Presentation CSCI 540 Due Date: See schedule We have spent the semester getting familiar with multiple topics in of databases. Some topics were practical (e.g., how to use a few non-relational databases), some were algorithmic (e.g., indexing structures), and some were theoretical (e.g. CAP theorem and consistency models). Now, it is your turn to lead the class and help everyone understand something that you are interested in. Earlier in the week, I asked you to send me a topic you would like to learn about and introduce the class to. I have used your topic suggestions to organize the rest of the lectures. The lecture schedule is below. Description For your topic, you and your partner will be the lecturers. You will have two steps: • By at least midnight, TWO days before your lecture, post on piazza links to resources and a description of what students should do prior to your lecture to be prepared. Sources may be materials that you put together, papers, video, software to install, problems to work through, message board postings, etc. Note that if you need to post content, for example a PDF, Box is a campus supported option for sharing. Students are expected to come prepared to class by working through the material you suggest. Note that you should target the student preparation at under an hour, it should NOT exceed two hours. • On the day of your presentation, arrive at least five min early for class to be ready to start on time. You may use between 30-45 min of the lecture period. We will use the last five min to fill out feed back forms (see below). Feel free to get creative. Your lecture may be interactive, you can have people work on problems, write code, discuss in groups, or anything else that you think may help you to introduce the class to your topic. You will be graded on the following: As a lecturer: • 10 points Pre-lecture materials • 30 points Demonstration of knowledge of the presented material • 20 points Preparation of the lecture • 10 points Effectiveness of lecture As a student: • 15 points Your preparation as a student • 15 points Your participation as a student 1
Schedule Date Topic Group Wed Nov 15 Spark Dataframes Group 3: Neil Walton, Hongchuan Wang Fri Nov 17 Query optimization Group 8: Alexander Huleatt, Baiqiang Wen Mon Nov 20 Pub/Sub Group 5: Rohan Khante, Joseph Debruycker Mon Nov 27 Ontologies Group 6: Nashea Wiesner, Lucia Williams Wed Nov 29 Voldemort Group 2: Bonnie Hardin, Karishma Rahman, Seraj Mostafa Fri Dec 1 Data Warehousing Group 4: James Beck, Amy Peerlinck Mon Dec 4 Negative Databases Group 1: Rituparna Halder, Susmit Sengupta Wed Dec 6 Deployment Group 7: Kierstyn Brandt, Gregory Hess 2
Anonymous Suggestions About Lecture 1 Presenter: Topic: Date: Pre-class material • About how long did you spend working through the pre-material? • How suitable was the material for the lecture? • How beneficial was the material for the lecture? Content • What were the learning objectives? • Did you learn what you think you were intended to learn? • How, and how well, did the lesson peak and maintain your interest? • How suitable was the level of the material? • How suitable was the material for the amount of available time? Presentation • How through was the preparation? • How could the visuals be improved? • Was the delivery loud enough? • Was the interaction effectively encouraged? How? • Was interaction effectively handled? – Were responses on point? – Were responses respectful? • Was the lesson fun? (Not all lessons are supposed to be.) Other comments of suggestions 1 Adapted from feedback form used in http://cs.unc.edu/academics/graduate/phd-info/comp-915 3
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