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446 lines
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446 lines
16 KiB
:description: Swarmlabs usage tool for students!
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:keywords: Cloud, swarm
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:data-uri:
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:toc: right
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:toc-title:
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:toclevels: 5
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:source-highlighter: coderay
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:icons: font
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= Swarmlab quick-start guide!
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Welcome to the vast world of Swarmlab! +
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Swarmlab is a powerful collaboration tool that connects tutors and students in a unique all-in-one environment that gets work done fast and easily. +
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In other words Swarmlab is the way to make your learning fun while at the same time getting to your goals faster! +
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But let's get you started... +
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Note: These instructions are general targeted at both students and tutors. +
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If you wish to skip to the specific instructions for tutors (lab creation, student invitation etc) click here. +
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WARNING: "General info WILL NOT be repeated so if you have basic questions regarding registration or labroom usage please read on from here. +
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== The first steps
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Before you have all of the powerfull tools of Swarmalb at your grasp you will have to create an account. +
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To do that navigate to the home page at https://api-client.swarmlab.io:8088 +
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You should have been greeted by our login screen! +
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image::images/registration/login.png[]
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To register click on the 'login with sso' option and accept the terms. +
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image::images/registration/terms.png[]
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Now you should be redirected to the login screen and you should be able to use the 'register' option at the bottom to make a new account! +
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image::images/registration/login_main.png[]
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Now fill in the required details +
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image::images/registration/register_details.png[]
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and follow the remaining instructions to activate your account. +
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Now that your acount is ready, lets get to know Swarmlabs main page. +
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== Main Menou
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=== The main page
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Once loaded the main page should look like this:
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image::images/run/main_page.png[]
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On the left we can see that there are two areas inside swarmlab: ::
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. the dashboard where our services live +
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. the 'mylab' tab from which we can control our labrooms. +
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The dashboard page is pretty straight forward: ::
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. The left list shows all the available services and allows you to run them. +
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. The other shows the available lab rooms and allows you to interact with them (p.e. subscribe). +
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With that out of the way lets enter the heart of our platform, 'my lab'! +
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=== My Lab
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Nested under 'mylab' are both creation tools (bootstrap) and execution tools (run).
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=== The run menu
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Inside the run menu there are three areas: ::
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. 'Rub lab instance' +
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. 'Enter lab room' +
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. the console +
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As the names suggest we can use the first to *run* one of our available lab instances, the second to *enter* a created labroom, and the third to *execute* scripts. +
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Lets look at the options one by one. +
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For the purpose of this walkthrough 'testmpi2' and 'test 18' were created. +
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Since the console is explained along with the first area we dont feel there is a need to have seperate walkthrough.
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==== Run lab instance area
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===== Creating a lab
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To create a lab instance simply add a repo to your git! +
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You will then be able to locate that repo inside the instance list and run it. +
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For more info on this please refer to the Bootstrap chapter link:main.adoc.html#_bootstrap[here] ! +
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===== Running a lab instance
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First we have to select the lab we want to run. To find a specific lab we can use the search bar at the top. +
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image::images/run/lab_instance_list.png[]
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After we have located the desired lab we can run it by using the cloud icon. image:images/run/cloud_icon.png[] +
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To request more info about the lab we use the info icon image:images/run/info_icon.png[] and the trashcan image:images/run/trash_icon.png[] deletes the lab (forever). +
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Carefull, forever is a long time! +
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So lets go back to running the lab. After clicking on the according icon we should be redirected to the execution screen. +
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image::images/run/execution_screen.png[]
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Here we can use the command line on the bottom to execute the required commands. Our results will be visible in the console above. +
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image::images/run/ls_results_console.png[]
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Note that you can choose to use the editor of your liking from the drop down menu.
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For more complicated tasks that may require responsivines from the machine you can use the terminal option to open a full-blown unix command line. +
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==== Enter lab room area
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This is the area where you will find the available labrooms created by tutors and join the desired one. +
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===== Browsing labrooms
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You can easily browse throught the available labrooms in the list using the search bar at the top. +
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image::images/run/lab_room_list.png[]
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You can get more info about a specific labroom by clicking the info button image:images/run/info_icon.png[]. +
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image::images/run/info_poppup.png[]
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Active labrooms are indicated using a green color while closed ones with orange. +
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===== Entering a labroom
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Once you have found the labroom you were looking for you can enter by simply clicking on the cloud icon image:images/run/cloud_icon.png[]. +
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You should see a screen as follows:
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image::images/run/password_big.png[]
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The passwords are randomly generated and you can use them to connect to your lesson (see picture bellow). +
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image::images/run/password_user.png[]
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If the tutor is sharing his screen you can watch by clicking on the according button and using the respective password. +
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image::images/run/password_tutor_screen.png[]
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Now, under the password area there are three other options: ::
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'Meeting' image:images/run/meeting_button.png[]::
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Here you can join a meeting with your group (this will redirect you to a jitsi implementation). +
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For more visit https://jitsi.org/ +
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'Gui' image:images/run/gui_button.png[]::
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This loads a graphic unix environment.
