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The ENCODE project used a wide range of experimental techniques, ranging from RNA-seq, CAGE-seq, Exon Arrays, MAINE-seq, Chromatin ChIP-seq, DNase-seq, and many more.
One of the most important techniques used was ChIP-seq (chromatin immunoprecipitation followed by sequencing). The first step in a ChIP experiment is to target DNA fragments associated with a specific protein. This is done by using an anti-body that targets the specific protein and is used to immunoprecipitate the DNA-protein complex. The final step is to assay the DNA. This will determine the sequences bound to the proteins.
ChIP-seq has several advantages over previous techniques (e.g. ChIP-chip). For example, ChIP-seq has single nucleotide resolution and its alignability increases with read length. However, ChIP-seq has several disadvantages. Sequencing errors tend to increase substantially near the end of reads. Also, with low number of reads, sensitivity and specificity tend to decrease when detecting enriched regions. Both of these problems arise when processing the data and many of the computational techniques seek to rectify this.
24.2 Theories and Perspectives in Science Education
Numerous theories and perspectives concerning the teaching and learning of science are addressed in this book, a few of the more prominent ones of which are referenced here.
24.2.1 – Active Learning: Learn by Doing
Active learning is a set of strategies that posits the responsibility for learning with the student. Discovery learning , problem-based learning (22.3), experiential learning, and inquiry-based instruction (22.1) are examples of active learning. Discussion, debate (22.4), student questioning (5.1, 22.1, 23.1), think-pair-share (25.7), quick-writes (25.7), polling, role playing, cooperative learning (22.3, 22.5), group projects (13.1-8, 22.5), and student presentations (22.4) are a few of the many activities that are learner driven. It should be noted, however, that even lecture can be an active learning event if students processes and filter information as it is provided. Cornell notes (3.1) and diagramming (16.2) are a couple of activities that can make lectures active learning events.
24.2.2 – Teaching to multiple learning modalities
We can learn through any of our five senses, but the three most valuable are vision, hearing, and touch. Theorists and practitioners claim that learners have a preference for one learning style over another. Visual learners learn best by watching, while auditory learners learn best by verbal instruction, and kinesthetic learners learn best by manipulation. Because of the demands of the profession, teachers often resort to the instructional style that requires the least time and preparation, namely lecture and discussion. Although these may be valuable approaches to teaching and learning, they fail to take advantage of other learning modalities, and disenfranchise students whose primary modality is visual or kinesthetic. Throughout this book we emphasize the use of all three modalities in teaching and learning.
24.2.3 – Teaching to multiple intelligences
Intelligence is a property of the mind that includes many related abilities such as the capacities to reason, plan, solve problems, comprehend language and ideas, learn new concepts, and think abstractly. Historically, psychometricians have measured intelligence with a single score (intelligence quotient, IQ) on a standardized test, finding that such scores are predictive of later intellectual achievement. Howard Gardner and others assert that there are multiple intelligences, and that no single score can accurately reflect a person’s intelligence. More importantly, the theory of multiple intelligences implies that people learn better through certain modalities than others, and that the science teacher should design curriculum to address as many modalities as possible. Gardner identifies seven intelligences, which are listed below. The numbers in parentheses indicate sections in this book that address each intelligence.
- Logical /Mathematical Intelligence is used when thinking conceptually (6.1-4, 7.1-7, 10.1-5, 13.9, 16.1-6, 18.1-3), computing (14.1-3, 15.1-7, 17.1-7, 20.1, 20.8), looking for patterns (1.1-4,16.4, 16.6, 17.5-7), and classifying (8.1-6, 19.1-5)
- Linguistic/Language Intelligence is used when learning by listening (21.1), verbalizing (1.1-4, 3.1-4, 11.2-4, 22.6), reading (2.1-4), translating (14.1-3), and discussing (8.6, 22.4).
