GEOG 586
Geographic Information Analysis

Syllabus

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GEOG 586: Geographic Information Analysis

2020

This syllabus is divided into several sections. You can read it sequentially by scrolling down the length of the document. 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."

Instructors

Amy Griffin
Amy Griffin
Fritz Kessler
Fritz Kessler

College of Earth and Mineral Sciences
The Pennsylvania State University

  • Email: Please use Canvas Inbox
  • Office Hours: by appointment

2217 Earth & Engineering Sciences Building
College of Earth and Mineral Sciences
The Pennsylvania State University

  • Phone: 814-863-1508
  • Email: Please use Canvas Inbox
  • Office Hours: by appointment

NOTE: All faculty will read and respond to email and discussion forums at least once per day during the work week (Monday through Friday). You may also see us online occasionally on the weekends.


Course Overview

GEOG 586: Tonny Oyana and Florence Margai. GEOGRAPHIC INFORMATION ANALYSIS. Choosing and applying analytical methods for geospatial data, including point pattern analysis, interpolation, surface analysis, overlay analysis, and spatial autocorrelation. 2016. CRC Press. BocaRaton, FL ISBN: 978-1-4987-0763-3

Prerequisite: GEOG 485 or GEOG 486 or GEOG 487 or equivalent experience

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 are established start and end dates 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, 2, 3, 4, 6 and 7) and a more substantial term 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 spatial data analysis. 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. Each week, students acquire familiarity with the 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 limitations and application. Problem scenarios range across demographic, planning, crime analysis, landscape analysis, and other application areas.

The term 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. Students with previous programming experience should consider developing customized tools to automate repetitive analysis tasks to enhance efficiency.

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, readings, and commentary during the weekly lessons. This book covers considerably more material than we could ever get through in the 10 weeks of this course, but should serve as an important resource both now and in the future.

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 or discussion 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.
  5. Term project: In addition to these activities, a term 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 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 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.

Each week, since course weeks run from Wednesday to the following Tuesday, I strongly advise that you aim to complete the reading and quiz (or quizzes) by Friday or Saturday so that you have plenty of time to tackle the weekly project and submit it by the Tuesday night deadline.

Discussion forums have been provided for students (you) and the instructor (me) to share comments, pose questions, and suggest answers. I strongly encourage you to get in the habit of checking this regularly. 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. I assign participation grades based on both the quantity and quality of your contributions to discussion, with quality being more important than quantity. Comments that explore ideas and help your fellow students grow in their understanding are valued more highly than simply stating 'I agree'. Posing questions about things you feel you do not fully understand is also a valued form of participation. You can be sure that if you are puzzling over something, other students likely are too, and by working together, you will collectively improve your understanding of the material.

We 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.

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.

... 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). If you are really stuck then also send me an email.

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.


Required Course Materials

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 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 online 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 email at psuwd@psu.edu (link sends email).

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

Textbook: The required material you need to purchase is:

Oyana, Tonny. and Margai, Florence., 2016, Spatial Analysis: Statistics, Visualization, and Computational Methods. (CRC Press, Boca Rotan, FL). ISBN 978-1498707633. The Second Edition of this text has just been published (August 2020). You are welcome to use this new edition for the course. The library copy is not yet available for the second edition.

E-Book Option: An online version of one or more of your texts is available at no cost as a Penn State Library E-Book. You can access the E-Book through the Library Resources link on the course navigation. Some E-Books will only be available online, while others will be available to download in full or in part. You may choose to use the E-Book as an alternative to purchasing a physical copy of the text. For questions or issues, you can contact the University Libraries Reserve Help (UL-RESERVESHELP@LISTS.PSU.EDU).

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

  • R Studio and R the free statistical analysis software package;
  • GeoDa, free exploratory spatial data analysis software available from Chicago University: The Center for Spatial Data Science
  • Esri's ArcGIS and/or ArcGISPro that includes the Geostatistical Analyst and Spatial Analyst extension. The best way to request access to the software is to visit GIS @ Penn State. 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.
  • the required course website that contains the online lessons and communications tools, such as message boards and an email system.
  • Zoom: available through Penn State

Additional recommended texts:

Additional resources will be introduced during the relevant lessons each week.

