GEOG 586
Geographic Information Analysis

GEOG 586 Syllabus

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GEOG 586: Geographic Information Analysis

This syllabus is divided into several sections. You can read it sequentially by scrolling down the length of the document or by clicking on any of the links below to "jump" to a specific section. It is essential that you read the entire document as well as material covered in the Course Orientation. Together these serve as our course "contract."


Instructor

Fritz Kessler

Dutton e-Education Institute and the Department of Geography
The Pennsylvania State University
Earth and Engineering Sciences Building
University Park, PA 16802 USA

E-MAIL: Please use the course e-mail system in Canvas. If the matter is urgent, and the course e-mail is not working correctly, you can try my personal e-mail at fck2@psu.edu


Course Overview

GEOG 586: GEOGRAPHIC INFORMATION ANALYSIS. Choosing and applying analytical methods for geospatial data, including point pattern analysis, interpolation, surface analysis, overlay analysis, and spatial autocorrelation.

Prerequisite: GEOG 485 or GEOG 486 or GEOG 487

Geography 586 is a required course in the Penn State Professional Masters in Geographic Information Systems. This section is being offered to students around the globe through Penn State's World Campus. It is a "paced" course, which means that there is an established start and end date and that you will interact with other students throughout the course. The course is 10 weeks in length (plus a required "Orientation Week"), at a rate of 1 lesson per week. The course is organized around six short weekly projects (due in weeks 1, 3, 4, 5, 6 and 8) and a more substantial project pursued through all ten weeks of the course. Weekly projects include associated readings, quizzes, and discussions about the analysis of spatial data.

This is a course in analytical methods for handling specifically spatial data, that is, data where the arrangement of observations in space is thought to be of significance. The techniques introduced are often mathematically complex, but while these aspects are covered in the course, the emphasis is on the choice and application of appropriate methods for the analysis of the spatial data often encountered in applied geography. Weekly projects are hands-on, using geographic information systems or other appropriate computational tools, so that students appreciate the practical complexities involved, and the relative limitations of these methods in contemporary desktop GIS.

Through the weekly projects, students acquire familiarity with use of a single method or family of methods in standard desktop tools, so that they can focus on aspects of that method and develop a thorough understanding of its potential and of its limitations. Problem scenarios range across demographic, planning, crime analysis, landscape analysis, and other application areas. The term-long project is intended to allow students to formulate a research problem in a topic area of their own choosing, to gather and organize appropriate available datasets, and to understand how a variety of methods among those covered in the course can be applied in combination to thoroughly explore real questions. Students will be asked to engage with their peers' work during the project planning stage. They will also be encouraged to consider developing customized tools to automate repetitive analysis tasks, if they have previous programming experience.

Like other courses in the program, this is a 10 week course. Throughout this course, there is a strong emphasis on the theory behind the methods you will be applying to help you understand which methods are appropriate and when. This is particularly important when deciding on the method to use since this may actually determine which GIS package you will use to tackle a given problem (because not all methods are supported by all GIS programs).

Almost all the theory you need for the course is covered in the course text, Geographic Information Analysis, supported by supplementary notes and commentary in the weekly lessons. It's worth noting that this book covers considerably more material than we could ever get through in the 10 weeks of this course—so don't be too alarmed at its 400+ pages! Each week, you will be given clear instructions about exactly what you need to read, including guidance on which aspects it is particularly important that you understand.

The general format each week is:

  1. First, I will provide you with an overview of the lesson, which typically includes an introduction, lesson learning objectives, textbook reading assignments, and an outline of the deliverables for the lesson (i.e., things you need to submit by the end of that week).
  2. Next, I will provide some commentary for the lesson, which you should read once you have completed the textbook reading assignments for the lesson. Think of the commentary as the "lecture notes" for the lesson. There, I will expand on the information covered in the readings, try to clarify any information you might find troublesome, and will link to additional information. You may find that it helps to read these notes before tackling the textbook reading—so that you have an idea of what to focus on.
  3. Once you have read the textbook assignments and the commentary, you will complete a self-test quiz (some weeks there are two) designed to help you assess your comprehension of the material. You have an unlimited number of attempts on each quiz and must score 90% or more.
  4. Finally, I will wrap up each lesson with "Final Activities"—specific instructions for the lesson activities and/or how to submit the lesson deliverables.

