PPT-Core Methods in Educational

Data Mining HUDK4050 Fall 2014 Wow Welcome Theres a lot of you Its great to see so much continuing interest in EDM at TC Administrative Stuff Is everyone signed up for class If not and you want to receive credit please talk to me after class. M. Reddy, A. . Livorine. , R. . Naini. , H. Sucharew, A. Vagal. University of Cincinnati Neuroscience Institute. Poster No: EP-65. Control No: 1041. Disclosures. Mahati Reddy : None. Data Mining. HUDK4050. Fall 2015. Quick question. I’m now going to be in NY the first week of December. I was thinking of un-cancelling class on 12/1,. in exchange for 12/8. What do people prefer? Let’s take . . Science Centres Educators. Long Jinjing. Introduction. PART 1: . A brief review to the evolution of the. educator's function as well as the . educational philosophy in science. Data Mining. EDUC545. Spring 2017. Last Lecture. Slides 34-36. Textbook part 1. Pelanek. example. W002V004v5. Who would like me to . review this?. Feature Engineering . Not just throwing spaghetti at the wall and seeing what sticks. Data Mining. EDUC545-010. Spring2017. Discussion forums read-only for auditors. Who here is impacted?. For-credit students: are you OK with switching to Piazza?. RTFF. Introducing Prof. Alex Bowers. Top researcher in the world in using big data for educational leadership. Data Mining. HUDK4050. Fall 2014. What is the . Goal . of Knowledge . Inference?. What is the . Goal . of Knowledge . Inference?. Measuring . what a student knows at . a specific time. Measuring what . Data Mining. EDUC545. Spring 2017. The Homework. Let’s go over . basic homework 2. Q1. Build a decision tree (using operator W-J48 from the Weka Extension Pack) on the entire data set. What is the non-cross-validated kappa. Data Mining. HUDK4050. Fall 2014. Any administrative questions?. The Homework. Let’s go over the homework. Q1. Build a decision tree (using operator W-J48 from the Weka Extension Pack) on the entire data set. What is the non-cross-validated kappa. Data Mining. EDUC545. Spring 2017. Last Lecture. Slides 34-36. Textbook part 1. Pelanek. example. W002V004v5. Who would like me to . review this?. Feature Engineering . Not just throwing spaghetti at the wall and seeing what sticks. EDUC545. Spring 2017. Data Used to Be. Dispersed. Hard to Collect. Small-Scale. Collecting sizable amounts of data required heroic efforts. Like we heard about from Alex Bowers last week. Tycho. Brahe. Data Mining. EDUC545. Spring 2017. The Homework. Let’s go over the homework. Let’s go over some of the solutions . you handed in….. I will call on a small number of you. Let’s go over some of the solutions . Data Mining. HUDK4050. Fall 2014. Did you have a nice week?. My week. Towards Better and More General . Prediction . Models of Engagement. Ryan Baker. Teachers College, Columbia University. Learning Analytics. Data Mining. HUDK4050. Fall . 2015. Hi!. PFA Assignment. General questions?. PFA Assignment. What is SSR?. Do you want a higher or lower SSR?. PFA Assignment. Were you able to get the Excel Equation Solver to work?. Core Methods in Educational Data Mining EDUC691 Spring 2019 Welcome! Administrative Stuff Is everyone signed up for class? If not, and you want to receive credit, please talk to me after class Class Schedule