After yesterday’s post about making the most of Google Keep I received a few emails from readers wanting to know a bit more about how Google Keep works. To answer those questions I recorded the short video that you see embedded below (click here if you cannot see the video).
Recently, ED/IES SBIR announced its 2015 awards. There are 21 awards in all, covering a range of topics and forms of technology. For example, Zaption is designing a mobile app to help teachers integrate video into science instruction; Speak Agent is building an app to help students with speech disabilities to communicate; and Lingo Jingo is developing a platform to help teachers guide English learners. (To view short video demos of the eight new Phase II projects, see this playlist.)
The 2015 awards highlight two trends that have emerged in the ED/IES SBIR portfolio in recent years –games for learning and bridging the research-to-practice gap in education.
Trend #1: Games for Learning
Strange Loop Games to build a virtual world to engage students in learning about ecosystems,
Kiko Labs to develop mini games to strengthen young children’s thinking and memory skills, and
Schell Games to create a futuristic “ball and stick” molecular modeling kit and app to augment chemistry learning.
For a playlist including videos of these games and 19 others out of the ED/IES SBIR program, see here.
The games for learning trend echoes the movement surrounding games in the field, and is highlighted by recent ED sponsored events including ED Games Week in Washington, DC, last September and the Games for Learning Summit in New York City, in April. Both events convened stakeholders to showcase games and discuss the potential barriers and opportunities for collaboration necessary to accelerate the creation of highly effective games for learning. Stay tuned for more information and initiatives on games for learning out of ED’s Office of Technology.
Trend #2: Bridging the Research-to-Practice Gap
Mindset Works, which built on results from prior research including a 2002 IES research grant, to successfully propose a 2010 ED/IES SBIR project to develop SchoolKit. This multimedia platform enables broad distribution of the growth mindset intervention which teaches students to understand that intelligence can be developed through effort and learning. SchoolKit is now in use in more than 500 schools across the country, including half the middle schools in Washington, DC.
Learning Ovationsis building on two prior IES research grants in their 2014 ED/IES SBIR project. The prior IES funding supported the research team as they developed and evaluated an intervention to improve children’s reading outcomes,. This award is supporting the development of an implementation platform to enable large-scale use of this evidence-based intervention across settings. The project is scheduled to end in 2016, after which the platform will be launched.
The new ED/IES SBIR 2015 awards continue the research-to-practice trend. An award to Foundations in Learning furthers basic research from a 2013 National Science Foundation grant (NSF); an award to SimInsights builds on 2005 and 2008IES research projects and a 2011 Defense Advanced Research Project Agency (DARPA) research project; and an award to Apprendris advances a prior 2012 IES research project and prior 2010 and 2013 NSF research projects.
Computers and the software they run are not magic. Nor should they be perceived as such.
Learning to code is not valuable because everyone needs to program computers, but because such an integral part of modern life needs to be understood at a basic, comprehensible level.
I am including a couple whitepapers you can review and forward to all staff who may be curious about our teaching and learning tool and would be attending the demo on May 11th at 1.00pm
Please see the go to meeting instructions for our Bluepulse v1.5 walkthrough.
If you have any questions about the integration, training or implementation, please do not hesitate to email or call and as always I am more than happy to help.
harvest students; feedback – anonymous way to ask questions. D2L surveys offer already this opportunity; Twitter and other the free options for polling apps give the same option, e.g. Polleverywhere gives a word cloud option
the follow up q/n as demonstrated is limited to 160 characters. Why?
i like that it compartmentalize the anonymity but I really ask myself: would SCSU faculty go to such length?
presumptions: non-tenured faculty is interested in the top layers students and wants to find out what works for them best. this loaded, since, if there ARE different learning styles, then what worked for the top layer might be exactly what did not work for the bottom layer, but this approach will gave the faculty a justification to keep stratifying students, instead of thinking of diverse ways to approach all layers. this part of sale, not pedagogy. sorry.
weakness; the entire presentation is trying to sell a product, which might be good for different campus, but not for SCSU, where faculty are overworked, the class load is so great that going to such details might be questionable.
exporting CSV for data massaging is not big deal. indeed the easy of this particular software is admirable, but if the faculty has time to go into such details, they can export the data from D2L or Google Forms and open it in SPSS
Greg’s question: mobility.
libraries and services. pole users without being tied to course. again, that all can be done with other services in the library. if the library cares about it at all.
