Helping students understand and generate appropriate hypotheses and test their subsequent predictions – in science in general and biology in particular – should be at the core of teaching the nature of science. However, there is much confusion among students and teachers about the difference between hypotheses and predictions. Here, I present evidence of the problem and describe steps that scientists actually follow when employing scientific reasoning strategies. This is followed by a proposed solution for helping students effectively explore this important aspect of the nature of science.

## Introduction

I taught high school biology and chemistry for 8 years before beginning a doctoral program in ecology and environmental science at the University of Illinois. Graduate school revealed that, while I had been effective in teaching science content to my students, I had mostly failed in teaching them the nature of science (NOS). Indeed, I had even promoted several of the myths of science outlined by McComas (1996) – most blatantly that “a hypothesis is an educated guess” and “science is procedural more than creative.” I had even failed at understanding and teaching the hypothetico-deductive method of science that so many science teachers (this author included) mislead their students into thinking is the only way to practice science: formulate a hypothesis, deduce its consequences (make a prediction), and observe those consequences (perform an experiment and collect data).

For example, in my second year of graduate school, a chance conversation in the woods with one of my committee members revealed my own shortfalls. When pressed for the hypothesis I was testing with my research, I delivered the prediction that if we had an average spring warm-up, then the timing of leaf growth, caterpillar hatching, and bird migration would be synchronized, but if we had an early or late spring, there would be a mismatch in one or more of the trophic levels. I had given my committee member an “educated guess,” an “If…, then…” statement exactly in the form I had learned in my science classes and identical to how I had taught my high school students to write hypotheses. While I may have based my prediction on some overarching patterns or underlying mechanisms that were already known for the community interactions I was studying, I certainly could not verbalize them.

Since returning to teaching high school biology after graduate school, I work to help my students hone the scientific reasoning strategies of abduction (ingenuity, or borrowing an idea from earlier studies), deduction, and induction. But with such an NOS focus in my classroom on these reasoning skills, I have become somewhat hypersensitive to moments when students get it wrong – for example, when students inappropriately marry a method with the tail end of a deductive statement (If I do X, then Y will happen) and call it a “hypothesis.”

Most commonly in scientific research, a hypothesis is a tentative, testable, and falsifiable statement that explains some observed phenomenon in nature. We more specifically call this kind of statement an explanatory hypothesis. However, as we will see, a hypothesis can also be a statement that describes an observed pattern in nature. We call this kind a generalizing hypothesis.

In the sections that follow, I present evidence that students, teachers, textbooks, and even practicing scientists confuse predictions with hypotheses. I then discuss the ways the terms are defined and used in the logical practice of scientific reasoning. Finally, I provide some simple ideas for how we can improve the teaching of NOS in the classroom.

## There Is a Problem: Data from the Field

In 2006, I chaperoned a group of high school students presenting precollege research at the Intel International Science and Engineering Fair (Intel ISEF) in Indianapolis. Upon inspection of a wide range of student poster presentations, I observed that several students had written predictions on their posters but labeled them “hypotheses.” In the interest of quantifying this misconception, I quickly designed a small survey and randomly sampled all non-engineering and non-math projects with project numbers ending in 1, 4, or 7 (n = 127). In this initial survey, 78 (80%) of 98 student posters reviewed had incorrectly identified a prediction as a hypothesis.

Where had these students gone wrong or been misled during their formal science education or in their science-fair preparation work? Indeed, it is human nature to formulate explanations for observed natural phenomena (Brewer et al., 1998; Lawson, 2004). Cognitive scientists sometimes argue that children are themselves “little scientists.” For example, children with little or no formal training in the process of science can propose functional hypotheses to explain a natural event (Vosniadou & Brewer, 1992) and causal hypotheses to explain how one event in nature may affect another (Samarapungavan & Wiers, 1997). Have we, the science educators, excised reasoning skill from our students?

For the Intel ISEF Indianapolis survey and other surveys I report next, I followed the definitions of hypotheses described above, as candidate explanations or generalizations for observations seen in nature. If a proposed explanation or generalization of a pattern is valid, then we can anticipate (predict) a particular outcome from an experiment or that we will see the pattern elsewhere in nature. Therefore, a scientific hypothesis can lead to predictions (Singer, 2007; Campbell et al., 2008) but is not, itself, “just a prediction” (a very common misconception).