    Additional Statistics books. These are all useful in different ways. One stats book will not cover all the information you need. As you use stats you will find yourself dipping in and out of different resources. Find a resource that you find useful.

    Assistance with Textbooks:

    Penn State honors and values the socioeconomic diversity of our students. If you require assistance with the costs of textbooks for this course, contact the Office of Student Care and Advocacy, 120 Boucke Building, 863-4926. For additional needs related to socioeconomic status please visit Project Cahir.


    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 and and to test your knowledge. Weekly quizzes must be completed by the stated deadline. Any quiz that you fail to complete by the stated deadline will count for 0. Each quiz is 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: Geospatial Data Science and Analysis: integrating the two and understanding what is in your data. An exercise using R and applying descriptive statistics.
      • Week 2: Geospatial Data Science and Spatial Statistical Analysis: Point Patterns and why statistical analysis is important for quantifying what you see. An exercise using R to examine crime in St Louis using point pattern analysis.
      • Week 3: Spatial Analysis and why it is special: Exploring the Modifiable Area Unit Problem .
      • Week 4: Cluster Analysis & Spatial Autocorrelation: An exercise applying spatial autocorrelation measures to assessing ethnic segregation in Auckland, New Zealand using GeoDa.
      • Week 6: Interpolation Methods simple to advanced: Practical experience with interpolation methods so that you develop a feel for the characteristics of the surfaces produced by different methods using ArcGIS/ArcGIS Pro.
      • Week 7: Surface Analysis: Using surface analysis 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 using ArcGIS /ArcGIS Pro.
    • 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:

    • post topic ideas (week 1)
    • develop a project proposal (week 2)
    • organize interactive peer-review time and date with your group (week 3)
    • peer review feedback for project proposal (week 5)
    • refine and submit a final project proposal (week 6)
    • final project is due at the end of week 9
    • discussions of final projects (week 10)

    Items in the term 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. In addition to participation in weekly discussion forums, your thoughts and reactions to the article on multiple regression analysis in Week 5 contributes to your participation grade. Because you get points assigned directly for peer review discussions about the term-long project, your participation in them is not considered directly in this component of your grade.

    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 93-100%
    A- 90-92.9%
    B+ 86-89.9%
    B 82-85.9%
    B- 78-81.9%
    C+ 74-77.9%
    C 70-73.9%
    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

    printer graphicPrintable 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 Geospatial Data Analysis: Dealing with data
    1. Explain spatial data analysis, concepts and how the two are integrated
    2. Understand how the research framework works and will be applied
    3. Understand data types and why spatial data is special.
    4. Explain basic concepts in inferential statistics including descriptive statistics, and samples and populations.
    5. Visualizations, summarizing data and presenting of information

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

    Weekly Project: Complete the Project 1 activities.

    Term Project: Familiarize yourself with the schedule for the term project and post a topic idea.

    Week 2

    Point Pattern analysis and why statistical analysis is important

    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 how the idea of a stochastic process might be applied to the line, area, and field objects.
    4. Define point pattern analysis and list the conditions necessary for it to work well.
    5. Explain how quadrat analysis of a point pattern is performed and distinguish between quadrat census and quadrat sampling methods.
    6. Discuss relevant factors in determining an appropriate quadrat size for point pattern analysis.
    7. Describe in outline kernel density estimation and understand how it transforms point data into a field representation.
    8. Describe distance-based measures of point patterns (mean nearest neighbor distance and the G, F, and K functions).
    9. Explain how distance-based methods of point pattern measurement are derived from a distance matrix.
    10. 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.
    11. Explain how Monte Carlo methods are used when analytical results for spatial processes are difficult to derive.
    12. Discuss the merits of point pattern analysis versus cluster detection, and outline the issues involved in real-world applications of these methods.

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

    Weekly Project: Complete the Project 2 activities.

    Term Project: Provide a project proposal outline.

    Week 3 Why spatial data is special
    1. List four major problems in the statistical analysis of geographic information: autocorrelation, the modifiable areal unit problem, scale dependence, edge effects.
    2. Outline the concepts of distance, adjacency, interaction, and neighborhood, and show how these can be recorded using matrices.
    3. Explain how proximity polygons and Delaunay triangulation are developed for point objects, and relate this technique to concepts of distance, adjacency, interaction, and neighborhood.
    4. Explain how point data sets can be converted into a set of areal units using proximity polygons.
    5. Describe how a set of areal units can be converted into a set of point data by assignment of values to centroids.
    6. Outline how point data may be converted to field data by density estimation.