- Naturalist Intelligence is used to question (5.1, 22.1, 23.1), observe (5.2-3, 22.2), investigate (23.2), and experiment (5.1-10, 23.3-4).
- Visual / Spatial Intelligence is used when learning with models (12.1-5), photographs (16.4, 16.6), videos (16.5), diagrams (8.1-6, 16.1-3, 20.2-7), maps (21.1-7) and charts (20.2-7).
- Bodily kinesthetic intelligence is used to process knowledge through bodily sensations (12.2), movements (12.2), physical activity (labs in companion volumes, Hands-on Chemistry and Hands-on Physics ), and manipulation (22.2).
- Interpersonal Intelligence is used when learning through cooperative learning experiences (22.3, 22,5), group games (13.1-8), group lab work (22.5), and dialog (8.6, 23.4).
- Intrapersonal Intelligence is used when learning through self-dialog (7.1-3,11.1), studying (11.2-4) and self-assessment (7.4-7).
- Musical Intelligence is used when learning through rhythm, melody, and non-verbal sounds in the environment (24.8).
24.2.4 – Metacognition: Teaching students to think about their thinking
John Flavel argues that learning is maximized when students learn to think about their thinking and consciously employ strategies to maximize their reasoning and problem solving capabilities. A metacognitive thinker knows when and how he learns best, and employs strategies to overcome barriers to learning. As students learn to regulate and monitor their thought processes and understanding, they learn to adapt to new learning challenges. Expert problem solvers first seek to develop an understanding of problems by thinking in terms of core concepts and major principles (6.1-4, 7.1-7, 11.1-4). By contrast, novice problem solvers have not learned this metacognitive strategy, and are more likely to approach problems simply by trying to find the right formulas into which they can insert the right numbers. A major goal of education is to prepare students to be flexible for new problems and settings. The ability to transfer concepts from school to the work or home environment is a hallmark of a metacognitive thinker (6.4).
24.2.5 –Developing higher order reasoning
Perhaps the most widely used classification of human thought is Bloom’s Taxonomy . Benjamin Bloom and his team or researchers wrote extensively on the subject, particularly on the six basic levels of cognitive outcomes they identified – knowledge, comprehension, application, analysis, synthesis, and evaluation. Bloom’s taxonomy (6.1) is hierarchical, with knowledge, comprehension and application as fundamental levels, and analysis, synthesis and evaluation as advanced (6.1-6.4). When educators refer to “higher level reasoning,” they are generally referring to analysis, synthesis and/or evaluation. One of the major themes of this book is to develop higher order thinking skills through the teaching of science.
24.2.6 –Constructivism: Helping students build their understanding of science
Constructivism is a major learning theory, and is particularly applicable to the teaching and learning of science. Piaget suggested that through accommodation and assimilation, individuals construct new knowledge from their experiences. Constructivism views learning as a process in which students actively construct or build new ideas and concepts based upon prior knowledge and new information. The constructivist teacher is a facilitator who encourages students to discover principles and construct knowledge within a given framework or structure. Throughout this book we emphasize the importance of helping students connect with prior knowledge and experiences as new information is presented, so they can dispense with their misconceptions (7.4-7) and build a correct understanding. Seymour Papert, a student of Piaget, asserted that learning occurs particularly well when people are engaged in constructing a product. Papert’s approach, known as constructionism, is facilitated by model building (12.5), robotics, video editing (16.5), and similar construction projects.
24.2.7 – Pedagogical content knowledge (PCK) in science
An expert scientist is not necessarily an effective teacher. An expert science teacher, however, knows the difficulties students face and the misconceptions they develop, and knows how to tap prior knowledge while presenting new ideas so students can build new, correct understandings. Schulman refers to such expertise as pedagogical content knowledge (PCK), and says that excellent teachers have both expert content knowledge, and expert PCK. In How People Learn, Bransford, Brown and Cocking state: “Expert teachers have a firm understanding of their respective disciplines, knowledge of the conceptual barriers that students face in learning about the discipline, and knowledge of effective strategies for working with students. Teachers' knowledge of their disciplines provides a cognitive roadmap to guide their assignments to students, to gauge student progress, and to support the questions students ask.” Expert teachers are aware of common misconceptions and help students resolve them. This book is dedicated to improving science teacher pedagogical content knowledge.