Faculty request to lay voice over a presentation with pictures. Solutions:
PowerPoint:
Windows / PC
ppt voice over
Apple/Mac
voice over PPT on Apple
advantages:
– unfortunately, faculty are way too familiar with PPT. Familiar to the point that they don’t want to try something better.
– FERPA complient
disadvantages:
– too old. PPT is pre-Internet. It does not matter how much Microsoft is trying to adapt it, the concept is old. There is a myriad of cloud-based solutions, which do better job: https://blog.stcloudstate.edu/ims/2013/09/30/the-5-best-free-slideshow-presentation-and-creation-tools-for-teachers/
– too many files, too many variations
– PPT posted in D2L displays in the D2L Viewer. The visuals are there, but the voice is not. In order to hear the voice, students must download the presentation. Faculty must reflect this in the syllabus.
– faculty need to know how to upload on their web space and figure out URL, if PPT is not place in LMS (D2L)- if faculty places PPT in LMS (D2L), then it is behind password; nearly impossible to share (can share only with SCSU and/or MnSCU members.
– faculty must remember to indicate in the syllabus and/or D2L / Content that “in order to hear the voice over, user must download presentation.”
SlideShare
slideshare
advantages:
– it is a “social” app, like LinkedIn and Twitter. Tagged correctly, the presentation is a platform for “same-minded” people to discuss mutual interests.
– excellent for sharing: conferences, MOOCs etc.
– it has discussion group in LinkedIn.
disadvantages:
– voice over presentation: way to cumbersome compared to PPT. Watch their presentation
– by FERPA regulations, if the presentation contains personal data about students, it cannot be shared on SlideShare
– it is a “social” app, like LinkedIn and Twitter. Tagged correctly, the presentation is a platform for “same-minded” people to discuss mutual interests.
– excellent for sharing: conferences, MOOCs etc.
– like PPT, very easy upload of pix and voice over. Better the PPT, since it is online and easy to distribute.
– easy to upload PPT and easy to voice over each slide
disadvantages:
– does not embed in D2L (it is D2L issue, not the app), but works perfectly as a link
– faculty must remember to indicate in the syllabus and/or D2L / Content that when clicking on the URL to the PPT, user must simultaneously press “Ctrl” key to open PPT in a separate browser window or tab
– by FERPA regulations, if the presentation contains personal data about students, it cannot be shared on SlideShare
– consistently voted through last 5 years by K12 educators as great interactive tool.
– video, images, audio and text.
– “constructivist” premiss: teacher and students can exchange asynchronously ideas by using images, video, text and audio.
disadvantages:
– free option has limited features.
– by FERPA regulations, if the presentation contains personal data about students, it cannot be shared on on this site.
– voice over too complex (very much the same as with SlideShare)
SoftChalk
advantages:
– FERPA compliant; endorsed by MnSCU
disadvantages:
–
others
I have not included TechSmit’s Jing https://www.techsmith.com/jing.html, because their video output (Flash file) is obsolete and impossible to convert for free. While it still can be played, shall faculty want to upload the video file on Youtube or similar social media, it will be impossible.
Integers: A signed or unsigned whole number running from -32,768 to 32,768 or from 0 to 65,535 if not signed. Integers are used anytime something needs to be counted.
Long Integer: Any whole number outside the above range. Python doesn’t distinguish between the two though many languages do. Practically, Python’s integers range from −2,147,483,648 to 2,147,483,648 or 0 to 0 to 4,294,967,295. Most of us will be very happy with this many whole numbers to choose from.
Real and Floating Point Numbers: Real numbers are signed or unsigned numbers including decimals. The numbers 2,3,4 are Integers and Real Numbers. The numbers 2.1, 2.9,3.9 are Real Numbers, but not Integers. Real Numbers can include representations of irrational numbers such as pi. Real numbers must be rational, that is a decimal number that terminates after a finite number of decimals. You will sometimes encounter the term Floating Point Numbers. This is a technical term referring to the way that large Real Numbers are represented in a computer. Python hides this detail from you so Real and Floating Point are used intercangeably in this language.