In addition to these activities, a term-long project is required of you to complete the course. This is a more substantial piece of work, where you are expected to apply ideas and methods learned in the course. By prior agreement with me, ideas and methods not explicitly covered in the course, but which fall under the description 'spatial analysis,' may also be used. Each week, there are deadlines in the term-long project to keep you on track, so that you work consistently on the project throughout the term rather than leaving it all to the last minute. More details of the term-long project are provided on the Project Overview page.

Using the Lessons link in the menu bar above, you can navigate to any lesson in the course. From there, you can also access each page within the lesson. Each is clearly titled.

Given this overall structure, I would strongly advise that you do the reading and quiz part of the course work early each week. Since course weeks run from Wednesday to the following Tuesday, you should therefore aim to complete the reading and quiz (or quizzes) by Friday or Saturday each week. This leaves plenty of time to tackle the weekly project so that you can submit it by the Tuesday night deadline. 

This course requires a minimum of 8-12 hours of student activity each week, depending on the speed at which you work. Included in the 8-12 hours each week is time to complete projects and related activities. Some weeks, you may spend less time than that, so keep this in mind in the tougher weeks (when you'll be making up the difference!). You'll be glad to know that you don't have to show up for class at a certain time! All you need to do is complete each project and a quiz before the published deadline at the end of the course week.

You will need to check out the course discussion forums regularly. That's where students and the instructor share comments, pose questions, and suggest answers. I strongly encourage you to get in the habit of logging in to the course website every day to check in on the class. With only occasional exceptions, I check discussion forums six (and usually seven) days a week. You can be sure that I will read, but not necessarily respond to, every single message. If I anticipate not logging in for more than a day, I will let you know and also clearly state when you can next expect to hear from me.

My colleagues and I have worked hard to make this the most effective and convenient educational experience possible. How much and how well you learn is ultimately up to you. You will succeed if you are diligent about keeping up with the class schedule and if you take advantage of opportunities to communicate with me, as well as with your fellow students.

Finally, I would reiterate the importance of contributing to discussions on the course Discussion Forums. In an online course, this is particularly important to give everyone a sense of involvement with the course. It is also worth 5% of the final credit!

... And what you can expect from me (the course instructor)

I have to be organized in much the same way that you are in order to teach the course!

I aim to answer any specific queries about the readings and commentary within 24 hours, unless otherwise indicated in course announcements, particularly relating to times when I am travelling during the term (which I do).

My answers may not always be direct - if it seems to me that you are relying too heavily on answers from me and others rather than on careful reading and your own efforts. I also won't answer questions that are rephrasings of the quiz questions!  However, feel free to post questions about the quiz questions on the forums to see what others are thinking and initiate discussions.

I also hope that you will all chip in with responses to the puzzlement of your colleagues. Any such contributions will be noted when it comes to final grading. Of course, I will add to any comments from students, especially when they are inaccurate (i.e., wrong!) or incomplete.

Whenever possible, I will respond more quickly to problems with the projects, as I know how frustrating it can be if things seem not to be working. Again, please feel free to help one another out here. While I will treat questions about the projects as urgent, practical considerations mean that I can't commit to a more rapid response time than 24 hours. Note that this means it is imperative that you be well underway with the project work each week by Sunday, so that any problems can be resolved in good time for you to continue working and still submit on Tuesday night.


Required Course Materials

The course materials consist of a textbook; Esri ArcGIS with Spatial Analyst, and Geostatistical Analyst extensions; R a free statistical analysis package available online; GeoDa a free exploratory spatial data analysis software available from the GeoDa Center for geospatial analysis and computation at Arizona State University; and a required course website that contains the online lessons and communications tools, such as message boards and an e-mail system.

In order to take this course, you need to have the required course materials listed below.  All (other) materials needed for this course are presented online through our course website and in Canvas. In order to access the online materials, you need to have an active Penn State Access Account user ID and password (used to access the on-line course resources). If you have any questions about obtaining or activating your Penn State Access Account, please contact the Outreach Helpdesk. They can be reached at 1-800-252-3592 in the US or internationally at 814-865-5403 (country code 1). You may reach them by e-mail at psuwd@psu.edu (link sends e-mail).

