EdTech 505: Week 9 - Data Sources and Data Analysis

Data Sources and Data Analysis

Chapters 6 & 7 in B&D text

Assignment: Answer the three questions on p. 141 in B & D text.

Bonus: Data Analysis website

URL:  http://onlinestatbook.com/index.html, specifically focusing on the "Interactive e-book" for iPad and OS X (selected since Java issues created problems accessing the online version): https://itunes.apple.com/us/book/introduction-to-statistics/id684001500?mt=11

Description: This e-book by David Lane (Rice University) functions as a combined textbook and workbook on the introductory statistics involved in data analysis.  It offers multimedia examples and an overview of basic principles of statistics including graphing and summarizing distributions, probability, estimation, testing means, analysis of variance, research examples, etc.  The e-book gets quite complex in its study of techniques for selecting, analyzing, interpreting, representing, and making decisions based on data.  There are plenty of mathematical equations featured in this book, but not to the point where it becomes inaccessible. The scope of this text certainly goes beyond the tools necessary in data analysis for program evaluation.  Nevertheless, it's easy enough to navigate by jumping to and skimming desired topics. The interactive workbook format is helpful because one can easily access glossary information (and create study cards of vocabulary terms), define a word, bookmark a page, view a video explanation or example, or take many self-evaluation quizzes. In addition to interactive explanations woven throughout the book, there are also external links to relevant, helpful websites to expound upon the topic of focus.

**two other interesting Statistics Education sites:  http://wise.cgu.edu and https://www.usablestats.com

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Discussion Posts

#1: "How Evaluation of Technology Was Born" Caveman Tale

Educational technology, like the banana leaf used as a loudspeaker, certainly provides more efficient, effective, (and magical?!) ways to reach the masses. They feature tools for increased productivity, creativity, collaboration, problem-solving... -- the "meat" of education. As many in the field of education teach students, colleagues, and administrators how to "hunt" for this kind of learning and reap the benefits of this meat, excitement is catching on like wildfire.  More and more Thoks are emerging as wise, forward-thinking guides to help spread a) enthusiasm these new ways of learning and b) guidance on how to go about using new digital tools for this kind of learning.

There are Vals out there how do not understand and make no effort to try to embrace the "hunt" for this learning. They see the fruits of its labor as ineffective or inefficient.  This is perhaps because they don't enough about educational technology to a) use it properly or b) gauge its impact properly. Assumptions guide attitudes and false "conclusions" about the value of these new tools and ways of learning.

Therefore it is the job of the Thoks to not only teach about and model the proper use of educational technology, but also show its value through a more systematic approach.  That's where evaluation fits in.  Educating others about educational technology means showing them evidence, which is gathered through data collection -- not just theory.  It's showing how much more "meat" can be gathered by employing these tools and these teaching styles through observations, surveys, inventories, objective discussions, statistics, etc.

We know that Val's conclusion is quite ridiculous because she didn't use the technology tool in any way remotely related to its intended purpose.  Her "data collection" was skewed from the get-go because it wasn't tied to any objectives, program, or process.Here is where Thok can dive in and help. He can plan an evaluation which we know will ultimately reveal that Val's banana leaf (aka ed tech) use is flawed. He can then help her change her plan for its use (by tying it to objectives) and evaluate it again. Val might then be more convinced of the role of technology in education after that because she went through the rough and bumpy road of program planning and evaluation with her own two hands.  Just hearing about it wasn't enough for her. Or maybe Thok's "proclaiming" wasn't substantiated by enough evidence.  Sometimes we just have to see for ourselves!

Reply to peer post: I don't think students are uncomfortable having opportunities to find new tools to solve a problem or find new problems to be solved with a tool. I think students do have that spark of creativity, ingenuity, and pride that leads to great innovations.  Perhaps what they are uncomfortable with is that they, as learners, are going to be evaluated on their product. What if the whole concept fails, what if the design is impractical, what if it's too risky -- there's just too much at stake to take a chance (not to mention peer rapport (i.e. what will my friends think?))  So I guess I'm saying students may enjoy dabbling in the challenge of "reusing the leaf" in a new way, they just don't want to be judged on that first iteration.  And sometimes we just can't afford to give them time (and grade book real estate) for more iterations.

#2: National Center for Education Statistics (NCES) is the primary federal entity for collecting and analyzing data related to education. http://nces.ed.gov/ If you're into data and statistics about education, then this site is a great location. Review the site. What'd you find that's connected to EDTECH 505? To chapters 6 and 7? Find something useful?

Wow -- this site is sure robust!  First of all, I had not realized there was a "Congressional mandate to collect, collate, analyze, and report complete statistics on the condition of American education; conduct and publish reports; and review and report on education activities internationally", which is the mandate of the NCES.

I was impressed with the number of publications that (mostly appear to) address issues of economics and student profiles related to behaviors.  There are a TON of surveys and programs that look at beginning teachers, crime and safety, early childhood, high school and beyond, private schools, school staffing, urban education, etc. A variety of subgroups and educational activities are put under the microscope in these studies.  The Fast Facts section offers a myriad statistics about these various data filters. (However it's a bit challenging to work through these due to their "dryness" (mostly text and a few very busy charts and graphs!)) I feel a person really needs to know what they're looking for when they delve into this site.

It was quite interesting to conduct a "school search" to read about my own district's information, characteristics, enrollment by race and by grade. This could be a great starting point for the "public records" aspect of antecedent data that is discussed in our textbook, although it doesn't go into great detail.  The college navigator was an interesting surprise, and definitely something I'll recommend to our HS guidance department as an objective tool for students exploring higher ed options.  Younger students might enjoy exploring the Kids Zone: http://nces.ed.gov/nceskids/, especially in math class working with graphing authentic data sets. It's also a great way to engage students in their own education process (learning about their school, comparing it with others, etc.)

I have never heard of our district's students participating in the National Assessment of Educational Progress (NAEP), which is "the largest nationally representativ​e and continuing assessment of what America's students know and can do in various subject areas" -- I'd be curious to learn more about who participates in this (esp. being a national, vs. state, assessment tool), as I haven't heard of it before.

It would be helpful if the site had more information for students, educators, or administrators looking to conduct their own educational research. It appears this site is mostly fact-providing not skill-focused.  A lot of the data-tools appear very advanced and tailored for a specialist audience.  In addition, it's difficult to interpret what data collection tools were used in many cases.