Core Concept: Data and Analysis
 
 Survey Title:Computer Science Standards Development - Public Survey
 
 Survey Properties:
 
 Total Respondents:1401
 Responses By Question Analysis:
 

 
   Demographic Information
 
 2.  County
  Response Total Response Percent
Apache Response equal to 1 3 1%
Cochise Response equal to 3 11 3%
Coconino Response equal to 2 8 2%
Gila Response equal to 0 2 0%
Graham Response equal to 0 2 0%
Greenlee Visual spacer 0 0%
La Paz Visual spacer 0 0%
Maricopa Response equal to 65 269 65%
Mohave Response equal to 1 3 1%
Navajo Response equal to 2 10 2%
Pima Response equal to 16 65 16%
Pinal Response equal to 3 12 3%
Santa Cruz Response equal to 2 7 2%
Yavapai Response equal to 1 6 1%
Yuma Response equal to 3 11 3%
Out of State Response equal to 2 7 2%
Total Respondents  416 100%
 
 3.  Visitor Role
  Response Total Response Percent
K-12 Teacher Response equal to 65 269 65%
K-12 Administrator Response equal to 8 35 8%
K-12 Parent/Guardian Response equal to 5 19 5%
K-12 Student Visual spacer 0 0%
Higher Education Response equal to 6 26 6%
Retired Educator Response equal to 2 10 2%
Business Representative Response equal to 3 12 3%
Community Member Response equal to 4 18 4%
Elected Official Response equal to 0 1 0%
Media Response equal to 0 1 0%
Other Response equal to 6 25 6%
Total Respondents  416 100%
 
 4.  How important is it to develop standards for Data and Analysis? Standards for Data and Analysis would include developing an understanding of collection, storage, visualization and transformation of data, and using inference and models in data science.
Response TotalResponse Percent
Very Important 18253%
Important 14342%
Unimportant 154%
Very Unimportant 41%
Total Respondents344
(skipped this question) 1057
 5.  Please add any comments about developing standards for Data and Analysis.
1.Data will exist forever, and is used to drive change in any type of data utilization. Evidence-based practice and evaluation are methodologies which are becoming increasingly more common due to a high demand for systems-level work and change. This is absolutely needed, specifically what to do with data and data analyses once complete - what to apply the data to and how to do so. Making data tell a meaningful and impactful story to initiate a change movement.
2.Today's students need to learn more about data and analysis and critical thinking skills.
3.Understanding how cloud storage works and virtual memory is essential in understanding how data is stored and transferred.
4.This applies to all types of learning and has application in a lot of content areas.
5.This is not applicable to a junior high setting (where I teach). If students are on a business track at the higher level, then they should have an understanding of this.
6.Data and Analysis applies to almost every professional sector, as well as a foundation to become a responsible, knowledgeable and involved member of society.
7....and this understanding must be contextualized within disciplines and real world problems--not just number-crunching exercises. The sciences and economics offer rich opportunities for data visualization, manipulation and transformation.
8.These are akin to math and science skills though with their own nuance. These can/should be co-taught with existing STEM practices.
9.This is not important at the elementary school level.
10.Ethics and big data needs to be included.
11.the most important area! students MUST be able to effectively evaluate data of all types, and, as this field is so broad, we need to develop an overall model to help teachers deal with this area
12.This standard could support the math standards in organizing and using data in support of developing problem solving strategies.
13.I am not sure what this entails.
14.none
15.This is not applicable to elementary age students. It is also not relevant to their world at this time.
16.To me these are all important questions. Data and analysis is how we understand our others and our world.
17.Should have an understanding of how to use programs to use in classes to input data.
18.This is more important because is helps one learn to organize.
19.This should be integrated with science standards and STEM education.
20.Critical thinking for solutions and challenges in the community require these skills. These skills help save money, improve safety and offer better living by using evidenced based practices.
21.Data and analysis are concepts that integrate with math, computation and critical thinking.
22.Data Science is very important and should be done in conjunction with mathematics, where I see already more data science concepts are available in 7-12 (my wife is a math teacher grades 9-10 and my kids are in grades 7-11).
23.Data and analysis skills are extremely important. I hate being bottlenecked by students who are uncomfortable working with digital data. Being able to pull data from a variety of sources into a common format and display it (say, within a spreadsheet using a pivot table or a few graphs) should be second nature.
24.Data structures are an important topic to master simply because they are the common technical interview questions for most software development jobs in the industry today.
25.Data privacy, in particular, is critical to convey to students, in a grounded way that makes them understand how their data can be at risk on the internet.
26.Knowledge is more important then data. Data could be distorted by to many factors in education. Teach what we can as much as we can with the tools to do the best we can!
27.This field would appeal to students like myself who liked math and analytics, but didn't have an understanding of ways to apply the skills other than becoming a math teacher.
28.This is important.
29.Data analysis rests at the core of all decision making. Providing students with a clear and distinct way to grow that muscle will enable them to make good decisions throughout life. From an engineering perspective the future of software and web applications is nestled in the ability to take data and create recommendations and find patterns in order to deliver value to customers.
30.the two components of all computations are data and algorithms, so some introduction to data structures should be in the standards.
31.It is a foundational skill to be able to work successfully in the information age.
32.Yes, this is a good practical standard that should be written in the context of content/subject matter.
33.I believe that students will naturally develop these skills. We don't need to push these on them when we already have reading, writing and math standards that are much more important.
34.I believe this will vary by content area. Those taking Art might analyze data differently from students taking Biology or Algebra II or American History...
35.Data and data warehouses store a variety of information in all kinds of topics. Learning about what is collected, stored, shared and protected is important. This can be everything from your personal information to your health records.
36.The concepts studied in data and analysis will bring a cross-curricular application to the study of Computer Science, with applications to the other sciences, social studies, languages, culture, and arts.
37.data & analysis are of great importance
38.math does some of this. but there need to be more practice Regression ideas would be helpful.
39.This is the future of tech.
40.Data and analysis should include curriculum dedicated to the scientific method under the paradigm of inference and models in data science
41.Refer to the College Board's and CTSA's networking standards for APCS Principles
42.Again this is math, reading, critical thinking, and communication skills, with a focus on these things as apposed to a specific technology or software package in operation today.
43.I'm marking this as "Unimportant" to indicate its lesser importance to the standards. It pains me to do this because my degree in geography(GIS) and livelihood is all about data visualization and transformation.