You will need to purchase course materials from MBS Direct (the bookstore used by Penn State's World Campus) or another bookstore, such as Amazon. For MBS pricing and ordering information, please see MBS Direct. MBS Direct can also be contacted at 1-800-325-3252. Materials will be available at MBS Direct approximately three weeks before the course begins. Be sure to order early enough to allow for shipping and installation prior to the course start date

The required material you need to purchase is:

O'Sullivan, D. and Unwin, D. J., 2010, Geographic Information Analysis, 2nd edition (Wiley, Hoboken, NJ).

Or, perhaps a copy of the e-book from the Penn State Library. You can find the book through LionSearch by typing in the title.

Additional recommended texts:

Field, A., Miles, J. and Field, Z. (2012) Discovering Statistics using R Statistics, First Edition, SAGE Publications Ltd. California, CA.

Burt, J. E., Barber, G. M., & Rigby, D. L. (2009). Elementary statistics for geographers. 3rd Ed. New York: Guilford Press.

Software

You will also need to have access to the following software:

  • R, the free statistical analysis software package;
  • GeoDa, free exploratory spatial data analysis software available from Arizona State University GeoDA Center for Geospatial Analysis and Computation
  • Esri's ArcGIS that includes the Geostatistical Analyst and Spatial Analyst extension

IMPORTANT: In addition to these free materials, you will be using Esri's ArcGIS and Geostatistical Analyst software including the Spatial Analyst extension in this course. The best option for this if you do not have access to a copy is to obtain a free one-year student licensed copy, which you are entitled to do as a student in the class.

The best way to request access to the software is through our order form

Through the order form, we ask you to confirm that the e-mail address(es) we have on file are current accounts that you check frequently before submitting your order.  This helps us make sure that we have your current contact information. In the future, please use this form.

As a registered student in GEOG 586, you will also be able to use this software through the University system that delivers Arc/Info to students. It's called Web Apps. Specific instructions and points of contact for using this solution will be provided. NOTE: The best way to request access to the software is through our order form at https://courseware.e-education.psu.edu/mgisdb/software.php (link is external). Thru the order form we ask you to confirm that the email address(es) we have on file are current accounts that you check frequently before submitting your order.  This helps us make sure that we have your current contact information. However, most students find it more convenient to work with a personal copy of the software, so this is the preferred option if you can organize it. Here is additional information on the download and install process here:/geog586/sites/www.e-education.psu.edu.geog586/files/downloads/ArcGIS104_DownloadInstallInstructions-May2016.pdf. For further questions please contact the instructor.

NOTE: ArcGIS is a commercial software package that is restricted to personal use by the student. It is unlawful for anyone to use this software package without the appropriate commercial license from Esri Inc. to generate personal or corporate profit or revenue.


Assignments and Grading

Your course grade will be based on four components:

  • Weekly Quizzes - 20% of course grade. This means that each quiz is worth about 2% of the final course credit. Note that the primary purpose of the quizzes is to encourage you to do the reading, rather than to test your knowledge - you get as many goes as you need to score 100% on the quizzes, so this is intended for you to use as a way of reviewing the reading, not as a 'test'. Weekly quizzes will attract full points provided they are completed by the stated deadline and you were able to score 90% or more for each one. Any quiz that you fail to complete by scoring 90% or more by the stated deadline will count for 0, with each quiz treated as equal value. Deadlines will be rigidly applied: Canvas will not allow you to submit results after the deadline.
  • 6 Weekly Project activities - 45% of grade (7.5% each):
    • Week 1: Spatial data conversion using census data to construct population surfaces.
    • Week 3: An exercise using R to improve your understanding of the concept of a spatial process.
    • Week 4: Using R to perform the point pattern analysis methods discussed in this week's lesson. You will analyze some 1980s St Louis crime data, to demonstrate some of the point pattern analysis methods that have been discussed in this week's lesson.
    • Week 5: The aim of this week's project is to give you practical experience with interpolation methods, so that you develop a feel for the characteristics of the surfaces produced by different methods.
    • Week 6: In this project, we will use surface analysis based to determine potential sites for a new school in the Centre County region of Pennsylvania (around Penn State). This will show how complex analysis tasks can be performed by combining results from a series of relatively simple analysis steps.
    • Week 8: An exercise applying spatial autocorrelation measures to assessing ethnic segregation in Auckland, New Zealand.
  • Weekly projects must be submitted by the stated deadline. As a general guide, you can expect the following letter grades to apply:
    • F / D for non-completion.
    • C / C+ / B- for submission of unsatisfactory work that fails to answer all questions or supply all the requested items. Exactly where you fall on this scale will depend on how bad the submission is!
    • B for work that answers all questions asked and includes all requested items, and shows some insight into the lesson materials.
    • B+ points for work that covers all requested items, and shows a firm grasp of all the material.
    • A- for work at least as good as the previous category, but where answers show evidence of thinking carefully through issues and problems related to the material.
    • A for exceptional work that in places goes beyond what is asked. This could include gathering outside data or reference sources, or providing truly outstanding analysis and graphics.

