Science Reasoning Text

Science Reasoning Text

Science involves describing, predicting and explaining nature and its changes, in the simplest way possible. Scientists continually refine their understanding of the natural world so that it is as precise and complete as possible. How do scientists do their work? In other words, what methods and skills do scientists use in their work?

Although there is no one scientific method that all scientists use, there are many common elements of the scientific enterprise:

  • how research is conducted and reported,
  • what attitudes are characteristic of scientists,
  • what language they use, and
  • what processes are often used in empirical and theoretical studies.

All of these elements are important to gain a general understanding of scientific reasoning. Select your interest from the links provided at the top of the left frame.

**New materials are included in the Adapted Primary Literature section of the website.

"If we teach only the findings and products of science—no matter how useful and even inspiring they may be—without communicating its critical method, how can the average person possibly distinguish science from pseudoscience?"

— Carl Sagan, astronomer and author

Evaluating Claims to Knowledge

Citizens in a democratic society are often required to read and interpret media reports of scientific research. Health and environment research reports are, for example, commonly portrayed in the media. Sometimes the research reports appear to contradict each other and sometimes the reports promote more uncertainty than certainty. Understanding the terminology and concepts for describing a research study is increasingly important for responsible citizenry. Listed below are some of the terms and concepts that will help you understand and critique media reports of research.

Types of Studies

correlational study—the connection or degree of agreement (e.g.,–0.3, +1.0) is sought between two variables, often without controlling for other variables; correlational studies often lead to cause-and-effect studies

cause-and-effect study—one variable is manipulated and all other variables, other than the responding variable, are controlled

control experiment—see cause-and-effect study

clinical trial—a controlled study involving people; usually a final-stage, double-blind study

Design Factors

term of study—the duration of the experiment e.g., observations over 5 s, 30 min, 3 mon or 15 a; long-term studies are most often preferred

sample size—the number of entities or people in a study; generally large sample sizes are preferred

random sample—one chosen randomly from the population of entities (to reduce bias)

replication—repetition of a study, generally, by an independent research group

placebo—in medicinal experiments, an inactive item (e.g., sugar pill) or treatment given to the control group

placebo effect—a beneficial effect arising from a patient’s expectations; present in both the control group and the experimental group

single blind—the subject (e.g., patient) does not know whether she/he has received the treatment or a placebo, but the experimenter knows

double blind—neither the subject (e.g., patient) nor the directly involved experimenter knows whether the subject has received the treatment or a placebo

control—a standard or comparison value, or procedure (e.g., leaving one of several identical samples unaltered for comparison), or a placebo

control group—a comparison group that does not receive the experimental treatment experimental group—a group that receives the experimental treatment

experimental group—a group that receives the experimental treatment

Nature of Evidence and Results

anecdotal—based upon personal experience or hearsay

reliable—reproducible or consistent time after time

valid—judged to be supported by adequate designs, materials, procedures, and skills

accurate—judged to be true or agreeing with the accepted value

precise—closely related or very similar; related to reproducibility of results

statistical bias—a sampling or testing error caused by systematically favouring some outcomes over others

random result—a result that could be expected on the basis of probability (e.g.,50% heads and tails when flipping a large number of coins)

coincidence—a result that is accidental and irrelevant to the study

significant difference—a difference that is greater than could be randomly expected when an experimental group and a control group are compared

certainty—the degree to which something is accepted by an individual or community (e.g., the evidence may have a high or low degree of certainty);measured by, for example, counting significant digits

Reporting Research

refereed journal—an academic journal for which research papers are sent to subject experts to determine whether the report is of sufficient quality to publish; also called peer-reviewed journal

funding agency—a report in a research paper of who funded the research. This may be important when a bias might be considered due to the self-interest of a funder.

abstract—a short summary describing the research processes and results

* Reprinted with permission from Nelson Chemistry, Alberta 20-30, Jenkins et al, © 2007, Nelson, a division of Thomson Canada Limited.

Nature of Scientific Research—Exercise

1. A study is proposed to determine whether there is a relationship between the presence of heavy metal ions in the water from a river and the root growth of an aquatic plant. Based on this information, this type of study would be a

A. correlational study

B. cause-and-effect study

C. control experiment

D. clinical trial

Answer A

2. What is the least number of variables present in a control experiment?

A. 0

B. 1

C. 2

D. 3

Answer D

Briefly explain your answer.


A control experiment must have a manipulated variable, a responding variable and at least one controlled variable.

3. From a large group of people, some were given an experimental drug and some a placebo to test the effect of the new medication. Other specifications are required to improve this design.

1. term of study

2. single blind

3. double blind

4. placebo effect

5. random sample

The factors in the above list that should be specified to obtain the best possible design are ____________.


1, 3, 5

4. In an experiment to test the value of a known constant, a percent difference of 28% was obtained. This indicates a

A. poor precision

B. high certainty

C. low accuracy

D. high accuracy

Answer C

5. High quality evidence from a valid experiment is __i__ and also __ii__, but not necessarily __iii__.

Which of the following rows, best completes this statement?





















Answer A

6. Act as a referee (peer-reviewer) to critique the following experimental design including, if necessary, suggestions for improvement.

Ten volunteers are provided with their horoscope for the test day. The volunteers orally respond in a group to the question: Does this horoscope describe your personality and life situation?


This experimental design is very inadequate because:

· ten volunteers is a very small sample size; the number needs to be at least 100 or more, randomly selected from thousands

· to control the horoscope variable, all subjects should be provided with the same horoscope

· to control subject interaction and influence, subjects should be isolated from one another

· to provide for accurate reporting of the subjects’ responses, investigators should make audio or audiovisual recordings

7. Create an experimental design to test a new drug to promote weight loss.


Randomly selected control and experimental groups of 1000 volunteers are studied over two years. Both receive pills: the experimental group unknowingly receives the drug; the control group unknowingly receives a placebo. Technicians, who do not know which group each person is in, record the weight of the subjects every month. Experimenters, who never meet or see the volunteers, analyze the evidence gathered.

8. List some examples of questionable claims made in the media without any indication of valid scientific research.


Many examples are possible such as:

- A salesperson claims that wrapping magnets around water pipes will reduce the amount of hard-water scaling that accumulates on the inside of the pipes.

- A salesperson claims that a copper bracelet relieves pain in the wrist.

- A psychic claims to be able to bend spoons with his mind—a feat called psychokinesis.

- An alternative medical care provider claims to be able to cure a disease that standard medical practices cannot.

9. A researcher claims to have been studying magnets for considerable time in order to "develop real scientific evidence about the effectiveness of magnetic therapy." (Skeptic, Vol. 14, No. 1, 2008, p. 7). Critique the statement made by the researcher.


A more acceptable statement for a researcher would be to "gather evidence to help judge the effectiveness, if any, of magnetic therapy." Alternately, to "discover whether or not magnetic therapy is effective." A researcher should not be trying to validate a claim, she or he should be trying to test a claim.

10. A researcher establishes three large (>600) randomly selected groups of patients to test the claim that prayer provides an effective medical treatment for post-operative coronary bypass surgery. (Skeptic, Vol. 14, No. 4, 2009, p. 47). What would likely be the treatment (or not) provided to each of the three groups?


Group 1 unknowingly received prayer.

Group 2 knowingly received prayer.

Group 3 unknowingly did not receive prayer.

(A group was not established to knowingly not receive prayers. Why not?)

Double Blind Exercise


James Randi, magician and reknown skeptic, defines double blind as an experimental design where "neither the subject of the experiment ... nor the experimenter knows the answer that is being sought." Double blind experiments are, for example, regularly conducted during clinical trials of drugs. Another scenario for using double blind experiments is for testing claims of the paranormal (often called pseudoscience or false-science). Examples of pseudoscience include astrology (e.g., horoscopes), psychic surgery (e.g., removing tumours without surgery), alien abductions, mindreading, speakking to the dead, and UFOs.The James Randi Education Foundation ( has runs the Million Dollar Challenge for anyone who can provide evidence for the legitimacy of their pseudoscience claims. This money has been available for a long time and has endured many attempts to claim the money. The only stipuation is that the claim must pass a scientific test--just like all knowledge that is accepted by the scientific community.


Recently a claim was made by an individual that he could dowse for gold (not unlike many who claim that they can dowse for water). Dowsing is also called witching or divining. Many of these dowsers use a Y-shaped willow branch or a T-shaped wire. They walk with the device until the vertical portion of the device points downward.

Your task is to create a double-blind experimental procedure to test the claim being made by the gold dowser. Assume that the dowser has brought his or her own small sample of (real, verified) gold that can be placed in one of twenty styrofoam cups, each with a lid, throughout a large room.

[Alternately, the Purpose, Problem, Design, Materials, and/or Procedure could be completed.]

[Another possibility is to have a dowser or students trained by a dowser complete the experiment.]

[Yet another possibility is to have students evaluate the claims that are made on Internet websites--claims that are often not tested.]



1. The dowser tests that gold can be found in the styrofoam cups in the room being used for the experiment.

[Claimants often claim afterwards that the test was unfair; e.g., in this case the styrofoam cup or the characteristics of the room affected the results. If the test is pre-accepted as fair then the experiment proceeds.]

2. The dowser and the experimenter each leave the room and videotaping begins.

[There must be no contact between the dowser, the experimenter or the third party.]

3. The third party randomly places gold in one of the ten styrofoam cups.

[An electronic random number generator is used each trial to determine where the gold is placed.]

4. The third party calls the dowser and the experimenter back to the room--without making visual contact.

[The third party must not in any way consciously or unconsciously convey the answer to others.]

5. The dowser seeks to locate the gold and indicates the cup number.

[The dowser does not get to immediately test the accuracy of his/her evidence.]

6. The experimenter records the cup number for this trial.

[The experimenter does not know the accuracy of the result.]

7. Steps 2-6 are repeated 19 more times.

Analysis and Evaluation for a Completed Experiment


Based upon the evidence gathered in an experiment described in Skeptic (Vol.14 No.4 2009) by James Randi, a dowser was able to accurately identify the location of the gold in two (2) out of twenty (20) trials.


The design, materials, procedure and skills employed in the experiment appear to be exemplary. The evidence gathered is considered to be of sufficient quantity and quality to be used to evaluate the hypothesis.

The hypothesis that dowsing can be used to locate gold is falsified by the evidence gathered in this experiment.

The scientific purpose of the experiment has been fulfilled: the hypothesis has been fairly tested.


Anecdotal evidence can only create a hypothesis to be tested--it does not validate the hypothesis. Anecdotal evidence/claims/hypotheses should always be followed by a fair and rigourous scientific test.

Creating and Critiquing Experimental Designs Exercise


1. Scholars publish their research in a refereed (peer-reviewed) journal. Some research papers submitted for publication are rejected because of some fault in the study. As a referee (peer-reviewer), critique the following experimental designs.

(a) One group of 10 patients is given experimental medication for an illness while another group of 10 patients is not given the medication. The health of all twenty patients is monitored for six months.

(b) One chemistry teacher completes a unit of study without doing any laboratory work; another teacher completes the same unit of study by doing four laboratory investigations. Student achievement is compared on the results of a unit test.

