The Challenge

It’s a typical Tuesday afternoon after school. Maybe you watch a video your friend sent you on the bus ride home and tag him in a photo while you scroll through Facebook. When you get home, perhaps your mom nags you to buy those sneakers you need for soccer tryouts and you buy them on Amazon. You might send a few snapchats to keep your streaks going, check the number of likes on your Instagram shot from this morning, and maybe make a Musical.ly or two while you wait for dinner.

All these interactions online are little pieces of you – gigabytes and megabytes – sent out into the world that create a larger cyber representation of who you are, what you like, and how you live. As soon as you log on, sign in, or create anything on the web, the material is contributing to an ever-evolving digital identity. Each account is like an alter ego in which you, through a screen, interact with others and send a piece of yourself out far beyond your physical presence.

Is anyone collecting this information? Paying attention to this evolving digital identity? Yes. Your social media accounts and platforms analyze the information that you have put out there about yourself. For instance, YouTube and Amazon track the type of video you watch/products you view and recommend other options you might be interested in. Each online interaction gathers information from you that is aggregated and readable. Each click in which you send out your name, your opinions, your preferences, or your information adds to this technological extension of self. So, not only are you constantly feeding your digital identity, but corporate companies out there are also constantly interpreting that identity and feeding that interpretation back to you.

Marshall McLuhan, in his seminal book, Understanding Media, said, “The use of any kind of medium or extension of man alters the patterns of interdependence among people, as it alters the ratios of the senses. It is the persistent theme… that all technologies are extensions of our physical and nervous systems to increase power and speed.”  This Meridian Challenge agrees and asks you to take it a step further: if technologies are extensions of ourselves, what does our tech self look like? Would we recognize it? Can we shape it?

In this challenge, you and your team will want to track where you go digitally over a five-day time period; articulate the data mathematically and graphically, and then create a visual and creative technological self-portrait of yourself.

Let’s take this one step at a time:

First, you will work in a team to gather data about your individual technological identities. This includes collecting all digital media with which you interact, comment on, or create over a five-day period, including all digital interactions from emails to shopping online.

Second, prepare a presentation of your collective data gathering in a mathematical graph(s).

Third, working individually, create an artistic self-portrait that in some way indicates your new understanding of self, given your exploration of your digital identity.

Fourth, present your self-portrait to your team.

The final video product involves a) the presentation of the collective data; and b) the unscripted (but edited) moment of you and your teammates sharing your self-portraits with each other. During this latter part, your teammates can ask up to two questions during your (more or less) 60-second presentation of self. This will allow time for everyone to be included in this video, which can’t run more than five minutes in total.

In the end, your team will explore your digital identities – your out-of-body, extended selves – as based on real data collection and to reflect on yourselves as composite – biological and digital – beings. After your presentations…what did you learn? Tell the camera.

Deliverables include:

  • Tech You Video (this is the only Meridian Stories deliverable)
  • Data Summary Report (at the teacher’s discretion)
  • Technology Self-Portrait (at the teacher’s discretion)

 

Assumptions and Logistics

 

Time Frame – We recommend that this Meridian Stories Competition takes place inside of a three to four-week time frame.

Length – All Meridian Stories submissions should be under 4 minutes in length, unless otherwise specified. And this Competition is ‘otherwise specified’: 5-minute maximum length.

 

Submissions – Keep in mind that each school can only submit three submissions per Competition (so while the entire class can participate in the Challenge, only three can be submitted to Meridian Stories for Mentor review and scoring).

Teacher Reviews – All reviews by the teacher are at the discretion of the teacher and all suggested paper deliverables are due only to the teacher. The only deliverable to Meridian Stories is the media work.

Teacher’s Role and Technology Integrator – While it is helpful to have a Technology Integrator involved, they are not usually necessary: the students already know how to produce the media. And if they don’t, part of their challenge is to figure it out. They will! The teacher’s primary function in these Challenges is to guide the students as they engage with the content.  You don’t need to know editing, sound design, shooting or storyboarding: you just need to know your content area.

Digital Rules/Literacy – We strongly recommend that all students follow the rules of Digital Citizenry in their proper usage and/or citation of images, music and text taken from other sources. This recommendation includes producing a citations page at the end of your entry, if applicable. See the Digital Rules area in the Resources section of the site for guidance.

Location – Try not to shoot in a classroom at your school. The classroom, no matter how you dress it up, looks like a classroom and can negatively impact the story you are trying to tell.

 

Slate – All media work must begin with a slate that provides:

  1. the title of the piece;
  2. the name of the school submitting;
  3. the wording ‘Permission Granted’ which gives Meridian Stories the right to a) publicly display the submission in question on, as linked from or related to Meridian Stories digital media; and b) use it for educational purposes only; and
  4. We strongly recommend that students do not put their last names on the piece either at the start or finish, during the credits.