### Students

My interest in student misunderstanding of the hypothesis was piqued at the 2006 Intel ISEF, so colleagues and I have now surveyed 1864 student projects at eight Intel ISEF competitions (2006, 2008–2014; Table 1). Students in the sample identified hypotheses on 1448 (78%) of these projects but wrote predictions 81.2% of the time; they wrote candidate explanations or generalizations on only 272 (18.8%) of the projects (Table 2). Failure to write hypotheses was consistently greater than success across years, and the two groups were statistically distinguishable (paired t-test: t = 20.55, df = 7, P < 0.001). Informal interviews with students revealed that while some could explain their research as hypothesis-driven, these students could not avoid predictive statements (e.g., “If I do X, then Y will happen”).

Table 1
Summary of data collected at eight different Intel International Science and Engineering Fair (ISEF) competitions.
ISEF CompetitionsTotal Projects SurveyedA Hypothesis Identified and Correctly ConstructedA Hypothesis Identified but Written as a Prediction
n%n%
Indianapolis, 2006 127 20 20.4 78 79.6
Atlanta, 2008 199 20 14.1 122 85.9
Reno, 2009 248 29 14.1 177 85.9
San Jose, 2010 256 32 15.4 176 84.6
Los Angeles, 2011 299 41 17.7 190 82.3
Pittsburgh, 2012 230 54 26.0 154 74.0
Phoenix, 2013 225 41 22.8 139 77.2
Los Angeles, 2014 280 35 20.0 140 80.0
Totals 1864 272 $X¯=18.8%$ 1176 $X¯=81.2%$
ISEF CompetitionsTotal Projects SurveyedA Hypothesis Identified and Correctly ConstructedA Hypothesis Identified but Written as a Prediction
n%n%
Indianapolis, 2006 127 20 20.4 78 79.6
Atlanta, 2008 199 20 14.1 122 85.9
Reno, 2009 248 29 14.1 177 85.9
San Jose, 2010 256 32 15.4 176 84.6
Los Angeles, 2011 299 41 17.7 190 82.3
Pittsburgh, 2012 230 54 26.0 154 74.0
Phoenix, 2013 225 41 22.8 139 77.2
Los Angeles, 2014 280 35 20.0 140 80.0
Totals 1864 272 $X¯=18.8%$ 1176 $X¯=81.2%$
Table 2
Authentic examples of incorrectly and correctly written hypotheses from (1) students at the Intel International Science and Engineering Fair (ISEF), (2) science textbooks, (3) teachers, (4) scientific papers, and (5) science educators.
SourceIncorrectCorrect
ISEF students If a plant receives fertilizer, then [it] will grow to be bigger than a plant that doesn't receive fertilizer. It is hypothesized that the structural and functional integrity of the system as a whole is dependent on nerve activity.
I believe resin content of various pine species will affect [their] energy output. The foraging patterns of S. carpocapsae, as measured by directional response, are affected by electrical fields.
It is hypothesized that a forefoot strike pattern will correlate with lower ground reaction forces. Aspirin inhibits key oncogenic factors and/or activates pivotal tumor suppressor genes.
Textbooks If food is present in the aquarium, then snails will move with greater speed (toward the food). (Green, 2004Marsh grass growth is limited by available nitrogen. (Miller & Levine, 2010
Teachers If the farmer burns the prairie then the next year will produce taller plants in his field than the previous year. The fire is replenishing the nutrients in the soil.
Scientists We aimed to test the hypothesis of whether young healthy women will increase muscle mass and lose fat mass after undergoing 12 wk of intense resistance training. (Josse et al., 2010Based on this observation, we hypothesized that natural selection may have influenced AMY1 copy number in certain human populations. (Perry et al., 2007
Science educators published in The American Biology Teacher Micro-eukaryote diversity in the water samples will be different from micro-eukaryote diversity in sediment samples. If this hypothesis is true, we predict that we will obtain different DGGE banding patterns for water/sediment samples. (Lauer et al., 2012In this example, the hypotheses could be that (1) rhizobia increase plant performance and (2) nitrogen fertilizer reduces plants’ dependency on rhizobia. (Suwa & Williamson, 2014
SourceIncorrectCorrect
ISEF students If a plant receives fertilizer, then [it] will grow to be bigger than a plant that doesn't receive fertilizer. It is hypothesized that the structural and functional integrity of the system as a whole is dependent on nerve activity.
I believe resin content of various pine species will affect [their] energy output. The foraging patterns of S. carpocapsae, as measured by directional response, are affected by electrical fields.
It is hypothesized that a forefoot strike pattern will correlate with lower ground reaction forces. Aspirin inhibits key oncogenic factors and/or activates pivotal tumor suppressor genes.
Textbooks If food is present in the aquarium, then snails will move with greater speed (toward the food). (Green, 2004Marsh grass growth is limited by available nitrogen. (Miller & Levine, 2010
Teachers If the farmer burns the prairie then the next year will produce taller plants in his field than the previous year. The fire is replenishing the nutrients in the soil.
Scientists We aimed to test the hypothesis of whether young healthy women will increase muscle mass and lose fat mass after undergoing 12 wk of intense resistance training. (Josse et al., 2010Based on this observation, we hypothesized that natural selection may have influenced AMY1 copy number in certain human populations. (Perry et al., 2007
Science educators published in The American Biology Teacher Micro-eukaryote diversity in the water samples will be different from micro-eukaryote diversity in sediment samples. If this hypothesis is true, we predict that we will obtain different DGGE banding patterns for water/sediment samples. (Lauer et al., 2012In this example, the hypotheses could be that (1) rhizobia increase plant performance and (2) nitrogen fertilizer reduces plants’ dependency on rhizobia. (Suwa & Williamson, 2014