2. Critiquing and creating experimental designs are important skills for scientific literacy. Create experimental designs to test at least two of the claims made by the following individuals.

(a) A salesperson claims that wrapping magnets around water pipes will reduce the amount of hard-water scaling that accumulates on the inside of the pipes.

(b) A psychic claims that he can see halos over the heads of some identified individuals in the audience and not over others.

(c) A psychic claims to be able to bend spoons with his mind—a feat called psychokinesis.

(d) A salesperson claims that a copper bracelet relieves pain in the wrist.

(e) A believer in the power of magnets claims that sleeping with flexible and padded magnets in your pillow provides a more restful sleep.

(f) A group of disbelievers claims that the photos and videos from the 1969 Apollo 11 landing on the moon are fake because the shadows created by the Sun are not parallel in the video and photos.

(g) A psychic claims to be able to reproduce simple drawings made by a person who comes up from the audience.

(h) An alternative medical care provider claims to be able to cure a disease that standard medical practices cannot.

(i) A commercial for a shampoo claims that your hair will have more body if you use this shampoo.

(j) A commercial claims that a particular detergent removes grass stains from clothes better than other leading detergents.

3. Design the best possible experiment to test the role of pH in hair shampoos.

4. Scientists have a high standard for recognizing knowledge as valid/acceptable. Write a short paragraph for a double blind experimental design to test the effectiveness of, for example, using lime to neutralize lakes. You may choose your own context for answering this question.

These questions taken from Nelson Chemistry Alberta Edition 2008.

Testing Claims to Knowledge Exercise

Your assignment is to read the article or listen to the argument being made and to check off the information that is provided that would help to support the claim to knowledge being provided. Place an ý or a þ or a ? in the box provided. If the criterion does not apply to this kind of research, please put a cancelling stroke through the whole item; e.g., researcher(s) cited. At the end of the exercise write a short descriptive paragraph about the information that you have found. Next write a short evaluative paragraph about the claim(s) to knowledge being made. (Download the Word file below.)

Criteria for testing claims to knowledge: Descriptive Paragraph:

¨ clear question

¨ peer-reviewed research

¨ research journal cited

¨ reputable journal

¨ researcher(s) cited

¨ researcher credentials cited

¨ reputable researcher in other field

¨ reputable researcher in this field

¨ scientific attitude(s) evident

¨ country(ies) of researcher(s)

¨ institution(s) of researcher(s)

¨ review of other research

¨ replication of other research

¨ acknowledges counter-research

¨ funding source(s) cited

¨ sample size

¨ random sample

¨ kind(s) of subjects

¨ experimental group(s)

¨ control group

¨ control(s) Evaluative Paragraph (below):

¨ single blind study

¨ double blind study

¨ clinical study or animal study

¨ term of study

¨ placebo used

¨ placebo effect noted

¨ fair/valid test (design)

¨ anecdotal evidence

¨ petition science

¨ survey evidence

¨ correlational evidence

¨ cause-and-effect evidence

¨ reliable and/or valid evidence

¨ statistically significant difference

¨ degree of certainty stated

¨ significance of study

¨ risk-benefit analysis

¨ further study needed

¨ balance-opinion controversy

¨ multiperspective view

Scientific Attitudes

The methods and skills used by scientists are intimately connected to a set of attitudes common in the practice of science. A scientific attitude is a disposition to act in a certain way or a demonstration of feelings and/or thoughts. Studies of the actions of scientists have led to lists of scientific attitudes such as displayed below. Some attitudes such as honesty would be expected in any human endeavour, but other attitudes such as tolerance of uncertainty are more characteristic of scientists. Note that scientific attitudes are different from attitudes about/towards science. Also note the exercises available in the top of the left frame on this webpage.

Scientific Attitude*



· looks for inconsistencies

· consults a number of authorities

· challenges the validity of statements

suspended judgment (restraint)

· recognizes the restrictions in generalizations and theories

· generalizes only to the degree justified by available evidence

respect for evidence

· looks for evidence (empirical approach) to support or contradict statements

· demands interpretations that fit the evidence

· collects as much evidence as possible


· reports all evidence even when it contradicts hypothesis or expectations

· acknowledges the work of others


· considers all pros and cons

· considers all evidence available

· considers and evaluates statements by others

willingness to change opinions

· recognizes all hypotheses, generalizations and theories as being tentative

· evaluates evidence which contradicts prediction

· alters hypotheses when necessary to accommodate empirical evidence


· considers several possible options when investigating a problem

· considers and evaluates ideas presented by others

questioning attitude

· looks for inconsistencies

· challenges the validity of unsupported statements

· asks many questions starting with who, where, when and how

tolerance of uncertainty

· accepts that there is always some uncertainty

· strives for greater and greater certainty

* Most of the attitudes and characteristics are taken from a list originally compiled by M. A. Nay, J. Kozlow and R. K Crocker. Sample reference: M. James Kozlow, Marshall A. Nay. (1976) An approach to measuring scientific attitudes. Science Education 60:2, 147-172 (Abstract)

Scientific Attitude Exercise

1. A scientist shows that he or she is open-minded when the scientist

A. discusses ideas with other scientists.

B. asks other scientists to provide evidence to support their ideas.

C. agrees with ideas presented by other scientists.

D. evaluates ideas which do not agree with his or her ideas.

Answer: D

2. Looking for inconsistencies in evidence or ideas is part of each of the following scientific attitudes except

A. objectivity

B. critical-mindedness

C. tolerance of uncertainty

D. questioning attitude

Answer: C

3. If you come across a scientific idea that goes against your common sense, which one of the following courses of action should you follow?

A. Look for published evidence or do an experiment.

B. Disregard common sense because it is not reliable.

C. Disregard the scientific idea because common sense is better.

D. Try to produce a compromise between the scientific idea and common sense.

Answer: A

4. Suppose you did an experiment in a high school science lab, but the results were not what you expected. What should you do?


Ideally you should repeat the experiment; however, in all cases you should honestly report the results you obtained.

Use the following information to answer questions 5 and 6.

Galileo obtained much evidence about stars, planets and the motion of terrestrial objects to create ideas about the universe. Because Galileo’s ideas were contrary to those held by the powerful Roman Catholic church and philosophers of his time, he was forced to say that he was wrong and was prevented from practicing science.

5. Which one of the following statements best applies to this situation?

A. Galileo should have collected more evidence before disagreeing with the prevailing ideas.

B. Galileo’s ideas became wrong when he was forced to say that they were wrong.

C. Galileo was justified in questioning the prevailing beliefs.

D. Galileo should have avoided any investigations which could lead to disagreements.

Answer: C

6. What does this situation illustrate about the evaluation of scientific work?


Attitudes and beliefs in society are sometimes used to evaluate scientific work. Evidence, not beliefs, is the cornerstone of science.


7. A boy goes skating on a pond and breaks through the ice. He is rescued and given a drink of hot chocolate by someone who is sneezing and coughing. A few days later the boy also has a cold. Which one of the following best describes the reason for the boy’s cold?

A. The reason why he got a cold is not yet determinable.

B. He got the cold from the person who rescued him.

C. He probably had a cold starting before he went skating.

D. His cold is due to falling in the cold water and getting wet.

Answer: A

8. Are scientific attitudes unique to science? Explain briefly.


· Most scientific attitudes would be useful or desirable in many aspects of society, including voting on complex issues and purchasing an expensive item.

· Endeavours based on faith and/or anecdotal evidence would least likely involve attitudes/dispositions similar to scientific attitudes.

* Most of the questions are taken or adapted from a “Test on Scientific Attitudes”, 1981, by G. Andruski, J. Kozlow and M. A. Nay.

Scientific Attitudes in Action

Scientific attitudes are habits of mind that guide ones predisposition to think and act in a certain way when encountering problem solving scenarios (e.g., climate change). Use this blank table to generate a list of actions that would be consistent with each of the scientific attitudes listed. Try to be as specific as possible—perhaps by taking examples from a lecture, debate or video.

Scientific Attitude*



suspended judgment (restraint)

respect for evidence



willingness to change opinions


questioning attitude

tolerance of uncertainty

* Most of the attitudes and characteristics are taken from a list originally compiled by M. A. Nay, J. Kozlow and R. K Crocker. Reference: M. James Kozlow, Marshall A. Nay. (1976) An approach to measuring scientific attitudes. Science Education 60:2, 147-172 (Abstract)

Scientific Language

Reasoning is an activity that requires putting together thoughts that combine evidence-based knowledge and logical arguments. Any thought is dependent on language; in other words, you need words and grammar to conceive and communicate what you are thinking and/or doing. Whatever language is used in the classroom conveys a view of the natures of science. The following examples of scientific language (for teachers and students) convey an accepted modern view of the nature of scientific knowledge and of the scientific reasoning. Check out the links at the top of the left frame on this web page.

The language used by scientists to communicate their work reflects the nature of science. Scientific language used by scientists includes:

  • appeals to evidence. E.g., "Based upon the evidence gathered in this investigation, ...."
  • expressions about the validity and reliability of the evidence. E.g., "The design called for the control of ....", "A new technology allowed for ....", "This procedure ....", "The skill of the technician was such that we were able to ....",
  • appeals to prominent scientists. E.g., "Ian Stirling found in his research that ...."
  • appeals to accepted literature. E.g., "A research study reported in Science indicated that ....", "Peer reviewed research in Nature suggests that ...."
  • expressions of (un)certainty. E.g., "This was an initial study ....", "The sample size was small but ....",
  • appeals to the nature of science. E.g.,"Although science requires us to be open-minded about this counter-claim, ....", "This is only a correlational study and not a cause and effect study so ....".
  • appeals to logical reasoning. E.g., "If ..., then ....", "If ... and ...., then ....", "Logical consistency requires that ...."

These characteristics are typically found in scientific research papers and ideally in science educational materials such as science textbooks. Popular science magazines and newspaper articles about science often take liberties with scientific language by translating it into more common everyday language. This translation often removes important aspects about the nature of science, or worse, misrepresents the nature of science. Two common problems with popular science articles are a lack of expression of appropriate uncertainty (tending to more absolute statements) and a confusion between evidence and interpretation.

Evidence is the ultimate authority in science even though all evidence is uncertain to some degree. Expressions such as “facts”, “exactly”, “absolutely” or “we proved …” are not appropriate in the context of a scientific investigation. Evidence can support or fail to support a prediction and/or hypothesis, but cannot “prove” either. “Proof” is considered too absolute and does not connote the uncertainty accompanying all scientific evidence and knowledge.

Some Examples of the Use of Scientific Language

Expressing the Authority

Expressing the Degree of Certainty

Based on the concept of …

The certainty is three significant digits.

According to the law of …

Based upon the limited evidence gathered, …

Using the theory of …

Without full control of all variables …

Based on the evidence obtained in this investigation …

The experiment needs to be replicated by another group but …

In our judgment, …

Careful control of all known variables suggest …

Out interpretation of the evidence is that …

Accepting that all knowledge is uncertain, …

If this concept is valid, then …

The accuracy as a percent difference is …

This accepted concept leads us to believe that …

Having a high degree of confidence in the evidence, it is appropriate to …

Logical and consistent reasoning suggest that …

In this correlational (not cause and effect) study …

The document above can be downloaded as a Word file below. An alternative presentation with several more examples is available in the PowerPoint file below. Also see Scientific Language Exercises (top left) to practice the identification of scientific language in research reports. Then try to use this language in your writing and identify it when you are reading or listening to research reports.

