A Dozen Remarks on Academic Writing

These comments have been developed over a period of years to help graduate students develop an effective academic writing style. They are by no means comprehensive nor are they exhaustive. Rather, these twelve comments represent a few tips that may prove useful to a few who are in the process of improving their writing skills.

1.      Academic writing is quite different than writing fiction or essays for popular consumption. Academic writing typically involves the development and elaboration of a concept or the reporting of a study or series of studies aimed at exploring the efficacy of an intervention of some kind. The piece is about the concept or the study – it is not about you.

2.      Keep the intended audience in mind. Typically, readers will be professionals, scholars or researchers who want to know about the concept or intervention being presented. As a consequence, the scope and purpose of the piece should be made evident at the beginning of the paper – in the introduction and usually in the first paragraph or page.

3.      One can express complex ideas using short, descriptive sentences. Sentences that are long and that involve multiple dependent and independent clauses create a cognitive load on readers that is unnecessary and that is likely to detract from the purpose of the paper. As a general guideline, sentences should be relatively short – fewer than 30 or 35 words. It is generally desirable to express just one distinct thought in each sentence.

4.      It is all too easy to introduce unnecessary distracters and ambiguities in a paper. One source of ambiguity is the use of multiple terms to refer to the same thing. When a new term is introduced, the reader is inclined to believe that a new concept is being introduced. Minimize the use of what you may regard as synonyms for a term because the reader may not regard those terms as synonymous. You can clarify terminology early in the paper and mention that others use different terms to refer to the concept you are elaborating, but then use one term uniformly after the initial definition and elaboration of that term.

5.      Another source of ambiguity is the use of relative and personal pronouns such as ‘it’, ‘he’, ‘she’, and so on. In addition to creating potential ambiguity, relative and personal pronouns are a source of cognitive load as they create a need in the reader to construct the referent, which might not be as obvious as you think. Use a noun phrase to eliminate any possible misinterpretation and to minimize cognitive load in the reader. An exception might be the use of a relative or personal pronoun in a dependent clause in the same sentence.

6.      Avoid praising your own work. Simply describe what was done. Rather than claim that your intervention was highly creative and innovative, simply describe the intervention and let the reader make such judgments.

7.      Avoid exaggerations. Use of words like ‘all’, ‘always’, ‘never’, ‘impossible’, ‘proof’, ‘must’, and so on are difficult to defend. The reader is likely to start generating exceptions to such claims. Modest claims are typically more effective. Rather than claim that a study conclusively proves a point, a more likely conclusion is that a study suggests something of significance. Likewise, avoid multiple modifiers for a noun – rather than say, for example, “X was a highly articulate person” it is sufficient to say that “X was articulate.” 

8.      Cite the most credible and reliable sources for each of your major points. Rarely is it the case that one invents something altogether new. Rather, one may be building on the work of others to extend that work in some way. Failure to recognize the well known work of others will detract from the credibility of your own work. Moreover, while  you may think that a certain point is obvious, if that point has been argued effectively by an established scholar, give that scholar the credit when making the same point.

9.      Structure a paper so that it tells a story. Begin with the scope and purpose – tell the reader where you are headed. Then develop an organizational framework that builds up to the main point in a logical and coherent manner. Keep the focus on where you are headed, and remind the reader why you are covering specific topics along the way. Resist the temptation to tell everything you might know about related subjects – always stay focused on the major point(s) and resist telling the reader about everything you learned in the process of developing a concept or conducting a study.

10.  Be sure you are familiar with the requirements of the publication venue and with representative pieces previously published in that venue.

11.  Recognize that one cannot conduct a perfect study or a perfect conceptual framework. There are usually limitations and constraints. These should be recognized in the paper. Modesty and humility can be powerful allies in making your reasoning effective.

12.  Recognize that one cannot write a perfect paper. Once you have a draft, have a colleague read it and provide feedback. You do not want simple praise at this point – you want constructive criticism that will help improve the coherence and clarity of the paper.