### Textbooks

In addition to the surveys conducted at Intel ISEF, I analyzed 66 current middle school, high school, and college science textbooks by assessing all NOS chapters, all laboratory prompts, and glossaries. Fifty-four of the 66 science textbooks included instruction for understanding the hypothesis; 12 (18%) did not contain any mention of the hypothesis. Forty-two percent of textbooks that mentioned the hypothesis failed by confusing it with a prediction in either (1) the definition of the hypothesis, (2) an example hypothesis, or (3) a lab prompt (e.g., “Propose a hypothesis about what will happen…”) (for more examples, see Table 3). The largest proportion (13 of 17; 76%) of textbooks with this confused definition and/or use of the term hypothesis was in the middle school sample. Six (17%) of the 35 high school science textbooks failed in at least one of the assessed categories. The 14 textbooks designed for the college market (and used in our upper-level, IB, and AP classes) fared best; only one (7%), a biology textbook, failed to teach the hypothesis as distinct from the prediction.

Table 3
Instructional statements with definitions of hypothesis from 3 textbooks (selected from a sample of 66), with an assessment of the ability of each to effectively teach hypothesis and not confuse it with prediction.
TextbookInstructional StatementAssessment
Middle school
Definition: A possible explanation to a set of observations or answer to a scientific question. (p. 15)
Example: If I add salt to fresh water, then the water will freeze at a lower temperature. (p. 810)
Lab prompt: Write a hypothesis for an experiment you could perform to answer your question. (p. 27)
The definition is correct, but the example is incorrect – it is a method followed by a prediction. The lab prompt is written in a way that may encourage students to write a prediction.
Biology (Miller & Levine, 2010)
High school
Definition: A scientific explanation for a set of observations that can be tested in ways that support or reject it. (p. 7)
Example: Marsh grass growth is limited by available nitrogen. (p. 6)
Lab prompt: Form a hypothesis: given the objective of this lab and the materials you have to work with, what kind of change, if any, do you expect to see in the pH of the kimchi over the course of several weeks? (p. 266)
The definition and example are correct. However, the lab prompt is confusing because it instructs students to “form a hypothesis” but then prompts them to write a prediction.
Biology (Campbell et al., 2008)
College
Definition: A tentative answer to a well-framed question – an explanation on trial. (p. 19)
Example: The batteries in the flashlight are dead. (p. 19)
Lab prompt: None
Both the definition and example are correct. No lab prompts appear in this textbook.
TextbookInstructional StatementAssessment
Middle school
Definition: A possible explanation to a set of observations or answer to a scientific question. (p. 15)
Example: If I add salt to fresh water, then the water will freeze at a lower temperature. (p. 810)
Lab prompt: Write a hypothesis for an experiment you could perform to answer your question. (p. 27)
The definition is correct, but the example is incorrect – it is a method followed by a prediction. The lab prompt is written in a way that may encourage students to write a prediction.
Biology (Miller & Levine, 2010)
High school
Definition: A scientific explanation for a set of observations that can be tested in ways that support or reject it. (p. 7)
Example: Marsh grass growth is limited by available nitrogen. (p. 6)
Lab prompt: Form a hypothesis: given the objective of this lab and the materials you have to work with, what kind of change, if any, do you expect to see in the pH of the kimchi over the course of several weeks? (p. 266)