When submitting each project, you should use the drop box supplied in that week's lesson materials. You may submit in either PDF or Word doc formats.

  • 1 Term Project - 30% of grade: Throughout this course, a major ongoing activity is a personal GIS project that you will develop and research on your own (with lots of input from everyone else taking the course!). This is a more substantial piece of work than the weekly projects, where you are expected to apply concepts learned in the course. By prior agreement with me, ideas and methods not explicitly covered in the course, but which fall under the description 'spatial analysis'  may also be used. Many students enrolled in the MGIS program find this project to be a great opportunity to explore an idea for their capstone project. You should expect to work on different activities in the term-long project each week. This is designed to keep you on track, so that you work consistently on the project throughout the term rather than leaving it all to the last minute. Waiting until the last minute is never a good practice in spatial statistics. 

The 30% credit available will be divided as follows:

  • 2 point for posting topic ideas (week 2)
  • 4 points for on-time submission of satisfactory brief project proposal (week 3)
  • 3 points for feedback for project proposal (week 5)
  • 6 points final project proposal (week 6)
  • 2 points for on-time submission of final project (week 9)
  • 10 points for quality of the project content and report (week 10)
  • 3 points for your involvement in discussions of the final project (week 10)

Items in the term-long project will have drop-boxes and deadlines will be rigidly enforced by the Canvas course management system.

  • Participation - 5% of course grade: Class participation is expected throughout the course on discussion forums and in feedback to other students. 

While posting questions is considered participation, you should also try to help others out with their questions. Consistently constructive input will be the most valued and beneficial.

  • Late Submission - Each late submission is subject to a late penalty.

Letter grades will be based on the following percentages:

Letter Grades
A 90-100%
A- 87.5-89.9%
B+ 85-87.4%
B 80-84.9%
B- 77.5-79.9%
C+ 75-77.4%
C 70-74.9%
D 60-69.9%
F <60%
X Unsatisfactory (student did not participate)

Percentages refer to the proportion of all possible points earned by the student.

Final overall grades may be determined based on relative performance of all students, and not on a fixed points basis, especially if overall percentages are too high or too low.


GEOG 586 Course Schedule

imagePrintable Schedule

Below you will find a summary of the primary learning activities for this course and the associated time frames. This course is ten weeks in length, with an orientation week preceding the official start of the course. See our Calendar in Canvas for specific lesson time frames and assignment due dates.

GEOG 586 Schedule
Week / Lesson Course Objectives Assignments and Activities
Week 0 Course Orientation
  1. Articulate your own course expectations as a student in GEOG 586.
  2. Understand the expectations we have of you as a student in GEOG 586.
  3. Locate key information about the course, including assignments, due dates, technical information, places to get help, and course policies.
  4. Become familiar with the library and materials available to you as a Penn State Student.
  5. Understand the rules and regulations regarding Academic Integrity and plagiarism at Penn State.
  6. Understand how to communicate in this course environment.

Please post a brief personal introduction to the "Introductions" discussion forum and then review those your peers have posted to learn more about them.

Term Project: Familiarize yourself with the schedule for the term-long project.

Week 1 Why spatial data is special
  1. Differentiate point, line, and area objects, and fields and give examples.
  2. Differentiate nominal, ordinal, interval, and ratio attribute data and give examples.
  3. Distinguish between spatial objects and spatial fields, and discuss the merits of each as a representation.
  4. List four major problems in the statistical analysis of geographic information: autocorrelation, the modifiable areal unit problem, scale dependence, edge effects.
  5. Outline the concepts of distance, adjacency, interaction, and neighborhood, and show how these can be recorded using matrices.
  6. Explain how proximity polygons and Delaunay triangulation are developed for point objects, and relate this technique to concepts of distance, adjacency, interaction, and neighborhood.
  7. Explain how point data sets can be converted into a set of areal units using proximity polygons.
  8. Describe how a set of areal units can be converted into a set of point data by assignment of values to centroids.
  9. Outline how point data may be converted to field data by density estimation.