Tensions between Educational Research and Practice

I recently participated in a meeting sponsored by the US Department of Education for project directors and evaluators award i3 (Investing In Innovation) grants. I am the lead evaluator on one of those 49 projects. It is clear that the overarching purpose of the i3 program is to improve educational practice (in terms of learning outcomes and quality of instruction) in America’s schools. It is also clear that the grantees are expected to have and implement very high quality research and evaluation plans to support claims about improved learning and instruction. There were many references to the What Works Clearinghouse and its standards (see http://ies.ed.gov/ncee/wwc/). If one does a search on the word ‘learning’ in the category of ‘evaluation reports’ one finds only one entry since January 1, 2009. Perhaps this is why some people refer to this site as the “Nothing Works Clearinghouse.”Entries in the Clearinghouse must meet specific standards set by the Institute for Education Sciences (IES; see http://ies.ed.gov/).

It occurs to me that there is some tension with regard to what IES and some educational researchers might regard as clear and convincing evidence that a particular intervention (instructional approach, strategy, technology, teacher training, etc.) works well with certain groups of students compared with what some educational practitioners would be inclined to accept as clear and convincing evidence. The stakes are different for these two groups. IES and its researchers are spending federal dollars – often quite a lot of money – to make systemic and systematic improvements in learning and instruction. They are accountable to congress and the nation who want to see a certain kind of evidence that investments have been used wisely. These people do not have to take the implications of findings back into classrooms.

On the other hand, educational practitioners do have to go into classrooms and their primary responsibility is doing their best, given many serious constraints and limitations, to improve the learning and instruction that occurs in our schools. Teachers are the ones who will put new instructional approaches, strategies and technologies into practice. Teachers are not trained in experimental design and advanced statistical analysis. Teachers are trained in implementing curricula appropriate for their students. While the experimental research may show that using an interactive whiteboard rather than a non-interactive whiteboard has no significant difference in terms of measured student outcomes, a teacher may believe that such use does gain and maintain the attention of students and result in a more well organized lesson, or something else that is not so easily measured. One can imagine other cases where the experimental research suggests no significant difference in X compared with Y but teachers believe that there are significant differences of some kind involved.

Should we simply disregard these teachers and only support the very few things that appear to have clear and convincing evidence of effectiveness as determined by IES standards? Should we expect teachers to understand the sophisticated statistical analysis that supports that kind of clear and convincing evidence? If so, then perhaps we ought to expect those making policy and funding decisions to understand the realities of teaching in a classroom for six or more hours every day. It strikes me that what is needed is research that can be practically implemented in classrooms that has reasonable evidence of effectiveness which can be understood by teachers. These teachers must be properly trained and supported in implementing innovations, which means their schools and school districts must understand both the value and likely impact of an innovation and the need to properly support such innovations.

This now comes full circle, since such innovations typically require funds, which means that parents and the community must then be convinced of the value of properly supporting education and electing officials who will provide the necessary local, state, and national support. What matters in the end is not the quality of educational research findings but the quality of professional teaching practice. I would like to see much less distance between [federally funded] educational research and [locally funded] educational practice. I would like to see research aimed at promoting teachers in achieving their widely held goals rather than research aimed at promoting the careers of researchers and program officials at federal agencies. It is clear that conducting rigorous randomized control trials and quasi-experimental studies in school settings presents serious challenges for those collecting and analyzing data – much more serious than that associated with similar kinds of studies in other sectors, such as medical care or computer science (which are admittedly complex and challenging areas for research). The variations in students, teachers, schools, communities, subject areas, and more make classroom practice a very tough research area. As a result, increasingly sophisticated analytical techniques are emerging which only a few researchers understand and can implement. The worry I am trying to express is that we may be closing the door on evidence that should be considered and might prove quite practical and effective in the classroom. We may be creating a research area that is closed to all except for an elite few who do not have to put findings into practice in the classroom. Is this an unfounded worry?

Teacher- and Learner-Centered Approaches

It has now been some time since I have made an entry in this blog. Perhaps no one is listening. No matter. I am writing mostly for myself – to try to become more clear in my thinking. Being snowed in for three days in Athens, Georgia has helped. Lately, I have been thinking about false dichotomies and misguided distinctions.

