Syllabus

Published

Updated 2024-08-27

Instructor

Course details

Tuesday/Thursday
2024-08-27 to 2024-12-13
11:30 AM - 12:50 PM
Lorch 471
Slack

All administrative course questions which can be public to the class should be made on Slack channels. Questions of a personal nature can be sent via Slack DM. I will respond to messages within 1 ‘business’ day (weekdays 9-5pm). I may not respond to questions which are answered in the syllabus or on Canvas - please check these information sources before sending inquiries since unnecessary messages will delay my response to more critical questions.

General Policies

Accommodations and Access

This course is intended for all U-M students, including those with mental, physical, or cognitive disabilities, illness, injuries, impairments, or other circumstances that impact one’s equitable access to education. If, at any point in the term, you find yourself not able to fully access the space, content, and experience of this course, you are welcome (and not required) to contact us to discuss your specific needs. I also encourage you to contact the Services for Students with Disabilities (SSD) office at http://ssd.umich.edu. If you have a diagnosis, SSD can help you document your needs and create an accommodation plan. By making a plan through SSD, you can ensure appropriate accommodations without disclosing your condition or diagnosis to course instructors.

Classroom Culture of Care

LSA is committed to delivering our mission while aiming to protect the health and safety of the community, which includes minimizing the spread of COVID-19. Our entire LSA community is responsible for protecting the collective health of all members by being mindful and respectful in carrying out the guidelines laid out in our Wolverine Culture of Care and the University’s Face Covering Policy for COVID-19. Individuals seeking to request an accommodation related to the face covering requirement under the Americans with Disabilities Act should contact the Office for Institutional Equity.

In our classrooms all students are expected to adhere to the required safety measures and guidelines of the State of Michigan and the University of Michigan, wearing a face covering that covers the mouth and nose in all classrooms, and not coming to class when ill or in quarantine. It is important to also be thoughtful about group gatherings as well as about classroom activities and exercises that require collaboration.

Any student who is not able and willing to comply with campus safety measures for in-person components of this course should contact the course instructor or their academic advisor to discuss alternate participation or course options. Students who do not adhere to these safety measures while in a face-to-face class setting, and do not have an approved exception or accommodation, may be asked to disenroll from the class.

For additional information refer to the LSA Student Commitment to the Wolverine Culture of Care and the OSCR Addendum to the Statement of Student Rights and Responsibilities on the OSCR website.

Mental Health and Wellbeing

University of Michigan is committed to advancing the mental health and wellbeing of its students, while acknowledging that a variety of issues, such as strained relationships, increased anxiety, alcohol/drug problems, and depression, directly impacts students’ academic performance. If you or someone you know is feeling overwhelmed, depressed, and/or in need of support, services are available. For help, contact Counseling and Psychological Services (CAPS) at (734) 764-8312 and https://caps.umich.edu/ during and after hours, on weekends and holidays, or through its counselors physically located in schools on both North and Central Campus. You may also consult University Health Service (UHS) at (734) 764-8320 and https://www.uhs.umich.edu/mentalhealthsvcs, or for alcohol or drug concerns, see http://www.uhs.umich.edu/aodresources. For a listing of other mental health resources available on and off campus, visit: http://umich.edu/ mhealth/.

You are important - take care of yourself.

Student Sexual Misconduct Policy

Title IX prohibits sex discrimination to include sexual misconduct: harassment, domestic and dating violence, sexual assault, and stalking. If you or someone you know has been harassed or assaulted, you can receive confidential support and academic advocacy at the Sexual Assault Prevention and Awareness Center (SAPAC). SAPAC can be contacted on their 24-hour crisis line, 734-936-3333 and online at sapac.umich.edu. Alleged violations can be reported non-confidentially to the Office for Institutional Equity (OIE) at institutional.equity@umich.edu. Reports to law enforcement can be made to University of Michigan Police Department at 734-763-3434. All students should be aware of the University’s policy on student sexual misconduct:
http://studentsexualmisconductpolicy.umich.edu.

Financial and Housing Assistance

Any student who has difficulty affording groceries or accessing sufficient food to eat every day, who lacks a safe and stable place to live, or who experiences an emergency requiring financial support beyond their means, and believes this may affect their performance in this course is urged to contact Professor Levinson or Student Life (assist-me@umich.edu) for support. Other resources you might find helpful include Student Emergency Funds https://studentlife.umich.edu/article/student-emergency-funds, affordable produce on campus from Student Food Co. http://www.studentfoodco.com, free groceries from Maize & Blue Cupboard https://www.facebook.com/maizeandbluecupboard, and legal services for students, https://studentlegalservices.umich.edu.

Learning Objectives

The primary goals of this course are that at the end of the semester, students will have improved in their abilities to:

identify and visualize patterns in language-related data,
use computer programming as a tool to answer domain-specific questions,
solve data analysis challenges using the R programming language,
prepare data for analysis using spreadsheet software or R,
create a variety of visualizations, from bar charts to maps,
design data collection plans, and
share data analyses in reproducible reports as webpages or term papers.