Scientific Note Taking

Sometimes during lectures (especially public lectures outside our your area of expertise), you have to use a different strategy to note taking. One such strategy is a two-column approach the includes standard content and scientific language.

Standard Content

  • “Major economic impact …”
  • “Global temperature by …”
  • “Projected ice extent …"
  • “Stress in populations …”
  • “More productive in …”
  • “Current UV radiation …”
  • “Spread of new insects …”
  • “Cultural importance of …”
  • “The oil and gas industry …”
  • “In Buenos Aires on Nov 15…”

Nature of Science Language

  • “The assumption is that …”
  • “An argument is that …”
  • “According to the concept…”
  • “As a result of of this study…”
  • “It tends to suggest that …”
  • “Key findings were …”
  • “There may be a connection…”
  • “We could predict that …”
  • “People believe that …”
  • “You can see here that …”


Start to listen for, read and write nature of science messages; e.g.,

  • take scientific language notes in two columns
  • underline nature of science messages in your readings
  • write by justifying your knowledge claims in your laboratory reports
  • talk like a scientist who is speaking carefully on a topic of high uncertainty

See the PowerPoint file below to access the above text and another example.

Scientific Language Exercises

The language expressing scientific reasoning in published scientific papers is the subject of this web page. The specific scientific content of the papers, especially references to unfamiliar concepts, is not important here. Do not be distracted by unfamiliar scientific words; you are not expected to understand the research. Look for and note all examples of language depicting the nature of science; e.g., characteristics of science, appeals to evidence, reference to theories, uncertainty (tentativeness), and scientific reasoning. Check on the links in the top left frame of this webpage

  1. for classroom exercises requiring students to investigate the use of scientific language in various publications. See the exercise(s) in each of the sections listed in the frame to the left, and
  2. for sample answers to the exercises provided.

Try to get in the habit of listening for nature of science language being used in news reports on TV and radio and in newspapers, in lectures by scientists, and in your own classroom. Does your speaking and writing about science convey a modern view of the natures of science?

Follow the links below.

Scientific Language: Beamish exercises and answers

The language expressing scientific reasoning in published scientific papers is the subject of this web page. The specific scientific content of the papers, especially references to unfamiliar concepts, is not important here. Do not be distracted by unfamiliar scientific words; you are not expected to understand the subject of the research. Look for and note all examples of language depicting the nature of science; e.g., characteristics of science, appeals to evidence, reference to theories, uncertainty (tentativeness), and scientific reasoning.

Your task is to identify the scientific language used in the attached physics research paper. A knowledge of the science is not important. A knowledge of the language used to convey the scientific reasoning is necessary. Click on the following links to research reported in a peer-reviewed journal

  • Read the physics research paper by the physicist, Dr. Beamish. Identify scientific language depicting the nature of scientific work.
  • Check out a sample answer provided.
  • Check out the professional analysis provided.

What for this kind of scientific language being used in your textbook and in the talk in your classroom.

Scientific Knowledge

The nature of knowledge is a subject contemplated by philosophers for a very long time. The main difference between scientific and other types of knowledge is that scientific knowledge must be testable both logically and experimentally.

Studies of knowledge in science indicate that knowledge may be classified into two major categories—empirical (observable) or theoretical (non-observable).

Table 1: Characteristics of Empirical and Theoretical Knowledge

Scientific Knowledge



· based on observations and experiment

· used to describe and predict phenomenon

· communicated by qualitative and quantitative descriptions, empirical hypotheses, empirical definitions, generalizations and scientific laws*


· based on ideas/concepts of the unseen

· used to describe, predict and explain phenomenon

· communicated by qualitative and quantitative descriptions, theoretical hypotheses, theoretical definitions, and theories*

* Some branches of science, like biology, sometimes use laws and theories in a different way. This is discussed in more detail in the sections about empirical and theoretical processes.

In general, the methodology of any branch of science can be described as the collection and analysis of observations to find valid empirical concepts, and the development and testing of theories to explain this empirical knowledge. Except for a few modern examples, the empirical work generally starts first and the theoretical work follows at some later time. Some examples from the history of chemistry are provided in Table 2. The dates in Table 2 come from Asimov’s Biographical Encyclopedia of Science and Technology and Brock’s The Chemical Tree.

Table 2: Some Empirical and Theoretical Concepts in the History of Chemistry

Empirical Concept

Theoretical Concept

conservation of mass (Lavoisier, 1770s)

conservation of atoms (Dalton, 1805)

conservation of momentum (Wallis, 1668)

particle repulsion (Van der Waals, 1873)

gas laws (Boyle, 1662 & Charles, 1787)

kinetic molecular theory (Maxwell, ~1860)

Faraday’s laws (Faraday, 1832)

electrochemical theory (Debye, 1923)

periodic law (Mendeleev, 1869)

Bohr model of atom (1913)

stoichiometry (Richter, 1792)

mole ratio (after Avogadro, >1856)

definite composition (Proust, 1799)

atomic theory (Dalton, 1805)

multiple proportions (Berthollet, 1799+)

valence theory (Pauling, 1928+)

rate of reactions (van’t Hoff, 1884)

particle kinetics (Hughes & Ingold, 1933)

equilibrium (Berthollet, 1798)

equilibrium (Gibbs, 1890s)

Le Chatelier’s principle (1888)

equilibrium & kinetics (Gibbs, 1890s)

neutralization (Ostwald, 1877)

H+(aq) of Arrhenius (1884)

electricity (Franklin, 1752)

electron flow (Thomson, 1897)

line spectra (Kirchoff, 1859; Balmer, 1885)

quantization of energy (Bohr, 1913)

law of gravitation (Newton, 1666 & 1687)

theory of gravitation (still coming)

Note that the concepts listed in Table 2 are created by different scientists. One could describe the scientists who created the empirical concepts as empiricists (experimental scientists who emphasize laboratory work). The scientists who create theoretical knowledge may be called theoreticians. However, classification schemes like this are created by human beings to help organize our knowledge—it is not likely that any one scientist can be classified as either/or, just having a different degree of empiricism at any point in time in his/her work.

Empirical and Theoretical Ways of Knowing

Scientific ways of knowing may also be classified as empirical and theoretical. An empirical way of knowing is characterized by a dependence on experience and experiment, while a theoretical way of knowing is characterized by thinking about entities and actions that are not visible to the human eye. The history of science can be seen as involving parallel streams of work—empirical and theoretical. Every situation is unique, for example, the empirical study of a phenomenon may be decades, centuries or millennia ahead of theoretical work or the empirical and theoretical work may be feeding off one another on an ongoing basis—each making advances in knowledge that is communicated to the other. Modern scientific work is increasingly teamwork, with empiricists and theoreticians working closely together, along with their counterparts from related disciplines (e.g., chemistry, physics and biology).

Table 3: Empirical and Theoretical Scientific Work

Empirical stream of work

(typically ahead)

Theoretical stream of work

(typical behind, in time)

empirical descriptions based on observations and communicated as

· evidence

· tables

· graphs

theoretical concepts based on ideas about the invisible (to explain the evidence)

· theoretical definitions

· theoretical hypotheses

· theoretical generalizations

· theoretical models

empirical concepts (from the evidence)

· empirical definitions

· empirical hypotheses

· empirical generalizations

· empirical models

· scientific laws

theoretical descriptions (from the concepts)

, for example,

· according to the Bohr model of the atom, a carbon atom has four valence electrons

[This page can be downloaded as a Word document below.]

Scientific Knowledge Exercise

Scientific Knowledge—Exercise

1. Classify the each of the following activities as science or non-science.

(a) predicting the weather

(b) fortune telling

(c) astronomy

(d) astrology

(e) studying animal behaviour

(f) observing the Northern Lights

(g) ESP (extrasensory perception)


science: (a), (c), (e), (f)

non-science: (b), (d), (g)

2. Classify the each of the following statements about carbon as empirical or theoretical.

(a) Carbon atoms are composed of six electrons and six protons.

(b) Carbon is found in several forms in nature; for example, graphite and diamond.

(c) Graphite conducts electricity, but diamond does not.

(d) Graphite contains loosely held electrons; whereas the electrons in diamond are all tightly bound in the atoms and bonds.


empirical: (b), (c)

theoretical: (a), (d)

3. Which one of the following is not classified as empirical knowledge?

A. tables of evidence

B. generalizations

C. explanations

D. observations

Answer: C

4. Many people firmly believe in an afterlife or reincarnation after death. This statement can best be described as

A. empirical.

B. theoretical.

C. scientific.

D. non-scientific.

Answer: D

Briefly justify your choice.


This statement is not scientific because it cannot be tested empirically.

[This Scientific Knowledge Exercise can be downloaded as a Word document below.]

Empirical Problem Solving & Processes

Empirical problem solving is a foundation of scientific work. This is the work done in and around the laboratory or field study. Empirical work involves experience and experiment--it involves what we see and do. Products of empirical work include evidence and empirical concepts, such as empirical definitions, generalizations and laws. (See the Scientific Knowledge link to the left for forms of knowledge (e.g., empirical and theoretical) created from scientific work).)

Scientific reasoning in this section is portrayed through an examination of

  • create-test-use as a way of understanding a cycle of scientific work (i.e., from uncertain to more certain) and also a way of understanding the relationship among forms of scientific reasoning (i.e., inductive, hypothetico-deductive and deductive reasoning)
  • evidential bases as different ways of gathering/presenting evidence to create, test or use scientific concepts in the classroom. Evidential bases include, for example, thought experiments, dry labs, and computer simulations.
  • scientific lab reports as a way of communicating empirical work. Lab reports do not communicate a scientific method but do, to a certain extent, communicate the different purposes of scientific work (e.g., to create, test and use concepts).
  • open-entry laboratory work as a way of promoting the creativity of students by allowing them the opportunity to create the Purpose, Problem, Hypothesis, Prediction, Design, Materials, and/or the Procedure sections of a lab report.

Each of these sections of this website include downloadable examples and exercises to help students to learn about scientific reasoning--to assist with deeper understanding of all subject matter.

Inductive and Deductive Reasoning

In both lines of scientific work—empirical and theoretical—we can describe the sequence of work as a create-test-use (CTU) process.

· Create the empirical or theoretical concept/hypothesis, inductively.

· Test the empirical or theoretical concept/hypothesis.

· Use the empirical or theoretical concept/hypothesis, deductively.

This CTU process also describes the different scientific purposes of scientific work. At any one time, some scientists are creating new empirical or theoretical concepts, some are testing current concepts to determine its limits, and some are using accepted concepts to add to the knowledge base and solve practical problems. The following section and exercise is restricted to discussing create (inductive) and use (deductive) reasoning.

Inductive and Deductive Reasoning

Greek “science” was not really science in the modern sense because it involved no experimentation. Instead the Greeks developed knowledge by logically arguing from a set of assumed concepts such as Aristotle’s theory of matter as composed of four elements—earth, air, fire and water. The initial premise or proposition was established and accepted simply based on authority, not evidence. However, once the initial concept is accepted, specific conclusions can be deduced by logical arguments. This method of reasoning from the general to the specific is the method of deduction. In modern science, once an empirical or theoretical concept becomes widely accepted within the scientific community, deductive reasoning is necessary to use the concept in various applications.