There is a legitimate distinction between teacher-centered and learning-centered approaches to instruction. However, this distinction is widely misunderstood and misrepresented. Teacher-centered approaches tend to emphasize the activities that a teacher will use to promote learning. Learner-centered approaches tend to emphasize the activities that will engage learners and result in desired outcomes. Stated in this way, the two approaches are not mutually exclusive nor are they necessarily incompatible. Because the goals of most teachers and instructional designers involve actions and activities that will result in improved learning and desired learning outcomes, a teacher-centered approach is likely to take into account those activities that are likely to be engaging and meaningful for learners. Moreover, once learner-centered activities are identified and elaborated, it is quite natural to consider how teachers can best support those activities. Considered this way, one can say that the difference has to do with emphasis and where one begins analysis and planning to support learning. The optimum end result is likely to include both learner-centered activities and teacher-centered support.

Imagine a Venn diagram (see the figure below) with a circle for teacher-centered approaches and an intersecting circle for learner-centered approaches. This results in four distinct areas: (1) teacher-centered without any learner centering (quite rare), (2) learner-centered without any teacher-centering (also quite rare), (3) both teacher- and learner-centered (highly desirable), and (4) neither teacher- or learner-centered (e.g., some museum environments). Associated with these two approaches is a continuum from structured, directed learning environments to unstructured, open-ended learning environments. Evidence suggests that the extreme ends of this continuum are not likely to be especially effective for a great many learners. Rather, some structure and directed learning blended with some open-ended activities are likely to engage many learners and result in desired learning outcomes, including a desire on the part of learners to pursue further study in the subject area.

A challenge for instructional designers is to determine for which learning tasks and learners it is appropriate to include more emphasis on structured learning or open-ended learning. A challenge for teachers is to realize that the roles and responsibilities are different depending on the nature of the particular learning activity. A challenge for learners is to realize the value of the particular approach and activity in which they are engaged – their roles and responsibilities are also somewhat in these different kinds of activities.

The question is not which approach to always use. The question is which kind of approach is likely to be successful for the particular goals, tasks, and learners involved. A thoughtful and reflective teacher or instructional designer will see value in both kinds of approaches. A thoughtful and reflective student is likely to succeed if the approach is clear and appropriate for that learner’s particular situation. This is not intended to be a middle-of-the road response to the debate about teacher-centered and learner-centered approached. It is intended to be a muddle-elimination response that recognizes the value of significant evidence in support of both approaches in different situations.

For example, a person who is not familiar with structural equation modeling is likely to desire and benefit from a structured, directed learning approach from a highly qualified expert with feedback on representative tasks that gradually build up competence and confidence. However, a person who is somewhat familiar with meta-analysis is likely to desire and benefit from a more open-ended approach with a highly qualified expert on hand to guide and suggest improvements in various learning tasks and activities. In summary, the two approaches are not mutually exclusive nor are they incompatible. In effective instruction, they are more likely to be blended together with both directed and open-ended learning activities.

http://dl.dropbox.com/u/4943446/teacher-learner-centered-figure.jpg 

Incantation on Constructivism

The world is wide and mysterious to the willing eye …

To a trained ear, sometimes loud and often off-key …

A wonderland of sensations for the child at play …

A lifetime of experience each and every day …

Where is the meaning in what we see and hear?

How to make sense of experiences that come our way?

What can be gathered from coincidence that will last?

Ludwig said that we picture facts to ourselves …

We create internal representations to make sense …

Ludwig noted that we talk about these pictures with others … we externalize …

Is it not amazing that we create internal representations to make sense of experience?

Is it not amazing that we engage in language games to make sense of those representations?

Well, that is what we do, it seems … there is no stopping it …

We are meaning makers … even when we are making mean …

An anti-meanness message embedded in an incantation on meaning …

The message here is simple … plain and unflavored …

We are constructors of meaning regardless of what is happening here and there …

We construct meaning regardless … that’s our nature … it’s what we do …

Construct this … a new movie … starring ... none other than … YOU!


J. Michael Spector (12 Nov 2010)

The Times They Are Changing

AECT 2010 has come and gone. Now I am the Immediate Past-President with new and different responsibilities, including finding folks to run for President-elect next year and serving as the AECT Board liaison to the ECT Foundation. The conference was a tremendous success, thanks to Barbara Lockee, Miriam Larson, Lois Freeland and Dalinda Bond. The organization is healthy with new collaborators and affiliates all around the world; there were 30 Indonesians at AECT 2010 and they added insight and diversity to a meeting already quite rich in terms of quality and multiple perspectives. AECT is now in the very capable hands of Barbara Lockee.