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'Console' image:images/run/console_button.png[]::
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This loads a unix terminal.
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By now it should propably be clear how to run a lab from the list or enter a labroom. +
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But you are propably wondering 'My list is empty how am i supposed to run labs from it?!' +
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Well here is where the final but most basic menu comes into play: *'Bootstrap'* ! +
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=== Bootstrap
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image::images/bootstrap/bootstrap_main.png[]
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Here we can create and add labs to our list.
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To do so we have to go through a series of steps, but lets first understand some basic things about how swarmlab works...
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TIP: Every swarmlab lab instance resides in a git repo created inside link:https://git.swarmlab.io:3000[our git^] and owned by the lab creator. This repo then serves as a 'home' for all the work inside that lab. +
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So for us to create and run a lab we have to link a service to a git repo. +
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Asuming we have an account (using the same email as our swarmlab account!) all our repos should be shown on the list in the top left corner. +
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To search for any public repo we can use the search bar. +
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image::images/bootstrap/test_search_repo.png[]
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From that list we can now select the desired repository that we want to use by clicking on the plug icon. image:images/bootstrap/plug_icon.png[] +
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We can use any repo we like, but we will be able to commit only to those that we have access to. +
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If we wish to edit or contribute to the development of a project we are not part of we can use the clone option as usual! +
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Now we have to select the service that our lab will be using. We just select the desired one from the list on the right and it will be automatically linked to the project. +
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image::images/bootstrap/service_select.png[]
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Finally we have to save the lab instance by filling in the required info at the bottom. +
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image::images/bootstrap/save_lab_details.png[]
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== Tutors Menou
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Tutors have access to an extended 'my lab/bootstap' page where they can create labrooms from existing lab instances. +
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To do so we have to scroll all the way down whilst on the Bootstrap page. +
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There we should find two menus, 'My labrooms' and 'Bootstrap Labroom' +
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=== 'My labrooms'
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image::images/for_tutors/my_labrooms.png[]
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Here we can see a list of all the labrooms programmed to run today. Again like in the run tab we can distinguish open from closed ones by color (green/orange). +
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image::images/for_tutors/todays_labrooms.png[]
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We can also get info using the info icon image:images/for_tutors/info_icon.png[] or delete the labroom using the trashcan icon image:images/for_tutors/trash_icon.png[] . +
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To search for a specific labroom we can use the searchbar at the top. +
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IMPORTANT: The delete command is *FORCED* even if the labroom is running!!! +
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=== 'Bootstrap Labroom'
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Now lets see how we can bootstrap a new labroom using one of our lab instances. +
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To do that lets navigate to the respective tab that should look like this: +
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image::images/for_tutors/bootstrap_labroom.png[]
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Here we can select the desired (existing!) lab instance that will be used to create the labroom using the plug icon image:images/for_tutors/plug_icon.png[]. +
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image::images/for_tutors/lab_instance_choose.png[]
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Then we have to specify starting date and time and also set the duration for which our lab room will be open. +
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image::images/for_tutors/timeframe_selection.png[]
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CAUTION: You can only start a labroom every whole or half hour (p.e. 12.00 or 14.30) and never inbetween so please plan ahead!! +
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Also note that the duration cannot be greater than three hours since we consider that the maximum for any type of lesson! +
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Now using the searchbar that follows (you HAVE to search for students for them to come up) we search and select (image:images/for_tutors/plug_icon.png[]) the students that we want to invite to the lesson. +
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Note that only students that have subscribed to our labroom will be available for invites to avoid confusion! +
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image::images/for_tutors/student_selection.png[]
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After selecting all the desired students we have to fill in the last details at the bottom of the page. +
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Please give concise titles and good descriptions to your labrooms!! +
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image::images/for_tutors/bootstrap_details.png[]
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Now we shall check and upon making shure that everything is right we click the 'bootstrap your lab' button!
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WARNING: Bootstraping is final and no further edits are allowed!!
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== Learning Objects Notebooks
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A LO Notebook *is a reusable web-based interactive chunks of e-learning* designed to explain a stand-alone learning objective, which can be used, reused or referenced during technology supported learning.
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*Swarmlab.io Notebooks includes the following key characteristics*:
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- *Learning objects are a new way of thinking about learning content*. Traditionally, content comes in a several hour chunk. Learning objects are much smaller units of learning, typically ranging *from 2 minutes to 15 minutes.*
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- Are *self-contained* – each learning object can be taken independently
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- Are *reusable* – a single learning object may be used in multiple contexts for multiple purposes
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- Can *be aggregated* – learning objects can be grouped into larger collections of content, including traditional course structures
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- Are *tagged with metadata* – every learning object has descriptive information allowing it to be easily found by a search
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[NOTE]
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====
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Learning Object Notebooks is:
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[quote, IEEE ]
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"A digital self-contained and reusable entity, with a clear educational purpose, with at least three internal and editable components: content, learning activities and elements of context.".footnote:[Learning Technology Standards Committee (2002), Draft Standard for Learning Object Metadata. IEEE Standard 1484.12.1 (PDF), New York: Institute of Electrical and Electronics Engineers, retrieved 2008-04-29]
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[quote, Wikipedia]
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"learning object any entity, digital or non-digital, that may be used for learning, education or training".footnote:[https://en.wikipedia.org/wiki/Learning_object#Definitions]
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====
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=== Usage
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LO notebooks have a wealth of different uses including as a testing ground for development work, a presentation platform, and more.
