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Robert Talbert RobertTalbert

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RobertTalbert / gist:746808be87b9a593eb0451c10f51f955
Created Sep 11, 2018
Script to add all users to a Slack channel
View gist:746808be87b9a593eb0451c10f51f955
var foundAny=false;
function selectAllByLetter(remainingLetters) {
var letter = remainingLetters.pop();
setTimeout(function() {
$(".channel_invite_member:not(hidden)").each(function(i, obj) {
RobertTalbert /
Created Jan 10, 2018
Snippets for common info questions

Thanks for the message. The information you're requesting can be found in the course syllabus, which is linked to our Blackboard site. Did you have any questions about finding the syllabus or understanding that information? Thanks-- rt

Thanks for the message. The information you're requesting can be found in the course calendar, which is linked to our Blackboard site. Did you have any questions about accessing the calendar or understanding that information? Thanks-- rt

Thanks for the message. The information you're requesting was announced [in class | on Slack] on [date]. Did you have any questions about finding that announcement or understanding that information? Thanks-- rt

RobertTalbert / Instructor
Created Jan 10, 2018
Syllabus blurb on instructor availability
View Instructor

Instructor availability: Please note that I do not typically check email or Slack messages during the hours of 6pm and 6am on weekdays, and I do not check these at all on the weekends in order to devote time to family, rest, and religious observances. Messages received during these times will receive attention once I am back online. Otherwise you can expect to receive a response to your message within 6 hours, often much sooner. If you post questions to Slack, you are likely to receive responses faster.

RobertTalbert /
Last active Aug 12, 2017
Potential way to beat the SBSG end of semester death march by using assessment phases

A typical way to set up SBSG with reassessment is to allow students to reassess on those Learning Targets at any point all the way up through the end of the semester.

  • Pros: More true to the spirit of SBSG because the grade shows what students were eventually able to master; lowers stress by giving the entire semester to reassess
  • Cons: Almost always results in a crush of student reassessment at the end of the semester due to procrastination and/or students needing many attempts to pass a Target.

It's possible that students who "need" lots of attempts to pass a learning target would pass it earlier if the deadline for passing weren't so late; placing tighter limitations on the time frame for reassessment might inject more energy and purpose into student preparation for reassessment.

Proposal: Split the semester up into a small number of "phases". Each phase focuses on a subset of the Learning Targets. When the phase comes to an end, no more reassessment on those learning targets is permi


MTH 325 Learning Targets


  • P.1: I can set up a framework of assumptions and conclusions for proofs using direct proof, proof by contraposition, and proof by contradiction.
  • P.2: I can identify the predicate being used in a proof by mathematical induction and use it to set up a framework of assumptions and conclusions for an induction proof.
  • P.3: I can identify the parts of a proof, including the technique used and the assumptions being made.
  • P.4: I can perform a critical analysis of a written proof and provide a detailed explanation of the steps used in the proof.


View cp13_table.txt
| $n$| Number of nodes in $T_n$ | Number of leaves in $T_n$ | Number of internal vertices in $T_n$ | Height of $T_n$ |
|:--:|:-----------------------:| :-----------------------:| :-----------------------:| :-----------------------:|
| 1 | | | | |
| 2 | | | | |
| 3 | | | | |
| 4 | | | | |
| 5 | | | | |
| 6 | | | | |
| 7 | | | | |
| 8 | | | | |
RobertTalbert /
Created Feb 2, 2017
Code for Guided Practice 7, MTH 325
# Import networkx
import networkx as nx
# Import two functions from the "random" library:
# randint(a,b) generates a random integer between a and b
# random() generates a random floating point number between 0 and 1
from random import random, randint
# Generates 5 random graphs with random numbers of nodes and
RobertTalbert /
Created Feb 2, 2017
Solution to MTH 325 Guided Practice 7 review question 2.
import networkx as nx
import matplotlib.pyplot as plt
g = nx.Graph( [(0, 3), (1, 2), (1, 4), (2, 3), (3, 4)])
nx.draw(g, with_labels=True, node_color="orange")

Since taking over the facilitation of the Pew FTLC Grants Program in May 2013, I have made two significant enhancements to the Faculty Conference Travel Grant in consultation with the Pew FTLC faculty/staff, the Pew FTLC Advisory Committee, the Pew FTLC Grants Sub-Committee , and in response to questions/concerns raised by faculty from across the university. Each quarter, the window of time between when the grant system opened and the funding was depleted grew shorter until it became an online race to see which faculty could get into the system first and have access to funds. It was clear that the demand for grant funds was far surpassing the supply and that many of the same faculty were receiving funding year after year. Our first revision to the grant was to implement an every-other-year eligibility so that we could distribute the funds more widely among the faculty. While this temporarily took some pressure off of the online system, our applicant pool continued to grow to the extent that funds were

View MTH 325 W17 syllabus

MTH 325 course banner

About this course and the syllabus

Welcome to MTH 325, Discrete Structures for Computer Science 2. This document contains all the information you need to know about the course. Your job is to read this document carefully in the first week of class and familiarize yourself with how the course works and maintain that familiarity throughout the semester. Almost all questions about the course that you might ask can be answered by referencing the syllabus.

Course catalog description: Properties of relations, equivalence relations, partial orderings, fundamental concepts of graphs, trees, digraphs, networks, and associated algorithms; computer science applications. Offered fall and winter semesters. Prerequisite: MTH 225.

Course information

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