 

Collaboration – We strongly recommend that students work in teams of 3-4: part of the educational value is around building collaborative skill sets. But students may work individually.

Presentation – We strongly recommend that at the end of this process, the student teams present their work either to the class and/or to assembled parents and friends as a way to showcase their work. The workforce considers Presentational Skills to be a key asset and we encourage you to allow students to practice this skill set as often as possible. These short videos provide a great opportunity for kids to practice their public presentational skills.

Our research indicates this to be a really useful exercise for two additional reasons:

  1. Students actually learn from their peers’ presentations – it is useful to hear a perspective that is not just the teacher’s; and
  2. The public setting – painful as it is for some students – provides them with an opportunity to ‘own’ their work and to be more accountable.

 

The Process

Below is a suggested breakdown for the students’ work.

During Phase I, student teams will:

  • Work with your team to decide the boundaries of the data that you are collecting.
    • Take some time to list out websites, accounts, and other parameters about what your team considers a technological extension of self.
      • This list may grow or shrink during data collection.
    • Decide with your group in what way the data is going to be collected.
      • Is each member journaling? Keeping a blog? Creating a document? A photo journal?
        • Your group must decide as a team how to quantify the abstracted data points
        • The data will be put in graph format after the five days, so make sure the data is in a form that is transferable and mathematically viable.
      • Keep in mind that you and your team are responsible for creating a mathematically accurate representation and analysis of this data, so your collection and recording methods need to be clear and precise.
    • Decide what other information will be recorded with the data.
      • A few examples might be:
        • How long you were on a certain page?
        • How the link was provided to you/recommended by a website/related by other videos you’ve watched/tagged by a friend/shared?
        • How much information about your real physical identity was given with it?
        • Can your peers see the information/tech you’ve shared/created or the website/platform only?
      • Collect the data over the course of five days.
        • Each student will record their own data, careful to not alter their habits due to process of monitoring and aggregating.
        • Teacher’s Option: Data Summary Report – Teachers may require that teams hand in a report summarizing the data they collected.

During Phase II, student teams will:

  • During or after the five days, sort the data into categories to make the aggregation and graphing easier.
    • For example:
      • Collecting all the terms that had been searched in a search engine in one place, careful to keep date/time/duration with the data.
      • Collecting all the (descriptions/images of) items purchased in one place.
      • Collecting all the emails received by a subscription in one category.
    • Use a minimum of three of the specific types of data/information that has been sent out over the five days, to be represented graphically.
      • These specific categories must represent different aspects of one’s digital identity and show trends in behavior and/or reactions from the outside (peers, websites, sellers, etc.)
        • For example:
          • One could choose to represent average time required for amazon/ebay/facebook/instagram to use or make suggestions/create ads based on search history or past activity.
          • One could choose to represent number of likes (throughout all platforms) throughout the week to see usage trends in time of day or day of the week.
        • Choose with your group a method(s) of mathematical graphing to represent the data.
          • (i.e. scatter plot, pie chart, bar graph, etc.)
        • Graph the group data in the type of graph(s) you have chosen
          • You must use data from every group member in each graph.
          • The graphs must show data/conclusions of substance, so make sure to pick axis and graph types that show the interesting pieces of the data collected.
        • Consider what the graph(s) show and mean:
          • Were there any surprises?
          • Are there any consistent trends of behavior within the group?
          • Does one person’s data differ drastically from another?
        • Does showing the data in a graph format make it easier to interpret?
      • Create the cyber self-portraits.
        • Now the team will break apart for a beat and work individually. You will take all the information and create a visual and artistic representation of your composite digital/biological/physical selves. In other words, you will create one self-portrait that shows both the similarities and the differences between your digital identity and a physical one.
        • Some questions to consider:
          • Does your digital identity shock you? Does it not correlate to what you considered your physical identity?
          • What pieces of the data surprised you most? What parts of the data fit with what you’d expect?
          • Does the visual artistic representation show the digital identity – the one that is out there, active, while you may be sleeping at home – at odds with the physical identity or are they one and the same to you?
          • What piece of the data seems to make up the most of your digital identity? Does it show where you spend most of your time? Does it show that more information about your physical self is present online than you realized?
          • Does the data make you question your digital identity? Or make you want to alter it?
        • The student can use all or most of the pieces of data collected. And keep in mind that a self-portrait doesn’t have to be hand-drawn art. It can be comprised of words and existing images/graphics as well. The only criteria here is…put it in a frame.
        • Teacher’s Option: Technology Self-portraits– Teachers may require that the each member hand in their self-portrait
      • Plan out the final reflection piece in which:
        • You will discuss the difficulty level of the process and knowledge learned through the experience.
        • You will discuss the final self-portrait and what it represents
        • You will discuss any takeaways that you will remember and/or keep in mind as you continue to evolve your digital life.
        • Keep in mind that the planning in this stage is done privately.
      • Pre-produce the video as a team.
      • Scout locations for shooting – where is a comfortable place to reveal your self-portraits to your friends?
      • Create costumes, props and other set pieces, as needed; and
      • Prepare the logistics for the actual shooting of the video.