The American educational system, however, does not have such a bright outlook, especially with the November 2nd election looming large in the USA. I wish I could somehow magically transfer what I have learned working with Indonesians the last five years to the voters who decide how well to support their school districts and schools. I have seen how highly Indonesians value education, from remotely located multi-grade rural schools to the Ministry of Education. It is not just talk about how an education should be valued - the Indonesians are putting substance and meaning to such words. It seems like we used to do that in America, and I am sure it happens here and there ... but considered as a large-scale system, my sense is that American public education is faltering.

With my new found free time I wish I could think of something to do that would yield substantial and sustained improvement, but I just do not know what would really help. Please help me learn how to help improve our schools - I am a slow learner, but I am willing to learn.

Mike Spector

Is Educational Technology a Discipline?

The question about whether or not educational technology is a discipline is not new. One can imagine at least three contexts for such a question. First, it might be motivated in response to those who question or fail to appreciate what educational technologists do. Second, it might be motivated by efforts to consolidate programs/units and cut costs. Third, it might be motivated by educational technology professionals (instructional designers, technology and media specialists, performance technologists, training developers, university professors, etc.) who are seeking to identify the central theories and principles that drive educational technology research and practice. My main interest here is with the third context, but I feel compelled to comment on the first two as well.

An academic discipline can be defined in an operational way as simply any field of study or branch of knowledge that is typically taught and researched at the college or university level. Using that simple and straightforward definition, one would conclude that educational technology is a discipline, at least in North America, as there are relevant courses and programs at many colleges and universities in educational technology, instructional design, instructional systems, instructional technology, learning design and technology, and so on. These program prepare professionals for careers in many contexts, including business and industry, higher education, secondary and elementary education, and governmental and non-governmental agencies. Positions in these contexts include school library media specialists, technology coordinators, instructional designers, program evaluators, training developers, training managers, performance technologists, curriculum planners, among others. In addition to there being university programs and recognized jobs in a wide variety of contexts, there are professional associations that support the work these professionals, including the Association for Educational Communications and Technology (AECT), the International Society for Performance Improvement (ISPI), the International Society for Technology in Education, the Instructional Technology Special Interest Group of the American Educational Research Association, and many more. Moreover, there are many journals and professional publications that support the research and practice of educational technology professionals.

Given the abundant evidence, one might wonder who would ask such a question. Such a question could be a form of challenge or even a form of disparagement by someone who simply does not understand or appreciate the challenges and specific knowledge and skills required to effectively plan, design, implement, evaluate, and manage instructional programs, learning environments and performance support systems. One response to such a person that I have found effective is to ask that person about an educational goal he or she might have set for students. I then explore how that person elaborates the goal in terms of specific objectives, learning activities and assessments. This usually turns the conversation into something productive and much less challenging and confrontational. However, there is no cure for arrogance, and I have also had to simply walk away from such discussions.

In response to those who pose the question because of cost-cutting considerations and program consolidation, I can only say that it makes sense to keep the conversation focused. It is one thing to cut costs and consolidate programs. It is quite another to go to argue that the newly merged mega-department reflects the real discipline and the merged programs did not really reflect separate disciplines. One can concede the need to cut costs without giving up the identity of a program or discipline – and that is the best one can do once the economic planners take over. In short, the justification for consolidating programs need not include any claims about the legitimacy of a discipline. I urge those who might be involved in such efforts to make this distinction very clear to the cost cutters and program choppers.

Finally we start to get to the heart and soul of the question. What are the theories and principles that drive our research and practice? We are asking the question – not someone else who wants to eliminate or disparage our program. We want to know what our core knowledge base is and what the primary kinds of problems and issues are that define us as a discipline. This is a legitimate form of the question, I think. I am reminded of similar questions that arose in the early years of applied computing in what is now the well-established software engineering community. Much soul searching went on in response to computer scientists were brow beating a group they viewed as having inferior knowledge and skills (the first type of question indicated earlier). That led those in the community to accept the question and go on to define themselves in terms of knowledge and skills that were different from those of traditional computer scientists. Our situation is somewhat akin to that, but there are additional factors to consider. We work in the education sector. Unfortunately there are many people who imagine themselves as educational specialists simply because they managed to survive or even thrive in a particular educational system. There are some who think our principles are obvious, common sense ideas or perhaps vague, feel-good notions. Others fail to understand and appreciate the differences between basic research contexts and applied, real-world settings that have constraints and unanticipated and dynamic factors requiring attention.