The definition and example are correct. However, the lab prompt is confusing because it instructs students to “form a hypothesis” but then prompts them to write a prediction.
Biology (Campbell et al., 2008)
College
Definition: A tentative answer to a well-framed question – an explanation on trial. (p. 19)
Example: The batteries in the flashlight are dead. (p. 19)
Lab prompt: None
Both the definition and example are correct. No lab prompts appear in this textbook.

### Teachers

I surveyed 17 preservice science teachers in a graduate-level teacher preparation course focused on NOS at the University of Colorado; and 59 biology teachers, selected at random (a convenience sample), at the 2011 annual meeting of the National Association of Biology Teachers (NABT). I gave both groups (on the first day of the term for the students in the science education course) a “pop quiz” on paper that asked them to (1) write a definition of the hypothesis in science; and, after reading a set of observations, (2) write a hypothesis about the observations that could be tested with an experiment. In the science education course, 5 of the 17 teacher-candidates (29%) showed mastery of the hypothesis, while 12 (71%) confused the hypothesis with the prediction. Less than half of all responders (27/59; 45%) at the NABT meeting exhibited a genuine understanding of scientific hypotheses. Thirteen (48%) of the 27 responders with correct understanding were biology teachers with Ph.D. degrees.

As a comparison, Lawson (2002) reported that in a sample of preservice middle and high school biology teachers, 96% “confused hypotheses with predictions and agreed with the statement that a hypothesis is an educated guess of what will be observed under certain conditions.” If this situation is not addressed explicitly, teachers are likely to pass this misunderstanding on to their students.

### Scientists

I analyzed 300 peer-reviewed, published scientific papers that are part of a teaching collection I have accumulated over several years of teaching various biology courses. The papers are mostly from fields of biology in which hypothesis testing is common, but other fields of science are also represented, as well as science education papers (including several papers published in The American Biology Teacher). Sixty-two percent (186/300) of the scientific papers analyzed use some form of the term (hypothesis, hypotheses, hypothesize, or hypothesized), and 12.3% (23/186) mislabel predictions as hypotheses. Again, see Table 2 for examples of incorrectly and correctly written hypotheses from students, textbooks, teachers, scientists, and science educators.

## How Should Hypothesis & Prediction Be Defined?

Many textbooks oversimplify the definition of the hypothesis to an educated guess. But as McComas (1996) asks, “An educated guess about what?” Some textbooks do better; in their popular upper-level textbook, Biology, Campbell et al. (2008) define the hypothesis as “A tentative answer to a well-framed question – an explanation on trial” (p. 19) (Table 3). However, getting to that tentative answer or explanation is not as easy as it seems, and many scholars have written about it.

### Generalizing & Explanatory Hypotheses

McComas (1996, 2004, 2015) explains that observations of natural phenomena can produce two strands of hypothetical reasoning: generalizations and explanations. We often use generalizing hypotheses to summarize patterns we observe in nature, and we can refer to these types of hypotheses as immature laws. If the generalizations hold true over and over again, they become established laws of nature. We then use explanatory hypotheses to provide reasons for the generalizations. Explanatory hypotheses can also be referred to as immature theories, because if the explanations survive various angles of rigorous testing they become established theories. Thus, theories can explain laws but never become laws.

