Future of Work Opinion

Grad Requirements: From Know Science, To Do Science, To Automate Science

By Tom Vander Ark — May 01, 2017 9 min read
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The duty of a man who investigates the writings of scientists, if learning the truth is his goal, is to make himself an enemy of all that he reads and…attack it from every side. He should also suspect himself as he performs his critical examination of it, so that he may avoid falling into either prejudice or leniency.

~ Ibn al-Haytham (965-1040 CE)

In the Dark Ages (when I went to school), the focus was on ‘knowing’ science: memorizing facts and formulas with little inquiry, translation or application.

Fortunately for most American students, the focus has shifted to ‘doing’ science: conducting inquiries and constructing understanding. Next Generation Science Standards (NGSS) have supported this shift by suggesting a three-dimensional approach:

  • Crosscutting Concepts have application across all domains of science. They include patterns, similarity and diversity; cause and effect; scale, proportion and quantity; systems and system models; energy and matter; structure and function; stability and change. These concepts need to be made explicit for students because they provide an organizational schema for interrelating knowledge from various science fields into a coherent and scientifically based view of the world.

  • Science and Engineering Practices describe what scientists do to investigate the natural world and what engineers do to design and build systems. The practices better explain and extend what is meant by “inquiry” in science and the range of cognitive, social and physical practices that it requires. Students engage in practices to build, deepen and apply their knowledge of core ideas and crosscutting concepts.

  • Disciplinary Core Ideas are the key ideas in science that have broad importance within or across multiple science or engineering disciplines. These core ideas build on each other as students progress through grade levels and are grouped into the following four domains: Physical Science, Life Science, Earth and Space Science and Engineering.

NGSS reflects the interconnected nature of science as it is practiced and experienced in the world. The standards focus on deep understanding as well as the application of concepts. The new standards encourage a rethinking of how high school science is organized.

The figure below outlines courses based on a conceptual progression or core ideas.

How Are Leading Schools Using NGSS?

The Teton Science Schools use the standards as guides for their school network, the graduate program and its science field education courses. “We have a strong emphasis on science and engineering practices through our place-based education core of inquiry and design thinking,” said Nate McClennon, VP of Education and Innovation. “We preach often that science is a verb (action) rather than a noun (collection of facts). Too many students leave science classes with a belief that science is only a set of facts to be memorized.”

At Teton Valley Community School, the middle school is competency based and project driven. NGSS guides the competencies, which then are addressed during the projects.

“All of our graduate students are taught to use the inquiry process (scientific method) and design thinking as a teaching approach for place-based education,” said McClennon. This framework is beginning to be systematically applied to all of their programs across all levels.

Teton Science is conducting research on the Nature of Science--a perspective incorporated into the standards. Their early research suggests that project- and place-based education (#PlaceBasedEd) improves student science knowledge, self-efficacy and attitudes toward science

McClennon has been advising the government of Bhutan on their approach to STEM. Below is a picture from a recent trip that included a challenge to build the tallest possible structure with ten pieces of paper.

High Tech High is known for engaging students in what director Kaleb Rashad called “seriously wicked (open-ended) problems that require investigation, collaboration, sense-making, testing, iterations, making connections across subjects and generating new knowledge.”

High Tech High projects are generally NGSS aligned but start with a compelling topic--immigration, the future of work, principles of flight, heart disease, astrophotography or rocketry--rather than a standard (see this recent blog and podcast).

Design Tech High in Silicon Valley also features inquiry-based hands-on projects. Founder Ken Montgomery said, like High Tech High, they will sacrifice coverage for depth but also said, “The challenge is that the rest of the educational ecosystem is not aligned to support this philosophy.” He adds, “Our students have to do some intense SAT test prep because we don’t cover everything that’s on the test.”

Design Tech transcripts list Physics, Chemistry, Biology and Engineering for similar reasons. “We don’t want to have to do too much translation as we align ourselves with UC expectations,” said Montgomery. “It’s the constant challenge of real K-16 alignment and managing the constraints created by college admission requirements.”

Buck Institute For Education (BIE) is the leading advocate for high-quality project-based learning. Rody Boonchouy, who directs innovation and partnership for BIE, finds NGSS aligns with PBL learning values. He appreciates the crosscutting concepts (below) because they offer opportunities for depth over coverage and for “looping” of content.

NGSS Crosscutting Concepts That Bridge Disciplinary Boundaries

1. Patterns. Observed patterns of forms and events guide organization and classification, and prompt questions about relationships and the factors that influence them.