Complete the two self-test quizzes satisfactorily (you have an unlimited number of attempts and must score 90% or more).

Weekly Project: Complete the Project 1 activities. Spatial data conversion using census data to construct population surfaces

Term Project: Familiarize yourself with the schedule for the term-long project.

Week 2 Statistics
  1. Explain basic concepts in inferential statistics including descriptive statistics, and samples and populations.
  2. Explain a variety of descriptive statistics (measures of central tendency and spread, the concept of outliers).

Complete the self-test quiz satisfactorily (must score 90% or more).

Weekly Project: None

Term Project: Provide one or more suggested topics.

Week 3 Classical spatial analysis
  1. Describe and provide examples of simple deterministic and stochastic spatial processes.
  2. List the two basic assumptions of the independent random process (i.e., no first or second order effects).
  3. Outline the logic behind derivation of long run expected outcomes of the independent random process using the quadrat counts for a point pattern as an example.
  4. Outline how the idea of a stochastic process might be applied to line, area, and field objects.

Complete the self-test quiz satisfactorily (must score 90% or more).

Weekly Project: Complete the Project 3 activities. An exercise using the R statistics package to help you to better understand the concept of a spatial process.

Term Project: Submit a brief project proposal.

Week 4 Point pattern analysis
  1. Define point pattern analysis and list the conditions necessary for it to work well.
  2. Explain how quadrat analysis of a point pattern is performed and distinguish between quadrat census and quadrat sampling methods.
  3. Discuss relevant factors in determining an appropriate quadrat size for point pattern analysis.
  4. Describe in outline kernel density estimation and understand how it transforms point data into a field representation.
  5. Describe distance-based measures of point patterns (mean nearest neighbor distance and the G, F and K functions).
  6. Explain how distance-based methods of point pattern measurement are derived from a distance matrix.
  7. Describe how the independent random process and expected values of point pattern measures are used to evaluate point patterns, and to make statistical statements about point patterns.
  8. Explain how Monte Carlo methods are used when analytical results for spatial processes are difficult to derive.
  9. Justify the stochastic process approach to spatial statistical analysis.
  10. Discuss the merits of point pattern analysis versus cluster detection, and outline the issues involved in real world applications of these methods.

Complete the two self-test quizzes satisfactorily (must score 90% or more).

Weekly Project: Complete the Project 4 activities. Applying point pattern analysis methods discussed in this week's lesson.

Week 5 Interpolation--from simple to advanced
  1. Explain the concept of a spatial average and describe different ways of deciding on inclusion in a spatial average.
  2. Describe how spatial averages are refined by inverse distance weighting methods.
  3. Outline the basis of interpolation by spline-fitting, or piece-wise polynomial fitting.
  4. Explain why the above interpolation methods are somewhat arbitrary and must be treated with caution.
  5. Show how regression can be developed on spatial co-ordinates to produce the geographical technique known as trend surface analysis.
  6. Explain how a variogram cloud plot is constructed and, informally, show how it sheds light on spatial dependence in a dataset.
  7. Outline how a model for the semi-variogram is used in kriging and list variations on the approach.
  8. Make a rational choice when interpolating field data between inverse distance weighting, trend surface analysis, and geostatistical interpolation by kriging.
  9. Explain the conceptual difference between interpolation and density estimation.

Complete the two self-test quizzes satisfactorily (must score 90% or more).

Weekly Project: Complete the Project 5 activities. Exploring interpolation methods so that you develop a feel for the characteristics of the surfaces produced by different methods.

Term Project: Peer-review of proposals in an online forum.

Week 6 Surface analysis
  1. Describe data models for field data: regular grid, triangulated irregular network, closed form mathematical function, control points; and discuss how the choice of model may affect subsequent analysis.
  2. Explain the map algebra concept and describe focal operations, local operations and between-map operations.
  3. Understand the idea of slope and aspect as a vector field.
  4. Explain how slope or gradient can be determined from a grid of height values.
  5. Describe how surface aspect may be derived from a grid of height values.
  6. Re-express these operations as local operations in map algebra.
  7. Describe how map algebra operations can be combined to develop complex functionality.