Another broader goal for the course is that students will feel more prepared to pursue further work analyzing data for seminars, honors thesis projects, or research positions, as well as for further coursework in inferential statistics or programming.

Instructor Expectations

During the semester, I will:

Work to create an environment that supports your academic success and growth
Prepare and/or post materials in a timely manner
Facilitate and moderate class discussion and activities
Visit the course websites to answer questions at least once each weekday (M-F)
Moderate and provide feedback on conversations on Slack
Respond to messages within 1 business day
Provide assignment feedback within 2 weeks of submission (if submitted on time)
Be available at least 2 hours per week for appointments (group and individual)

Student Expectations

In this section the expectations for your participation in the course are outlined, including any policies specific to those expectations.

Web Resources

The course has a Canvas and github.io website, and you are expected to check the sites regularly for assignments, feedback,readings, etc..

Slack Community

There is never enough time in class and section to go deep into the material and troubleshoot all of the questions! This is why we also will have a Slack space dedicated to the course. Participation in the Slack is not graded directly, but I expect that you will use this space to connect with both me and your classmates. You are welcome to start threads and comment on those of others. You can ask questions, share relevant articles you’ve come across, or discuss an interaction you had outside of class.

Participation in Slack should follow standards of academic conduct and general ‘netiquette’, though your writing can be informal/colloquial. In fact, I encourage you to write naturally in a way that makes it easy to convey your ideas and lets your ‘voice’ shine through. Criticism should be constructive and well-intentioned. Be respectful of your peers. Do not violate anyone’s privacy. Please do not “spam” - I reserve the right to remove any posts that do not contribute productively to the conversation.

Engagement

Practice and continuous engagement is extremely important to learning the technical skills in this course, and in developing the relevant mindset for working with data. For this reason, engagement is worth half of your final grade. Evaluation of engagement will be done primarily by assessment of your participation in class activities and completion of preparation quizzes.

There are essentially 2 points associated with each class - 1 for in-class activities, 1 for preparation work. These will be mixed across different technology depending on the day, but will be added up and computed as a percentage for grading purposes. Each engagement point is roughly equivalent to a class percentage point.

The 8 lowest engagement scores will be dropped (which could be across 4 missed days where both preparation and in-class work are missed, or might be from a mix of different days). Note that there are 28 scheduled class days total for the semester, and some days may not have engagement points due for various reasons.

In-class Activities

The meetings for this class are synchronous (real-time) and practice-oriented, with only short portions of `lecture’ material. Since we will be doing hands-on computing work, you will need to have a computer to work on during class. If you are not able to afford a suitable laptop, the LSA Laptop Program can provide laptops to those on financial aid. Let me know of any challenges that you have with technology access so we can work out the best solution.

The main software we will be using in class is RStudio, and the R programming language. We will also use Google Sheets. These are all free to install and/or use. More information about using and setting these up will be posted to the course website and covered in class material.

During class time, we will be using iClicker Cloud as a student response system. Each day there will be a variety of questions - some of these will be graded (see below), and may be based on preparation assignments or material presented in class. Other questions will be more like ungraded surveys to gauge your comprehension or to collect your viewpoints on different topics. The latter are considered part of “in-class activities”, potentially along with other types of activities that may be relevant for a specific day.

To participate in with iClicker Cloud, you should use the computer that you are using for other in-class work, so that you can copy and paste code for short answers. It is your responsibility to set up your iClicker Cloud account and software, and to seek assistance from ITS if you have technical difficulties.

iClicker Cloud will record your “attendance”, but these records are only used for informational purposes, not grading, so you don’t need to worry about the attendance reports in iClicker, which may sometimes show an “absence” on days that no iClicker activity was held. You will be able to view your total score in Canvas, and details via the Cloud app or site. You will earn daily engagement credit (1pt) for answering at least 50% of the questions. This is intended to be a ‘low stakes’ activity. I am looking for engagement with the material, not perfect knowledge or fastest response time. Since it is expected that most students will miss some days, have days where their software isn’t working, and have topics that aren’t clear until they have spent more time with them, some scores will be dropped to accommodate for this (see above). Individual missed days cannot be excused due to these issues (there would be no feasible way for me to manage this equitably). See the sections on grade appeals, late/missed work, and group work below for other relevant policies, including cases where you have an extended illness or crisis.

All question sessions will be designed to allow enough time for all students to complete them, including those who require 1.5x or 2x time accommodations, with the principes of Universal Design for Learning (UDL) in mind. If you finish early, it is recommended that you quietly wait for class to continue to minimize distraction for other students.