So, what are the foundation and guiding theories and principles of educational technology? There are very good books that one might consult to begin answering this question. Among the more notable are: (a) a classic text is Instructional Technology Foundations edited by Robert Gagné; (b) a more recent classic is Principles of Instructional Design by Bob Gagné, Walt Wager, Katharine Golas, and John Keller; (c) The Conditions of Learning (4th ed.) by Gagné should be considered a foundation piece; and (d) the International Encyclopaedia of Educational Technology edited by Tjeerd Plomp and Don Ely is another good source. One could also visit the Websites of the Association for Educational Communications and Technology (www.aect.org) and the International Board of Standards for Training, Performance and Instruction (www.ibspti.org) and find pointers to other relevant sources and considerations.

In these short remarks, I want to add my initial take on our foundation. I think our foundations come primarily from the learning of psychology, broadly conceived to include communications theory and the role of mental models and language. There are many principles on which we build that can be located at this level, including, for example, the familiar limitations of short term memory that has strong implications for the design of units of instruction and computer interfaces. I am referring, of course, to George Miller’s (1956) claim that people typically can only hold about seven (plus or minus two) information chunks in short-term memory at any given point in time (in the case of administrators, it is minus two … in the case of digital happy teens, it plus two … in the case of aging authors of blogs such as this, the actual number approaches one). Figure 1 reflects one way to imagine the underlying foundations of our discipline. There are others ways to depict educational technology, such as layers (an onion metaphor) or pillars (a bridge metaphor), and so on. If one were to examine a number of these representations, I am convinced that there would be a great deal of similarity and overlap, which is further evidence that educational technology is an important discipline.

I close with my memory of what Bob Gagné once told me: “Our goal is to help people learn better.” When one begins to reflect on that goal, one will surely be left thinking that we have a huge responsibility. It is probably more productive to focus on that goal rather than spend time worrying about whether or not educational technology is a discipline.

References

Gagné, R. M. (1985). The conditions of learning and theory of instruction (4th ed.). New York: Holt, Rinehart, & Winston.

Gagné, R. M. (Ed.) (1987). Instructional technology foundations. Hillsdale, NJ: Erlbaum.

Gagné, R. M., Wager, W. W., Golas, K., & Keller, J. M. (2005). Principles of Instructional design (5th ed.). New York: Wadsworth.

Miller, G. A. (1956). The magical number seven, plus or minus two: Some limits in our capacity for processing information. Psychology Review, 63(2), 81-97.

Plomp, T., & Ely, D. P. (1998). The international encyclopaedia of educational technology (2nd ed.). Dordrecht: Springer.

Unstated and Implicit Learning Goals

A long-established principle within instructional systems design is to be complete and clear in analyzing learning needs and transforming those needs into learning goals and objectives (Dick, Carey, & Carey, 2009). It can and does happen, however, that a careful needs assessment can fail to uncover unstated goals. I recall an effort involving the development of a computer-based lesson for Air Force electronics training. Such training for newly recruited enlisted personnel took place at a Technical Training Center where senior enlisted personnel (non-commissioned officers; NCOs) led face-to-face lessons. The needs assessment was motivated by the lack of available of senior NCOs. The requirement then became to replace some of the instructor-led lessons with computer-based lessons. For the targeted subject matter, this was relatively easy as the things to be learned were primarily concepts pertaining to electronics along with some simple procedures to perform diagnostic tests. When a first prototype of a representative lesson had been constructed, the training commander rejected it because it did not include any of the behaviors and demeanor of senior NCOs. The designer’s natural question was “What does that have to do with electronics?” The commander replied that one goal of basic electronics training was to show recently recruited personnel how enlisted personnel were expected to behave. Fortunately, the change to include modeling NCO behavior was easily incorporated into the computer-based lessons using video clips.