Bonwell, C. & Eison, J. (1991). Active Learning: Creating Excitement in the Classroom AEHE-ERIC Higher Education Report No.1. Washington, D.C.: Jossey-Bass.
Bruner, J. S. (1961). The act of discovery. Harvard Educational Review 31(1): 21–32.
Table of contents
You should begin with a specific research question in mind. You may need to spend time reading about your field of study to identify knowledge gaps and to find questions that interest you.
We will work with two research question examples throughout this guide, one from health sciences and one from ecology:
Example question 1: Phone use and sleep
You want to know how phone use before bedtime affects sleep patterns. Specifically, you ask how the number of minutes a person uses their phone before sleep affects the number of hours they sleep.
Example question 2: Temperature and soil respiration
You want to know how temperature affects soil respiration. Specifically, you ask how increased air temperature near the soil surface affects the amount of carbon dioxide (CO2) respired from the soil.
To translate your research question into an experimental hypothesis, you need to define the main variables and make predictions about how they are related.
|Research question||Independent variable||Dependent variable|
|Phone use and sleep||Minutes of phone use before sleep||Hours of sleep per night|
|Temperature and soil respiration||Air temperature just above the soil surface||CO2 respired from soil|
Then you need to think about possible extraneous and confounding variables and consider how you might control them in your experiment.
|Extraneous variable||How to control|
|Phone use and sleep||Natural variation in sleep patterns among individuals.||Control statistically: measure the average difference between sleep with phone use and sleep with phone use rather than the average amount of sleep per treatment group.|
|Temperature and soil respiration||Soil moisture also affects respiration, and moisture can decrease with increasing temperature.||Control experimentally: monitor soil moisture and add water to make sure that soil moisture is consistent across all treatment plots.|
Finally, put these variables together into a diagram. Use arrows to show the possible relationships between variables and include signs to show the expected direction of the relationships.
Here we predict that the amount of phone use will have a negative effect on hours of sleep, and predict an unknown influence of natural variation on hours of sleep.
Here we predict that increasing temperature will increase soil respiration and decrease soil moisture, while decreasing soil moisture will lead to decreased soil respiration.
24.2: Experimental Techniques - Biology
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Feature Papers represent the most advanced research with significant potential for high impact in the field. Feature Papers are submitted upon individual invitation or recommendation by the scientific editors and undergo peer review prior to publication.
The Feature Paper can be either an original research article, a substantial novel research study that often involves several techniques or approaches, or a comprehensive review paper with concise and precise updates on the latest progress in the field that systematically reviews the most exciting advances in scientific literature. This type of paper provides an outlook on future directions of research or possible applications.
Editor’s Choice articles are based on recommendations by the scientific editors of MDPI journals from around the world. Editors select a small number of articles recently published in the journal that they believe will be particularly interesting to authors, or important in this field. The aim is to provide a snapshot of some of the most exciting work published in the various research areas of the journal.
Low-cost Solutions for Velocimetry in Rotating and Opaque Fluid Experiments using Ultrasonic Time of Flight
Authors (first, second and last of 4)
- Fabian Burmann
- Jerome Noir
- Andrew Jackson
- Content type: Research paper
- Open Access
- Published: 30 June 2021
Development of an Integrated Load Testing Device for a Substructure Hybrid Test of a Curved Bridge
Authors (first, second and last of 5)
- C. Du
- T. Wang
- Y. Lei
- Content type: Research paper
- Published: 28 June 2021
The Effect of Load Phase Angle on Roof Components of Electric Driven Bus Fatigue Damage
Numerical Simulations of Modal Tests on Yingzhou Bridge Using a Passing Vehicle as the Excitation
- J.H. Fan
- Z.H. Xiao
- X.X. Cheng
- Content type: Applications paper
- Published: 28 June 2021
J-integral Analysis of the Simulated Heat-affected Zone of the Elevated-temperature Martensitic Steel
Authors (first, second and last of 5)
- B. Zečević
- L. Milović
- V. Aleksić
- Content type: Research paper
- Published: 24 June 2021
Learn about the technologies underlying experimentation used in systems biology, with particular focus on RNA sequencing, mass spec-based proteomics, flow/mass cytometry and live-cell imaging.