Preparation Quizzes (p1, etc. and iClicker)

Preparation quizzes based on readings or other out of class practice, and will be due right before the class that it is preparation for, or at the beginning of class (as a Canvas quiz or graded iClicker questions). These are “formative” assignments, designed to help you review the material and discover any areas of confusion. Some Canvas quizzes may allow you to submit multiple times (as indicated), and keep the highest grade earned before the due date. For such quizzes, make sure not to re-submit quizzes after the deadline - this will alter your submission deadline and mark your submission late.

There is no textbook for this course; some readings will be posted in PDF format, and others are web-based books or articles.

See the sections on grade appeals, late/missed work, and group work below for other relevant policies.

Other Engagement

Participation and collaboration are strong predictors of success and learning retention, so please make an effort to find a way that works well for you to participate and engage with your colleagues as well as the course material. The following will not be directly assessed in your grade, but are other recommended engagement activities:

Ask and answer questions during class
Post questions or answer questions on Slack
Come to office hours
Share relevant links or resources on Slack, with an explanation of their relevance and commentary
Create and share course-related tutorials, literature summaries or reviews, memes, gifs, videos, comics, or other art
Participate in a study or small discussion group with your peers out of class time
Go back to Perusall/Hypothesis readings and continue conversations after the deadline and completing the initial assignment

Homework Assignments (h1, etc.)

Homework assignments will be practical computing exercises, requiring submission of code and/or outputs. The primary aim of these assignments is to give you more practice time with the concepts, and for me to assess your progress and give you feedback.

Homework itself will be graded on a complete/incomplete/missing basis, marked as 1/.5/0 in the gradebook. Missing includes assignments submitted late without an extension.

Feedback on homework will be provided per student on a rolling basis, after completion grades have been assigned. Each week a subset of students will receive feedback on any submitted work that they have not received comments on. This helps me to provide more substantive feedback and to see your progress over assignments. This feedback will be used towards your portfolio grades.

The lowest homework grade (not including projects, discussed below) will be dropped.

Homework Projects (hp1 & hp2)

Projects are larger homework assignments that are graded in the same way, but cannot be dropped. For the final (second) project, you will have some choices for the topic, to provide everyone with an opportunity to focus on areas of greatest interest. A project proposal confirming the choice of final project and implementation plan is due separately but must be submitted and approved prior to the project to receive project credit. This will help me support you in your project work.

The first project will focus on visualizing and generating a report for a pre-collected, “rectangular” dataset. The second project will incorporate more complex data gathering, either from student-generated surveys and experiments, or from non-rectangular textual data such as corpora or web scraping. For the second project students will also incorporate more advanced reporting and visualization techniques.

See the sections on grade appeals, late/missed work, and group work below for other relevant policies.

Portfolios

As you work through the course, you will be building a portfolio of your work completed in class and in assignments. I will evaluate this work collectively at the midterm point and at the end of the semester (final portfolio). Each portfolio will be associated with demonstration of a set of a skills which will be posted on Canvas at least two weeks before evaluation.

Ungraded Tools

We may use other tools to support coursework, but these will not be graded directly. Perusall and/or Hypothesis may be used as a tool to help with annotated reading, and web exercises will be used for live engagement. These are optional but very useful resources.

Evaluation

Your progress towards the objectives of the course will be evaluated based on your performance in all of the areas specified above, according to the following weights towards the final grade:

Class Engagement	50 %
Homework Completion	20 %
Portfolios	30 %

There may be a few opportunities to earn small (~1pt) amounts of extra credit available to all students during the semester. No additional extra credit will be granted on an individual, ad hoc basis.

Grading Scale:

Percentage	Letter
94-100	A
90-93	A-
87-89	B+
84-86	B
80-83	B-
77-79	C+
74-76	C
70-73	C-
67-69	D+
64-66	D
60-63	D-
0-59	F

You will receive regular feedback on your progress in the course via grades and comments on assignments. If you are concerned about your grade or your progress in the class, please contact me. Final grades will not be changed unless it can be shown that an error was made in determining the grade. See below for the grade appeal policy for individual assignments. (A determination for A+ grades may be decided based on the final course grades at my discretion.)

Course-Specific Policies

Grade Appeals and Corrections for Individual Assignments, Quizzes, and Exams

Requests for re-evaluation or correction of potential grading errors on assignments must be made directly via email within one week of receiving a grade or other feedback. This is to ensure consistency in grading and accuracy of grades throughout the semester.

Absences and Late or Missed Work

As there is no attendance grade in this course, individual absences from class do not need to be excused or explained. We all encounter circumstances that require us to miss commitments from time-to-time, and this is why flexibility is built into the grading scheme with dropped assignments and the extension bank.

If you have an extended illness or crisis which prevents you from attending class or completing work, you should contact me about it as soon as possible. If it is illness-related (this includes mental health concerns), I also recommend reporting it via this LSA form, so that all of your instructors and advisors can be notified without your having to do so individually: https://webapps.lsa.umich.edu/SAA/UGStuAdv/App/Illness/RptIll.aspx. I will work with you to make an alternative plan for your coursework, or can advise you on whether it might be best for you to re-take the class in another term. According to LSA policy https://lsa.umich.edu/lsa/academics/dates-and-deadlines/religious-holidays.html, please notify us of any conflicts due to religious observances no later than the drop/add deadline of the current term.