 

During Phase III, student teams will:

  • Shoot the video (no more than five minutes in total)
    • The video format is a recorded presentation and can be filmed in a comfortable, intimate setting.
    • First, record the presentation of the graphs.
      • The entire team will present the graphs and discuss briefly what the graph represents, the conclusions that follow from it, and the impact of the conclusions.
    • Second, record the presentation of the digital self-portraits
      • Each person will individually and succinctly discuss/present their digital self-portraits to the camera and the other group members.
      • The other group members may ask brief questions.
    • Third, record the conclusions and reflections
  • Edit the video, adding stills and graphics as desired.
  • Record any additional voice-over or narration, as necessary (sometimes you may need a sentence or two to bridge the gaps from one idea to the next).
  • Post-produce the video, adding music and sound effects as desired.

 

Media Support Resources

Meridian Stories provides two forms of support for the student teams:

1.    Media Innovators and Artists – This is a series of three to four minute videos featuring artists and innovative professionals who offer important advice, specifically for Meridian Stories, in the areas of creativity and production.

2.    Meridian Tips – These are short documents that offer student teams key tips in the areas of creativity, production, game design and digital citizenry.

Recommended review, as a team, for this Competition include:

Meridian Innovators and Artists Media Resource Collection
On Nonfiction – Margaret Heffernan

On Memoir and Nonfiction – Liza Bakewell

On Producing – Tom Pierce

On Editing – Tom Pierce

“Creative Brainstorming Techniques”

“Sound Recording Basics”

“Six Principles of Documentary Filmmaking”

“Video Editing Basics”

 

 

Evaluation Rubric – Tech You

 

CONTENT COMMAND
Criteria 1-3 4-7 8-10
Data Aggregation

and Graphing

Mathematical graphs are not present or inaccurate Mathematical graphs representing the three or more data categories are mostly accurate and partially explained Mathematical graphs representing the three or more data categories are accurate, creatively presented, and well-explained
Data Analysis The analysis of the graphs and data is not present or inaccurate The analysis of the graphs and data is attempted but not entirely clear The analysis of the graphs and data is complete, incorporated, and insightful
Final Reflection The final discussion of technological extensions of self – one’s digital identity – is superficial or incomplete The final discussion of technological extensions of self – one’s digital identity – is complete The final discussion of technological extensions of self – one’s digital identity – is interesting and insightful with thoughtful conclusions

 

 

STORYTELLING COMMAND
Criteria 1-3 4-7 8-10
The Story of the Graph The story of the graph is hard to follow. The story of the graph is clear The story of the graph is insightful and thought-provoking
Individual Self-Portraits and Explanation The self-portraits are missing or not reflective of the data or conclusions drawn. The self-portraits are reflective of the data and conclusions drawn The self-portraits are creative, original, and thoughtfully reflective of the data and conclusions drawn.
The Whole Experience The video does not tie together the various parts in order to tell a cohesive story about the team. The video does tie together the various parts in order to tell a cohesive story about the team. The video ties together the various parts in a compelling way in order to tell a cohesive and honest story about the team.

 

MEDIA COMMAND
Criteria 1-3 4-7 8-10
Location and Shot Selection  The location and shooting approach – shot framing – does not enhance engagement with the video The location and shooting approach – shot framing – services our engagement with the video The location and shooting approach – shot framing – enhances our engagement with the video
Editing The video feels patched together and the overall editing detracts from the video narrative The video generally flows, servicing the video narrative The video is edited cleanly and effectively, propelling the video forward

 

21st CENTURY SKILLS COMMAND (for teachers only)
Criteria 1 – 3 4 – 7 8 – 10
Collaborative Thinking The group did not work together effectively and/or did not share the work equally The group worked together effectively and had no major issues The group demonstrated flexibility in making compromises and valued the contributions of each group member
Creativity and Innovation The group did not make a solid effort to create anything new or innovative The group was able to brainstorm new and inventive ideas, but was inconsistent in their evaluation and implementation of those ideas The group brainstormed many inventive ideas and was able to evaluate, refine and implement them effectively
Initiative and Self-Direction The group was unable to set attainable goals, work independently and manage their time effectively The group required some additional help, but was able to complete the project on time with few problems The group set attainable goals, worked independently and managed their time effectively, demonstrating a disciplined commitment to the project