Most of this topic can really be spread out into some of the other areas. Fundamentals of data storage belong in Computing Systems. File types and formats (PNG, JPEG, GIF, MP4, other video/audio codecs) also likely belong in Computing Systems. Data security belongs in Networks and the Internet.

If you really want this to be it's own standards area this is going to be the one that needs the most attention so it doesn't get overloaded. From a fundamental skill set if a student doesn't walk away being able to at least know what happens why their document breaks going from .Pages to .Docx, to .RTF, to .TXT. Or why their professor keeps getting mad that them for turning in .Docx when they were told to turn in .PDF. If a student leaves schools being able to comfortably move between MSOffice, iWorks (Pages, Keynote, Numbers), GoogleDocs, and LibreOffice that is a success in my view.

Again as someone trained in GIS who works with back-end databases and transformation of geographic datatypes, it is hard thing to lower the priory on this as topic.

When it comes to data analysis, this is again where computer science can and should be going hand-in-hand with the existing sciences. Any time a student is doing data collection for any scientific topic they can also be practicing good digital skills. This also can reasonably be expanded to literary projects. A bibliography is a database. Its format can also be changed (different standards of presentation, APA, MLA, Chicago/Turabian, etc.). You do not need purely computer focused tasks to point out good data collection, storage, use, and analysis.

