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In Order to Learn: How the Sequences of Topics Affect Learning

Tomorrow's Teaching and Learning

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The order of presentation of material influences the speed of learning as well as what is learned, how it is learned, and sometimes even if it is learned. Theoretical and empirical work can make suggestions about how to use these effects to advantage in the classroom.


The posting below notes some of the issues of how the order of instructional material influences learning. It is a synopsis of Chapter 1, Call to order: How sequence effects in humans and artificial systems illuminate each other, by Frank Ritter ( and Josef Nerb ( from: In order to learn: How the sequences of topics affect learning. Edited by Frank E. Ritter, Josef Nerb, Erno Lehtinen, and Timothy M. O'Shea, published in 2007 by Oxford University Press. ISBN 78-0195178845. This synopsis provided exclusively to Tomorrow's Professor. The book can be ordered at:

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Rick Reis

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Tomorrow's Teaching and Learning


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In Order to Learn: How the Sequences of Topics Affect Learning

In order to learn: How the sequences of topics affect learning.


In medieval Europe, some performances started with building a nailless bridge, a spectacular beginning, and indeed, an artistic one, for the artists then used the bridge as a stage. What matters for the construction of the bridge is the right sequence in putting together the pieces. The correct sequence leads to success-a bridge; an incorrect sequence leads to failure-a heap of sticks. Leonardo da Vinci first analyzed the bridge's construction and discovered its design principles. The bridge was explained by means of scientific methods, so its construction principles could be reused and not just imitated. Through this process the bridge's construction moved from art to technique.

A similar process is being performed today in instructional science. The presentation order of instructional material can strongly influence what is learned, how fast performance increases, and sometimes, even that the material is learned at all. This is true for both skills and facts, and remains true whether the material is presented by an instructor or explored alone by a learner. The analogy to the bridge continues to hold: just as Leonardo's analysis of the bridge's construction moved it from art to science, as we discover the underlying principles of the order effects in learning, we move instruction away from idiosyncratic expression and closer to a controlled and predictable science.

Our book presents detailed empirical and theoretical evidence that order effects are more pervasive and important than they have previously been treated, and explores how learning order affects the final outcome of learning, and how methods and findings from the range of cognate disciplines that study learning (e.g., psychology, artificial intelligence (AI), cognitive modeling, and instructional design) can be fruitfully combined to understand and improve learners' performance. We include case studies, theories, and numerous questions that provide food for thought for professionals working in these areas, including professionals in education.

Order of the book

Our book begins with overviews of the relevant areas of instructional design, machine learning, cognitive models (symbolic and connectionist), and human data. The second group of five chapters presents information-processing models that predict order effects as well as provide supporting data in many cases. The final group of three chapters illustrates order effects empirically obtained (or not obtained) in educational settings along with reflections about why they do or do not occur. The effects in these models and experiments are typically about 25%, but include predictions that with the wrong order learning can't happen. A concluding chapter (by John Sweller) pulls together the results, and calls for further, more detailed exploration of order effects by using techniques and data across, rather than simply within, the relevant areas.

Suggestions for changing instruction

The introduction and conclusion chapters compile suggestions for improving learning through better sequences of learning materials and highlight some of the numerous questions that the chapters raise, including how to use order effects to test theories, and how to vary the order to help later transfer. Perhaps most importantly, we can note some ways and places where order is not important or can be mitigated, including: allowing reordering by teacher or learner, short lessons, ordering the material to provide the basics first (no surprise here), including context for complex skills and for language materials, modifying the order to encourage transfer between problem types, reducing the complexity of the learning itself, providing human tutors to assist with computer-generated instruction, and to constrain novice learners more than expert learners.

Future research: Questions within the core areas

The contributions in this book allow us to identify meta-issues related to order effects in the core areas of psychology, AI, and instructional design. We note a few here. For psychology, can we discover new ordering effects in human learning? Can we understand when they occur and what factors influence human learners?

For machine meaning, can we develop flexible and powerful incremental learning algorithms that have benign or minimal ordering effects? How do algorithm complexity, speed, and space requirements influence order effects?

For instructional design, can we determine that order experimentally or computationally, and how can we create tools to help compute that optimal order automatically, even tailoring it to individual learners? And what is the space of instructional-design activities in which ordering can be safely ignored?

Finally, we will have to examine long-term objectives and influences. The chapters examine mostly direct and short-term effects and results. Different orders may also have longer-term and more subtle effects, including the quality of long-term performance, long-term learning, transfer to different problem types, motivation, and other qualities yet to be measured.

Future research: Bridging these areas

There are meta-questions that link the relevant disciplines studying learning, and each chapter addresses at least one of them. These questions help unify the chapters, so that a reader interested in or knowledgeable about multiple relevant fields may find their own insights.

(a) How do interfaces and learning environments affect the individual's need to consider order when organizing attempts at learning? Or is the rapid progress in computing environments (and cheap access to them) going to make this issue moot through improved interfaces alone?

(b) Can we develop machine-learning algorithms that model the effects of order on humans? Several chapters provide steps toward an answer to this question, showing how cognitive architecture mechanisms give rise to order effects.

(c) Can we use theories from AI and data from cognitive psychology to develop approaches to instructional design that take advantage of human ordering effects? This is clearly one of the broadest possible practical applications of this research, if not the most important.

In her poem "Girder", Nan Cohen noted that bridges lead in two directions. We hope this book serves as a bridge between these increasingly related fields.