Key Ideas
Computing and science are connected:
scientists utilize computers as tools for conducting research
computer-based models and a computational approach are increasingly used
computer science is a rigorous field of study regarding "artificial" systems
utilizes the scientific method and experimentation; computational thinking
new scientific fields such as bioinformatics and data science blur the lines
Programming is a tool for:
solving problems
experimentation
analysis
Computer science is more than just programming:
problem solving
design & analysis of algorithms
hardware design and manufacturing
interface design and implementation
theoretical understanding of computation
Skills Developed
Problem-solving skills
Analytical/Empirical reasoning skills
Communication skills
Web page development
Programming Concepts
static (HTML) vs. dynamic (JavaScript) pages
dynamic elements (images, buttons, boxes, divs, spans)
element attributes (href, src, id, height, value, innerHTML, style)
event handling (onclick, onmouseover, onmouseout)
variables & assignments
e.g., gallery.html, form.html, story.html
data types & expressions
e.g., tip.html, increment.html, grades.html
functions & libraries
e.g., pick4.html, dice1.html, coin.html, oracle.html
conditional execution
e.g., tip3.html, letter.html, dicestats1.html, slots.html
repetition & simulation
e.g., interest.html, disease.html, manyrolls.html, volleyball.html
counters & sums
e.g., dicestats3.html, slots.html, manyrolls.html
General Concepts
Computer basics
von Neumann architecture, hardware vs. software
World Wide Web
history, browser & server, HTTP, caching, cookies
Internet
history, distributed, packet switching, TCP/IP, DNS
History of computers
generations (relays, vacuum tubes, transistors, IC, microprocessors, ULSI)
Scientific & Computational Thinking
history, scientific method, consistency vs. accuracy, computational thinking
Algorithms & programming
algorithms, efficiency, high-level languages, compilers & interpreters
Computer Science as a Discipline
CS as science?, central themes (software, hardware, theory), subfields, related fields
Inside the Data
analog vs. digital, number/text/sound/image/video representations
Inside the Computer
transistors, gates, integrated circuits, circuit manufacture, Moore's Law
Computers & Society
positive impacts: everyday tasks, info source, communications, commerce, ...
potential dangers: overreliance, overload, privacy & security, digital divide, ...
Applications in science
biology/bioinformatics: computer tools, modeling, biological databases
data science: supervised (e.g., neural networks) vs. unsupervised (e.g., clustering)
modeling & simulations: Monte Carlo methods, random walks, dice, slots