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Cheryll Witting
If you are learning alone, or if you are a parent assisting your child, you may want to purchase the accompanying Answer Book. The Answer Book is an ideal way to check the exercises from the Workbook have been completed correctly.
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As mentioned above, the Answer Books are typically used by students who are learning music theory without the aid of a music teacher. They will allow you, or the parent of a child student, to review the work completed in the Workbooks and see where mistakes have been made.
We always recommend following the direct advice of your music teacher. In most cases, the music teacher will review your answers with you, helping you fill in the gaps in your knowledge and setting additional practice tasks where necessary.
Students will typically sit several mock exams in the run up to the real exam. This will help prepare for the exam structure, the types of questions and the experience of sitting an exam under the appropriate conditions. This kind of practice is especially helpful for children sitting their first exam.
The evaluation of this project is to answer trivia questions. You donot need to do well at this task, but you should submit a system thatcompletes the task or create adversarial questions in that setting. This will help the whole class share data andresources.
Quiz bowl is an academic competition between schools inEnglish-speaking countries; hundreds of teams compete in dozens oftournaments each year. Quiz bowl is different from Jeopardy, a recentapplication area. While Jeopardy also uses signaling devices, theseare only usable after a question is completed (interrupting Jeopardy'squestions would make for bad television). Thus, Jeopardy is rapaciousclassification followed by a race---among those who know theanswer---to punch a button first.
Expanding on a 1908 paper by Smoluchowski, he derived a formula forthe intensity of scattered light in media fluctuating densities thatreduces to Rayleigh's law for ideal gases in The Theory of theOpalescence of Homogenous Fluids and Liquid Mixtures near the CriticalState. That research supported his theories of matter first developedwhen he calculated the diffusion constant in terms of fundamentalparameters of the particles of a gas undergoing Brownian Motion. Inthat same year, 1905, he also published On a Heuristic Point of ViewConcerning the Production and Transformation of Light. Thatexplication of the photoelectric effect won him 1921 Nobel in Physics.For ten points, name this German physicist best known for his theoryof Relativity.
Two teams listen to the same question. Teams interrupt the question atany point by "buzzing in"; if the answer is correct, the team getspoints and the next question is read. Otherwise, the team losespoints and the other team can answer.
You are welcome to use any automatic method to choose an answer. Itneed not be similar nor build on our provided systems. In addition tothe data we provide, you are welcome to use any external data exceptour test quiz bowl questions (i.e., don't hack our server!). You arewelcome (an encouraged) to use any publicly available software, butyou may want to check on Piazza for suggestions as many tools arebetter (or easier to use) than others.
We will use Dynabech website ( ). If you remember the past workshop about Dynabench submission, this is the way to do it. The specific task name is "Grounded QA". Here, with the help of the video tutorial, you submit your QA model and assess how your QA model did compared to others. The assessment will take place by testing your QA model on several QA test datasets and the results of yours and your competitors will be visible on the leaderboard. Your goal is to rank the highest in terms of expected wins: you buzz in with probability proportional to your confidence, and if you're more right than the competition, you win.
Alternatively, you can also write 50 adversarial questions thatchallenge modern NLP systems. These questions must be diverse in thesubjects asked about, the skills computers need to answer thequestions, and the entities in those questions. Remember that your questions should be factual andspecific enough for humans to answer, because your task is to stumpthe computers relative to humans!
We want questions from many domains such as Art, Literature, Geography, History,Science, TV and Film, Music, Lifestyle, and Sport. The questionsshould be written using all topics above (5 questions for eachcategory and 5 more for the remaining categories). Indicate in yourwriteup which category you chose to write on for each question.
Other than category diversity, if you find an ingenious way of writing questions about underrepresented countries, you will get bonus points (indicate which questions you included the diversity component in your writeup). You may decide which are underrepresented countries with your own reasonable reason (etc., less population may indicate underrepresented), but make sure to articulate this in your writeup.
Question Writing: You'll need to have answers selected for all ofyour questions and first drafts of at least 15 questions. This mustbe submitted as a JSON file so that we run computer QA systems on it.
Question Writing: You'll need to have reflected the feedback from the first questions and completed a first draft of at least 30 questions. You'll also need machine results to your questions and an overall evaluation of your human/computer accuracy.
Who did what. For example, for the question writing project a team of five people might write: A wrote the first draft of questions. B and C verified they were initially answerable by a human. B ran computer systems to verify they were challenging to a computer. C edited the questions and increased the computer difficulty. D and E verified that the edited questions were still answerable by a human. D and E checked all of the questions for factual accuracy and created citations and the writeup.
Review how well you did (based on the competition or your own metrics). If you do not use the course infrastructure to evaluate your project's work, you should talk about what alternative evaluations you used, why they're appropriate/fair, and how well you did on them.
Provide an error analysis. An error analysis must contain examples from thedevelopment set that you get wrong. You should show those sentencesand explain why (in terms of features or the model) they have thewrong answer. You should have been doing this all along as youderive new features, but this is your final inspection ofyour errors. The feature or model problems you discover should notbe trivial features you could add easily. Instead, these should befeatures or models that are difficult to correct. An error analysisis not the same thing as simply presenting the error matrix, as itdoes not inspect any individual examples. If you're writing questions, talk about examples of questions that didn't work out as intended.
The linguistic motivation for your features / how your wrote the questions. This is acomputational linguistics class, so you should give precedence tofeatures / techniques that we use in this class (e.g., syntax,morphology, part of speech, word sense, etc.). Given two featuresthat work equally well and one that is linguistically motivated,we'll prefer the linguistically motivated one.
Your system should be sent directly to the professor and TAs in zip files, including the correct dependencies and a working inference code. Your inference code should run successfully in the root folder (extracted from zip folder) directory with the command:
If you have any notes or comments that we should be aware of while running your code, please include them in the folder as a .txt file. Also, dependency information should be included as a .txt file.
For systems, please do not go over 2500 words unless you have a really good reason.Images are a much better use of space than words, usually (there's nolimit on including images, but use judgement and be selective).
For question writing, you have one page (single spaced, two column) per question plus a two page summary of results. Talk about how you organized the question writing, how you evaluated the questions, and a summary of the results. Along with your writeup, turn in a json including the raw text of the question and answer and category. The json file is included in this directory. Make sure your json file is in the correct format and is callable via below code. Your submission will not be graded if it does not follow the format of the example json file.
All members of the group will receive the same grade. It's impossible for the course staff to adjudicate Rashomon-style accounts of who did what, and the goal of a group project is for all team members to work together to create a cohesive project that works well together. While it makes sense to divide the work into distinct areas of responsibility, at grading time we have now way to know who really did what, so it's the groups responsibility to create a piece of output that reflects well on the whole group.
This course focuses on helping students develop an understanding of the role and contributions of African Americans to the growth and development of the United States. This course is also designed to develop an understanding of the causes, character, and consequences of the African American experience and its influence on the world, the United States, and the African American community. Beginning with a historical, geographical, social, political, economic, and cultural understanding of the African continent, the course will provide a descriptive and corrective overview that will introduce the student to the study of the African and African American experiences.
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