Extension Bank

For short-term interruptions - the weeks when you have lots of exams, when you have a cold, when your childcare falls through (temporarily) - everyone starts with a bank of 10 days of extension. These extension days can be used all for one assignment that is 10 days late, or broken up and used for shorter extensions on multiple assignments. Otherwise late submissions will not earn credit (and can be dropped if not exceeding the maximum number of drops per category). If you would like to use one of your extension days, please submit the Extension Bank Withdrawal Form (also linked on Canvas) within 1 week after the original assignment deadline so that I can adjust make sure you get credit for the assignment.

Remember to contact me if you are having an ongoing health or other concern that is impeding your progress in the class, or if you need an excused extension for the observation of a religious holiday - you do not need to use the extension bank for such cases.

Late-registration

It is the students’ responsibility to catch up on work if registering late for the course. No deadlines will be extended more than a week past the registration date. Students who join late should make up all previous quizzes and homeworks within the same one-week period after their registration. Upcoming assignments (due within 1 week after registration) may be extended to the same due date - if you need such an extension, please submit an extension bank request form but it will not be counted towards your balance. Lecture engagement points prior to registration will be excused/waived since they cannot be made up.

If you have registered late and have an accommodations letter, make sure to have it sent to me as soon as possible! Often students send them out at the beginning of the semester and don’t realize that classes they have joined later do not have access to the letters.

Electronic Submission Challenges

You are responsible for confirming that any electronically submitted assignments are properly posted or uploaded and in the proper file format. Extensions will not be granted for ‘mysteriously missing’ submissions, corrupted files, or other improperly formatted submissions, and these will be marked as 0 unless corrected and extended via the extension bank.

What should you do if you have technical difficulties? (click for details)

If an assignment or test is due electronically and you have technical difficulties submitting an assignment via Canvas, notify us as soon as possible of the issue.

If you have an internet connection but Canvas is not responding or working properly, you must contact Canvas support both to receive help and to document the issue. You can contact the Canvas support team at 734-764-4357 (or via the support links in Canvas, if you are able to access it). As a last resort option, if Canvas itself is not functioning and you are not able to successfully submit an assignment with the help of Canvas support staff, you may DM the assignment to me, in PDF format, and explain your difficulties with Canvas.

If you need technical assistance with Canvas or Slack, you may also consult with LSA IT BlueCorps https://lsa.umich.edu/technology-services/services/bluecorps.html.

Group Work

Students are encouraged to work in groups outside of class to discuss material from the course and work on assignments. However, all assignments must be written up / completed individually unless otherwise specified. Code should not be shared with other students. For example, if you are discussing a challenge, you might suggest a relevant function or function argument to use, but should not share a typed up solution. You could also point each other to existing examples in course materials or elsewhere that provide solutions to a similar problem. This will help everyone build the skills to write their own code, even when that means adapting general solutions from StackOverflow (very common in programming!).

Academic Integrity and Academic Misconduct

All students are expected to be aware of the College of LSA’s standards of academic integrity posted at https://lsa.umich.edu/lsa/academics/academic-integrity.html and
https://www.lib.umich.edu/academic-integrity.

Cheating and plagiarism will not be tolerated. The following is a non-exhaustive list of examples of unacceptable conduct for this course:

Copying code or other text from the internet without attribution or using an automated code/text generator.
Sharing code with another student.
Copying homework from another student, with or without the student’s knowledge.
Copying answers from the quiz from another student, with or without the student’s knowledge.
Having a person complete any course-related work who is not the one whose name or account is associated with that work.
Using material from any source (slides, books, articles, internet sites) for submission in written assignments or exams without proper citation.

Cases of academic misconduct may result in failure of the course for all students involved and will be reported to Student Academic Affairs/Office of the Assistant Dean.

Schedule and Topics

The schedule for assignment due dates will be posted on Canvas. The topics of the course and their order are somewhat flexible and adaptable to student background and interest. The topics that are planned include the following, but some will be pursued through individual projects and not required for all students:

file systems and working with files
working with data in spreadsheets (basic skills)
tidy data principles
basic programming and computing foundations
R programming and the tidyverse (used for all following)
data import and cleaning (system files and web)
data wrangling and reshaping
data visualization with ggplot2 and extensions
data ethics and bias
creating analysis reports and papers for the web and “print”
Quarto and R Markdown
study design for gathering data (surveys and experiments)
web scraping
working with corpus data and text analysis
basic word frequency and n-gram analysis
analyzing phonetic data
maps for typology and geographical demos