Complete the self-test quiz satisfactorily (must score 90% or more).

Weekly Project: Complete the Project 6 activities. Using surface analysis to determine potential sites for a new school in the Centre County region of Pennsylvania (around Penn State).

Term Project: A revised (final) project proposal for the term-long project is due this week (about 500-800 words).

Week 7 Overlay analysis
  1. Formally describe Boolean map overlay.
  2. Explain how this technique has been widely used in suitability mapping.
  3. Understand why co-registration of input maps in overlay is critical to the success of the analysis.
  4. Describe how co-registration is achieved by a combination of translation, rotation, and scaling transformations.
  5. Outline how overlay is implemented in vector and raster GIS.
  6. Outline approaches to overlay based on alternative ways of combining layers-additive and indexed schemes, fuzzy methods, and weights of evidence methods.
  7. Describe how model-based overlay approaches and regression are related to one another.

Complete the self-test quiz satisfactorily (must score 90% or more).

Weekly Project: None

Term Project: Continue the work on term-long project.

Week 8 Spatial autocorrelation
  1. Define autocorrelation with reference to Tobler's 'first law' of geography and distinguish between first and second order effects in a spatial distribution.
  2. Differentiate between isotropic and anisotropic spatial distributions.
  3. Justify, compute, and test the significance of the joins count statistic for a pattern of area objects.
  4. Compute Moran's I and Geary's C for a pattern of attribute data measured on interval or ratio scales.
  5. Explain the importance of spatial weights matrices to the development of autocorrelation measures and variations of the approach, particularly lagged autocorrelation.
  6. Explain how autocorrelation measures can be generalized to compute and map Local Indices of Spatial Association (LISA).
  7. Describe how Monte Carlo methods may be used to determine significance for LISA.

Complete the self-test quiz satisfactorily (must score 90% or more).

Weekly Project: Last weekly assignment. Complete the Project 8 activities. Applying spatial autocorrelation measures.

Term Project: Continue with your term-long project.

Week 9 Project work time (no content this week)

School's out...!

Note that there are no other course activities at all this week, to give you plenty of time to work on completion of the project.

Term Project: Complete the term-long project work and post a report with links to data, maps, charts etc., summarizing project activities and results. Post the final report at the end of this week.

Week 10 Putting it all together: applied research using GIS Course and project reviews

You are DONE! Well almost.

This week's lesson will pull together all that we have learnt during the course, by critically and constructively evaluating each other's project work. This is a process we will all participate in using the online forums.


Course Policies

Technical Requirements

For this course, we recommend the minimum technical requirements outlined on our "Program Technical Requirements" page. If you need technical assistance at any point during the course, please contact the Outreach Helpdesk (for World Campus students) or the IT Service Desk (for students at all other campus locations).

Internet Connection

Access to a reliable broadband Internet connection is required for this course. A problem with your Internet access may not be used as an excuse for late, missing, or incomplete coursework. If you experience problems with your Internet connection while working on this course, it is your responsibility to find an alternative Internet access point, such as a public library or wireless hotspot.

Mixed Content

This site is considered a secure website, which means that your connection is encrypted. We do, however, link to content that isn't necessarily encrypted. This is called mixed content. By default, mixed content is blocked in Internet Explorer, Firefox and Chrome. This may result in a blank page or a message saying that only secure content is displayed. Follow the directions on our technical requirements page to view the mixed content.

Penn State E-mail Accounts

All official communications from the Penn State World Campus are sent to students' Penn State e-mail accounts. Be sure to check your Penn State account regularly, or forward your Penn State e-mail to your preferred e-mail account, so you don't miss any important information.

Academic Integrity

This course follows the guidelines for academic integrity of Penn State's College of Earth and Mineral Sciences. Penn State defines academic integrity as "the pursuit of scholarly activity in an open, honest and responsible manner." Academic integrity includes "a commitment not to engage in or tolerate acts of falsification, misrepresentation, or deception." In particular, the University defines plagiarism as "the fabrication of information and citations; submitting others' work from professional journals, books, articles, and papers; submission of other students' papers, lab results or project reports and representing the work as one's own." Penalties for violations of academic integrity may include course failure. To learn more, see Penn State's "Plagiarism Tutorial for Students."

