Preventing Problems while Permanently Storing Grades in PowerSchool

Peculiar enrollment situations can lead to issues when permanently storing grades at the end of a term. For instance, if a student changes from one section of a course to another during a term, one grade could get stored for each section if the “Exclude enrollments” dates are not selected wisely.

"Exclude Enrollments" options

While we keep a file of “Special Cases” to review at the end of each term, but there are often such cases that sneak by us. To catch them, I track down all enrollment anomalies before storing grades.

To do this, I use DDE (…/admin/tech/dde/):

In DDE:

  • Select the CC table
  • TermID >= current year term (2900, 3000, 3001, etc.)
  • SchoolID = 200 for MS or 300 for HS (in our case)
  • DateEnrolled >= “A couple weeks after the start of the term”
  • Export to a spreadsheet
  • Sort by course name and delete non-courses: clubs, sports, A-Block, etc.
  • Sort by DateEnrolled and look for any peculiar dates later in the term
  • Decide appropriate cutoff date for “enrolled… after”
  • Note any enrollments that may be improperly included or rejected for later followup
  • Repeat above steps changing DateEnrolled to DateLeft and find an appropriate time for “dropped… before”

I typically check “Exclude … dropped before…” about a week before the end of the current term. Checking for outlier dates can help identify individual students and enrollments that may need attention.

Air Quality Monitoring on a Corporate Scale

NOTE: This project started out small, simple, easy-peasy. It has expanded well beyond what can comfortably be contained in a single blog post. If you’re looking into setting up air monitoring on your campus, I would be very happy to help you as much as you’d like – from a general “Here’s a website to look at” to a complete “Here’s a fully functional pm2.5/pm10/temp/humidity/barometric pressure sensor and dashboard”, I’m probably the guy you want to talk to.
My current setups use $75 DYI sensors as well as a multi-thousand dollar commercial sensor, Python scripts, api calls, HTML, CSS, Google Sheets, and JavaScript to create responsive displays showing current and recent AQI readings. Let me know if you have any questions or would like some help. Otherwise, feel free to continue on to the post I made a few years back . . .


South Korea doesn’t have the worst air in the world, but it’s also no Chippewa Falls, Wisconsin. Recognizing that very bad air days are a threat to the health of our students and staff, our school developed a systematic plan to monitor the air we breath and to filter bad air when necessary. As part of this effort, several staff, faculty and students worked together to build a network of air quality monitoring stations around campus to collect timely data, share current data with stakeholders, and record data long-term for research and future planning. These devices are surprisingly accurate except during times of high humidity when the SDS011’s readings become unreliable. Ultimately, the school’s brass decided to go with a commercially available system for it’s needs. But I have preserved the following explanation of how we built the devices and installed the software to disseminate current data and stored data for future use.

We built a variation of the Sensor.Community’s project. This uses the Plantar SDS011 PM2.5/PM10 particulate matter detector, BME280 temperature/humidity/pressure monitor, the WEMOS D1 Mini ESP8266 development board and a super small breadboard to bring it all together. Note that these items can also be commonly found virtually anywhere that sells microelectronics components and they’re inexpensive. The SDS011 sensor is around $17, the others are a few dollars each.

Setup is fairly straightforward. We attach headers to the Wemos D1 Mini and the BME280. Then we connect the 5V pin of the D1 to the 5V pin of the SDS011,

Wiring Connections:

Wemos D1 MiniSDS011BME280
5V5V
3.3VVIN
D1TXD
D2RXD
D3SDA
D4SCL
GNDGND
Sensor wiring connections

Once everything is connected, we’ll want to flash the Wemos D1 Mini’s code. Visit the Sensor.Community’s download page to retrieve the appropriate version. Connect the Wemos D1 to your computer, and run the flashing program to set it up. If your computer does not recognize the Wemos D1, you may need to install the driver to see it. The driver page is mostly in Chinese, so you will need to look closely to discern which version is needed for your OS.

Once flashed, you’ll need to reboot the device by disconnecting from your computer and then reconnecting – either to your computer or another micro-USB power source.

The first time it restarts, it won’t know how to connect to your local WiFi, so it creates its own WiFi network. On your computer, look for a new SSID that begins with Feinstaubsensor-ID or airRohr-ID followed by a chip ID such as 13597771. Connect to that SSID and note the chip ID as it will be needed later. Once connected, point your browser to 192.168.4.1 and you should see the device setup page. From here, you can select your preferred language, enter your local WiFi network name and password, and identify the sensors connected to the device. Be sure to click the “Zurük zur Starseite” button to save the settings and restart the device.

There are are a couple ways to check your sensor readings. You can access your device directly on your local network if you can identify and visit its local ip address. Alternatively, you can create an account at https://sensor.community to conveniently access your device data online. You’ll need the Chip ID you wrote down earlier to find your sensors. But once your account is set up, you’ll be easily able to bookmark your device to see your local air quality, temperature and humidity conditions.