Binary Numbers: And Octal and Hexadecimal. These are numbers used internally by computers. You will run into these values fairly often. For instance, when you see color values in HTML such as “FFFFFF” or “0000FF”,
Hexadecimal and Octal are used because humans can read them without too much trouble and they are compromise between what computers process and what we can read. Any time you see something in Octal or Hexadecimal, you are looking at something that interfaces with the lower levels of a computer. You will most commonly use Hexadecimal numbers when dealing with Unicode character encodings. Python will interpret any number which begins with a leading zero as binary unless formatting commands have been used.
Numbers such as 7i are referred to as complex. They have a real part, the 7, and an imaginary part, i. Chance are you won’t use complex numbers unless you’re working with scientific data.
A String consists of a sequence of characters. The term String refers to how this data type is represented internally. You store text in Strings. Text can by anything, letters, words, sentences, paragraphs, numbers, just about anything.
Lists are close cousins to Strings, though you may never need to think of them that way. A list is just that, a list of things. Lists may contain any number of numbers or any number of strings. List may even contain any number of other lists. Lists are compared to arrays, but they are not the same thing. In most uses, the function the same so the difference, for our purposes, is moot. Strings are like lists in that, internally, the computer works with strings in an identical manner to lists. This is why the operations on Strings are so different from numbers.
The last main data type in the Python programming language is the dictionary. Dictionaries are map types, known in other languages as hashes, and in computer science as Associative Arrays. The best way to think of what the dictionary does is to consider a Library of Congress Call Number(something this audience is familiar with). The call number is what’s called a Key. It connects to a record which contains information about a book. The combination of keys and records, called values, comprises a dictionary. A single key will connect to a discrete group of values such as the items in this record. Dictionaries will be touched on in the next lesson in some detail in the next course. These are fairly advanced data structures and require a solid understanding a programming fundamentals in order to be used properly.
Statements, an Overview
Programs consist of statements. A statement is a unit of executable code. Think of a statement like a sentence. In a nutshell, statements are how you do things in a program. Writing a program consists of breaking down a problem you want to solve into smaller pieces that you can represent as mathematical propositions and then solve. The statement is where this process gets played out. Statements themselves consist of some number of expressions involving data. Let’s see how this works.
An expression would be something like 2+2=4. This expression, however is not a complete statements. Ask Python to evaluate it and you will get the error “SyntaxError: can’t assign to operator”. What’s going on here? Basically we didn’t provide a complete statement. If we want to see the sum of 2+2 we have to write a complete statement that tells the interpreter what to do and what to do it with. The verb here is ‘print’ and the object is ‘2+2’. Ask Python to evaluate ‘print 2+2’ and it will show ‘4’. We could also throw in subject and do something a bit more detailed: ‘Sum=2+2’. In this case we are assigning the value of 2+2 to the variable, Sum. We can then do all sorts of things with Sum. We can print it. We can add other numbers to it, hand it off to a function and so on. For instance, might want to know the root of Sum. In which case we might write something like ‘print sqrt(sum)’ which will display ‘2’.
A shell is essentially a user interface that provides you access to a system’s features. Normally, this means access to an Operating System. In cases like this, the shell provides you access to the Python programming environment.
Anything preceed by a “#” is not interpreted or executed by the programming shell. Comments are used widely to document programs. One school of programming holds that code should be so clear that comments are uncessary.
Operations on Numbers
Expressions are discrete statements in programming that do something. They typically occupy one line of code, though programmers will sometimes squeeze more in. This is generally bad form and can really make your program a mess. Expressions consist of operations and data or rather data and operations on them. So, what can you do with numbers? Here is a concise list of the basic operations for integers and real numbers of all types:
Arithemetic:
Addition: z= x + y
Subtraction: z = x – y
Multiplication: z = x * y. Here the asterisk serves as the ‘X’ multiplication symbol from grade school.
Division: z = x/y. Division.