Traditionally, the view of science is as a process of collecting many objective (unbiased) observations with the aim of creating general patterns. This view, as expressed by Sir Francis Bacon in 1620, is the method of induction—reasoning from the specific to the general. Although this method appears to be a useful description of the early days of modern science when comparatively few empirical and theoretical concepts existed, it is not a method that is generally used by scientists today. Nevertheless, it is still widely used in the teaching and learning of science—as history is re-enacted.


1. A student-group tests the properties of elements on the left side a modern periodic table in the laboratory. They find that these elements conduct electricity and are shiny and bendable. They write an empirical definition of these elements that we now call metals. The type of scientific reasoning that they are employing is

A. inductive reasoning

B. deductive reasoning

C. reasoning from the general to the specific

D. reasoning that uses a concept

Answer: A The reasoning was from the specific to the general—creating an empirical definition for metals.

2. A student group in a laboratory setting are given the task of determining the resistance of several resistors, without using an ohmmeter. The measure the current through the individual resistors and the voltage drop over the same resistor in a simple electrical circuit. They then calculate the resistance from Ohm’s law (I = V/R or R = V/I). The type of reasoning that they are employing is

A. inductive reasoning

B. deductive reasoning

C. reasoning from the specific to the general

D. reasoning that creates a concept

Answer: B The reasoning was from the general to the specific—using Ohm’s law to calculate the resistance of the resistors.

3. Inductive and deductive reasoning are pervasive in science, in science education, and in everyday life. For example, scientists and science students use concepts (e.g., F = ma) deductively everyday to calculate an unknown from a given number of variables (e.g., m). Classify the following reasoning as inductive or deductive.

a. anecdotal evidence is used to generalize that eating candy creates misbehaviour

b. misbehaviour of a specific child is blamed on the eating of candy

c. a prediction is made from an hypothesis

d. evidence is analyzed to create a hypothesis

e. knowledge of experimental designs is used to evaluate a specific design

Answer: inductive; deductive; deductive; inductive; deductive

4. Students often confuse interpretations and observations. One description is that observations are recorded in the Evidence section of a laboratory report, while interpretations of the observations are made in the later Analysis section of a laboratory report. Interpretations may be inductive or deductive; i.e., an interpretation can create a concept from observations inductively, or an interpretation can use a concept, deductively. Classify the following as an observation, an inductive interpretation, or a deductive interpretation.

a. This rock is not alive.

b. This rock does not grow.

c. Rocks do not grow.

Answer: deductive interpretation, observation, inductive interpretation (Of course, one can argue about the interpretation of the word “grow”.)

Use the following information to answer questions 5 and 6.

The planet Neptune was observed by Galileo in 1613 and also by later astronomers without being recognized as a planet. About two hundred years later, another astronomer, named Le Verrier, predicted (based upon Newton’s law of universal gravitation) the existence of Neptune to account for the orbit of Uranus. Le Verrier predicted the mass, diameter, and calculated the orbit of Neptune. Within a very short time, several astronomers discovered the new planet as predicted.

5. The prediction of Neptune by Le Verrier is an example of

A. inductive reasoning

B. deductive reasoning

C. a theoretical hypothesis

D. none of the above

Answer: B (Newton’s law of universal gravitation was employed deductively to make the prediction.)

6. Why is Galileo not credited with the discovery of Neptune? What does this illustrate about the nature of science?


Galileo did not interpret his observation as being a planet. This illustrates that having the concept allows you to interpret an observation, deductively.

Open-Entry Laboratory Work

We often talk about open-ended laboratory work and often apply the term to all openness allowed in laboratory work. However, it has been found to be useful to distinguish between open-entry and open-ended laboratory work.

  • open-entry laboratory work allows the opportunity for students to be creative about the initiation of laboratory work. Students create, for example, the scientific purpose, the problem, the hypothesis, the prediction, the design, the materials choice, the procedure, and/or the blank table of evidence for laboratory work. These processes involve the pre-lab work--before entering the laboratory.
  • open-ended laboratory work allows the opportunity for students to be creative about the execution, analysis and evaluation of laboratory work. Students create, for example, the evidence, the analysis, and the evaluation of laboratory work. Often synthesis is also involved in open-ended work. These processes involve the interactive and post-lab work--while in the laboratory (in-lab work) and after leaving the laboratory (post-lab work).

Open-entry laboratory work is promoted by gradually introducing students to activities that require them to complete the initiating components of laboratory work--both in wet- and dry-lab experiences. (See the use of lab exercises (pencil and paper labs).) As students gain confidence in these scientific processes, the expectations can be expanded. Pedagogic experience and experiment have shown that providing students with the opportunity to complete one, then two, then three, etc. initiating processes increases their confidence and reduces their frustration. Perseverance is necessary. Confidence is the goal and the reward.

For example, the Purpose of the laboratory work below can be inferred from the Hypothesis being provided, and the Design and Materials sections can be completed by reading the Procedure section of the report.

Investigation 1: The Effect of Temperature on Bitumen Extraction

Reducing the temperature reduces the energy input needed to extract bitumen from oil sand. Research provides information to determine the feasibility of reducing the temperature—by testing the stated hypothesis. Complete the Purpose, Design, Materials, Evidence, Analysis and Evaluation (Parts 1, 2 and 3) sections of the following laboratory report. Use the Problem, Hypothesis and Procedure to help complete the Purpose, Design and Materials sections of the report.



How does the temperature of the chemical system affect the extent of bitumen extraction from oil sand?


According to Karl Clark and many other researchers since the 1920s, the extent of bitumen extraction from oil sand increases as the temperature increases.




Safety: Do not overheat the vials—they may explode from air pressure. Be cautious with the hot plate and hot water (and glass). Wear safety glasses and a laboratory apron.

1. Obtain the three sealed glass vials with oil sand in a controlled mixture.

2. Measure and record (in the Materials) the height of oil sand, pH solution and air in each vial.

3. Use water baths such as 250 mL beakers and enough water (e.g., 125 mL) at about 20 ºC, 50 ºC and 80 ºC to three-quarters immerse the vials (to a controlled height).

4. Place the vials vertically in the constant-temperature, hot-water baths on hot plates for 5 min.

5. Measure and record the temperature of the water in the baths/beakers at the end of 5 min.

6. Remove the vials one at a time by grasping the plastic cap and avoiding the hot water.

7. Wrap several layers of paper towel around each vial and hold tightly.

8. Shake the vial for 45 s horizontally and 15 s vertically and set it to settle for 5 min.

9. Record evidence of the relative separation of bitumen from the oil sand.

Scientific Lab Reports

A research paper in a scientific journal is the primary communication used by scientists. A number of scientists have argued that this printed communication does not really reflect the thought processes and trial-and-error work that often occurs. Instead it represents a summation culled from a variety of work and thought.

“We have a habit in writing articles published in scientific journals to make the work as finished as possible, to cover all the tracks, to not worry about the blind alleys or to describe how you had the wrong idea first, and so on. So there isn't any place to publish, in a dignified manner, that you actually did in order to get to do the work …” Richard Feynman, Nobel Prize lecture in Physics, 1965.

According to some people, the common format or style of scientific papers in peer-reviewed journals tend to make the work look like a purely inductive process. Modern philosophers of science, such as Karl Popper, argue that most of the work in science involves testing predictions. Still others indicate that deduction is the primary logic used in science and engineering. These three categories are more easily described as create, test and use; i.e., a concept is created and tested in the laboratory before being used.

A Report Outline

A model that accommodates induction, hypothesis testing, prediction testing and deduction (create-test-use) is shown below. This is not “the scientific method”; it is a way of reporting scientific laboratory work; i.e., it is a communication convention. This outline for a scientific report is generic—it allows for many kinds of investigations. For inductive work there is no hypothesis or prediction section—an hypothesis is created in the Analysis. For testing an hypothesis, the pre-active hypothesis is compared to the empirical hypothesis in the Analysis. This comparison is made in the Evaluation, after evaluating the quality of the evidence gathered.

Table 1: Laboratory Report Headings and Descriptions




most often the purpose is to create, test or use a scientific concept.


a question to be answered (a general question for inductive-type labs and a specific question for deductive-type labs)


a general concept (untested or previously tested) that provides a possible explanation; predictions may be made from the hypothesis


a specific answer to a specific Problem (the general Hypothesis is used to make a specific Prediction; e.g., F=ma is used to predict m.


a general plan or overview of the procedure including a list of variables and controls; designed to obtain valid and reliable evidence


a specific list of sizes and quantities of all materials used


a set of numbered instructions designed to obtain evidence


all relevant qualitative and quantitative observations


manipulations, interpretations and calculations based on the evidence and used to answer the Problem statement


judgments about the validity of the experiment and evidence, and the acceptability of the Prediction and Hypothesis

The Create-Test-Use Problem Solving Processes

The processes (lab headings) that are logically applicable to each of the CTU(T) (create-test-use-test) problem solving approaches vary. A checklist of what is logically included and not is provided in Table 2. (See the definitions and descriptions of CTU elsewhere.)

Table 2: Natures of Science Processes in Lab Reports














(create, test or use)
























(general concept)










(specific deductive)








Exp. Design




































Evaluation Step 11






Evaluation Step 22


½ verify

yes, verify


yes, falsify

Evaluation Step 33






Notes: Evaluate (1) the evidence, (2) the prediction and/or hypothesis, and (3) the purpose

CTU Acids & Bases Definitions Example

The scientific/historical context of this CTU series of investigations is the expansion of the empirical definitions of acids and bases. Assume that acids have been defined previously by the reaction of acids with an active metal (e.g., zinc) to produce hydrogen gas. Also, assume that bases have been previously defined by their ability to neutralize the properties of an acid.

Creating an Extension of the Empirical Definitions of Acids and Bases—inductively

  • Purpose: To create and extension of the empirical definitions of acids and bases.
  • Problem: Which of the provided chemicals is an acid or a base?
  • Hypothesis &/or Prediction: (none)
  • Design: Each of the solutions is tested with red and blue litmus paper.

Testing Litmus as Part of the Empirical Definitions of Acids and Bases—HI [verification]

  • Purpose: To test litmus as part of the empirical definitions of acids and bases.
  • Problem: Which of the provided chemicals is an acid or a base?
  • Hypothesis: Acids are those substances that turn blue litmus red. Bases ….
  • Design: Each of the solutions is tested with litmus papers.

Testing Litmus as Part of the Empirical Definitions of Acids and Bases—HD [verification]

  • Purpose: To test litmus as part of the empirical definitions of acids and bases.
  • Problem: Which of the provided chemicals is an acid or a base?
  • Prediction: According to the hypothesis that …, the acids will turn blue litmus red ….
  • Design: Each of the solutions is tested with litmus papers.