Repeating, many of these topics should be integrated with and help to reinforce traditional academic areas.
44.Data and analysis gets to a meta issue that would mean an overall better outcome in students' ability to approach new knowledge domains, categorize the new information therein, and quickly adapt to that information. In short, a focus here will likely have an impact in most other school subjects.
45.Data analytics will be the key factor in the use of computer technology as the students graduate and move into the work force.
46.Data analysis is becoming crucial for nearly every area in college studies and business.
47.Developing standards help guide me.
48.Data is everything.
49.Learning to collect will be in their best interest. More data more accuracy!
50.this is the were our world is going, students should be able to use technology class for collecting, storage and usage when in class(dedicate 1 quarter for this type of research) and usage.
51.Data and Analysis; This COULD be a huge leap for project research implemented in each subject area in the k-12 realm. The student would then know more by interacting with using a digital device to open/read/modify documents, thus retaining more information and maintaining interest in their project's progress.
52.But, this should be embedded with mathematical standards--which should be applied to science inquiries.
53.for the upper grades, possibly high school.
54.many levels of this....
55.This could be a great cross curricular component to integrate math concepts.
56.Data and Analysis are critical to thinking and operating in this and future centuries
57.Ties nicely to math, social science, hard science, language, image or sound recognition used in the world today as a measure of scientific proof of confidence ... building legal argument, patent approval, business forecasting, programming, etc
58.Data collection can be easy but to analyze it is another story. We must learn how to filter through the data we are collecting - which is the new oil - and find ways that the information can be used to improve on processes and business.
59.Data and analysis capabilities and needs are quickly growing with technology advancement today. This is a major business need as digital transformation is impacting most businesses today. This is one of the highest projected skills gap areas in the coming decade.
60.This standard could be easily implemented across all subjects.
61.For today's job market and for continued global competitiveness, I think these are skills that our students must know.
62.One of the largest growing fields in industry
63.What role will this have in regards to the Arizona State Technology standards that many of us are already teaching?
64.Especially standards on inferences from data science and creating accurate & aesthetically purposeful models of data
65.same as above
66.This is the way of the world...depending on what career they want to go into.
67.Data and Analysis is another standard that needs to be taught using hands-on scenarios and students need to develop critical thinking skills.
68.Some students will never be more into computers than turning on a phone and connecting to the phone's network.
69.Students need to see how they are progressing and there need to be procedures in place that hemp students see how they are progressing through the school year.
70.Data and Analysis could be meshed with Math standards.
71.With most businesses dealing with boards, communities and internal executive staff, students need to know what the data reads, how to collect the data and how to interpret the data to achieve higher paying jobs. This will not only help the individual but also the community and the state become more advanced. With that advancement, there is the ability for the state to attract high tech companies to the state.
72.Students are more likely to become proficient in computer science when they can see different ways to apply skills from another context. The STEM careers of the future will rely heavily on students being able to notice patterns in data and create solutions to global problems.
73.I feel this is the 2nd most important part of Computer Science
74.Any higher level thinking processes benefits students.
75.Our society and jobs increasingly relies on BIG DATA. Our citizens should have an understanding of this.
76.cross over here to accounting and math/statistics - as well marketing and forecasting. Perhaps in secondary school - not going to be culturally or socially relevant in primary or middle grades.
77.Students need to understand how what they do online produces data and how others use that data to influence and direct them and others.
78.This would be important only at higher grade bands.
79.K-6 already has a lot on their plates, so this should not add to the already full days of standards taught my teachers that already struggle to have time for other subjects.
80.Data visualization and models are very important for development.
81.I believe this should be taught to all students and built upon as they progress through school.
82.The complete Computer Science standards should be taught from the beginning to the end, i.e. Objectives, specifications, etc
83.Using computers for data collection and analysis is important and students will need to be able to do this to be successful in college and in the business world.
84.Just as Math, as a course, is important - math on computers (and what computers can do with math) is also important. I don't think every student must understand this concept, though.
85.Data analysis careers will always be in-demand.
86.I believe this area is very important because it can be extended to many other school subject areas. I also believe that this content is a useful skill for many areas of adult life.
87.You have to be careful about being over specific as the changing technology and so many different paths students can take. Some are not interested in hardware but want to be software oriented and vica versa both are different careers in CS so that needs to be thought about when creating standards
88.This is a strong link to other disciplines and would help many areas of study.
89.Because this standard deals with more abstract notions and involves thinking patterns that are both creative and precise, I feel this is Very Important to develop, starting at an early age, and building throughout our education. This is where critical thinking, testing, good reasoning, and curiosity need to be applied together. It is a holistic way of thinking, and can blend the "engineer" and the "artist" -- and I think this happens best if we start early... like K-1.
90.These standards would teach students the importance of collecting data to support their ideas in order to make future connections.
91.for higher grades
92.This is important to understand the basics of where we can store information, and find information. How we find the information is also important. Since there is so much to sifter through it is important to teach students how to search for the information through research, inference, and data.
93.Important , but needs to be at a higher level. My 2nd grade student are just learning basics... reading data
94.with a host of applications being moved to the cloud this topic will increase in importance.
95.Similarly to networking standards the more specialized nature of data and analysis lend itself to consideration later in a students academic endeavors.
96.project based learning
97.Jr/Sr High
98.Supportive of all other core courses
99.At developmentally appropriate levels commensurate with si.ilar math and science standards.
100.data visualization
101.I cant imagine any job where this skillset would not be needed. It is crucial in understanding and navigating the massive amounts of data and information that are being generated on a daily basis by our computing systems, sensors, internet of things.
102.This is an important area that ties to our rapid development of networked and distributed sensors and large databases
103.It is important, however, I do feel basic organization is important but storing and analyzing data may be specific to certain fields and may not have a real-life application for students that don't go into specific fields.
104.Data analysis is a specialization, and while a growing field of importance, is not a fundamental CS topic
Total Respondents  104