Exponents: z = x ** y or xy, x to the y power.
Operations have an order of precedence which follows the algebraic order of precedence. The order can be remembered by the old Algebra mnenomic, Please Excuse My Dear Aunt Sally which is remeinds you that the order of operations is:
Parentheses
Exponents
Multiplication
Division
Addition
Subtraction
Operations on Strings
Strings are strange creatures as I’ve noted before. They have their own operations and the arithmetic operations you saw earlier don’t behave the same way with strings.
Putting Expressions Together to Make Statements
As I noted earlier, all computer languages, and natural languages, possess pragmatics, larger scale structures which reduce ambiguity by providing context. This is a fancy way of saying just as sentences posses rules of syntax to make able to be comprehended, larger documents have similar rules. Computer Programs are no different. Here’s a break down of the structure of programs in Python, in a general sense.
Programs consist of one or more modules.
Modules consist of one or more statements.
Statements consist of one or more expressions.
Expressions create and/or manipulate objects(and variables of all kinds).
Modules and Programs are for the next class in the series, though we will survey these larger structures next lesson. For now, we’ll focus on statements and expressions. Actually, we’ve already started with expressions above. In Python, statements can do three things.
Assign a variable
Change a variable
Take an action
Variable Names and Reserved Words
Now that we’ve seen some variable assignments, let’s talk about best practices. First off, aside from reserved words, variable names can be almost any combination of letters, numbers and punctuation marks. You, however, should never ever, use the following punctuation marks in variable names:
+
–
!
@
^
%
(
)
.
“
?
/
:
;
*
These punctuation marks tends to be operators and characters that have special meanings in most computer languages. The other issue is reserved words. What are “reserved words”? They are words that Python interprets as commands. Pythons reservers the following words.:
True: A special value set aside for boolean values
False: The other special value set aside for boolean vaules
None: The logical equivalent of 0
and: a way of combining logical conditions
as: describes how modules are imported
assert: a way of forcing something to take on a certain value. Used in debugging of large programs
break: breaks out of a loop and goes on with the rest of the program
class: declares a class for object oriented design. For now, just remember not to use this variable name
continue: returns to the top of the loop and keeps on going again
def: declares functions which allow you to modularize your code.
elif: else if, a cotnrol structure we’ll see next lesson
else: as above
except: another control structure
finally: a loop control structure
for: a loop control structure
from: used to import modules
global: a scoping statement
if: a control structure/li>
in: used in for each loops
is: a logical operator
lamda: like def, but weird. It defines a function in a single line. I will not teach this becuase it is icky. If you ever learn Perl you will see this sort of thing a lot and you will hate it, but that’s just my personal opinion.
nonlocal: a scoping command
not: a logical operator
or: another logical operator
pass: does nothing. Used as placeholder
raise: raises an error. This is used to write custom error messages. Your programs may have conditions which would be considered invalid based on our business situation. The interpreter may not consider them errors, but you might not want your user to do something so you ‘raise’ an exception and stop the program.
return: tells a function to return a value
try: this is part of an error testing statement
while: starts a while loop
with: a context manager. This will be covered in the course after the next one in this series
yield: works like return
Variable names should be meaningful. Let’s say I have to track a person’s driver license number. explanatory names like ‘driverLicenseNumber’.
Use case to make your variable names readable. Python is case sensitive, meaning a variable named ‘cat’ is different from named ‘Cat’. If you use more than one word to name variable, start of lower case the change case on the second word. For instance “bigCats = [‘Tiger’,’Lion’,’Cougar’, ‘Desmond’]”. The common practice used by programmers in many settings is that variables start with lowercase and functions(methods and so on) start with upper case. This is called “Camel Case” for its lumpy, the humpy appearance. Now, as it happens, there is something of a religious debate over this. Many Python programmers prefer to keep everything lower case and join words in a name by underscores such as “big_cats”. Use whichever is easiest or looks the nicest to you.
Variable names should be unique. Do not reuse names. This will cause confusion later on.