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* *Ad hoc nature.* - The ad hoc nature of notebooks is excellent for trying things out
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** Designing, developing, and testing solutions to problems.
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* *Ready-to-Use Services.* - Easier start. Your just start with the cleaned data, the trained model, and get right to the analysis.
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** Presenting analyses, demonstrating both the code and the output, that can be easily turned into slides/pdf.
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* *Built for collaboration.* - Swarmlab.io notebooks are easy to collaborate with using version control systems (git). The YAML index file makes it extremely easy to tell where things belongs to.
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** Providing hands-on walkthroughs of new library modules, visualization techniques, and strategies for attacking existing problems. They allow someone to mostly follow along while allowing them space to try out new things right in-line.
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=== Run Learning Object Notebook
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==== Find
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image::images/llo/llo.png[]
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After we have located the desired LO we can
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- run it by using the cloud icon. image:images/run/cloud_icon.png[]
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- To request more info about the lab we use the info icon image:images/run/info_icon.png[]
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==== Run
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image::images/llo/llo-run.png[]
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- After we have Run the desired LO we can run "try it" by using the edit icon.
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==== Try
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image::images/llo/llo-try.png[]
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=== Create Learning Object Notebook
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==== Main Options
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image::images/llo/llo-create.png[]
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- *"My LabLearningObjects"* - LLO Admin panel
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- *"Publish LearningObjects"* - Metadata and Publish your LLO
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- *"Bootstrap LearningObjects"* - Create your LLO
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- *"How to Contribute"*
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==== Publish
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.Creative Commons
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[NOTE]
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====
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Get familiar with "The Creative Commons copyright licenses".
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‘About the Licenses'.footnote[http://creativecommons.org/about/licenses]
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Creative Commons is an international nonprofit that offers flexible copyright management tools for creative work. Many learning objects have CC licences.
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====
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image::images/llo/llo-publish.png[]
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==== Bootstrap
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image::images/llo/llo-bootstrap.png[]
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Learning Objects Notebooks Based on the following structure:
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[source,yaml]
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----
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--- # Programming language
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name: "test" // <1>
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author: "zeus"
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intro: "intro" # intro is a file // <2>
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base_url: "https://git.swarmlab.io:3000/labs/examples-mpi2/raw/branch/master" // <3>
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0_netstat: // <4>
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display_name: "netstat" // <5>
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swarmlabservice: "os2" // <6>
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info:
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file: "0_netstat/info" // <7>
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code:
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lang: "bash" // <8>
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exec: "/bin/bash" // <9>
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file: "0_netstat/code" // <10>
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options: "" // <11>
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mimetype: "bash" // <12>
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output:
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log: "console" // <13>
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mimetype: "bash"
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challenge: // <14>
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question: "0_netstat/q-info"
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codehelp: "0_netstat/codehelp"
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codeanswer: "0_netstat/codeanswer"
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mimetype: "bash"
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points: "1" // <15>
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output:
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log: "ascii"
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----
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<1> LabLearningObject Name
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<2> Here you can describe your LLO. Describe what students should know or be able to do at the end of the course that they couldn't do before!
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<3> The ''base url'' field is the landing page of your LLO.
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<4> Code spec
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<5> Task Name
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<6> A Swarmlab service is an dockerized microservice. It receives code snippets to execute, runs these code snippets, and returns the result and output of the execution.
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<7> Task info. Here you can describe your Task
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<8> Set the programming language!
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<9> The full path of the executable
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<10> Here you can add the code snippet to be executed. ( Using the ''Give It A Try'' option you can test your Code.)
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<11> Exec Options
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<12> Code block syntax highlighting
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<13> Output: Console, file
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<14> Challenge spec [Optional]
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<15> Difficulty - 1 beginer, 2 intermediate, 3 advanced, 4 expert, 5 guru
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This example LO is organized as follows
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[source,yaml]
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----
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/test // <1>
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├── 0_netstat // <2>
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│ ├── code // <3>
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│ ├── codeanswer // <4>
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│ ├── codehelp // <5>
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│ ├── info // <6>
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│ └── q-info // <7>
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└── intro // <8>
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----
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<1> Bare Directory - based on: LabLearningObject Name
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<2> Code spec - based on: Task Name
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<3> Code snippets to execute
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<4> Contain the answer.
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<5> Hints.
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<6> Task info file.
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<7> Question file
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<8> Intro file.
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== Get Involved
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Swarmlab.io is a open source project born to support interactive Virtual Labs and interactive Learning Objects across all programming languages and systems. i
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Swarmlab.io is open and welcoming to all.
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And we need your help.
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We invite anyone to come and participate in the creation of Swarmlab.io. Regardless of your skillset, we’re sure there is something you can add to our community and project.
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