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

    Weekly Project: Complete the Project 3 activities.

    Term Project: Organize peer-review session with your group.

    Week 4 Cluster Analysis & 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 quizzes satisfactorily (must score 90% or more).

    Weekly Project: Complete the Project 4 activities.

    Term Project: Refine Project Proposal.

    Week 5 Regression Analysis
    1. Intro to regression and how it is useful.
    2. Correlation.

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

    Read Paper and post in the Discussion forum.

    Weekly Project: None.

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

    Week 6 Interpolation: 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 coordinates 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 self-test quiz satisfactorily (must score 90% or more).

    Weekly Project: Complete the Project 6 activities.

    Term Project: A revised (final) project proposal for the term project is due this week.

    Week 7 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 the 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 Project 7 activities.

    Term Project: Continue the work on term project.

    Week 8 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 the 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 the 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 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 learned 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

    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 Penn State's College of Earth and Mineral Sciences Academic Integrity Guidelines for undergraduate students and Penn State's College of Earth and Mineral Sciences Academic Integrity Guidelines for graduate students. 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 Academic Integrity Training

    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 Office for Student Disability Resources website provides contact information for Campus Disability Coordinators at every Penn State campus. For further information, please visit the Office for Student Disability Resources 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 documentation guidelines at 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.

    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.

    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 Report Bias.

    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 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

    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.

    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 to others whom you do not know.

    Technical Requirements

    For this course, we recommend the minimum technical requirements outlined on the World Campus Technical Requirements page, including the requirements listed for same-time, synchronous communications. If you need technical assistance at any point during the course, please contact the HelpDesk (for World Campus students) or the IT Service Desk (for students at all other campus locations).

    Internet Connection

    Access to a reliable 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 Wi-Fi ® hotspot.

    Mixed Content

    This site is considered a secure web site 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.

    Equations

    This course must be viewed using the latest version of Firefox, Safari, Chrome, or Edge. Internet Explorer is not supported. If you use any other browser, or if you are not using the latest version of your browser, some pages containing equations will not render properly. In addition, javascript must be enabled for equations to render properly. If you have any issues with equations not rendering properly, please update your browser to the latest version or try using a different browser. If you need additional technical assistance at any point during the course, please contact the HelpDesk (for World Campus students) or the IT Service Desk (for students at all other campus locations).

    Deferred Grades

    If you are prevented from completing this course within the prescribed amount of time for reasons that are beyond your control, it is possible to have the grade deferred with the concurrence of the instructor, following Penn State Deferred Grade Policy 48-40. To seek a deferred grade, you must submit a written request (by e-mail or U.S. post) to the instructor describing the reason(s) for the request. Non-emergency permission for filing a deferred grade must be requested before the beginning of the final examination period.  It is up to the instructor to determine whether or not you will be permitted to receive a deferred grade. If permission is granted, you will work with the instructor to establish a communication plan and a clear schedule for completion within policy.  If for any reason, the coursework for the deferred grade is not complete by the assigned time, a grade of "F" will be automatically entered on your transcript.

    Diversity, Inclusion, and Respect

    Penn State is “committed to creating an educational environment which is free from intolerance directed toward individuals or groups and strives to create and maintain an environment that fosters respect for others” as stated in Policy AD29 Statement on Intolerance. All members of this class are expected to contribute to a respectful, welcoming, and inclusive environment and to interact with civility.

    For additional information, see:

    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.

    Mandated Reporting Statement

    Penn State’s policies require me, as a faculty member, to share information about incidents of sex-based discrimination and harassment (discrimination, harassment, sexual harassment, sexual misconduct, dating violence, domestic violence, stalking, and retaliation) with Penn State’s Title IX coordinator or deputy coordinators, regardless of whether the incidents are stated to me in person or shared by students as part of their coursework. For more information regarding the University's policies and procedures for responding to reports of sexual or gender-based harassment or misconduct, please visit Penn State's Office of Sexual Misconduct Prevention & Response website.

    Additionally, I am required to make a report on any reasonable suspicion of child abuse in accordance with the Pennsylvania Child Protective Services Law.


    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.