As an example, consider Harvard University evolutionary biologist Jonathan Losos, who, with his colleagues, studies the Anolis lizards of the Caribbean Islands. One specific pattern the researchers have consistently observed is that some anoles (e.g., Anolis valencienni) living on narrow twigs in their forest habitats have short legs (Losos & Schneider, 2009). This observed pattern produces the generalization (generalizing hypothesis or immature law) that particular body shapes and sizes in anoles are linked to particular habitats, and we can predict that anoles discovered living on twigs in forests on other islands will also have short legs. Losos and his colleagues proposed that adaptation to their twig habitats by way of natural selection was a likely explanation (explanatory hypothesis or immature theory) for the pattern of short-legged anoles living on twigs. In one experiment to test the twig adaptation hypothesis, small breeding populations of long-legged trunk anoles (A. sangrei) were placed on small anole-free islands with only small-twigged bushes as habitat (Losos et al., 2001). The prediction that follows the twig adaptation hypothesis is that, after several generations, the surviving anole population would have shorter legs as the environment and natural selection sift out the individuals with longer legs that are unable to use the twiggy habitat efficiently. Indeed, later generations of the anoles had significantly shorter legs than their ancestors. Figure 1 illustrates how these ideas are applied to the Anolis lizard example. Teachers might use a figure like this one in direct instruction to explain the situation – or ask students to create one after reading a scientific paper, to check for understanding.

Figure 1.

Two pathways to theories and laws by way of explanatory hypotheses and generalizing hypotheses. Note that both types can generate predictions and that explanatory hypotheses and their resulting theories can provide explanations for generalizing hypotheses and their resulting laws, respectively.

Figure 1.

Two pathways to theories and laws by way of explanatory hypotheses and generalizing hypotheses. Note that both types can generate predictions and that explanatory hypotheses and their resulting theories can provide explanations for generalizing hypotheses and their resulting laws, respectively.

### Abduction, Deduction, & Induction

In the above example, Losos and his colleagues moved through several levels of logic that have been summarized by Lawson (2010). These levels form the basic inferences of scientific reasoning, argumentation, and discovery – they are abduction, deduction, and induction. In noticing the short legs on twig anoles and that they moved easily in their twig habitat, the researchers proposed that the short legs were an adaptation driven by the uniqueness of the twig habitat. Proposing that the twig habitat may have driven the twig anoles to evolve short legs required some imagination and ingenuity on the part of Losos and his colleagues – a logical strategy in science called abduction and also known as the “creative leap” (Langley, 1999). However, sometimes the abductive strategy involves literally abducting (figuratively stealing) an idea from the results of an earlier study. Indeed, adaptation had already been shown as an explanation for traits in other species. For example, different beak shapes and sizes of the Galápagos finches (e.g., the medium ground finch, Geospiza fortis) function as adaptations to different food resources. Perhaps Losos and his colleagues saw the connection between the short legs of the anoles and their twig habitats as an analogy to the small beaks of the medium and small ground finches and the soft seeds the birds eat. In short, abductive reasoning produces explanatory hypotheses, sometimes through leaps of creativity.

If adaptation by natural selection is a reasonable hypothesis for the short legs on the twig anoles, then a logical consequence is that long-legged anoles placed in habitats with only twigs as perches would evolve shorter legs. This second logical strategy is called deduction – the researchers deduced an outcome of an experiment, a prediction, given the “adaptation by natural selection” hypothesis. Thus, deductive reasoning tests ideas with predictions.

When Losos and his colleagues looked at the results of their experiment, they found that the long-legged anoles had evolved shorter legs. They thus logically concluded that the result was in support of their twig habitat hypothesis and was also in support of established natural selection theory. This final logical step is called induction: if the observed result matches the predicted outcome, then the hypothesis is supported.

