivity. Element interactivity exists when multiple elements of information must be processed at the same time.

Schemas are described as a means of organizing information with existing information in long term memory which, in turn, reduced cognitive load. Instead of encoding each element of newly presented material, we are able to integrate new information with existing schemas. Automation describes the eventual automatic processing of information and is gained through practice and time. It allows a “bypass” of working memory and reduced processing demands.


Sweller and Chandler (1994) proposed that cognitive load is related to element interactivity, including the number of elements that must be considered together and the degree to which elements must be learned at the same time. While the element interactivity will be different based upon the existing knowledge of the learner, extraneous cognitive load can result through the design of instruction.

To study their hypothesis, they examined the impact of learning to use new equipment from manuals alone from manuals, plus the equipment.  In contrast to other theories which place emphasis on “learning by doing”, their research supported their prediction that the equipment would interfere with learning due to the interactivity noted above.

Influence of Paper

As noted, the forwarded hypothesis and research findings appear in direct contradiction to many prevalent “learning by doing” instructional prescriptions. Therefore, engagement in what Sweller and Chandler (1994) refer to as “irrelevant cognitive activities”, defined by them as “any activity not directed to schema acquisition and automation” may unnecessarily increase cognitive load and hamper the processing of to-be-learned material. Can you say “black box” waiting to be filling with knowledge?

While on a pure encoding and processing basis, it is hard to argue against their research findings. However, isn’t learning and knowledge creation more than about maximizing the information you can process during a single learning event? It seems to be also about gaining interest, long term engagement with the material, co-creation of knowledge with peers, and integrating to-be-learned information into ongoing lifetime activities. Using their research example, while it may be increase extraneous cognitive load, touching and manipulating the equipment likely increases interest in learning about the material. Likely, there is a balance to be struck between activities to encourage interest and engagement with the material and activities to purely promote cognitive processing. It seems a boring and bleak prospect to contemplate education where only activities “directed to schema acquisition and automation” are considered.

Reflection 2 – Mayer and Moreno


Mayer and Moreno (1998) report on research conducted to extend prior research on “split attention” effects.  While the results of their research are described as a split-attention effect in which learning is improved when pictures are accompanied by auditory narration as compared to written narration, a dual modality effect seems a more appropriate description. Mayer and Moreno suggest that when learners must attend to both words and pictures, they are better able to hold and process the information when the words are processed in auditory working memory (as verbal narrations) and pictures in visual working memory. In contrast, when words and pictures are presented visually, visual working memory is taxed. Further, when words and pictures presented in separate modalities, learners are are better able build connections between the two due to the availability of working memory to devote attention to the connections.


While prior research focused on paper based materials, Mayer and Moreno (1998) conducted their study using computer based multimedia. Within their study, they compared the learning outcomes of learners who viewed animation with on-screen text (Group AT) with those who viewed the animation with auditory animation (Group AN). Unlike Group AN, those in Group AT must represent all of the material in visual working memory. Therefore, based on dual-processing theory, a split-attention effect was predicted (again, a dual modality effect?) in which Group AN would perform better than Group AT in the study’s retention measures. This predicted result is in contrast to the information-equivalency hypothesis which would predict no difference given the same information was presented to both Group AT and Group AN.

The superior retention results of Group AN suggest support for dual-processing theory; presentation of words and visual images in separate modalities is more effective than presentation in the same modality. In turn, this provides evidence against the information-equivalency hypothesis.

Influence of Paper

As noted, this study suggests support for dual-processing theory and appears to conflict with the information-equivalency hypothesis which suggests the modality of delivery does not matter. As such, designers should not focus solely on what information to present to learners, but also how the information is presented. As suggested by this research, working memory appears to become taxed when both words and pictures are presented in the same modality. Therefore, as indicated by the researchers, multimedia presentations should mix auditory narration with visual presentations of pictures and animations.

Further, given that the results suggest it is possible to overload learners with information that cannot be effectively processed within working memory, care should be given to how much information is presented. Designers should resist the “everything AND the kitchen sink” and carefully vet information that is to be presented to learners.

Reflection 3 – Nadolski, Kirshner, van Merrienboer, and Worethchofer


Based on their research, Nadolski, Kirshner, van Merrienboer, and Worethchofer (2005) forward an instrument to measure and rank learning task complexity. This research builds off of several other task analysis scales, including that from Merrill’s Component Design Theory which ranks performance complexity across four levels (very simple, simple, complex and very complex).  The description on page 4 of the paper provides a meaningful description of how the authors conceive of “complexity” which reminded me of the spirit of the famed “Bloom’s Taxonomy”, as well as the condensed and amended version presented in the “Green Book” by Reigeluth (1999):


The research questions center on: 1) what characteristics makes a good rater and 2) what consistency is there in rankings across raters? Overall, the findings indicate that the raters’ experience as a student learning the task held greater influence than expertise.  In addition, raters were most consistent on the outer ends (categories 1 and 4), but overlapped significantly in the mid range (categories 2 and 3).
Based on the research findings, Nadolski et al. (2005) suggest other areas of future research. First, would clarification of the frame of reference result in more confident ratings from the raters? Second, does use of this rating tool increase the effectivenss of instructional designs?

