Midterm Portfolio Work Session

When locating code…

You can use any code from your Lab or Challenge assignments.

  • find 1-2 high quality examples (quality > quantity)
  • find examples that hit on multiple learning targets at the same time

For example..

the code below could be used to demonstrate proficiency with:

  • WD-2 – in two places (select() and starts_with())!
  • WD-7 – pivoting longer
  • WD-4 – reordering a factor
  • R-2 – tidy dplyr pipeline
ca_childcare |>
  select(study_year,
         mc_infant,
         mc_toddler,
         mc_preschool,
         region
         ) |>
  pivot_longer(cols = starts_with("mc_"), 
               names_to = "age", 
               values_to = "median_income"
               ) |> 
  mutate(age = fct_relevel(age, 
                          "mc_infant",
                          "mc_toddler",
                          "mc_preschool")
        )

semi_join() & anti_join()

An Example from Lab 5…

new_suspect <- drivers_license |> 
  filter(height > 64, height < 68,
         hair_color == "red",
         gender == "female",
         car_make == "Tesla",
         car_model == "Model S") |>
  # rename column so keys match
  rename(license_id = id) |> 
  inner_join(person,
             by = "license_id") |> 
  inner_join(facebook_event_checkin,
             join_by(id == person_id)) |> 
  group_by(id, event_name) |> 
  count() |> 
  filter(event_name == "SQL Symphony Concert",
         n == 3)
new_suspect
# A tibble: 1 × 3
# Groups:   id, event_name [1]
     id event_name               n
  <dbl> <chr>                <int>
1 99716 SQL Symphony Concert     3

semi_join() & anti_join()

An Example from Lab 5…

interview |> 
  semi_join(new_suspect,
            by = join_by(person_id == id)) |> 
  pull(transcript)
character(0)

Another way to think about it…

If there are lots of specific features you are looking for, you could put them into a tibble (or a data frame).

suspect_features <- tibble(
         hair_color = "red",
         gender = "female",
         car_make = "Tesla",
         car_model = "Model S")

Another way to think about it…

You can then use these data as a filtering join!

drivers_license |> 
  filter(height > 64, height < 68) |>
  semi_join(suspect_features) |> 
  # rename column so keys match
  rename(license_id = id) |> 
  inner_join(person,
             by = "license_id") |> 
  inner_join(facebook_event_checkin,
             join_by(id == person_id)) |> 
  group_by(id, event_name) |> 
  count() |> 
  filter(event_name == "SQL Symphony Concert",
         n == 3)

Reflective Essays (not Lightening Round)

Revising Your Thinking

  • Where have you revised your code?
  • What have you learned by doing revisions? Be specific!
  • How have you incorporated this knowledge into future assignments? Be specific!

Extending Your Thinking

  • On what assignments did you push yourself by extending beyond what we learned in class?
  • In what way? Be specific!

Looking for examples?



The Exemplary Student Work tab of the course website contains some exemplary code written by your peers!

Supporting Your Peers

  • What have you learned about collaboration through the groupwork protocol?
    • How have you grown as a collaborator? Be specific!
  • How have you supported your peers through code review?
    • Do you have a specific code review you are proud of? Show me!
  • Supporting your peers on Discord can look a variety of ways!
    • Did you ask questions that others could learn from?
    • Did you answer someone’s question?

Determining Your Grade

Determining Your Grade

I believe my grade equivalent to course work evidenced below to be an __.

Your goal is to argue, convincingly and with concrete evidence, that you have met the criteria that goes with a particular grade.

This involves every part of the criteria–content proficiency, evidence of continued learning, revising your thinking, and growth as a team member.

Plus / Minus Modifiers

+

  • You’ve met all the criteria for the letter grade along with a significant amount, but not all, of the criteria for the next letter grade up.

-

  • You have met the requirements for a letter grade but only in a way that you believe is a bare minimum.
  • You’ve met almost all the requirements for the letter grade except for a small number of minor criteria.

What if you don’t agree?

There are two ways this might happen.

You ask for a grade that is higher than the evidence supports.


That is, you grade yourself too highly. For example, you believe you earned an A in the course, but I do not feel the evidence you’ve provided supports this grade.


In this case, I’ll tell you what grade I would have given you based on the evidence you provided in the portfolio. You can then use this feedback when constructing your Final Portfolio.

You ask for a grade that was lower than your actual performance indicates.


That is, you “lowball” yourself, for example you say you earned a B when in fact I think you earned an A-.


In this case, I will tell you what grade I believe you have earned and why.

Midterm Portfolio Meetings

Will occur on Tuesday and Wednesday of next week.


Sign-up for your time here: link to Google Sheet