Using Litmus as Part of the Empirical Definitions of Acids and Bases—deductively

  • Purpose: To use the litmus part of the empirical definitions of acids and bases.
  • Problem: Which of the provided chemicals is an acid or a base?
  • Hypothesis &/or Prediction: (none)
  • Design: Each of the solutions is tested with litmus papers—a qualitative analysis.
  • Analysis: Using the litmus definition of acids and bases and the evidence gathered, the acids.

The rest of the create-test-use examples below use litmus paper as part of the empirical definitions of acids and bases to interpret the evidence in the Analysis section of the laboratory report.

Creating the Arrhenius Concept of Acids and Bases--inductively

  • Purpose: To create the Arrhenius concept of acids and bases.
  • Problem: What kinds of chemicals form acidic and basic solutions; i.e., are acids and bases?
  • Hypothesis and/or Prediction: (none)
  • Design: Each of the solutions is tested with litmus paper.

Testing the Arrhenius Concept of Acids and Bases—H-I [verification]

  • Purpose: To test the Arrhenius concept of acids and bases.
  • Problem: What kinds of chemicals form acidic and basic solutions; i.e., are acids and bases?
  • Hypothesis: Chemicals whose formulas begin with H are acids and end with OH are bases.
  • Design: Each of the several new solutions is tested with litmus paper.

Testing the Arrhenius Concept of Acids and Bases—H-D [verification]

  • Purpose: To test the Arrhenius concept of acids and bases.
  • Problem: Which of the provided solutions is an acid or a base?
  • Prediction: According to the Arrhenius concept, the acids are … and the bases are ….
  • Design: Each of the solutions is tested with litmus paper.

Using the Arrhenius Concept of Acids and Bases—deductively

  • Purpose: To use the Arrhenius concept of acids and bases.
  • Problem: Which of the provided solutions is an acid or a base?
  • Prediction: (none)
  • Design: Each of the solutions is tested with litmus paper—a qualitative analysis.
  • Analysis: Using the Arrhenius concept and the evidence gathered, the acids are ….

Testing the Arrhenius Concept of Acids and Bases—H-D [falsification]

  • Purpose: To test the Arrhenius concept of acids and bases.
  • Problem: Which of the provided solutions is an acid or a base?
  • Prediction: According to the Arrhenius concept, the acids are … and the bases are ….
  • Design: Each of the solutions is tested with litmus paper—a qualitative analysis.
  • Evaluation: Based upon the evidence gathered, the prediction is falsified and the concept is…

Creating the Bronsted-Lowry Concept of Acids and Bases—inductively [from the falsification evidence]

  • Purpose: To create the Bronsted-Lowry concept of acids and bases.
  • Problem: What kinds of chemicals form acidic and basic solutions; i.e., are acids and bases?
  • Hypothesis and/or Prediction: (none)
  • Design: Each of the solutions is tested with litmus papers.

Testing the Bronsted-Lowry Concept of Acids and Bases—H-I [verification]

  • Purpose: To test the Bronsted-Lowry concept of acids and bases.
  • Problem: Which of the provided solutions is an acid or a base?
  • Hypothesis: According to the Bronsted-Lowry concept, the acids are proton donors, and ….
  • Design: Each of the solutions is tested with litmus papers.

Testing the Bronsted-Lowry Concept of Acids and Bases—H-D [verification]

  • Purpose: To test the Bronsted-Lowry concept of acids and bases.
  • Problem: Which of the provided solutions is an acid or a base?
  • Prediction: According to the Bronsted-Lowry concept, the acids are … and the bases are ….
  • Design: Each of the solutions is tested with litmus papers.

Using the Bronsted-Lowry Concept of Acids and Bases—deductive

  • Purpose: To use the Bronsted-Lowry concept of acids and bases.
  • Problem: Which of the provided solutions is an acid or a base?
  • Design: Each of the solutions is tested with litmus papers—a qualitative analysis.
  • Analysis: Using the B-L concept of acids and bases and the evidence gathered, the acids are..

Testing the Bronsted-Lowry Concept of Acids and Bases—H-D [falsification]

  • Purpose: To test the Bronsted-Lowry concept of acids and bases.
  • Problem: Which of the provided solutions is an acid or a base?
  • Prediction: According to the Bronsted-Lowry concept, the acids are .. and the bases are ..
  • Design: Each of the solutions is tested with litmus papers.

Creating the Lewis Concept of Acids and Bases—inductive [from the falsification evidence]

… and on and on …

Create-Test-Use Concept

The debate over the natures of science has often led to either/or decision making for science education laboratory programs. For example, an inductive (specific to general) nature of science has predominately driven laboratory work for all of the twentieth century. Also, deductive (general to specific) reasoning has dominated classroom science education forever. The Science Council of Canada study of science education in the early 1980s called for a modern view of the nature of science in curricula. Yet a more modern hypothetico-deductive (verify or falsify) view of science is nearly non-existent in science curricula. Philosophical analysis of past scientific practice should not be the endpoint—the creation of an authentic laboratory program is required for the future; e.g., see Table 1 for an initial understanding.

Table 1: Natures of Science and Associated Laboratory Work

Lab Type

Nature of Science

Philosopher (e.g.)

Date Introduced

1. create


(specific to general)

Francis Bacon


2. test


(hypothesis testing)

Karl Popper


3. test


(prediction testing)

Karl Popper


4. use


(general to specific)


300s BC

This grouping of natures of science is not just eclectic—there is an implicit sequence. Logically a scientific concept may be created inductively, tested hypothetico-inductively and/or hypothetico-deductively, and used deductively. The sequence also reflects increasing certainty. When a concept is created, its predictive power should be tested. If the predictions are verified, then there is sufficient certainty in the concept to use it regularly. Scientists to not just leap-frog to the use of a concept and for teachers and students to do so misrepresents the nature of science. For a how-to in this regard, see the other subsections of this Empirical Problem Solving section.


1. List the historical (chronological) order that the type of scientific reasoning was employed.

Answer: deductive; inductive; hypothetico-inductive and hypothetico-deductive (from oldest to newest)

2. How could Aristotle have been using generalizations before inductively created generalizations were available?

Answer: Aristotle did not use inductive reasoning to create his initial premises/propositions. He created his initial premises from pure logical thinking. For example, it is intuitively logical that heavy objects fall faster than lighter objects, therefore any lighter object (e.g., a feather) will fall slower than a piece of lead. Inductive creation of generalizations from empirical (experimental) work did not begin in a formal way until the 1600s AD; e.g., with Galileo and later with Francis Bacon.

3. The modern nature of science is most reflected by the Popperian view. How does the change in the natures of science reflect the change in the nature of politics and/or society in the western world?

Answer: In the western world the nature of politics has become more and more democratic. The move from straight deductive logic (based upon singular authorities like Aristotle) to inductive logic (based upon the authority of experiment and evidence) illustrates a move from a more autocratic to a more democratic authority. The testing of authority that is depicted by a Popperian view allows for critical thinking and skeptism that are the hallmarks of democracy.

4. How has the nature of deductive logic changed over time in the sciences?

Answer: Aristotelian logic was based upon irrefutable propositions that were not created empirically. Deductive logic used empirically in modern science is based upon concepts that have been created by generalizing from formally gathered evidence. Modern science is also available for all to read and to critique--based upon anyone doing their utmost to falsify the hypothesis. The hypothesis can be used deductively to make a prediction--not be make irrefutable statements of absolute knowledge.

5. How can concepts of increased certainty be introduced into the scientific community?

Answer: A concept/hypothesis is created inductively by making a generalization from a large body of evidence. Next the concept is tested or a prediction from the concept is tested. If the concept passes many tests, then the concept comes to be used with confidence and certainty in the scientific community. However, tests continue--that eventually (based upon past experience) will lead to falsification and replacement.

CTU Mixed Examples

Evidence obtained from valid and reliable scientific investigations is the ultimate authority in science. The evidence not only provides all of the empirical knowledge but also is essential to test the predictions made from theories. In science, everything comes down to evidence. What kind of reasoning is involved to collect evidence through laboratory work? Most of the laboratory work up to the end of the twentieth century was predominantly inductive in nature. A modern view of the nature of science has expanded this into four categories—inductive, testing hypotheses, testing predictions, and deductive logic/reasoning.

Table 2: Examples of Scientific Research and Types of Reasoning



inductive (I)


To create an organization of known chemical elements.


How can the chemical elements be arranged in a logical way based on their properties?


Obtain all known empirical properties of elements. Order the elements based on similarities and differences.

inductive-hypothesis testing (H-I)



To test the hypothesis that the traits of the offspring are obtained from the parents.


How are traits passed on from parent to offspring?


The traits of the parent are passed to subsequent generations without any blending of parent characteristics.


Using the common pea plant, cross pollinate two plants with a different trait such as pea shape or colour, pod shape or colour, flower colour or position, and plant size. Observe the traits of the offspring. Self pollinate the offspring to produce several more generations, recording the traits in each generation.

deductive-prediction testing (H-D)



To test the Thomson model of the atom.


What effect do the atoms have on a stream of alpha particles passed through a thin layer of gold atoms?


According to the Thomson model, alpha particles should be deflected slightly or not at all.


A stream of alpha particles from a radioactive source is aimed at a thin gold foil. The alpha particles that have passed through the foil are detected by a scintillation screen.

deductive (D)


To use DNA to determine the number of grizzly bears in a specific population.


How many different grizzly bears exist in a particular area?


A string of barbed wire is mounted to encircle several trees with some bait placed in the centre. When a bear passes under the barbed wire a small tuft of hair is left behind. This hair is collected periodically and the DNA analyzed.

Also see the CTU series for Newton’s second law and the stoichiometric law where the laws are created, tested and tested again before being used.


1. In simplified terms, what is the difference between inductive and deductive reasoning?

Answer: Inductive reasoning starts with specific descriptions in order to obtain some general conclusion. Deductive reasoning starts with some general statements to obtain some specific conclusions.

For questions 2 to 5, match the type of reasoning (A to D) with the given description.

A. inductive

B. inductive-hypothesis testing

C. deductive-prediction testing

D. deductive

2. John Dalton, best known as for his atomic theory, spent about fifty-seven years recording over two hundred thousand observations about the weather with the aim of discovering general patterns.

Answer: A

3. Starting only with some general ideas and beliefs about nature, Democritus deduced that all substances were made up of the smallest possible particles which he called atoms (from the Greek, meaning indivisible).

Answer: D

4. Pasteur had a hunch that some microorganisms were the cause of contamination of fermenting beverages. He showed through a series of experiments that if the starting liquid were heated to kill these organisms no contamination occurred. This process was eventually known as pasteurization.

Answer: B

5. According to the phlogiston theory, there is a fire-like element that is contained in combustible materials and released during combustion. Antoine Lavoisier falsified this theory by showing experimentally that combustion does not produce a fire-like element but does require oxygen.

Answer: C

CTU Newton's Second Law Example

The following examples illustrate how Newton’s 2nd law can be presented in the laboratory with a scientific purpose of create, test (hypothesis), test (prediction), and/or use. Note that a (general) hypothesis (e.g., Newton’s second law) can be employed to make a (specific) prediction (e.g., the specific value of the mass, the unbalanced force or the acceleration). The examples below are the student handouts.

Example 1. Complete the Evidence and Analysis sections and evaluate the evidence gathered.


