Subtest II: Science Study Guide for the CSET Multiple Subjects Test

Science Skills

The Engineering Design Process

To design is to devise and describe a structure with certain desired features. The process of designing consists of transforming information about the conditions, needs, and requirements of a society or individual to a description of a structure that satisfies them and solves a problem.

Resources

There are plenty of resources that an engineer can use when solving problems. One of these tools is robust computer software with tools that enable the design, analysis, and simulation of mechanical components. Besides this resource, the engineer always needs technical information that can be found in science and engineering books, brochures, and catalogs from manufacturers.

Principles of Experimental Design

The goal of experimental design is to find if certain factors have an effect over a variable of interest, and then quantify that influence, if it exists. There are certain principles of experimental design that are described below:

Formulating testable questions—The questions that researchers try to answer using experimental design should be testable, meaning that a method can be designed to obtain data that answers the question. Open-ended questions like “Why…?” or “How…?” are rarely testable, but question formations like “What happens if…?” or “Is there any difference if…?” are testable.

Formulating testable hypotheses—A hypothesis is an affirmative or null affirmation that can be used to predict the result of an experiment (the answer to the question). A testable hypothesis should be formulated in quantitative terms and then compared with the data using statistical and probabilistic tools to check whether or not it is true. An example of a testable hypothesis is, “The speed of a car is dependent on the quality of its tires.”

Evaluating data—The data obtained in an experiment designed to test a hypothesis and answer a scientific question should be evaluated using statistical tools to check if it is accurate and reproducible, as well as to determine if the data contradicts the hypothesis, is inconclusive, or supports the hypothesis.

Describing Data

The data obtained in an investigation can be categorized as two broad types: categorical, which represents qualitative data such as gender, eye color, etc., and numerical, which represents quantitative data such as height, weight, speed, etc.

Variables

A variable is the observable characteristic or discernable aspect of an object of study that can adopt different values or be expressed in several categories. Variables can be classified as dependent and independent.

Independent—The independent variable is the characteristic that the researcher manipulates during the experiment to discover its relationship with the dependent variable.

Dependent—A dependent variable is the characteristic that changes according to the action that the researcher exerts over the independent variable.

Statistical Parameters

A parameter is a value that summarizes or describes the general behavior of a population. There are centralization parameters such as the mean, mode, and median, and dispersion parameters such as the mean deviation, variance, and standard deviation.

Relationships

Regression techniques allow researchers to predict how the values of the independent variable (x) will influence the dependent variable (y). The different types of relationships between these two variables are described below:

Linear—The relationship is linear if it forms a straight line when graphed.

Nonlinear—If the regression does not fit a straight line (i.e., the correlation coefficient is far from 1), the variables can still have a nonlinear relationship. Some common nonlinear relationships are quadratic, exponential, and logarithmic.

Discussing Findings

Results are the discussion of the findings of a study and the major scientific contribution that is covered in a scientific article. The results should describe only the findings of the study and be completely objective (without commentary or judgment). The text should be complemented with tables and graphs. The discussion of these results should explain the meaning of the results and put those results in context with existing evidence. When discussing results, the researcher should also identify the strengths and weaknesses of the investigation.

Using Academic Language

When discussing scientific findings, the researcher should use academic language, which is characterized by an impersonal tone, and specialized vocabulary, which should be used appropriately, including these terms:

Observation—Observation is the direct examination of a fact or phenomenon as it occurs spontaneously and naturally, with a defined purpose according to a plan, and recorded in a systematic way.

Organization—Organization refers to the arrangement of the sections of the report.

Experimentation—Experimentation is researching phenomena by acting upon them, creating conditions according to the goals the researcher wants to achieve.

Inference—Inference is the use of statistical tools to deduce the properties of a population from a small part of it (i.e., a sample).

Prediction—A prediction is a description of what will happen according to the scientific analysis of existing conditions made in advance of performing an experiment.

Evidence—Empirical evidence is the information obtained by means of observation, experience, or experiments, which are intended to support or oppose a hypothesis or scientific theory.

Opinion—Opinion is the subjective concept or judgment that a person or group of person has about something or someone.

Hypothesis—A scientific hypothesis is the tentative solution or explanation for a given problem. The degree of truth assigned to that hypothesis will depend on the way in which the empirical data support or don’t support what is stated in the hypothesis.

Theory—A theory is a framework that explains phenomena in a systematic, concise, coherent, and predictive way. Theories arise from a proven hypothesis with evidence that is considered valid.

Law—A law is a constant, universal, invariable, and necessary rule that governs the relationship between diverse phenomena in nature.

Following Procedures

When doing research, it is necessary to follow the procedures precisely when carrying out experiments, taking measurements, and performing technical tasks. That is not only to ensure the safety of the researcher, but also the reliability of the data obtained from the procedures.

Analyzing

Scientists build upon their own work and the work of others, so it is important for them to be systematic and consistent in their methods of collecting and analyzing data. Analyzing data starts with selecting the data that will be useful for the research, then discovering and explaining patterns using statistical tools, and, lastly, communicating the results in a way that can be understood by the scientific community.

Communicating

Communicating results is one of the most important parts of the scientific process. It allows for peer review of the results and for discussion that will enrich the scientific contribution of the research. Results can be communicated in scientific meetings or by publishing an article or report about the research in a journal or book. In both verbal and written formats, it is important to use visual aids (e.g., diagrams, graphs) to show the results and allow for better retention and understanding of the information.

Using Engineering Principles

The fundamental activity of an engineer is decision-making to solve problems. There are a series of steps that an engineer must follow when solving a problem:

Define a problem—The first step of the process is defining a problem. As Charles Kettering said: “A problem well-stated is half-solved.”

Identify constraints—After the problem is defined, identify the limitations or conditions that are essential to solving the problem. For example, there may be constraints on the size of a device or the budget for the solution.

Design multiple solutions—The core of the process involves designing preliminary solutions where the most promising ideas are used to create multiple plans and functional designs.

Optimize the solution—After a single solution is selected, the engineer then implements the design and evaluates it using meticulous mathematical and physical analysis techniques. The engineer also analyzes failures in the solution and provides feedback for the design and manufacturing stage.