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Questions of a personal nature can be sent via Slack DM. I will respond to messages within 1 'business' day (weekdays 9-5pm). I may not respond to questions which are answered in the syllabus or on Canvas - please check these information sources before sending inquiries since unnecessary messages will delay my response to more critical questions. # General Policies ## Accommodations and Access This course is intended for all U-M students, including those with mental, physical, or cognitive disabilities, illness, injuries, impairments, or other circumstances that impact one's equitable access to education. If, at any point in the term, you find yourself not able to fully access the space, content, and experience of this course, you are welcome (and not required) to contact us to discuss your specific needs. I also encourage you to contact the Services for Students with Disabilities (SSD) office at <http://ssd.umich.edu>. If you have a diagnosis, SSD can help you document your needs and create an accommodation plan. By making a plan through SSD, you can ensure appropriate accommodations without disclosing your condition or diagnosis to course instructors. ## Classroom Culture of Care LSA is committed to delivering our mission while aiming to protect the health and safety of the community, which includes minimizing the spread of COVID-19. Our entire LSA community is responsible for protecting the collective health of all members by being mindful and respectful in carrying out the guidelines laid out in our [Wolverine Culture of Care](https://campusblueprint.umich.edu/care/#wolverine-culture-of-care) and the [University's Face Covering Policy for COVID-19](http://ehs.umich.edu/wp-content/uploads/2020/07/U-M-Face-Covering-Policy-for-COVID-19.pdf). Individuals seeking to request an accommodation related to the face covering requirement under the Americans with Disabilities Act should contact the [Office for Institutional Equity](https://oie.umich.edu/american-with-disabilities-act-ada/). In our classrooms all students are expected to adhere to the required safety measures and guidelines of the State of Michigan and the University of Michigan, wearing a face covering that covers the mouth and nose in all classrooms, and not coming to class when ill or in quarantine. It is important to also be thoughtful about group gatherings as well as about classroom activities and exercises that require collaboration. Any student who is not able and willing to comply with campus safety measures for in-person components of this course should contact the course instructor or their academic advisor to discuss alternate participation or course options. Students who do not adhere to these safety measures while in a face-to-face class setting, and do not have an approved exception or accommodation, may be asked to disenroll from the class. For additional information refer to the [LSA Student Commitment to the Wolverine Culture of Care](https://lsa.umich.edu/lsa/academics/lsa-academic-policies/lsa-student-commitment-to-the-wolverine-culture-of-care.html) and the OSCR Addendum to the Statement of Student Rights and Responsibilities on the [OSCR website](https://oscr.umich.edu/). ## Mental Health and Wellbeing University of Michigan is committed to advancing the mental health and wellbeing of its students, while acknowledging that a variety of issues, such as strained relationships, increased anxiety, alcohol/drug problems, and depression, directly impacts students' academic performance. If you or someone you know is feeling overwhelmed, depressed, and/or in need of support, services are available. For help, contact Counseling and Psychological Services (CAPS) at (734) 764-8312 and <https://caps.umich.edu/> during and after hours, on weekends and holidays, or through its counselors physically located in schools on both North and Central Campus. You may also consult University Health Service (UHS) at (734) 764-8320 and <https://www.uhs.umich.edu/mentalhealthsvcs>, or for alcohol or drug concerns, see <http://www.uhs.umich.edu/aodresources>. For a listing of other mental health resources available on and off campus, visit: [http://umich.edu/ mhealth/](http://umich.edu/~mhealth/). **You are important - take care of yourself.** ## Student Sexual Misconduct Policy Title IX prohibits sex discrimination to include sexual misconduct: harassment, domestic and dating violence, sexual assault, and stalking. If you or someone you know has been harassed or assaulted, you can receive confidential support and academic advocacy at the Sexual Assault Prevention and Awareness Center (SAPAC). SAPAC can be contacted on their 24-hour crisis line, 734-936-3333 and online at sapac.umich.edu. Alleged violations can be reported non-confidentially to the Office for Institutional Equity (OIE) at <institutional.equity@umich.edu>. Reports to law enforcement can be made to University of Michigan Police Department at 734-763-3434. All students should be aware of the University's policy on student sexual misconduct:\ <http://studentsexualmisconductpolicy.umich.edu>. ## Financial and Housing Assistance Any student who has difficulty affording groceries or accessing sufficient food to eat every day, who lacks a safe and stable place to live, or who experiences an emergency requiring financial support beyond their means, and believes this may affect their performance in this course is urged to contact Professor Levinson or Student Life (<assist-me@umich.edu>) for support. Other resources you might find helpful include Student Emergency Funds <https://studentlife.umich.edu/article/student-emergency-funds>, affordable produce on campus from Student Food Co. <http://www.studentfoodco.com>, free groceries from Maize & Blue Cupboard <https://www.facebook.com/maizeandbluecupboard>, and legal services for students, <https://studentlegalservices.umich.edu>. # Learning Objectives The primary goals of this course are that at the end of the semester, students will have improved in their abilities to: - identify and visualize patterns in language-related data, - use computer programming as a tool to answer domain-specific questions, - solve data analysis challenges using the R programming language, - prepare data for analysis using spreadsheet software or R, - create a variety of visualizations, from bar charts to maps, - design data collection plans, and - share data analyses in reproducible reports as webpages or term papers. Another broader goal for the course is that students will