What is happening in public schools in this era of high stakes testing and accountability? The needs assessments and content analyses have supposedly been conducted and specific learning objectives developed. Test items are allegedly linked to those learning objectives. Schools and teachers are evaluated based on how well the children do on standardized tests. I am wondering how this emphasis on high stakes testing is transforming our educational system. Objectives should also be linked to overall goals and not simply linked to the analysis of content. What are the goals that we expect of an educational system? Would we not like children who spend twelve or more years in school to develop certain behaviors that might be associated with responsible citizenship? Might there be a parallel in public school settings with the situation in technical training? Might we want children to see responsible adult behavior and have them begin to act accordingly just as the training commander wanted new recruits to see exemplary military behavior and to begin to act accordingly? What is not being tested and, as a consequence, not being rewarded in this era of high stakes testing? Do we test how well a child gets along with others? Do we test how collaborative a child is? Do we test a child’s ability to think critically and act ethically? Would we like such things to be part of a child’s education? If so, why are they not tested or emphasized in the same way that reading skills are tested? The notion of a progressive education that emphasized critical thinking, inquiry, and social responsibility (Dewey, 1938) seems to be altogether missing in the current environment of high stakes testing.

My small thought on this subject is just this: be careful what you wish for because you just might get it. The No Child Left Behind Act (http://ed.gov/nclb/landing.jhtml) and the associated incentives seem designed to bring about an educational system in which children do learn to read and solve standard mathematical problems. Is such a system designed to foster life-long reading and encourage careers in complex and challenging areas such as quantum mechanics or astrophysics? That remains to be seen but the early evidence suggests that high school graduates in the USA are still not seeking higher education and careers in critical areas of science, technology, engineering or mathematics. Moreover, the high-school drop-out rate is alarmingly high (AEA, 2009) as is the juvenile crime rate (http://www.ojjdp.ncjrs.gov/ojstatbb/). Is this not troubling?

I am not suggesting that we ought to reward teachers whose students complete bachelors degrees in STEM subjects and do not commit crimes. This may not be such a bad idea, but it is certainly not simple to implement and it would surely introduce other disparities into an already complex educational system. What I am suggesting is that military commanders did trust their NCOs to model exemplary behavior and instill high standards of demeanor in recruits. Perhaps we should trust out teachers to model socially responsible behavior and instill high standards of demeanor in their students. Perhaps we could also trust our teachers to instill a sense of inquiry and other desirable habits of the mind. Maybe we ought to trust our teachers rather than treat them like servers in a cafeteria.

References

AEA (Alliance for Excellent Education) (2009). High school dropouts in America. Washington, DC: Allilance for Excellent Education. Retrieved from http://www.all4ed.org/files/GraduationRates_FactSheet.pdf April 20, 2010

Dewey, J. (1938). Experience and education. New York: Macmillan.

Dick, W., Carey, L., & Carey, J. O, (2009). The systematic design of instruction (7th ed.). Columbus, OH: Allyn & Bacon.

Scientific Terminology

Feedback on the third edition of the Handbook of Research on Educational Communications and Technology (Spector, Merrill, van Merriënboer & Driscoll, 2008) suggests that there is a need to clarify basic scientific terminology, such as ‘theory’, ‘model’, ‘principle’ and ‘hypothesis’. A discussion at the 2009 AECT Session on “Building the Scientific Mind” led by Jan Visser suggests that additional terms also require clarification – namely, ‘perspective’, ‘approach’, ‘framework’, and ‘implication’. The editors of the 4th edition of the Handbook (Mike Spector, Dave Merrill, M. J. Bishop, and Jan Elen) are discussing having a chapter devoted to the use of these scientific terms in the context of instructional design and educational technology research. Meanwhile, I thought I might venture into this terrain myself to see where I might trip or falter.

These terms are the source of confusion and misunderstanding outside the domain of educational research as well. For example, the word ‘theory’ has an everyday, non-scientific use that is roughly equivalent to ‘supposition’. A person discussing why gasoline prices are high with another might say something like this: “My theory is that the oil companies are being greedy and manipulating prices to maximize profits.” That person could have used ‘supposition’ or ‘guess’ or ‘hunch’ or perhaps ‘belief’. In this case, the word ‘theory’ is used to refer to a particular claim. In science, ‘theory’ typically refers to a body of knowledge represented by a set of related claims. Moreover, a scientific theory typically has implications for what might happen in the future in addition to providing a basis for explanations of observed phenomena.

