https://voicethread.com/share/14454769/

Education Technology has spread into every field and discipline, with numerous applications in each. This creates a seeming invincible ubiquity, untangling the interconnected lines of data-tracing is nearly impossible. Meinke’s “Student Data Harvested by Education Publishers: They haz more than u think,” discusses the overlapping strategies used by social media platforms and educational platforms to collect user information and process it to ostensibly create better interactions for all involved.

Many of the articles in this week’s readings discuss Cambridge Analytics’ use of Facebook data to facilitate getting targeted outreach and content to users for political ends. This revelation had little true impact on Facebook: their stock value temporarily dipped, and Zuckerbot had to go before Congress. Otherwise, not much happened, people still regularly went on Facebook to add their own personal content and click preferences to the information they explicitly volunteered to the create their user profile. “But education is different,” says Meinke: we take classes to earn degrees and are entitled to a sense of safety and guardianship from our institutions. I agree that education is different but for very different reasons, unlike with social media- which has no proven role in education and is ostensibly “free” in the market sense of the word- interactive course content comes with a hefty price tag. Nowhere is it understood that the students’ data will be held, analyzed and disseminated in perpetuity in payment for access to said content/platform. Indeed, the price of textbooks (e-book or dead tree) has gone up by triple digit percentages in the last decade, even adjusting for dollar values. Students have paid enough upfront for their privacy to have it remain intact, and to have access to their course content beyond the semester. Program learning outcomes are based on the idea that students will enlarge upon skills learned in previous courses.

The rationale for granting access to learning management system data to publishers is posited as the facilitation of platform use by both faculty and student. However, in the nascence of online textbook augmentation students entered a long activation key and would create their profile by selecting the school and course in which they were enrolled. There was nothing wrong with this model, however, the trend towards single sign on (SSO) has created a myth that people cannot handle having multiple logins and also that unique logins will deter platform uses. We can all agree that having to create a new account instead of using an existing Facebook or Google account will probably give some users pause enough to reconsider their buying or comment-posting choices- but there is a critical distinction between the user of mass-published educational content and just about any other instance of use that online learning is frequently compare to: the end-user has already paid to access the platform. The enticement and marketing ships have long sailed. Also, the pursuit of credentialed education should not be trivialized as being tantamount to posting comments or other casual engagements.

I would add to some of the responses in the Davis and Bulger interview with a recommendation that social media not be used in a classroom setting.  “One of the things that excites faculty the most and what they want to learn more about is different ways to use social media in the classroom. An assumption I encounter frequently is that as students are already using social media, social media will be easy to adopt and adapt for learning both for the professor and the student….” We may argue that there is no such thing as true privacy online, but the latent, abstract and remote impact of Cambridge Analytics knowing bits of your professional, social and academic life versus the immediate, and potentially devastating impact of your teacher or boss seeing these overlaps are incomparable.

For the class:

Do you use social media as part of your course activities? If so how?

Can open educational resources combat the integration and slick marketing of the big publishers?

In the wake of Cambridge Analytics, repeated data-breaches across industries, and the lackadaisical responses they’ve garnered, along with the high usage and access provided by freemium platforms, is their room for social action to preserve privacy or is it a matter of personal choice?

https://voicethread.com/share/13999906/

Jessica Elena Brodsky and Elizabeth Sergile

Instructions

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For this semester-long project, you will be asked to write a proposal for research project in which you will analyze data from the U.S. Census to answer a question of your choosing.  You will work together with a small group and coordinate via Microsoft Teams to complete this project. Beginning of the Semester: Preliminary Analyses

1. Start by learning about the United States Census: https://en.wikipedia.org/wiki/United_States_Census
2. To create your group for this project, you will rank your top five regions of the United States. I will use this information to group students based on shared regions of interest. 
3. Once groups are formed, you will be provided with the Census data file for 2010.
4. You will be asked to conduct preliminary analyses on your region’s Census data by providing descriptive statistics about your region (descriptive = describing). This will also help you get to know what data is collected by the Census.

East North Central Illinois (IL) Indiana (IN) Michigan (MI) Ohio (OH) Wisconsin (WI)	East South Central Alabama (AL) Kentucky (KY) Mississippi (MS) Tennessee (TN)	Middle Atlantic New Jersey (NJ) New York (NY) Pennsylvania (PA)	Mountain Arizona (AZ) Colorado (CO) Idaho (ID) Montana (MT) New Mexico (NM) Nevada (NV) Utah (UT) Wyoming (WY)	New England Connecticut (CT) Maine (ME) Massachusetts (MA) New Hampshire (NH) Rhode Island (RI) Vermont (VT)
Pacific California (CA) Oregon (OR) Washington (WA)	South Atlantic Delaware (DE) Florida (FL) Georgia (GA) Maryland (MD) North Carolina (NC) South Carolina (SC) Virginia (VA) West Virginia (WV)	West North Central Iowa (IA) Kansas (KS) Minnesota (MN) Missouri (MO) Nebraska (NE) North Dakota (ND) South Dakota (SD)	West South Central Arkansas (AR) Louisiana (LA) Oklahoma (OK) Texas (TX)	Click here to make your selections.