To create Newton’s second law. [inductively]


What is the relationship between acceleration and the unbalanced force applied to a mass?

Experimental Design

The unbalanced force applied to a constant mass is increased incrementally and the resultant acceleration is measured on an air table.

manipulated variable: unbalanced force

responding variable: acceleration

controlled variables: mass, apparatus, slope, environmental conditions


Example 2. Complete the Evidence and Analysis sections of the lab report, and evaluate the evidence and the hypothesis.


To test Newton’s second law. [hypothetico-inductively]


What is the relationship between acceleration and the unbalanced force applied to a mass?


There is a direct-proportion relationship between acceleration and the unbalanced force applied to a mass. It seems to make sense that if the unbalanced force is doubled, the acceleration of a given mass should double. Therefore, if the unbalanced force is increased in any proportion, then the acceleration should increase in the same proportion.

Experimental Design

The unbalanced force applied to a constant mass is increased incrementally and the resultant acceleration is measured on an air table.

manipulated variable: unbalanced force

responding variable: acceleration

controlled variables: mass, apparatus, slope, environmental conditions


Example 3. Complete the Evidence and Analysis sections of the lab report, and evaluate the evidence, the prediction and the hypothesis/authority (Newton’s second law).


To test Newton’s second law. [hypothetico-deductively]


What is the acceleration caused by a 1.5 N unbalanced force applied to a 250 g air puck on an air table?


According to Newton’s second law, the acceleration caused by a 1.5 N unbalanced force applied to a 250 g air puck on an air table is 6.0 m/s2. The reasoning behind this prediction is:

Experimental Design

An unbalanced force of 1.5 N is applied to a 250 kg mass and the resultant acceleration is measured on an air table.

manipulated variable: unbalanced force

responding variable: acceleration

controlled variables: mass, apparatus, slope, environmental conditions


Example 4. Complete the Evidence and Analysis sections and evaluate the evidence.


To use Newton’s second law. [deductively]


What is the mass of an air puck that is accelerated by a 1.5 N unbalanced?

Experimental Design

An unbalanced force of 1.5 N is applied to an unknown mass and the resultant acceleration is measured on an air table.

manipulated variable: unbalanced force

responding variable: acceleration

controlled variables: mass, apparatus, slope, environmental conditions

CTU Problem Solving Processes

The processes (lab headings) that are logically applicable to each of the CTU(T) problem solving approaches vary. A checklist of what is logically included in a laboratory report ("yes") and not (X) is provided in Table 1.

Table 1: Processes Involved in CTU(T) Lab Reports














(create, test or use)
























(general concept)










(specific deductive)




















Evaluation Step 13






Evaluation Step 23


½, verify

yes, verify4


yes, falsify5

I = inductive (hypothesis creation); H-I = hypothetico-inductive (hypothesis testing); H-D = hypothetico-deductive (prediction testing); D = deductive (hypothesis use)


1. The scientific purpose of laboratory work is often omitted. The Purpose and the Problem statements are only the same when inductive work is being done.

2. An hypothesis is a generalization--a concept; e.g., F = ma. A prediction is a specific qualitative or quantitative value that is predicted from an hypothesis; e.g., a = 1.2 m/s2.

3. Step 1 of the Evaluation involves evaluating the evidence. Step 2 involves evaluating the hypothesis and/or prediction. Reversing these steps does not allow for falsification as part of the nature of science.

4. One of the most common errors is to include all processes in the activity and reporting of scientific work. The only kind of laboratory work that can include all of the processes listed is hypothetico-deductive work--testing a prediction.

5. Eventually all scientific concepts in the past have been falsified. Scientists believe this to be true for all current concepts--as a matter of fact, a concept has to have the potential of being falsified or else it is not classified as a scientific concept.

In summary, processes are part of problem solving and the kind of problem solving is part of a kind of nature of science. Skills are subsumed within each process; e.g., the hierarchy is skills, processes, problem solving and natures of science.

CTU Stochiometry Examples

The following example illustrates the concept of create-test-use in the context of high school stoichiometry. The stoichiometry-based laboratory work follows the pattern: create the concept (inductively), test the concept directly (hypothetico-inductively), test the concept by making a prediction (hypothetico-deductively), use the concept (deductively) for quantitative analysis, and use the concept (deductively) to test another concept. There is an increase in certainty and confidence as this series of work unfolds—from creating the concept to using it (as a law) to test new hypotheses.

Recognizing that there is not enough time in any course to complete all of these create-test-use lab experiences, the concept of evidential bases has been created to provide efficiencies that allow for the complete CTU cycle. See the section in this website headed Evidential Bases Concept and access the PowerPoint presentation that can be downloaded there. One of the examples is stoichiometry.

CTU with Karl Popper & Thomas Kuhn

Popper and Falsification

In his famous book, The Logic of Scientific Discovery, Karl Popper said that the aim of science should not be verification but falsification. Experiments should be designed to try to falsify a prediction made from a concept/hypothesis. Albert Einstein clearly agreed with this view when he said, “No amount of experimentation can ever prove me right; a single experiment can prove me wrong.” Only by purposefully looking for a falsification can the limitations of a concept be determined. No significant new knowledge is created when the results of an experiment verify the concept—the concept is only held with greater certainty/confidence. Popper talks about testing a concept to death.

What happens when a valid experiment, replicated by other investigators, contradicts a concept? A simplified answer is the 3-Rs—restrict, revise, or replace. Restricting the concept means reducing its scope; that is, limiting its application to fewer situations or creating exceptions. This approach is generally not desirable because scientists want concepts to be as broad and powerful as possible. However, the restrict-approach is very commonly used in science education. Revising the concept to account for the new evidence is certainly the most common alternative in the usual progress of science. Concepts are adjusted and go through a gradual evolution from simpler to more complex. There are many examples of this from almost any branch of science. For example,

from physics, atomic concept: Dalton → Thomson → Rutherford → Bohr

from chemistry, acid- base concept: Davy → Arrhenius → Bronsted-Lowry

In these examples, there is typical cycle: create the initial concept from existing evidence, test the concept to establish its acceptability, use the concept in various applications, and then eventually falsify parts of the concept leading to a revised concept and the start of a new create-test&verify-use-test&falsify (CTvUTf)cycle.


1. Karl Popper, the British philosopher of science, is most famously known for his conceptualization of _______________________. [Answer: falsification]

2. Popper created his concept of falsification from evidence gathered by the ________________________________.

[Answer: historical analysis of science; observing of scientists at work; interviewing of scientists]

3. Popper is most famous for his emphasis on

a. restricting concepts

b. revising concepts

c. replacing concepts [Answer: c. replacing concepts]

4. Popper’s emphasis is best described by what kind of logic/reasoning?

a. induction (creating)

b. hypothetico-deductive (testing)

c. deduction (using) [Answer: b. testing]

5. Popper’s predisposition (scientific attitude) is best described by

a. testing a concept

b. verifying a concept

c. validating a concept [Answer: a. testing]

Kuhn and Scientific Revolutions

Sometimes the falsification is so successful that no amount of revision is going to make the concept work. In this case, the replace-option is necessary. The modern philosophy of science has been greatly influenced by two people—Karl Popper (1902-1994) and Thomas Kuhn (1922-1996). Popper described what he thought was the logic or reasoning behind the usual practice of science. Thomas Kuhn called this the period of normal science when scientists all shared the same set of assumptions, concepts, values and practices in a particular view of the world. In other words, scientists shared the same paradigm. However, Kuhn looked at the bigger picture and argued that science does not always progress in a linear fashion in which new knowledge accumulates and concepts are developed and revised. At some point in almost any science, there is an abrupt shift in thinking (a paradigm shift) which completely changes the nature of scientific inquiry in a particular field. The new paradigm includes the previous empirical knowledge plus the anomalies that have accumulated over the years of normal science. The change from an old paradigm to a new paradigm is called a “scientific revolution”. Examples of scientific revolutions include the transition from:

· Ptolemaic (Earth-centered) to Copernican (sun-centered) cosmology in astronomy

· phlogiston concept to Lavoisier’s combustion concept in chemistry

· creationist model to Darwin’s concept of evolution in biology

· Newton’s classical physics to Einstein’s relativistic physics

· classical mechanics to quantum mechanics in physics and chemistry


1. Thomas Kuhn, the American philosopher of science, is best know for describing what two different phases of scientific work? ______________ and _______________ [Answer: normal and revolutionary science]

2. During a period of normal science what kinds of products and processes are shared? [Answer: assumptions, concepts, values and practices, including a view of the world]

3. For Kuhn the concepts and processes held to be valid by scientists is described by the concept/term, _______________. [Answer: paradigm]

4. When a scientific revolution occurs, there is a paradigm ________. [Answer: shift]

5. A new paradigm, including a new major concept, must be able to describe and explain _________________________________.

[Answer: past and new evidence]

6. While Popper talks about __________________________, Kuhn talks similarly about _______________________.

[Answer: falsification; revolutions (paradigm shifts)]

7. Usually a revolution in thinking and conceptualization is revealed in your science education when a new course or new unit of work on a particular topic is started. Identify a revolution in science from your past or present science education. [Answer: e.g., wave model of light and of the electron]

Evidential Bases Concept

There are several ways that teachers can present evidence to be analyzed by students. Some of these presentation modes can save time and complete the create-test-use (CTU(T)) cycle. The assumption is that for students to understand the rules of the knowledge game they must repetitively see the full cycle of scientific concepts. They must see a concept created, tested, and then used with confidence. However, occasionally students must also see concepts tested and falsified (and then restricted, revised or replaced). Like all work in science, this requires evidence but the evidence does not always have to be collected by the student in a typical laboratory investigation. There are several evidential bases that can be used. Ideally, a full complement of evidential bases and at least one full cycle of create-test-use would accompany each unit of work in a course.

For definitions and examples of these evidential bases download the Word file and the PowerPoint file below. For a full description and examples of the create-test-use concept see the section with that heading on this website.

Unit of Work _______________ Concept ______________

Evidential Bases




Test (falsify)

1. thought experiment

2. demonstration

3. dry lab (lab exercise)

4. wet lab (in the laboratory)

5. field trip

6. video lab

7. computer video analysis

8. computer simulation/animation

9. computer probes/sensors

10. remote lab work (Internet)

Concepts of Evidence

What are Concepts of Evidence?

As students of chemistry, you collect evidence in laboratory settings on a regular basis. Evidence is data with a scientific purpose; e.g., to create, test or use a scientific concept. Assuming that the scientific purpose has been stated up front, you work with evidence that is eventually evaluated before judgements are made relative to the purpose of the experiment. This evidence may take various forms--qualtitative and quantitative.

Alternately, data can be collected and once it is evaluated (using concepts of evidence), the data becomes evidence. So either evidence becomes data if it fails tests provided by concepts of evidence or data becomes evidence if it passes tests provided by concepts of evidence. Most of the exercises provided on this website take the former view; i.e., we are gathering evidence with a scientific purpose (to create, test or use a concept) and we evaluate the evidence before judging that the experiment is a fair/valid.