feel more prepared to pursue further work analyzing data for seminars, honors thesis projects, or research positions, as well as for further coursework in inferential statistics or programming. # Instructor Expectations During the semester, I will: - Work to create an environment that supports your academic success and growth - Prepare and/or post materials in a timely manner - Facilitate and moderate class discussion and activities - Visit the course websites to answer questions at least once each weekday (M-F) - Moderate and provide feedback on conversations on Slack - Respond to messages within 1 business day - Provide assignment feedback within 2 weeks of submission (if submitted on time) - Be available at least 2 hours per week for appointments (group and individual) # Student Expectations In this section the expectations for your participation in the course are outlined, including any policies specific to those expectations. ## Web Resources The course has a Canvas and github.io website, and you are expected to check the sites regularly for assignments, feedback,readings, etc.. ## Slack Community There is never enough time in class and section to go deep into the material and troubleshoot all of the questions! This is why we also will have a Slack space dedicated to the course. Participation in the Slack is not graded directly, but I expect that you will use this space to connect with both me and your classmates. You are welcome to start threads and comment on those of others. You can ask questions, share relevant articles you've come across, or discuss an interaction you had outside of class. Participation in Slack should follow standards of academic conduct and general 'netiquette', though your writing can be informal/colloquial. In fact, I encourage you to write naturally in a way that makes it easy to convey your ideas and lets your 'voice' shine through. Criticism should be constructive and well-intentioned. Be respectful of your peers. Do not violate anyone's privacy. Please do not "spam" - I reserve the right to remove any posts that do not contribute productively to the conversation. ## Engagement Practice and continuous engagement is extremely important to learning the technical skills in this course, and in developing the relevant mindset for working with data. For this reason, engagement is worth half of your final grade. Evaluation of engagement will be done primarily by assessment of your participation in class activities and completion of preparation quizzes. There are essentially 2 points associated with each class - 1 for in-class activities, 1 for preparation work. These will be mixed across different technology depending on the day, but will be added up and computed as a percentage for grading purposes. Each engagement point is roughly equivalent to a class percentage point. The 8 lowest engagement scores will be dropped (which could be across 4 missed days where both preparation and in-class work are missed, or might be from a mix of different days). Note that there are 28 scheduled class days total for the semester, and some days may not have engagement points due for various reasons. ### In-class Activities The meetings for this class are synchronous (real-time) and practice-oriented, with only short portions of `lecture' material. Since we will be doing hands-on computing work, you will need to have a computer to work on during class. If you are not able to afford a suitable laptop, the LSA Laptop Program can provide laptops to those on financial aid. Let me know of any challenges that you have with technology access so we can work out the best solution. The main software we will be using in class is **RStudio**, and the **R** programming language. We will also use Google Sheets. These are all free to install and/or use. More information about using and setting these up will be posted to the course website and covered in class material. During class time, we will be using iClicker Cloud as a student response system. Each day there will be a variety of questions - some of these will be graded (see below), and may be based on preparation assignments or material presented in class. Other questions will be more like ungraded surveys to gauge your comprehension or to collect your viewpoints on different topics. The latter are considered part of "in-class activities", potentially along with other types of activities that may be relevant for a specific day. To participate in with iClicker Cloud, you should use the computer that you are using for other in-class work, so that you can copy and paste code for short answers. It is your responsibility to set up your iClicker Cloud account and software, and to seek assistance from ITS if you have technical difficulties. iClicker Cloud will record your "attendance", but these records are only used for informational purposes, not grading, so you don't need to worry about the attendance reports in iClicker, which may sometimes show an "absence" on days that no iClicker activity was held. You will be able to view your total score in Canvas, and details via the Cloud app or site. You will earn daily engagement credit (1pt) for answering at least 50% of the questions. This is intended to be a ‘low stakes’ activity. I am looking for engagement with the material, not perfect knowledge or fastest response time. Since it is expected that most students will miss some days, have days where their software isn’t working, and have topics that aren’t clear until they have spent more time with them, some scores will be dropped to accommodate for this (see above). Individual missed days cannot be excused due to these issues (there would be no feasible way for me to manage this equitably). See the sections on grade appeals, late/missed work, and group work below for other relevant policies, including cases where you have an extended illness or crisis. All question sessions will be designed to allow enough time for all students to complete them, including those who require 1.5x or 2x time accommodations, with the principes of Universal Design for Learning (UDL) in mind. If you finish early, it is recommended that you quietly wait for class to continue to minimize distraction for other students. ### Preparation Quizzes (p1, etc. and iClicker) Preparation quizzes based on readings or other out of class practice, and will be due right before the class that it is preparation for, or at the beginning of class (as a Canvas quiz or graded iClicker questions). These are "formative" assignments, designed to help you review the material and discover any areas of confusion. Some Canvas quizzes may allow you to submit multiple times (as indicated), and keep the highest grade earned before the due date. For such quizzes, make sure **not to re-submit quizzes after the deadline - this will alter your submission deadline and mark your submission late.