Python conventions. Python, as with any other programming language, has culture built up around it. That means there are some conventions surrounding variable naming. Two leading underscores, __X, denote system variables which have special meaning to the interpreter. So avoid using this for your own variables. There may be a time and place, but that’s for an advanced prorgramming course. A single underscore _X indicates to other programmers that this a fundamental variable and that they mess with it at their own peril.
Avoid starting variable names with a number. This may or may not return an error. It can also mislead anyone reading your program.
“A foolish consistency is the hobgoblin of little minds”. But not to programming minds. Consistency helps the readability of code a great deal. Once you start a system, stick with it.
Statement Syntax
Putting together valid statements can be a little hard at first. There’s a grammar to them. Thus far, we’ve mainly been workign with expressions such as “x = x+1”. You can think of expression as nouns. We’ve clearly defined x, but how do we look inside? For that we need to give it a verb, the print command. We would then write “print x”. However we can skip the middle statement and print an expression such as “print x + 1”. The interpreter evaluates this per the order of operations I laid out earlier. However, once that expression is evaluated, it then applies the verb, “print”, to that expression.
Print is a function that comes with the Python distribution. There are many more and you can create your own. We’ll cover that a bit in next lesson. Let’s look at little more at the grammar of a statement. Consider:
x = sin(b)
Assume that b has been defined elsewhere. x is the subject, b is the object and sin is the verb. Python will go to the right side of the equal sign first. It will then go to the inside of the function and evaluate what’s there first. It then evaluates the value of the function and finishes by setting x to that value. What about something like this?
x=sin(x+3/y)
Python evaluates from the inside out according to the rules of operation. Very complex statements can be built up this way.
x = sin(log((x + 3)/(e**2)))
Regardless of what this expression evaluates to (I don’t actually know), Python starts with the innermost parentheses, then works through the value of e squared then adds 3 to x and divides the result by e squared. With that worked out, it takes the logarithm of the result and takessthe sine of that before setting x to the final result.What you cannot do is execute more than one statement on a line. No more than one verb on a line. In this context, a verb is an assignment, or a command acting on an expression
markdown cell
code cell
Call up your copy of Think Python or go to the website at http://www.greenteapress.com/thinkpython/html/. Read Chapter 2. This will reiterate much of what I’ve presnted here, but this will help cement the content into you minds. Skip section 2.6 because IPython treats everything as script mode. IPyton provides you with the illusion of interactive, but everything happens asynchronously. This means that any action you type in will not instantaneously resolve as it would if you were running Python interactively on your computer. You will have to use print statements to see the results of your work.
Your assignment consists of the following:
Exercise 1 from Chapter 2 of Think Python. If you type an integer with a leading zero, you might get a confusing error:
<<< zipcode = 02492
SyntaxError: invalid token
Other numbers seem to work, but the results are bizarre:
<<< zipcode = 02132
<<< zipcode
1114
Can you figure out what is going on? Hint: display the values 01, 010, 0100 and 01000.
Exercise 3 from Chapter 2 of Think Python.Assume that we execute the following assignment statements:
width = 17
height = 12.0
delimiter = ‘.’
For each of the following expressions, write the value of the expression and the type (of the value of the expression).
width/2
width/2.0
height/3
1 + 2 5
delimiter 5
Exercise 4 from Capter 2 of Think Python. Practice using the Python interpreter as a calculator:
1. The volume of a sphere with radius r is 4/3 π r3. What is the volume of a sphere with radius 5? Hint: 392.7 is wrong!
2. Suppose the cover price of a book is $24.95, but bookstores get a 40% discount. Shipping costs $3 for the first copy and 75 cents for each additional copy. What is the total wholesale cost for 60 copies?
3/ If I leave my house at 6:52 am and run 1 mile at an easy pace (8:15 per mile), then 3 miles at tempo (7:12 per mile) and 1 mile at easy pace again, what time do I get home for breakfast?
In your IPython notebook Create a markdown cell and write up your exercise in there. Just copy it from the textbook or from the above write up. Next ceate a code cell and do your work in there. Please, comment your work thoroughly. You cannot provide too many comments. Use print statements to see the outcome of your work.
the intersection of computing and the disciplines of the humanities. five concepts: web design; digital exhibits; GIS geographical information systems; text mining; text encoding