3.1 The Scientific Inquiry Process

Quick Answer: The inquiry cycle is observe → question → hypothesize → test → analyze → conclude → communicate. The exam tests your ability to identify independent, dependent, and control variables; choose the right type of investigation; explain how multiple trials improve reliability; and distinguish systematic from random error. The history, ethics, and peer-review portions of Competency 003 are covered in the next section, "The History and Nature of Science," and are not repeated here.

The Inquiry Cycle

Scientific inquiry is a cycle, not a fixed recipe. A teacher should help students move through the steps above flexibly: a surprising result can send the class back to the question step, and a published study may generate a new observation. The hypothesis must be testable and falsifiable — a statement such as "plants grow better with more light" is testable, while "plants have a soul" is not.

Types of Investigations

TExES 116 expects you to distinguish three investigation types:

A controlled experiment is the gold standard when variables can be isolated, but descriptive studies are the right choice when manipulation is impossible or unethical (you cannot change a star's temperature). Comparative analysis lets students work with published data sets.

Designing a Controlled Experiment

The four design elements every TExES prompt expects you to label:

1. Independent variable (IV) — the one factor the investigator deliberately changes. Example: light color.
2. Dependent variable (DV) — the factor measured, expected to respond to the IV. Example: plant height after 14 days.
3. Controls (constants) — factors kept the same across all groups so only the IV can be responsible for differences in the DV. Examples: same plant species, same soil volume, same water amount, same temperature.
4. Control group — the group that receives no treatment (or the standard treatment), used as a baseline. Example: plants grown under natural white light.

A common error is calling a control group a "constant." Constants are conditions held identical across all groups; a control group is a treatment group used for comparison. Sample size should be large enough that a single unusual result does not dominate — three to five plants per treatment is a common middle-school standard, and each plant is one replicate.

Multiple Trials and Reliability

Reliability is the consistency of results when an investigation is repeated. Multiple trials reduce the influence of random error and let the analyst average results and compute a range. If three trials give 4.8 cm, 5.0 cm, and 4.9 cm of growth, the mean (4.9 cm) is more trustworthy than any single trial, and the small range signals high reliability. A single trial with an outlying result is a flag to repeat the trial, not to delete the data point.

Sources of Error

Two categories every teacher must distinguish:

• Systematic error — biases every measurement in the same direction (e.g., an uncalibrated balance, a stopwatch that runs slow, a thermometer placed in direct sun). Fix: calibrate or replace the instrument; redesign the procedure. Averaging more trials does not remove systematic error.
• Random error — unpredictable fluctuations from reading, environment, or instrument jitter. Fix: average multiple trials; report the range.
• Human / procedural error — misreading a meniscus, recording the wrong unit, skipping a step. Fix: training, checklists, peer checking of data entry.
• Flawed design — failure to control a variable, sample too small, no control group. Fix: redesign the experiment. This is not "error" in the measurement sense — it is a design problem.

The exam may also ask about sources of error specific to a context (e.g., heat loss to the air in a calorimetry lab, evaporation in a volume measurement). A good answer names the specific source, classifies it as systematic or random, and proposes a concrete correction.

Communicating and Defending Results

Communication is a graded step in the inquiry cycle. Students should present results in a form appropriate to the audience: a data table and graph for a class presentation, a written report following the standard IMRaD format (Introduction, Methods, Results, and Discussion), or an oral defense in which peers question the design and the student responds using the data. Replication — another investigator running the same procedure and getting the same result — is the strongest check on a conclusion, and a finding that cannot be replicated is treated with skepticism regardless of how plausible the original result looks. The history of science, ethics of research, and the role of peer review in evaluating explanations are covered in the next section, "The History and Nature of Science," and are not duplicated here.