** There is no textbook for this course; some readings will be posted in PDF format, and others are web-based books or articles. See the sections on grade appeals, late/missed work, and group work below for other relevant policies. ### Other Engagement Participation and collaboration are strong predictors of success and learning retention, so please make an effort to find a way that works well for you to participate and engage with your colleagues as well as the course material. The following will not be directly assessed in your grade, but are other recommended engagement activities: - Ask and answer questions during class - Post questions or answer questions on Slack - Come to office hours - Share relevant links or resources on Slack, with an explanation of their relevance and commentary - Create and share course-related tutorials, literature summaries or reviews, memes, gifs, videos, comics, or other art - Participate in a study or small discussion group with your peers out of class time - Go back to Perusall/Hypothesis readings and continue conversations after the deadline and completing the initial assignment ## Homework Assignments (h1, etc.) Homework assignments will be practical computing exercises, requiring submission of code and/or outputs. The primary aim of these assignments is to give you more practice time with the concepts, and for me to assess your progress and give you feedback. Homework itself will be graded on a complete/incomplete/missing basis, marked as 1/.5/0 in the gradebook. Missing includes assignments submitted late without an extension. Feedback on homework will be provided per student on a rolling basis, after completion grades have been assigned. Each week a subset of students will receive feedback on any submitted work that they have not received comments on. This helps me to provide more substantive feedback and to see your progress over assignments. This feedback will be used towards your portfolio grades. The lowest homework grade (not including projects, discussed below) will be dropped. ### Homework Projects (hp1 & hp2) Projects are larger homework assignments that are graded in the same way, but cannot be dropped. For the final (second) project, you will have some choices for the topic, to provide everyone with an opportunity to focus on areas of greatest interest. A project proposal confirming the choice of final project and implementation plan is due separately but must be submitted and approved prior to the project to receive project credit. This will help me support you in your project work. The first project will focus on visualizing and generating a report for a pre-collected, "rectangular" dataset. The second project will incorporate more complex data gathering, either from student-generated surveys and experiments, or from non-rectangular textual data such as corpora or web scraping. For the second project students will also incorporate more advanced reporting and visualization techniques. See the sections on grade appeals, late/missed work, and group work below for other relevant policies. ## Portfolios As you work through the course, you will be building a portfolio of your work completed in class and in assignments. I will evaluate this work collectively at the midterm point and at the end of the semester (final portfolio). Each portfolio will be associated with demonstration of a set of a skills which will be posted on Canvas at least two weeks before evaluation. ## Ungraded Tools We may use other tools to support coursework, but these will not be graded directly. **Perusall** and/or **Hypothesis** may be used as a tool to help with annotated reading, and web exercises will be used for live engagement. These are optional but very useful resources. # Evaluation Your progress towards the objectives of the course will be evaluated based on your performance in all of the areas specified above, according to the following weights towards the final grade: --------------------------------- ------ Class Engagement 50 % Homework Completion 20 % Portfolios 30 % --------------------------------- ------ There may be a few opportunities to earn small (~1pt) amounts of extra credit available to all students during the semester. **No additional extra credit will be granted on an individual, ad hoc basis**. Grading Scale: Percentage Letter ------------ -------- 94-100 A 90-93 A- 87-89 B+ 84-86 B 80-83 B- 77-79 C+ 74-76 C 70-73 C- 67-69 D+ 64-66 D 60-63 D- 0-59 F You will receive regular feedback on your progress in the course via grades and comments on assignments. If you are concerned about your grade or your progress in the class, **please contact me**. Final grades will not be changed unless it can be shown that an error was made in determining the grade. See below for the grade appeal policy for individual assignments. (A determination for A+ grades may be decided based on the final course grades at my discretion.) # Course-Specific Policies ## Grade Appeals and Corrections for Individual Assignments, Quizzes, and Exams Requests for re-evaluation or correction of potential grading errors on assignments must be made directly via email **within one week of receiving a grade or other feedback**. This is to ensure consistency in grading and accuracy of grades throughout the semester. ## Absences and Late or Missed Work As there is no attendance grade in this course, individual absences from class do not need to be excused or explained. We all encounter circumstances that require us to miss commitments from time-to-time, and this is why flexibility is built into the grading scheme with dropped assignments and the extension bank. If you have an extended illness or crisis which prevents you from attending class or completing work, you should contact me about it as soon as possible. If it is illness-related (this includes mental health concerns), I also recommend reporting it via this LSA form, so that all of your instructors and advisors can be notified without your having to do so individually: <https://webapps.lsa.umich.edu/SAA/UGStuAdv/App/Illness/RptIll.aspx>. I will work with you to make an alternative plan for your coursework, or can advise you on whether it might be best for you to re-take the class in