Concepts of evidence, as coined by Richard Gott, of the University of Durham, England, are “the underpinning ideas about how evidence can be collected, verified, analysed and interpreted” (Gott, 2004). Gott et al. (2003) have classified these concepts of evidence (CoEs) into 21 main categories which have additional sub-categories. (See the PDF file below--that uses the term data throughout.) These twenty-one categories range from simple ones such as observation to more complex ones such as reliability and validity. Each year of your science education will introduce more sophisticated concepts of evidence. Some examples of concepts of evidence that apply to high school science are highlighted below. Each concept of evidence presented includes a range of subconcepts some of which may be appropriate for each level of schooling.

  1. fundamental ideas (e.g., 1.2: establishing links between two or more variables)
  2. observation (e.g., 2.5: observations can be the start of an investigation)
  3. measurement (e.g., 3.2: the measured value can be subject to random or systematic error)
  4. instruments: underlying relationships (e.g., 4.1-4.4: linear, non-linear, complex and multiple relationships)
  5. instruments: calibation and error (e.g., 5.1 & 5.2: the instrument must be calibrated at endpoints and points inbetween)
  6. reliability and validity of a single measurement (e.g., 6.1: a reliable measurement requires an average of a number of repeated readings)
  7. the choice of an instrument for measuring a datum (e.g., 7.3: a precise measurement may not be accurate)
  8. sampling a datum (e.g., 8.2: the size of a sample is the number of measurements taken)
  9. statistical treatment of measurements of a single datum (e.g., 9.1-9.4: range, mode, median, and mean)
  10. reliability and validity of a datum (e.g., 10.1: ...a datum can only be weighed as evidence once ....)
  11. design of investigations: variable structure (e.g., types of variables are defined)
  12. design: validity, 'fair tests' and controls (e.g., 12.1: a fair test is one in which only the independent variable has been allowed to affect the dependent variable)
  13. design: choosing values (e.g., 13.4-13.6: the range, interval and number of values is determined)
  14. design: accuracy and precision (e.g., 14.2: large error bars may not allow trends to be determined)
  15. design: tables (e.g., table can be used as organizers for the design of an experiment)
  16. reliability and validity of the design (e.g., 16.0: will the measurements result in sufficiently reliable and valid data to answer the question)
  17. data presentation (e.g., 17.1-17.3: tables, bar charts and line graphs)
  18. statistics for analysis of data (e.g., 18.2-18.3: analysis of variance and linear and non-linear regression)
  19. patterns and relationships in data (e.g., 19.1: causal, consequential, indirect and chance associations)
  20. reliability and validity of the data in the whole investigation (e.g., 20.2-20.3: secondary data and triangulation)
  21. relevant societal aspects (e.g., 21.0: other factors outside the domain of science may become relevant)

CRYSTAL Research on Concepts of Evidence

The Representation of Evidence in High School Chemistry Textbooks

PI: Stephen P. Norris

Co-Investigators: Margaret-Ann Armour, Leno Delcioppo, Edie Ferris, Elizabeth Vergis

This project will explore how evidence is represented in the high school chemistry textbooks used in Canada. There are six different chemistry textbooks used in Canadian high schools, of which three will be studied intensively. The most extensive categorization of concepts of evidence has been developed by Richard Gott and his colleagues of the University of Durham, and an abbreviated version of this system will be used to base the analysis. More specifically, the textbooks will be examined for their representations of evidence in areas such as observation and measurement; calibration and error of instruments; reliability and validity of measurements; choice of measurement instrument; statistical treatment of data; design of investigations and fair test; data presentation; and patterns and relationships in data.

[This research has been completed and reported at several CRYSTAL forums. The research has also been submitted to a peer reviewed journal for publication. See below.]

Vergis, E. (2009). The representation of evidence in high school chemistry textbooks. Science Education, (under peer-review).

Creation and Evaluation of Theories

According to Albert Einstein, physical concepts such as theories are “free creations of the human mind, and are not, however it may seem, uniquely determined by the external world.” In other words, humans create theories using their imagination; theories do not exist in nature waiting to be discovered. There are many creative aspects to doing science, such as creating a clever experimental design; however, the flash of imagination in creating a new idea or theory is certainly the pinnacle of scientific creativity. The creation of a new theory is much like the creative inspiration of any artist.

Scientists who create theories are quite familiar with the evidence that exists. It is generally not the case that the scientist has made observations that no one else has seen. The best description was probably given by Albert Szent-Gyorgyi (Hungarian biochemist, 1937 Nobel Prize for Medicine) when he said, “Discovery consists in seeing what everyone else has seen and thinking what no one else has thought.”

Evaluation of Theories

Theories and other forms of theoretical knowledge must:

- be based upon evidence

- describe the natural phenomenon

- explain the natural phenomenon

- predict the results of future experiments

Some scientists and philosophers would also add, be as simple as possible, to this list of requirements.

Theories are initially created to describe and explain some known evidence. Because this is a retrospective activity, describing and explaining are the first and easiest criteria for a theory to meet; you keep adjusting your ideas until they fit with the evidence. Descriptive power refers to the ability of a theory to describe the natural phenomenon in terms of non-observable entities and processes. Explanatory power refers to the ability of a theory to explain all of the known evidence. Accepting the assumptions and propositions of the theory as correct, a conclusion is logically reached that (ideally) accounts for the evidence. A theory also needs to be internally consistent; in other words, it contains no contradictions within or between the propositions of the theory. Finally, the theory also needs to be externally consistent; in other words, it agrees with or fits with other accepted theories in related areas.

The most difficult test of a theory lies in its ability to generate testable predictions; in other words, its predictive power. The best and most highly valued theories are ones that generate predictions that are not falsified when the experiments are performed. This is a difficult test because you don’t know the results of a new experiment until it is done.

No theory is perfect so there is a range of descriptive, explanatory and predictive powers. In general, lower level theories have more descriptive and explanatory powers than predictive power. Theories are also not static; as more evidence becomes available, theories evolve. Restrictions and revisions are often made, and occasionally, the theory may be completely replaced by a new and better theory.

Theoretical Knowledge & Problem Solving

In general use the term theory is often used as being equivalent to concept or hypothesis; that is, any abstraction. In everyday language, theory may also be used as a speculation or even a wild guess and may bear no relation to any facts. In science, the term theory is used in a more restricted sense—it describes and explains using non-observable entities and processes and makes testable predictions. However, there are some differences in usage in the different sciences. For most sciences like chemistry and physics, theory means a set of fundamental non-observable ideas that are supported indirectly by a body of empirical knowledge. In physics the term theory is more often used to discuss the formation of a grand, unifying idea that could bring together, for example, separate concepts used to explain gravitational, electromagnetic, and nuclear force fields. In most sciences, theories are based on non-observable ideas and scientific laws are broad statements of well-established empirical knowledge. In contrast, the term theory in biology is sometimes used as being equivalent to the word hypothesis—a tentative concept. In biology, a scientific law may be a well-established theory; i.e., theories become laws. Recognizing these different approaches is an important start to sorting out useful definitions for these terms.

As used here, laws and theories are parallel concepts used to describe, explain and predict. An empirical way of knowing (using observables) yields empirical concepts, such as generalizations, empirical definitions and laws. A theoretical way of knowing (using unobservables) yields theoretical concepts, such as described below.

Classification of Theoretical Knowledge

Four levels of theoretical knowledge can be classified based on the more common scientific use of theory and theoretical as referring to non-observables entities and processes. Chemistry is the discipline that makes most use of (and has the most need for) the distinction between theoretical and empirical knowledge. Parallel streams of empirical knowledge (e.g., laws) and theoretical knowledge (e.g., theories) are common.






a specific statement based on a theory

chemistry: a water molecule contains two hydrogen atoms and one oxygen atom



a general statement that characterizes the nature of an entity or system in terms of non-observables

chemistry: an acid donates protons in an acid-base reaction

biology: cellular respiration as defined by the Krebs cycle



a theoretical concept that is tentative

physics: dark matter comprises most of the mass in the universe


a concept or set of ideas that explains a large number of observations in terms of non-observables

geology: plate tectonics (large sections of Earth’s crust riding on a fluid-like layer)

chemistry: atomic theory; acid-base theory; electrochemical theory

Communication of Theoretical Knowledge

As indicated above theoretical knowledge can be communicated as theoretical descriptions, theoretical definitions, theoretical hypotheses, and theories. However, in modern science, many theories are very abstract and much of the theoretical knowledge is expressed, whenever possible, as abstract mathematical equations. Most humans need to a way to visualize these theories and this is especially important in science education. Using various devices to communicate theoretical knowledge requires some form of “re-presentation”. The theory is represented in a different way—a way that usually emphasizes the descriptive qualities and limits the explanatory abilities.

A model is a diagram or apparatus used to simplify the description of an abstract idea. For example, marbles in a vibrating box could be used to describe and explain the three states of matter. A small heavy ball creating a depression in a stretched rubber sheet can be used to visualize the distortion of space around a star in Einstein’s theory of relativity. The main advantage of a model is that it communicates (usually in a visual way) an important idea; the main disadvantage is that it oversimplifies and limits the theory.

Two language devices (figures of speech) are also commonly used to help communicate theoretical knowledge. An analogy is a comparison to something more familiar. For example, atoms compared to billiard balls, and enzyme action compared to a lock and key. A metaphor is a more complex figure of speech in which one thing is spoken of as if it were another; for example, life is a roller coaster, full of ups and downs. The image generated is often vivid and insightful, but not necessarily logical. A prevailing metaphor in science is that of a physical mechanism; for example, the universe as a mechanical system and the human body as a machine. Some people argue that all or most of science is a metaphor; we think and learn using metaphors.

Theoretical Problem Solving

Scientists are sometimes classified as empiricists and theoreticians. Empirical scientists specialize in laboratory or field work. They gather evidence to test hypotheses and predictions. Theoretical scientists specialize in describing and explaining natural phenomena in terms of unobservable entities and processes. They also make predictions based upon their theories, although they might depend on the empiricists to complete the tests for them.

Theoretical problem solving primarily involves working with abstract ideas about non-observable entities and processes. For example, a theoretician might try to create a theoretical description and explanation for the rusting of iron or for cellular respiration. They might look at the evidence gathered in the laboratory and try to envisage the transfer process of electrons between the entities involved. The theory that is created is tested by its descriptive power, its explanatory power, and its predictive power. Note that it is easier to describe than explain and it is generally easier to explain than predict. The evaluation of the theory involves these three tests. If it passes these tests, then it is accepted (tentatively) in the scientific community. An example is that the Bohr atomic theory is able to describe a sodium atom, to explain the rapid reaction of sodium with chlorine, and to predict a less impressive reaction between sodium and iodine.

Adapted Primary Literature

Research and development of the use of primary scientific literature in university classrooms has led to the R & D of adapted primary literature for secondary classrooms and of hybrid adapted primary literature for elementary classrooms. In all of these cases and variations thereof the motivation for the research and development is, for example, to promote scientific and mathematical reasoning. Students are provided with the opportunity to read some PL, APL and/or HAPL along with their textbook and other readings. The hypotheses being tested range through topics such as motivation, achievement, reasoning, critical thinking, concepts of evidence, epistemology and ontology. For the CRYSTAL Alberta project these forms of literature provide a meeting place for students, teachers, undergraduate and graduate students, education researchers, and science researchers.