A key driver of the systems biology field is the technology allowing us to delve deeper and wider into how cells respond to experimental perturbations. This in turns allows us to build more detailed quantitative models of cellular function, which can give important insight into applications ranging from biotechnology to human disease. This course gives a broad overview of a variety of current experimental techniques used in modern systems biology, with focus on obtaining the quantitative data needed for computational modeling purposes in downstream analyses. We dive deeply into four technologies in particular, mRNA sequencing, mass spectrometry-based proteomics, flow/mass cytometry, and live-cell imaging. These techniques are often used in systems biology and range from genome-wide coverage to single molecule coverage, millions of cells to single cells, and single time points to frequently sampled time courses. We present not only the theoretical background upon which these technologies work, but also enter real wet lab environments to provide instruction on how these techniques are performed in practice, and how resultant data are analyzed for quality and content.
A Word From Verywell
While experimental psychology is sometimes thought of as a separate branch or subfield of psychology, experimental methods are widely used throughout all areas of psychology. Developmental psychologists use experimental methods to study how people grow through childhood and over the course of a lifetime. Social psychologists utilize experimental techniques to study how people are influenced by groups. Health psychologists rely on experimentation and research to better understand the factors that contribute to wellness and disease.
How to Use the Scientific Method
This article was co-authored by Bess Ruff, MA. Bess Ruff is a Geography PhD student at Florida State University. She received her MA in Environmental Science and Management from the University of California, Santa Barbara in 2016. She has conducted survey work for marine spatial planning projects in the Caribbean and provided research support as a graduate fellow for the Sustainable Fisheries Group.
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The scientific method is the backbone of all rigorous scientific inquiry. A set of techniques and principles designed to advance scientific research and further the accumulation of knowledge, the scientific method has been gradually developed and honed by everyone from the philosophers of ancient Greece to the scientists of today. While there are some variations on the method and disagreement over how it should be used, the basic steps are easy to understand and invaluable not only to scientific research but also to solving everyday problems.
Conducting the Experiment
An experiment is typically carried out by manipulating a variable, called the independent variable, affecting the experimental group. The effect that the researcher is interested in, the dependent variable(s), is measured.
Identifying and controlling non-experimental factors which the researcher does not want to influence the effects, is crucial to drawing a valid conclusion. This is often done by controlling variables, if possible, or randomizing variables to minimize effects that can be traced back to third variables. Researchers only want to measure the effect of the independent variable(s) when conducting an experiment, allowing them to conclude that this was the reason for the effect.
Career Opportunities in Biopsychology
If you are interested in a career in the area of biopsychology, then you have quite a few different options. Some who enter this type of field choose to work in research where they might work at a university, drug company, government agency, or other industry.
Others choose to work with patients to help those who have experienced some type of brain damage or disease that has had an impact on their behavior and functioning.
The following are just a few of the career specializations that are related to biopsychology:
- Behavioral neuroscientist: Analyzes how the brain, nervous system, and other organs impact behavior
- Cognitive neuroscientist: Investigates brain activity and scans to research how people think, learn, and solve problems
- Comparative psychologist: Looks at the behaviors of different species and compares them to each other and to humans
- Evolutionary psychologist: Examines the evolutionary bases of behavior
- Neurologist: Treats patients with damage or disease which affects the brain and nervous system