another term. According to LSA policy <https://lsa.umich.edu/lsa/academics/dates-and-deadlines/religious-holidays.html>, please notify us of any conflicts due to **religious observances** no later than the drop/add deadline of the current term. ## Extension Bank For short-term interruptions - the weeks when you have lots of exams, when you have a cold, when your childcare falls through (temporarily) - everyone starts with a **bank of 10 days of extension**. These extension days can be used all for one assignment that is 10 days late, or broken up and used for shorter extensions on multiple assignments. Otherwise late submissions will not earn credit (and can be dropped if not exceeding the maximum number of drops per category). If you would like to use one of your extension days, please submit the [Extension Bank Withdrawal Form]({{< var linkvars.extensionbank >}}) (also linked on Canvas) **within 1 week after the original assignment deadline** so that I can adjust make sure you get credit for the assignment. Remember to contact me if you are having an ongoing health or other concern that is impeding your progress in the class, or if you need an excused extension for the observation of a religious holiday - you do not need to use the extension bank for such cases. ## Late-registration It is the students’ responsibility to catch up on work if registering late for the course. No deadlines will be extended more than a week past the registration date. Students who join late should make up all previous quizzes and homeworks within the same one-week period after their registration. Upcoming assignments (due within 1 week after registration) may be extended to the same due date - if you need such an extension, please submit an extension bank request form but it will not be counted towards your balance. Lecture engagement points prior to registration will be excused/waived since they cannot be made up. If you have registered late and have an **accommodations letter**, make sure to have it sent to me as soon as possible! Often students send them out at the beginning of the semester and don’t realize that classes they have joined later do not have access to the letters. ## Electronic Submission Challenges **You are responsible for confirming that any electronically submitted assignments are properly posted or uploaded and in the proper file format**. Extensions will not be granted for 'mysteriously missing' submissions, corrupted files, or other improperly formatted submissions, and these will be marked as 0 unless corrected and extended via the extension bank. <details> <summary style="background-color: lemonchiffon; cursor: pointer;">What should you do if you have technical difficulties? <small>(click for details)</small></summary> If an assignment or test is due electronically and you have technical difficulties submitting an assignment via Canvas, notify us as soon as possible of the issue. If you have an internet connection but Canvas is not responding or working properly, you must contact Canvas support both to receive help and to document the issue. You can contact the Canvas support team at 734-764-4357 (or via the support links in Canvas, if you are able to access it). As a **last resort option**, if Canvas itself is not functioning and you are not able to successfully submit an assignment with the help of Canvas support staff, you may DM the assignment to me, in PDF format, and explain your difficulties with Canvas. If you need technical assistance with Canvas or Slack, you may also consult with LSA IT BlueCorps <https://lsa.umich.edu/technology-services/services/bluecorps.html>. </details> ## Group Work Students are encouraged to work in groups outside of class to discuss material from the course and work on assignments. However, all assignments **must be written up / completed individually** unless otherwise specified. Code should not be shared with other students. For example, if you are discussing a challenge, you might suggest a relevant function or function argument to use, but should not share a typed up solution. You could also point each other to existing examples in course materials or elsewhere that provide solutions to a similar problem. This will help everyone build the skills to write their own code, even when that means adapting general solutions from StackOverflow (very common in programming!). ## Academic Integrity and Academic Misconduct All students are expected to be aware of the College of LSA's standards of academic integrity posted at <https://lsa.umich.edu/lsa/academics/academic-integrity.html> and\ <https://www.lib.umich.edu/academic-integrity>. Cheating and plagiarism will not be tolerated. The following is a non-exhaustive list of examples of unacceptable conduct for this course: - Copying code or other text from the internet without attribution or using an automated code/text generator. - Sharing code with another student. - Copying homework from another student, with or without the student's knowledge. - Copying answers from the quiz from another student, with or without the student's knowledge. - Having a person complete any course-related work who is not the one whose name or account is associated with that work. - Using material from any source (slides, books, articles, internet sites) for submission in written assignments or exams without proper citation. Cases of academic misconduct may result in **failure of the course** for all students involved and will be reported to Student Academic Affairs/Office of the Assistant Dean. # Schedule and Topics The schedule for assignment due dates will be posted on Canvas. The topics of the course and their order are somewhat flexible and adaptable to student background and interest. The topics that are planned include the following, but some will be pursued through individual projects and not required for all students: - file systems and working with files - working with data in spreadsheets (basic skills) - tidy data principles - basic programming and computing foundations - R programming and the tidyverse (used for all following) - data import and cleaning (system files and web) - data wrangling and reshaping - data visualization with ggplot2 and extensions - data ethics and bias - creating analysis reports and papers for the web and "print" - Quarto and R Markdown - study design for gathering data (surveys and experiments) - web scraping - working with corpus data and text analysis - basic word frequency and n-gram analysis - analyzing phonetic data - maps for typology and geographical demos