2. Cause and Effect: Mechanism and explanation. Events have causes--sometimes simple, sometimes multifaceted. A major activity of science is investigating and explaining causal relationships and the mechanisms by which they are mediated. Such mechanisms can then be tested across given contexts and used to predict and explain events in new contexts.

3. Scale, Proportion and Quantity. In considering phenomena, it is critical to recognize what is relevant at different measures of size, time, and energy and to recognize how changes in scale, proportion or quantity affect a system’s structure or performance.

4. Systems and System Models. Defining the system under study—specifying its boundaries and making explicit a model of that system—provides tools for understanding and testing ideas that are applicable throughout science and engineering.

5. Energy and Matter: Flows, Cycles and Conservation. Tracking fluxes of energy and matter into, out of and within systems helps one understand the systems’ possibilities and limitations.

6. Structure and Function. The way in which an object or living thing is shaped and its substructure determine many of its properties and functions.

7. Stability and Change. For natural and built systems alike, conditions of stability and determinants of rates of change or evolution of a system are critical elements of study.

DSST is a school network in Denver that combines a focus on STEM with a focus on character development. Shared values include respect, responsibility, integrity, courage, curiosity and effort. Its commitment to discerning the truth and “possessing confidence and resolve to take risks and make right decisions in the face of pressure and adverse or unfamiliar circumstances” is generally missing from NGSS.

What’s Next? Data & Automation

NGSS include eight practices--scientific method meets design thinking (below). The one practice that is becoming more important in every field is #4: analyzing and interpreting data.

NGSS includes eight practices of science and engineering:

1. Asking questions (for science) and defining problems (for engineering).

2. Developing and using models.

3. Planning and carrying out investigations.

4. Analyzing and interpreting data.

5. Using mathematics and computational thinking.

6. Constructing explanations (for science) and designing solutions (for engineering).

7. Engaging in argument from evidence.

8. Obtaining, evaluating and communicating information.

Eric Lander said in a few years every biologist will be computational. The same is true for doctors, engineers, ecologists and economists. Impact entrepreneurs in every field are creating value by picking a problem, developing some domain expertise, building a dataset and applying smart tools. We call it Cause + Code and it often works like this:

What’s new and different is the cost of storage and computing is basically zero, making it possible to gather gigantic data sets and run computationally intensive machine learning models. As a result, the new step three (planning and carrying out investigations) often involves building public/private partnerships to assemble massive datasets, and the new step four (analyzing and interpreting data) is picking smart tools and pointing them at the data set.

Ahmed Alkhateeb, a molecular cancer biologist at Harvard Medical School, thinks the automation of the scientific process could greatly increase the rate of discovery. “If science is algorithmic, then it must have the potential for automation,” he said.

He explains that the challenge with the automating science is that the three main steps of scientific discovery occupy different planes: observation is sensual; hypothesis-generation is mental; and experimentation is mechanical. He adds, “Automating the scientific process will require the effective incorporation of machines in each step, and in all three feeding into each other without friction.”

Combining reductionist data-mining techniques with inductive computational models could transform our understanding of the natural world by generating and testing millions of novel hypotheses. Ahmed thinks “it would also provide a much-needed reminder of what science is supposed to be: truth-seeking, anti-authoritarian and limitlessly free.”


NGSS are an important contribution to science education. It encourages interdisciplinary inquiry and impact-oriented design.

It includes (but doesn’t adequately emphasize) the growing importance of data wrangling to every field. Cause + Code is the new impact formula. On a recent visit to Teton Science Schools, our partner in the #PlaceBasedEd campaign, I met Tyler, a Stanford ecology graduate student. His South American rainforest preservation projects were aided by big assembled data sets and his fluency in R, a language and environment for statistical computing. Tyler is an example of a young scientist applying the Cause + Code formula: passion for a cause, domain expertise, computational thinking, data wrangling, coding and effective advocacy.

In the next few years, every step of the scientific process will be aided then automated by smart machines. The rise of automated science will require updates--not just to science standards but to our conception of what graduates should know and be able to do.

Exponential technologies are raising economic and ethical issues that will impact the lives and livelihoods of all young people (see our #AskAboutAI series). Leading districts and networks combine inquiry-based science with a strong culture based on shared values. New science learning expectations should be adopted along with a graduate profile that encourages critical thinking, collaboration, and social contribution.

For more, see:

The opinions expressed in Vander Ark on Innovation are strictly those of the author(s) and do not reflect the opinions or endorsement of Editorial Projects in Education, or any of its publications.