In short, the word ‘theory’ has a very different meaning when used in the context of scientific inquiry. In science, a theory is generally regarded as a set of well-established statements and principles that are used to explain groups of facts or a range of observed phenomena. The confusion about these two meanings of ‘theory’ is most evident in debates about the theory of evolution. Certain religious groups who advocate creationism use the word ‘theory’ in the informal, non-scientific sense when referring to the theory of evolution. Biologists and other scientists use the word ‘theory’ in the phrase ‘theory of evolution’ in the second sense. In effect, the two groups are talking about different things. It is worth adding that scientists are interested in explaining many observed facts, such as genetic changes in populations of organisms over successive generations and long periods of time. Moreover, two major processes comprise the modern theory of evolution – natural selection and genetic drift or mutation. Evolutionary biologists can explain a large number of observed facts and make predictions with regard to as yet unobserved phenomena. Creationists, on the other hand, are not trying to explain any particular set of facts. Rather, they are advocating a particular religious doctrine (or a specific claim) with regard to the origin of all things.

A further difference is that scientific claims, including scientific theories, are generally subject to refutation; that is to say that the scientist making a claim or defending a theory is, in principle, willing to be shown that the claim is wrong or the theory wrong-headed. The willingness and readiness to be wrong is what makes scientific progress possible (Popper, 1963, 1972). Kuhn (1962) and others argue that scientific theories are quite resistant to change and scientists are not nearly as willing as Popper suggests to embrace refutation of a long-held or well-established theory. In spite of such variations within the scientific community, I shall proceed with the scientific notion of ‘theory’ while acknowledging variations in interpretation.

In these notes, I am interested in the scientific use of ‘theory’ as it pertains to instructional design and educational technology research. Reigeluth (1983) notes that instructional design theory is primarily prescriptive in nature, rather than being descriptive in the way that learning theory is. For example, a cognitive theory of learning might involve a set of related claims about the role of mental models and schema in the development of expertise and understanding. Descriptive claim within a mental model theory of learning might be that (a) people construct internal representations to make sense of new or unexplained phenomena, and (b) these internal representations are created just when needed and are relatively transitory. Both claims are descriptive and could in principle shown to be wrong. An instructional design theory that builds on mental model theory might include, for example, these claims: (a) learners who do not have pre-existing experience with or knowledge in a particular area will progress more rapidly if provided an elaborated version of an expert’s mental model, and (b) learners with significant prior knowledge and experience will be inhibited or slowed down when presented an expert model in the course of designing a solution to a complex problem situation. These claims are prescriptive in the sense that they suggest how best to support learning, and, like descriptive claims, they could turn out to be wrong.

I want to work from the inside out – that is to say I want to consider a claim in educational technology research and then work backwards toward principles, models and theories that might be relevant.

A Claim: Attrition in first-year college calculus courses for non-mathematics majors is high because students do not see any relevance of calculus in their daily lives on in their careers. Note that I am not suggesting that this claim is true; in fact, it assumes facts not yet accepted – namely, that attrition in such courses is higher than in other courses. The instructional design claim that follows this claim would be something like this: First-year college calculus courses for non-mathematics majors will have a reduced attrition rate if issues of relevance are addressed early and throughout the course.

A Principle: What body of relevant instructional design knowledge might be relevant? What existing instructional design principles could be invoked to support the claim that devoting explicit time to issues of relevance will improve attrition? One might cite the first of Gagné’s (1985) nine events of instruction – namely, gain and maintain the attention of the learner in order to make learning effective. Citing relevance of what is to be learned might be one way to do this. Another principle that might be cited could be one of Merrill’s (2002) first principles of instruction – namely, help the learner integrate what has been learned into daily activities. Both principles suggest what can be done to help make learning activities more effective. As with other principles, either or both may turn out not to make a significant difference in terms of learning outcomes in particular contexts.