Influence of Paper

This research and paper forwards an instrument to assist in rating task complexity.  Those who have attempted to create instructional strategies based off of a task analysis know how important, yet how difficult it is to have an understanding of where the learner is “at” in terms of being able to comprehend and synthesize the material.  However, the paper seems to leave several questions unaddressed.

As noted in the report, the complexity rankings appear to overlap greatly when assessing mid-range complexity (categories 2 and 3). Therefore, is it necessary to have 4 rankings or would 3 categories (simple, medium, complex) tell us just as much? Also, it is unclear how this ranking system influences the choice of instructional strategies. The paper doesn’t provide a tie in to how instructional strategies would differ based on the rankings. In other words, if the task is considered more or less complex, what does that mean in terms of what instructional design strategies to chose? In addition, is there a meaningful difference in what strategy one would employ beyond strategies to facilitate recall and application? Also, as these rankings are relative to the learner’s prior experience with the task, what is the tie in to the learner analysis? In other words, how are varying degrees of task complexity (based on learner’s prior knowledge) addressed when setting whole class instructional strategies?

Reflection 4 – van Merrienboer and Sweller


Integrating aspects from the other papers reviewed this week, van Merrienboer and Sweller (2005) consider cognitive load theory in relation to the instructional design of complex learning. Based on early research in cognitive load, prescriptions focused on the reduction of extraneous cognitive load, including recommendations of stripped down instruction to foster efficient information processing. Over time, these prescriptions have evolved. van Merrienboer and Sweller examine that evolution, including the research and resulting prescriptions.

Cognitive Load Theory

Early research on cognitive load focused on the limited working memory capacity to processes new information obtained through sensory memory during fairly limited learning situations. This research supported the hypothesis that there is not the same working memory limitation with regard to retrieval of information from long-term memory and suggested that, through experience, learners form and refine schemas to organize and aid in the processing of information. In turn, processing becomes more automatic over time and with practice.

Intrinsic cognitive load, which is associated with the task complexity, has largely been considered “a given” by researchers. Each task is considered to have a certain number of elements to be processed and working memory is limited to the amount it can process. In contrast, extraneous cognitive load can either positively or negatively impacted by how information is presented and instructional methods and practices. As noted previously, materials which add a high degree of interactivity are harder to process. A common assumption is that instructional methods which decrease extraneous cognitive load will in turn lead to better schema construction, automaticity, and better transfer.

In this paper, van Merrienboer highlight several studies which suggest instructional methods to reduce extraneous cognitive load (several discussed previously in this report) and track major new directions in cognitive load theory, including theory and research related to 1) embedding learning in authentic complex settings, 2) extended learning sessions, and 3) expertise assessment. These issues extend the evaluations of cognitive load from simple learning tasks to more complex learning situations.

Complex learning includes higher numbers of interacting elements which appear to be positively affected by a decrease in extraneous cognitive load (as previously discussed), as well as sequencing of content for reduction in intrinsic cognitive load. Some suggest sequencing should focus on a progression of the most familiar to the least, while others suggest beginning with the required elements which represent the whole. Further, research suggests complex learning tasks which involve problem-solving benefit from learning the processes and hints prior to engaging in problem solving (by developing schema prior to practice) and by sequencing and incorporating problem constraints in lieu of embedding the hints or cues into the problem, as is sometimes done with the use of problem-solving process worksheets.

Further, research regarding the expertise reversal effect suggests that instructional methods that foster learning for novices do not help (and may harm) the learning of experts. This line of research supports the instructional prescription of beginning with structured worked problems and progressing toward more realistic problems as the learner’s expertise increases. These findings and prescriptions carry through to computer mediated learning which suggests adapting the instruction to the learner’s expertise fosters learning more than presenting the same instruction regardless of level.    

Influence of Paper

This paper helps to meld previous research into cognitive load theory with other more recent instructional theories. As noted previously, many of the prescriptions related to cognitive load theory imply a stripped down instruction which focus on reducing extraneous cognitive load. This approach would seem to contradict other research which suggests situating learning in rich and authentic learning environments where learners tackle complex and ill defined problems. Therefore, this paper is important as it builds a bridge across cognitive load research, as well as to other seemingly less related theories and research findings.

Overall, the highlighted research suggests that learning in authentic settings with realistic problems can be supported through effective sequencing of content and by first learning problem solving processes prior to task engagement. In addition, it is important to consider than novices and experts respond differently to worked problems versus realistic problems. The worked problems which may help novices reduce extraneous cognitive load, may not be effective for experts. In contrast, realistic problems which may be most appropriate for experts may overburden novices. Therefore, effort should be made to gauge learner expertise and tailor the instruction according.


Mayer, R. E.; Moreno, R. (1998). A Split-Attention Effect in Multimedia Learning: Evidence for Dual Processing Systems in Working Memory. . Journal of Educational Psychology, 90(2) p312-20 Jun.

Nadolski, R. J.; Kirschner, P. A.; van Merrienboer, J. J.G. (2005). Development of an Instrument for Measuring the Complexity of Learning Tasks . Educational Research and Evaluation, 11(1) p1-27 Feb 2005

Reigeluth, C. M. (1999). Instructional design theories and models. Mahwah, N.J.: Lawrence Erlbaum.