The process described above is often referred to in textbooks as the hypothetico-deductive strategy of “the scientific method.” It is important to point out here that hypothetico-deductive reasoning, coupled with induction, is not without problems. First, a logical fallacy of induction is affirming the hypothesis without considering other explanations – there may be other hypotheses that explain the observed result. The case may simply be that females prefer to mate with short-legged males. Indeed, false hypotheses can produce true predictions. A second problem with induction is that in designing and carrying out our experiments and affirming our hypotheses, we may unknowingly be making several assumptions, also called auxiliary hypotheses, that if violated throw doubt on our conclusions. For example, Losos and his colleagues assume that leg length in anoles is a strongly heritable trait, similar to beak size in finches. If the trait is not heritable, they will not see their predicted result.

### Solving the Problem of “Hypothesis” in the Science Classroom

The results of the various surveys reported here are evidence that many of our students are not learning how to formulate and propose hypotheses to drive their scientific studies. Even our best science students, those who qualify for the Intel ISEF, are generating predictions but calling them “hypotheses.” These mistakes likely arise from several correctable teaching approaches. First – and perhaps the most commonly observed error in teaching hypothesis writing – is having students write “if…, then…” statements, where the if phrase is actually an experimental method, and the then phrase is a specific prediction. For example, a textbook, a teacher, or a student may propose the prediction, “If fertilizer is added to the soil, then the plants will grow taller,” but call it a hypothesis. Textbooks, teachers, students, and scientists who propose predictions in place of explanations are skipping abduction and analogical reasoning and proceeding directly to making predictions (Lawson, 2004).

The if–then mistake is correctable. For example, when my students verbalize or write predictions and call or label them “hypotheses,” I point out the mistake, but then ask them how or why they are able to make those predictions. Students invariably begin their answers with “Because…” and often end up stating something close to the hypothesis they are testing. Using this strategy, we can guide our students toward a generalizing hypothesis or help them work through analogical reasoning and abduct an explanatory hypothesis. An additional strategy to help students delineate the hypothesis from the prediction is to have students write predictions and label them as predictions when they are planning their investigations. Perhaps the most critical component of this pedagogical strategy is that students become focused on keeping their explanations (generalizing or explanatory hypotheses) as completely separate statements from their predictions.

A second, egregious, and all too common practice is when teachers require students to write hypotheses for “canned” lab activities, the likely objective of which is simply to make determinations, such as the value of a physical constant (Yip, 2007). In these cases, teachers can help students write generalizing hypotheses that explain patterns, but only after students have made some observations and recorded some data. In all cases, teachers may consider providing students a flow chart, similar to Figure 1, that helps them move through the two strands of generating explanatory and generalizing hypotheses and their related predictions.

Finally, teachers are advised to take a close look at the textbooks they are using and carefully assess how the textbooks define and use hypothesis. They may indeed be using a textbook that confuses students on some level about what hypotheses are.

Correcting this confusion – between the hypothesis and the prediction in particular, and about NOS in general – will not happen overnight, or even within the next few weeks, but it does begin with teachers like you.

## Conclusion

Science is an essential course in a student's formal education, but many have demonstrated that misunderstanding of NOS by students and teachers can be a major challenge. Perhaps the most important goal of science education in a democracy is to produce a future consensus of public policy makers and an informed electorate who have a scientific understanding of the natural world. Indeed, a lack of understanding of NOS has made it far too easy today for science denial and pseudoscience to influence personal and public decision making (Flammer, 2006). Science educators must teach students how to use the logical strategies of scientific reasoning and how to employ the procedures for obtaining meaningful and credible knowledge through scientific results that will contribute to scientific knowledge and to the formation of effective, evidence-based public policy (Dias et al., 2004; Forrest, 2011). The public must understand how science works, and I am convinced that we can produce a more scientifically literate public if we commit to a greater focus in science education on the nature of science, and starting with the hypothesis.

The author thanks the Boulder Valley School District and Cordon-Pharma Colorado for financial support for several trips to the Intel International Science and Engineering Fairs. H. Ayi-Bonte, K. Donley, H. Petach, and A. Smith contributed to data collection at various Intel ISEF events. Two anonymous reviewers and H. Ayi-Bonte, H. Petach, J. S. Levine, H. Quinn, S. M. Zerwin, J. M. Strode, and W. F. McComas provided invaluable comments on the manuscript.

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