Course Copyright

All course materials students receive or to which students have online access are protected by copyright laws. Students may use course materials and make copies for their own use as needed, but unauthorized distribution and/or uploading of materials without the instructor’s express permission is strictly prohibited. University Policy AD 40, the University Policy Recording of Classroom Activities and Note Taking Services addresses this issue. Students who engage in the unauthorized distribution of copyrighted materials may be held in violation of the University’s Code of Conduct, and/or liable under Federal and State laws.

For example, uploading completed labs, homework, or other assignments to any study site constitutes a violation of this policy.

Accommodations for Students with Disabilities

Penn State welcomes students with disabilities into the University's educational programs. Every Penn State campus has an office for students with disabilities. The Student Disability Resources (SDR) website provides contact information for every Penn State campus: Contacts for Disability Resources at all Penn State Campuses. For further information, please visit the Student Disability Resources (SDR) website.

In order to receive consideration for reasonable accommodations, you must contact the appropriate disability services office at the campus where you are officially enrolled. You will participate in an intake interview and provide documentation, see Applying for Services from Student Disability Resources. If the documentation supports your request for reasonable accommodations, your campus’s disability services office will provide you with an accommodation letter. Please share this letter with your instructors and discuss the accommodations with them as early in your courses as possible. You must follow this process for every semester that you request accommodations.

Counseling and Psychological Services

Many students at Penn State face personal challenges or have psychological needs that may interfere with their academic progress, social development, or emotional wellbeing.  The university offers a variety of confidential services to help you through difficult times, including individual and group counseling, crisis intervention, consultations, online chats, and mental health screenings.  These services are provided by staff who welcome all students and embrace a philosophy respectful of clients’ cultural and religious backgrounds, and sensitive to differences in race, ability, gender identity and sexual orientation. Services include the following:

Counseling and Psychological Services at University Park  (CAPS): 814-863-0395
Counseling and Psychological Services at Commonwealth Campuses
Penn State Crisis Line (24 hours/7 days/week): 877-229-6400
Crisis Text Line (24 hours/7 days/week): Text LIONS to 741741

Reporting Bias-Motivated Incidents

Penn State takes great pride to foster a diverse and inclusive environment for students, faculty, and staff. Acts of intolerance, discrimination, or harassment due to age, ancestry, color, disability, gender, gender identity, national origin, race, religious belief, sexual orientation, or veteran status are not tolerated (Policy AD29 Statement on Intolerance) and can be reported through Educational Equity via the Report Bias webpage.

Military Personnel

Veterans and currently serving military personnel and/or spouses with unique circumstances (e.g., upcoming deployments, drill/duty requirements, disabilities, VA appointments, etc.) are welcome and encouraged to communicate these, in advance if possible, to the instructor in the case that special arrangements need to be made.

Inclement Weather

In case of weather-related delays at the University, this online course will proceed as planned. Your instructor will inform you if there are any extenuating circumstances regarding content or activity due dates in the course due to weather delays. If you are affected by a weather-related emergency, please contact your instructor at the earliest possible time to make special arrangements.

Connect Online with Caution

Penn State is committed to educational access for all. Our students come from all walks of life and have diverse life experiences. As with any other online community, the lack of physical interaction in an online classroom can create a false sense of anonymity and security. While one can make new friends online, digital relationships can also be misleading. Good judgment and decision making are critical when choosing to disclose personal information with others whom you do not know.

Deferred Grades

If you are prevented from completing this course within the prescribed amount of time, it is possible to have the grade deferred with the concurrence of the instructor. To seek a deferred grade, you must submit a written request (by e-mail or U.S. post) to your instructor describing the reason(s) for the request. It is up to your instructor to determine whether or not you will be permitted to receive a deferred grade. If, for any reason, the course work for the deferred grade is not complete by the assigned time, a grade of "F" will be automatically entered on your transcript.

Attendance

This course will be conducted entirely online. There will be no set class meeting times, but you will be required to complete weekly assignments with specific due dates. Many of the assignments are open for multiple days, so it is your responsibility to complete the work early if you plan to travel or participate in national holidays, religious observances or University approved activities.

If you need to request an exception due to a personal or medical emergency, contact the instructor directly as soon as you are able. Such requests will be considered on a case-by-case basis.


Disclaimer

Please note that the specifics of this Course Syllabus can be changed at any time, and you will be responsible for abiding by any such changes. All changes will be communicated with you via e-mail, course announcement and/or course discussion forum.