South 고등학교 2학년 Convergent Science Inquiry
Chapters: 3
1. Understanding convergent inquiry
Science connected with other fields · Inquiry in art and social science · Scientific methods of inquiry · Digital tools including AI
- Interdisciplinary Science: Solving Problems Across Subjects – Real problems do not come sorted into school subjects. Interdisciplinary science means joining ideas and methods from several fields, such as physics, chemistry, biology, maths, technology, art and social science, to understand or solve one problem. This joined-up way of asking questions is also called convergent inquiry. Teams use the design cycle (research, plan, build, test, improve), make models, measure and share results, and think about how a solution affects people and nature. Climate change, clean water, medical scanners and smart cities are all solved this way.
- The Scientific Method – The scientific method is the careful way scientists find out how the world works. Observe something, ask a testable question, make a hypothesis (a clear, testable guess), test it with a fair experiment (change one variable, measure one, keep the rest the same), repeat and record data, analyse it, draw a conclusion and share it so others can check. Results that fail the test are useful too: they send you back to a new hypothesis.
2. The process of convergent inquiry
Finding a problem · Hypotheses and design · Collecting data · Processing data · Statistics: mean and SD · Drawing conclusions · Communicating results
- The Scientific Method – The scientific method is the careful way scientists find out how the world works. Observe something, ask a testable question, make a hypothesis (a clear, testable guess), test it with a fair experiment (change one variable, measure one, keep the rest the same), repeat and record data, analyse it, draw a conclusion and share it so others can check. Results that fail the test are useful too: they send you back to a new hypothesis.
- Data Handling: Collect, Organise and Show Data – Data is a set of facts, such as answers, counts or measurements. Data can be qualitative (words) or quantitative (numbers); numbers are discrete (counted) or continuous (measured). We collect data by surveys, observation, experiments or from existing sources, then organise it with tally marks into a frequency table. We show it with the right graph: bar graphs to compare groups, pie charts to show parts of a whole, line graphs for change over time and scatter graphs for links between two variables. Computers store data as structured tables or unstructured text, images and sound.
- Data Analysis – Data analysis means turning raw data into answers. It follows a cycle: ask a question, collect data, clean it (remove errors, repeats and blanks), organise and transform it, analyse it with summaries such as mean, median, range and patterns, show it with a good chart, and draw a careful conclusion. Watch for outliers, small samples and bias, and remember that a correlation between two things does not prove that one causes the other. Data must also be stored safely and used with permission.
- Measures of Dispersion: Range, Mean Deviation, Variance and SD – Dispersion means spread: how far the values sit from the centre. Range = largest − smallest. Mean deviation = average distance from the mean (or median). Variance = average of squared distances from the mean. Standard deviation = √variance. The same ideas work for grouped data when every term is multiplied by its frequency.
- Science Communication: Sharing and Judging Scientific Results – Science communication means sharing findings clearly and honestly, and judging what others claim. Fit the message to the audience without changing the facts. Reports and posters follow an order: question, method, results, conclusion with limits, references. Graphs need titles, labelled axes and units. In demonstrations and exhibitions, show the idea in action and invite questions. In the media, claims often grow bigger than the evidence, and everyday words like theory mean something different in science. Check the source, the evidence, the sample size and whether others confirmed it.
3. Outlook for convergent inquiry
Future of science and technology · Tackling humanity's hard problems · Research ethics · Solving social problems with science
- Science Inside Advanced Technology – Advanced technology is ordinary science used in clever ways. Sensors turn touch, light and motion into electric signals. Chips are made of silicon. New materials such as graphene get their power from how atoms are arranged. New medicines are designed to fit a target like a key fits a lock. When biology, information and nano-science meet, new fields appear.
- Sustainability – Sustainability means meeting our needs today without taking away the ability of future people to meet theirs. It rests on three pillars — environment, society and economy. A resource is used sustainably when we use it no faster than it renews. Today humanity uses about 1.7 Earths' worth of resources a year, and this use is very unequal. Stewardship, careful planning and spatial tools like GIS help us move towards sustainability.
- Research Ethics: Doing Research the Right Way – Research ethics are the rules that keep research fair and safe. Five big rules: do no harm, get informed consent, protect privacy, be honest with data, and give credit to every source. Good research needs both a good method and good behaviour.
- The Design Process: From Problem to Product – The design process is a loop of steps designers use to solve a real problem for real people: investigate the need, define it in a brief and a measurable specification, generate many ideas, build a prototype, then test and evaluate it against the specification. Whatever fails sends you back round the loop. This repeating is called iteration, and it is how almost every product, app, building and artwork is improved.