Difference between revisions of "SOCR DSPA ReadinessPretest"

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(SOCR Project - SOCR Graduate Data Science Readiness Self-Assessment Pretest)
(SOCR Project - SOCR Graduate Data Science Readiness Self-Assessment Pretest)
 
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===Description===
 
===Description===
This projects aims to develop a generic platform for SOCR web-based self-assessment. Specifically, the projects will develop a dynamic version of the [ttp://www.socr.umich.edu/people/dinov/2017/Spring/DSPA_HS650/DSPA_Pretest.html Data Science Readiness Self-Assessment Pretest] using HTMl5.  
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This projects aims to develop a generic platform for SOCR web-based self-assessment. Specifically, the projects will develop a dynamic version of the [http://www.socr.umich.edu/people/dinov/2017/Spring/DSPA_HS650/DSPA_Pretest.html Data Science Readiness Self-Assessment Pretest] using HTMl5.  
  
 
The new web pretest has to be mobile friendly and allow us to store the questions (an perhaps answers) in a JSON file as well as randomly pull questions from each of the 3 main categories (each including multiple (2-4) sub-categories).  
 
The new web pretest has to be mobile friendly and allow us to store the questions (an perhaps answers) in a JSON file as well as randomly pull questions from each of the 3 main categories (each including multiple (2-4) sub-categories).  
  
 
Each time a visitor tries the pretest, they see somewhat different questions in each of the 2-level categories. Randomness relates to randomizing the questions within each category and subcategory.
 
Each time a visitor tries the pretest, they see somewhat different questions in each of the 2-level categories. Randomness relates to randomizing the questions within each category and subcategory.
 
Below are some examples to review as you design the HTML5 version of the pretest:
 
* [http://www.flashbynight.com/tutes/mcqquiz/  Example 1 (mobile friendly)]
 
* [http://www.webdeveloper.com/forum/showthread.php?286477-How-to-make-a-javascript-quiz-to-choose-10-random-questions-from-100-questions Example 2 (several alternative suggestions)]
 
  
 
===Specifications===
 
===Specifications===
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* We will be expanding the JSON question/answer list once a working version of the platform for the pretest is available.
 
* We will be expanding the JSON question/answer list once a working version of the platform for the pretest is available.
  
 +
===Examples to review===
 +
Below are some examples to review as you design the HTML5 version of the pretest:
 +
* [http://www.flashbynight.com/tutes/mcqquiz/  Example 1 (mobile friendly)]
 +
* [http://www.webdeveloper.com/forum/showthread.php?286477-How-to-make-a-javascript-quiz-to-choose-10-random-questions-from-100-questions Example 2 (several alternative suggestions)]
  
 
===Knowledge Prerequisite===
 
===Knowledge Prerequisite===

Latest revision as of 11:52, 17 October 2016

SOCR Project - SOCR Graduate Data Science Readiness Self-Assessment Pretest

Description

This projects aims to develop a generic platform for SOCR web-based self-assessment. Specifically, the projects will develop a dynamic version of the Data Science Readiness Self-Assessment Pretest using HTMl5.

The new web pretest has to be mobile friendly and allow us to store the questions (an perhaps answers) in a JSON file as well as randomly pull questions from each of the 3 main categories (each including multiple (2-4) sub-categories).

Each time a visitor tries the pretest, they see somewhat different questions in each of the 2-level categories. Randomness relates to randomizing the questions within each category and subcategory.

Specifications

  • The platform should allow MathJax for test questions and test answers.
  • The platform should be generic and allow expansion of the categories, sub-categories (2-level deep only) and the lists of questions within each (perhaps allow multiple-choice answers)
  • We will be expanding the JSON question/answer list once a working version of the platform for the pretest is available.

Examples to review

Below are some examples to review as you design the HTML5 version of the pretest:

Knowledge Prerequisite

HTML5, CSS, JavaScript (JQuery and CoffeeScript experience or learning interest is a plus).

See also




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