A Model: A model goes beyond principles and might be conceived of a bridge between a theory and a set of principles. A model can guide the articulation and instantiation of principles within the context of a particular theory. Both of the principles cited previously have associated models. Gagné (1985) presented nine events and subsequently articulated a model for implementing those events (Gagné, 1993). In that model, Gagné argued that the nine events did not need to occur in any particular order and they could often be grouped into three phases of instruction and treated together (set-up phase, primary presentation phase, resolution phase). Likewise, Merrill’s principle is one of five that include centering instruction around problems, activating prior knowledge (of individual or groups of learners), demonstrating new knowledge, applying the new knowledge to practical problems (whole tasks) with opportunities to practice with feedback, and helping learners integrate new knowledge in their daily lives or professional activities. In both cases, the individual principles are parts of a prescriptive model intended to guide the creation of effective learning. These sets of principles, with their interconnections and relationships one to another, comprise a model. At least that represents one kind of instructional model.

A Theory: The difference models and theories may be difficult to establish in the domain of instructional design and educational technology. For example, cognitive apprenticeship (Collins, 1991) is sometimes called an instructional design theory, sometimes an instructional design model, and sometimes an instructional design method. I am inclined to think of cognitive apprenticeship as another model comprised of a set of principles – that is to say that I view cognitive apprenticeship as more akin to Gagné’s nine events and Merrill’s first principles. A theory that might be associated with these three models (Gagné’s nine events, Merrill’s first principles, and Collins’ cognitive apprenticeship) might be situated theory (Lave & Wenger, 1990). Situated learning postulates, in one sense, that learning that is situated within a meaningful problem solving context, will be more effective than learning that is disassociated from meaningful problem solving contexts. This is a prescriptive theory. It is closely associated with and linked to a descriptive theory about learning – namely, the notion that people create internal representations in order to make sense of puzzling situations and new experiences. In other words, meaning is created or constructed in the context of specific situations. Meaning is context sensitive, in that sense. My general point is that a prescriptive instructional design theory could and probably should be motivated by a closely associated and established descriptive theory of learning.

Concluding Remarks
While these remarks may seem focused on individual words, my concern is not with particular words but, rather, with the thinking associated with scientific inquiry in instructional design and educational technology. My elaboration of these terms is probably naïve and perhaps wrongheaded on key points. I hope others will provide insights and improved representations. I do believe that we need to be careful in our use of scientific terminology. An instructional design theory should represent a set of well-established principles which can be used to generate prescriptions for designing effective learning support in a variety of circumstances. There may well exist many instructional design models (Andrews and Goodson, 1980), but one would expect there to be only a small number of instructional design theories. We need to take the scientific aspects of our instructional design and educational technologies activities seriously. I believe this because I believe that progress in instructional design and educational technology will depend on adopting principled, evidence-based approaches rather than relying on loosely held beliefs and advocating positions that are in vogue.

References
Andrews, D. H., & Goodson, L. A. (1980). A comparative analysis of models of instructional design. Journal of Instructional Development, 3(4), 2-16.

Collins, A. (1991). Cognitive apprenticeship and instructional technology. In L. Idol & B.F. Jones (Eds.), Educational values and cognitive instruction: Implication for reform (pp. 121-138). Hillsdale, NJ: Lawrence Erlbaum Associates.

Gagné, R. M. (1985). The conditions of learning (4th ed.) New York: Holt, Rinehart, & Winston.

Gagné, R. M. (1993). Computer-based instructional guidance. In J. M. Spector, M. C. Polson, & D. J. Muraida (Eds.), Automated instructional design: Concepts and issues (pp. 133-146). Englewood Cliffs, NJ: Educational Technology Publications.

Lave, J., & Wenger, E. (1990). Situated learning: Legitimate periperal participation. Cambridge, UK: Cambridge University Press.

Merrill, M. D. (2002). First principles of instruction. Educational Technology Research & Development, 50(3), 43-59.

Kuhn, T. S. (1962). The structure of scientific revolutions. Chicago: University of Chicago Press.

Popper, K. (1963). Conjectures and refutations: The growth of scientific knowledge. London: Routledge.

Popper, K. (1972). Objective knowledge: An evolutionary approach. Oxford, UK: Clarendon Press.

Reigeluth, C. M. (Ed.) (1983). Instructional-design theories and models: An overview of their current status. Hillsdale, NJ: Lawrence Erlbaum Associates.

Spector, J. M., Merrill, M. D., van Merriënboer, J. J. G., & Driscoll, M. (Eds.) (2008). Handbook of research on educational communications and technology (3rd ed.). New York: Routledge.