Middle of the Semester: Identifying Your Research Question

1. Now that you are familiar with types of Census data collected and your region, you will identify a research question that you can answer using Census data for your region. To help you identify your research question, first think about the target audience for your proposal – this it the group of people that would be interested in some of the data collected by the Census. Then , think about what research questions that group of people would be interested in answering. Make sure that you can justify why this research question is of interest to your target audience.
2. To demonstrate that it is feasible to answer your research question using the Census data, identify the specific variables that you will need to extract from the Census data for your analyses.
3. With your group, complete Module A5 of the Socio-Technical Sustainability Roadmap to help your group determine how you will organize and document your project. This is a great opportunity to get familiar with Microsoft Teams and determine which features of this tool you will use for managing the different parts of your project. 
4. In class, each group will be asked to briefly present your research question, variables of interest, and project documentation plan to the class. You will have the opportunity to revise these three components based on feedback from me and your peers before submitting this part of the assignment.

End of the Semester: Addressing Your Research Question

1. Now it’s time to write your proposal. In this proposal, you should:
   1. Provide descriptives of your region using Census data from your region
   2. Describe your target audience
   3. Provide your research question
   4. Explain why this question would be of interest to your target audience
   5. Identify variables of interest
   6. Identify descriptive and inferential tests that you will conduct and explain why they are appropriate for your data and research question
   7. Describe how you will visualize your results and explain why the visualization is appropriate for your data
2. Once everyone’s proposal are submitted, you will be asked to peer-review each others proposal using the online rubric available here (see below for Evaluation Rubric).

Evaluation Rubric

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 Using this rubric document, evaluate each division’s proposal. Use a new copy for each division you will evaluate. Please use this link to deposit your completed evaluations.  

Response: Course Context

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A brief statement of the context of the course (discipline, level, institution type, instructional mode, is it real or imagined) This assignment is for an Introductory Statistics course that qualifies as Quantitative Reasoning course, as defined by CUNY Pathways. The course is taught face-to-face. This course is imagined, though Liz has taught Intro to Business Statistics and Statistics for Social Sciences; and Jessica has taught Experimental Psychology at Hunter, which incorporates review of basic statistical concepts and tests. Course Goals:

• Understand foundational statistical concepts
• Conduct and interpret appropriate statistical tests
• Apply statistics to real-world problems
• Demonstrate findings and conclusions using interpretative software
• Communicate and participate in group work both face-to-face and virtually

Why is this the final?

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Statistics is one the most challenging courses for instructors to teach (Conners, McCown, Roskos-Ewoldsen, 1998). Challenges include motivating students, helping students overcome their math anxiety, reconciling wide variations in students’ performance, and ensuring content retention. One of the most challenging aspects of an introductory statistics course is helping students see the relevance of the knowledge and skills they are learning to the issues in their lives. Students often leave a statistics course with more knowledge, but no change in their attitudes or perceived ability in statistics and worse perceptions of the usefulness of statistics (Sizemore & Lewandowski, 2009). Therefore, the goal of this assignment is to help students apply the knowledge and skills they’ve gained in this course to answering a research question that they consider to be relevant. We chose to break this project up into a 3-part semester-long final project because it is an introductory-level course and we wanted to be able to provide students with feedback and guidance throughout the assignment. We also wanted students to have time to practice communicating and collaborating via an online tool, like Microsoft Teams.

Technologies

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 Microsoft Teams provides a cohesive platform for communications, working in groups, collecting information. Teams empowers students to create groups, work plans, documentation and to track deliverables in a way that allows them to be in charge of the workflow and to practice using a tool that is being used in the workplace across various industries. Students will get to add this to their resumes. 

SPSS and/or Excel will be used for data-analysis and to produce data visualizations. These tools have easy-to-navigate interfaces, and will produce insights for discussion.PowerPoint will be used to share proposed methodologies and insights.  The rubrics for evaluation are Word documents that will be collected via Teams and shared with each group.

Evaluation Rubric

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The evaluation rubric is from the Association of American Colleges and Universities. This rubric is considered a standard in assessing quantitative reasoning and quantitative literacy skills nationwide. By using this students will gain the experience of using external criteria to frame their assessments. Students will also provide structured feedback to their colleagues.