 

Essential Questions

  1. What is data and how do you collect, collate and visually represent it in a way that can be understood by others?
  2. What is data analysis, how is it done and why is it important?
    1. How did graphing the data highlight trends and interesting data in this challenge?
  3. What is personal data?
    1. What have you learned through the process of collecting and sharing personal data?
    2. What has monitoring and collecting data about yourself taught you about your own habits?
  4. How are you represented in the digital sphere? How much/what type of information are you giving out and receiving each day without realizing it?
  5. How has immersion in the creation of original content and the production of digital media – exercising one’s creativity, critical thinking, and digital literacy skills – deepened the overall educational experience?
  6. How has working on a team – practicing one’s collaborative skills – changed the learning experience?

 

Student Proficiencies

  1. The student will have a solid understanding of how to collect, collate and visually represent data in a variety of ways.
  2. The student will understand how to analyze data in order to understand something – a pattern or behavior or narrative – that was not clearly evident before.
    1. This challenge allows for the data to show trends in usage that are unique to individuals as well as show how people of the same age have some areas of overlap in digital identity and some areas of discrepancy that prove individuality and uniqueness.
  3. The student will learn that personal data is a type of data dealing with specific people and their lives, which could range from standard data such as height and weight to more imaginative data such as how many times a person smiles in a day.
    1. The student will be able to articulate what the process of completing this project has taught them about themselves, the ubiquity of data, and connecting with other people.
    2. The student will have a deeper understanding of patterns of their own behavior. They will be able to see where most of their online time is devoted and reflect on their own online choices. They will note the differences between how they previously viewed their interactions online and how they actually interact and spend their time online.
  4. The student will broaden their understanding of how much information they are sharing on the Internet and the aggregated data that companies or other individuals can gather about them. The student will understand more about the ways they use technology everyday to communicate and share pieces of themselves.
  5. The student will utilize 21st century skills, with a focus on creativity, critical thinking and digital literacy, in their process of translating scientific content – the data collected – into a story about themselves.
  6. The student will have an increased awareness of the challenges and rewards of team collaboration. Collaboration – the ability to work with others – is considered one of the most important 21st century skills to develop in students as they prepare for life after secondary school.

 

Common Core Curricular Correlations

The Tech You Competition addresses a range of curricular objectives that are articulated in Common Core Mathematics Standards. Below please find the standards that are addressed, either wholly or in part.

Common Core – Mathematics

Statistics and Probability (Grade 6)

Students who demonstrate understanding can:

  • Display numerical data in plots on a number line, including dot plots, histograms, and box plots. (6.SP.B.4)
  • Summarize numerical data sets in relation to their context, such as by:
    • Reporting the number of observations. (6.SP.B.5.A)
    • Describing the nature of the attribute under investigation, including how it was measured and its units of measurement. (6.SP.B.5.B)
    • Giving quantitative measures of center (median and/or mean) and variability (interquartile range and/or mean absolute deviation), as well as describing any overall pattern and any striking deviations from the overall pattern with reference to the context in which the data were gathered. (6.SP.B.5.C)
    • Relating the choice of measures of center and variability to the shape of the data distribution and the context in which the data were gathered. (6.SP.B.5.D)

Statistics and Probability (Grade 7)

Students who demonstrate understanding can:

  • Informally assess the degree of visual overlap of two numerical data distributions with similar variabilities, measuring the difference between the centers by expressing it as a multiple of a measure of variability. (7.SP.B.3)

Statistics and Probability (Grade 8)

Students who demonstrate understanding can:

  • Construct and interpret scatter plots for bivariate measurement data to investigate patterns of association between two quantities. Describe patterns such as clustering, outliers, positive or negative association, linear association, and nonlinear association. (8.SP.A.1)
  • Know that straight lines are widely used to model relationships between two quantitative variables. For scatter plots that suggest a linear association, informally fit a straight line, and informally assess the model fit by judging the closeness of the data points to the line. (8.SP.A.2)

Functions (Grade 8)

Students who demonstrate understanding can:

  • Construct a function to model a linear relationship between two quantities. (8.F.B.4)

High School – Statistics and Probability

Students who demonstrate understanding can:

  • Represent data with plots on the real number line (dot plots, histograms, and box plots). (HSS.ID.A.1)
  • Fit a linear function for a scatter plot that suggests a linear association. (HSS.ID.B.6.C)