"Primary Scientific Literature contains the original writings on a science subject found in journals, technical reports, conference proceedings, patents, theses, and so on. This literature contains information about the scientific process as it is practiced and represented in the labs and workplaces of science, and provides a record of how and why knowledge evolves. There are several obvious obstacles to using PSL in the K-12 classroom, although there have been attempts to use it at the university and college level with some success (e.g., Almeida et al. 2005; Fikes 1989; Gallagher et al. 2002; Hoskins et al. 2007). Primary scientific literature is written by scientists for scientists and often contains jargon and technical language specific to the area of research. For these reasons, it may be difficult to understand by non-scientists, including high school students and teachers."

"Adapted Primary Literature (Falk et al. 2008) contains articles that have been adapted from primary literature, often by science writers and reviewed by scientists. We do not wish to imply that translating the original primary literature into a more accessible form can convey the same meaning. The scientific jargon and technical language used by scientists are designed to carry precise meanings that cannot be communicated otherwise. It is nonsense to think that simply by making the language of science less technical, the difficulties in communicating up-to-date and leading edge science can be overcome. Nevertheless, we do believe that some measure of success can be had with careful adaptations of original scientific writings."

"Hybrid Adapted Primary Literature (Shanahan et al 2009) is text pieces that integrate both narrative writing and adapted scientific writing--as a way to help students learn to read scientific text. This hybrid form integrates familiar narrative writing with APL. The examples used in this study include a narrative introduction to the scientists and their research, followed by a piece of APL drawn from their work. The aim is to help children gain, through narrative, an understanding of the scientists and the research before they begin to work with the adapted primary literature."

[The definitions/descriptions for primary scientific literature and adapted primary literature are from Norris et al 2009 in Research in Science Education, Volume 39, pages 313-319 ; and the definition of hybrid adapted primary literature is from Shanahan et al 2009 in the Alberta Science Education Journal, Volume 40, Number 1.]

Bridging the Gap with APL

Bridging the Gap Between the Language of Science and the Language of School Science Through the Use of Adapted Primary Literature

Linda M. Phillips, Canadian Centre for Research on Literacy, University of Alberta

Stephen P. Norris, Centre for Research in Youth Science Teaching and Learning, University of Alberta

Research in Science Education (2009) 39:313-319

Abstract In this paper we make the case that the language of school science and the language of science are widely divergent. We trace the divergence to a simple view of reading that prevails not only in science education but in most of schooling. Based upon the importance of language in science and the role of language in capturing the essential nature of scientific reasoning, we conclude that conceiving of reading as a form of inquiry could assist in bringing the two languages more into alignment. We recommend the use of adapted primary literature as one curriculum and instruction innovation that can be useful in illustrating the nature of reading as inquiry.

Keywords Adapted primary literature - Scientific language - Scientific literacy - Science reading

"Our position is simple to state: When scientists read, they are doing inquiry. Reading as inquiry could become a part of school science instruction. Nevertheless, the case for this position is complicated and the science curriculum and science educators have not been attuned to think of the importance of reading to science (Wellington and Osborne 2001; Yore et al. 1998). Thus, something resembling a radical change in perspective is required in order to make our position work in practice.

In this paper we treat the following topics: the importance of reading and writing to science, the language of science, the language of school science, the nature of reading, and the prospects of using adapted primary literature in bridging between the language of science and the language of school science." ...

"We have conducted our own analyses of data-based research reports in physics. For example, in a report covering just two journal pages of a study of hysteresis in silica aerogels (Beamish and Herman 2003), we identified a range of speech acts. The authors

  • motivated their study
  • reported relevant past results
  • reported limitations of past research
  • described what was done
  • argued for the suitability of techniques
  • explained observations
  • conjectured what might be happening, and
  • challenged alternative interpretations.

Similarly to Suppe, we found that the entire article was given to creating a series of arguments (for conducting the research, for the techniques employed, against alternative explanations of the findings) all in the service of supporting the interpretation of the findings that the authors favoured." ...

"As opposed to reading as word recognition and information location, we have argued that reading is best thought of as an inquiry process (Norris and Phillips 2008). The central idea of reading as inquiry is that reading is principled interpretation of text. Readers infer meaning from text by integrating relevant text information with their relevant background knowledge. Interpretation is about exploring meanings presupposed, implied, and reasonably justified by the text. Having knowledge about a topic prior to reading about it is useless to a reader who does not see the relevance of that knowledge by making inferential links between the knowledge and the text. Background knowledge is made relevant to an interpretation by forging inferential links between the knowledge and the text, highlighting reading as a constructive process." ...

"How, then, do we move the science curriculum and eventually science students away from the simple view of reading that has such deleterious consequences? To rephrase the premise with which we opened this paper, reading as inquiry could become part of the science curriculum with the assistance of adapted primary literature, conceived as literature that maintains the canonical form of scientific papers but is written so as to be understandable by school students (Baram-Tsabari and Yarden 2005; Falk et al. 2008). By design, adapted primary literature is more like the language of science than the language of traditional school science. As such, adapted primary literature can become the language of school science to the enormous benefit of students by helping to bridge the gap to the language of science."

This peer-reviewed journal article is published in the Research in Science Education journal ((2009) 39: 313-319) which is available on-line in some licensed institutions from

An adaption of this primary education research literature may appear in a future Alberta Science Educaiton Journal. Watch for it.

Hybrid Adapted Primary Literature (HAPL)

Hybrid Adapted Primary Literature:

A Strategy to Support Elementary Students in Reading About Scientific Inquiry

Marie Claire Shanahan, Julieta S Delos Santos and Ross Morrow

Centre for Research in Youth Science Teaching and Learning, University of Alberta

Alberta Science Education Journal Volume 40, Number 1, September 2009

[This peer-reviewed article will be available on-line here soon.]


For many years the trend in science education has been towards emphasizing hands-on opportunities for students and moving away from teaching practices that rely heavily on textbook reading. Teachers are encouraged to provide opportunities for exploration and experimentation and to engage students in doing science. Yore, Craig, and Maguire (1998) argue, however, that this emphasis has stifled efforts to use text in a valuable way in the science classroom. These and other researchers contend that to engage students in valuable inquiry, the answer is not removing scientific text but paying close attention to helping students learn to read scientific text.

To begin to accomplish this goal, this study examines the use of hybrid adapted primary literature (HAPL) – text pieces that integrate both the narrative form and adapted scientific writing – as a way to support students in learning to read scientific text. We focus on describing the creation and testing of these resources and whether there is evidence that hybrid resources can support students’ understanding of scientific inquiry and scientists.

Samples of hybrid adapted primary literature created by CRYSTAL Alberta researcher, Dr. Marie-Claire Shanahan, are provided below.

West Nile Virus: Using Adapted Primary Literature

West Nile Virus: Using Adapted Primary Literature in Mathematical Biology to Teach Scientific and Mathematical Reasoning in High School

Stephen P. Norris, John S. Macnab of the Centre for Research in Youth Science Teaching and Learning, University of Alberta

Marjorie Wonham, Gerda de Vries of the Centre for Mathematical Biology, University of Alberta

Research in Science Education (2009) 39: 321-329

Received: 29 July 2008 Accepted: 17 August 2008 Published online: 31 January 2009

Abstract This paper promotes the use of adapted primary literature as a curriculum and instruction innovation for use in high school. Adapted primary literature is useful for promoting an understanding of scientific and mathematical reasoning and argument and for introducing modern science into the schools. We describe a prototype adapted from a published article on a mathematical model of the spread of the West Nile virus in North America. The prototype is available as a web-based resource that includes supplemental pedagogical units. Preliminary feedback from use of the prototype in two classrooms is described and a sketch of an ongoing formal evaluation is provided.

Keywords Adapted primary literature - Mathematical biology - Scientific reasoning - Mathematical reasoning - Scientific literacy - Science reading

"We and others (e.g., von Aufschnaiter et al. 2008) have pointed to two perennial failures in the high school science curriculum: first, failure to treat systematically and comprehensively the nature of scientific reasoning and argument and how they are connected to scientific conclusions; and, second, failure to introduce students to some of the most interesting and important ideas of modern science, particularly of interdisciplinary research. In this paper, we wish to exemplify how both of these failures can be addressed through the use of Adapted Primary Literature. We shall proceed by first offering a distinction between Primary Scientific Literature (PSL) and Adapted primary literature (APL). Second, we shall describe a prototype of APL that we have produced in the area of mathematical biology. We finally will report some preliminary feedback from classrooms on the use of the APL and comment a bit about the future of our work in this area." ...

.....................[middle of article deleted due to copyright]

"In general, the topic exceeded expectations in terms of student motivation. That is, the students found the biology and the mathematics of the West Nile virus to be interesting. Their interests were not uniform as different students reported different interests: the calculus content, the population modelling, and the animal behaviour. Many students reported that the prototype improved their understanding of topics covered in Biology class, which was significant because a common complaint by students and teachers is that school mathematics and science classes seem to exist in separate worlds. Many students reported that the mathematics remained beyond their grasp, but that they understood the flow diagrams and felt a level of satisfaction with that understanding. The inclusion of the detailed discussion of the assumptions and restrictions of the mathematical model led to

some of the most fascinating comments from students. Many of them were very surprised to learn that the mathematical model did not mirror the world, but that it was an approximation based upon several compromises. For us, this lesson alone was worth the effort! The patterns of students’ attention were in some cases not what we had hoped. We had included some calculations for students to perform, such as determining various probabilities. In our judgement these were peripheral exercises that reinforced the application of basic high school mathematics to higher level modeling and biological problem solving, but were not crucial to engaging with the conceptual arguments in the unit. Nevertheless, many students spent considerable time on these supplementary problems and insufficient time on the more important tasks related to deeper understanding. This was a lesson for us to take out all the peripheral exercises, which we have done, and to consider including them in the supplementary teachers’ materials. It was precisely to avoid this approach to mathematics that was one of our major aims. Yet, given the chance students reverted to behaviour that was both comfortable and familiar to them. Despite this shortcoming, we concluded that students were capable of considerably deeper understanding than they are often given credit for in contemporary high school mathematics courses. Most interestingly, their understanding can far exceed the ability to manipulate symbols, which unfortunately is what they are called most upon to do and where their understanding of mathematics too frequently stops."


We have finished collecting data for the formal evaluation of the adaptation that will address a number of questions about the effectiveness of our pilot APL unit. We have modelled the research on the work done in Israel by Baram-Tsabari and Yarden (2005). We will not be able to study growth in understanding over years as they were able to do, because all of our students were in the same grade. There is an age spread in our sample of students, and age might make a difference to understanding. Also, our students have widely varying backgrounds in science, though not in mathematics, and we will look for effects there. We are interested in any gender effects and whether the approach to mathematics and science teaching and learning that we have adopted will be found more interesting than traditional approaches by both males and females. Finally, we are interested in whether students learn something about the nature of science and scientific reasoning and the use of some preliminary feedback from classrooms on the use of the APL and comment a bit about the future of our work in this area."

[This peer-reviewed journal article is published in the Research in Science Education journal ((2009) 39: 321-329) which is available on-line in some licensed institutions from]

[An adaption of this primary education research literature will appear in a future Alberta Science Education Journal. Watch for it.