Anna Arakelyan

The following STATEMENT OF TEACHING PHILOSOPHY is based on my 11-semester experience in teaching the Principles of Statistics course.

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Teaching Goals

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First, I aim to give my students fundamental knowledge of statistical concepts and to train important practical skills for research and business problem solving. I expect them to recognize statistical contexts in every day life, and clearly see how exactly the classroom ideas relate to them personally. For example, probability theory deals with random events, and each student encounters many random events every day from the weather outside to the number of text messages he or she receives during a day. The goal is to teach them to notice such connections and be confident with them. After the course, I expect my students to feel comfortable with data, and be capable to extract sensible insights from dry numbers.

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Second, I aspire to teach students to think deeply. The purpose is to help them to become independent thinkers, teach them to reflect, and capture not just some rambling algorithms, but the actual essence of the methods, so that they can use them appropriately. Besides, I wish to teach students to think broadly, to have a comprehensive vision, and try to embrace all the sides and caveats of concepts. Ideally, they would feel connections between the parts of the course, for example, between the descriptive statistics and inferential analysis.

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Third, I aim to inspire and motivate students, develop their life philosophy and attitudes. I hope to enrich students by being honest, sharing personal experience, and being truly involved with their questions and requests.

 

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Teaching Methods

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First, my belief is that teaching advanced quantitative concepts to students with different abilities and ways of thinking requires a comprehensive set of interactions. Repetitiveness is important. I use multiple teaching tools: lecturing on background theory, solving practical problems, and having lab sessions on statistical software (SPSS, Stata, or R) that teach how to apply the learned tools to real data. I use a large number of handouts and formula sheets and a large number of online materials.  I actively incorporate technology both as a teaching platform (Blackboard, MyStatLab, LauchPad), and as a way to connect with students (emails). Furthermore, I design unique data-based statistical tutorials both as written instructions and as online videos.

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Second, I make every effort to respond to students’ needs and challenges immediately. Having an extensive tutoring and teaching experience, I have worked with both undergraduate and graduate students, as well as community college students. I have had chance to teach students of diverse ethnic and social backgrounds and of different abilities and skills. It is crucial to adjust the course schedule and the problems used  to the specific class. For example, I use different strategies for students at Queens College than I use at City College. Queens College students need more time with mathematical ideas and formulas, so I study which problems cause the most troubles and mistakes, and approach them with extra focus and attention. City College students, however, seem to tackle mathematics easily, so, in addition to the main material, I offer extra tools on demand. I encourage inquisitiveness, and I am happy to show curious students after class, for example, how to derive a probability density function for a Poisson distribution. Moreover, my classes are very interactive and take a form of constant dialog with students, so when they get puzzled over some new technique, I have a chance to react instantly.

For various students, I bring up interesting and memorable examples that relate to their lives. For example, to illustrate normal distribution I describe daily calorie consumption which is random, but is very likely to be in some middle range (say with a mean of 2,500) and very unlikely to deviate much from that range.

 

Third, I keep my courses well-organized. The lectures are clear and well-structured, numbers and letters indicate the parts and subtopics; I provide students with plans of the upcoming classes. My blackboard notes are succint and to the point. Instead of wordy definitions, I give a formula or a statement as an anchor and provide a lot of verbal background information on it. Course materials are updated on an ongoing basis. I replace old assignments and modify coursework whenever I find that they can be improved. Student feedback plays an important role in the course improvement process.

 

Fourth, I connect with my students personally and build relationships. When presenting material, I refer to my own experience, research, and personal vision. I discuss with students the social and economic issues relevant for the time. For example, I tell statistics students about the “big data” trends and show that data analysis is much wider than what is covered in the course. Some students ask questions about life and career decisions, and I do my best to support and inspire them. Constant interaction with students – before and after class, by email, and during office hours, allows me to pay due attention to their needs.

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Teaching Assessments

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First, the students’ understanding is tested with various homework assignments and exams: theoretical questions, practical problem sets, data-based software tasks, and a creative group project. Moreover, the integrity of material is important. I test the students’ vision of the full picture by giving problems which start with the raw data and have them think through all the necessary steps to get to the inferences. That requires good understanding of different parts of the course and their connections.

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Second, I reward serious attitude and thoughtful work. Rather than attendance and participation, I include in the final grade formula the actual assignments and exams. Rather than page count for the paper, I value the deep thought and the quality of the content. Rather than mechanical reproduction of the formula, I reward correct use of it even if there are computational errors. I am generous in partial credit for the key things showing that a student is thinking in the right direction. For example, I give half of the credit for correctly identifying the parameter being tested for the statistical hypothesis tests.

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Finally, students’ creativeness and curiosity is greatly appreciated. For the group project, students are asked to find data online or collect it themselves on some topic they care about and perform statistical analysis. From the wide set of tools for data analysis, they should wisely choose the most appropriate ones for their research question. Each group produces a paper discussing their work and makes an in-class presentation of their results. Usually, this is the last class of the semester, and the questions students ask and how far they go to answer them, reveal their true interests and attitudes. This final class helps me to better evaluate the students’ efforts and performance.

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