1. KENT STATE UNIVERSITY
School of Library and Information Science
IAKM 60370: Semantic Analysis Methods and Technologies
Syllabus Spring, 2017. CRN: 14873
INSTRUCTOR
Sean Dolan, MLIS, and MS-IAKM, Adjunct Instructor
Office hours (Online): Tues and Thurs. (12:00PM – 8:00PM Eastern) OR by Appointment
Email: sdolan5@kent.edu (or Blackboard Learn course email)
Skype name: sdolan51
Phone: (440) 823-9535
COURSE OVERVIEW
Course delivery: 100% Online.
Class start & end dates: (15 weeks), January 17 – May 6, 2017 (Spring Break: March 27 – April 2, no class);
Course Description:
This course introduces students to the practical contexts, methods and tools associated with semantic analysis.
Students will gain an appreciation of the business value of knowledge trapped in unstructured data and understand
how semantic analysis can help to free this data at various stages of the Knowledge Life Cycle. Semantic technologies
will be presented not just as stand-alone tools, but also part of a larger landscape, the Semantic Grid/Semantic Web.
Focuses on early life cycle aspects of semantics, including identification and modeling of semantic problems, design of
semantic solutions, and the identification and implementation of appropriate semantic technologies. Covers natural
language processing, rule-based and grammar based concept extraction, rule-based and dynamic classification, and
automated summarization. Students will be exposed to a variety of semantic technologies. We will also take a brief
look at closely related disciplines (machine learning, data science, and text mining) and how they overlap with
semantic analysis.
Student Learning Outcomes:
After completing the course, the students will be able to:
1. Critically evaluate a semantic technology to gauge its ability to deliver expected results;
2. Draft an enterprise level semantic architecture for an organization;
3. Construct semantic profiles to support automated classification and indexing;
4. Recast knowledge organization systems as knowledge bases for semantic technologies;
5. Critically evaluate a text summarization application;
6. Develop a semantic solution to a business problem and describe a high-level design
Textbook:
• Zhai, C., & Massung, S. (2016). Text Data Management and Analysis: A Practical Introduction to Information
Retrieval and Text Mining. Morgan & Claypool.
• Additional reading lists will be posted on the Blackboard Learn for each lesson. The readings will either be
freely available on the Web, or available through the University Library’s KentLINK.
• Related professional activities and updates see: http://www.w3.org/standards/semanticweb/

2. COURSEWORK REQUIREMENTS
Graded Coursework: Total 400 points
See “Do This” section in each learning module in Blackboard Learn.
Activity Type Submissions Points
Discussion Posts and Responses 12 times; (5.0 each) 60
Quizzes 12 times; (10.0 each) 120
Semantic Analysis Methods (SAMs) 8 times; (20.0 each) 160
Semantic Problem Assignment 1 time; (60.0 each) 60
400
Description of Graded Activities
There are four types of graded activities throughout this course:
• Discussion Posts and Responses (15%)
• Weekly Quizzes over key concepts (15%)
• Semantic Analysis Methods (SAMs) (40%)
• Modeling a Semantic Solution assignment (30%)
Discussion Posts and Responses (15%)
Each week students will find a discussion question posted to the discussion forum. Students will post their thoughts
and discuss the ideas suggested by others. The online discussions among students help students to learn from one
another in a virtual community space, as we do not have a chance to interact in a real classroom setting. Discussion
postings are graded on effort and thoughtfulness. It is expected that students that perform this task appropriately will
receive the full points.
GRADING SCALE for DISCUSSION POSTS AND RESPONSES
Points Explanation
5 Initial post is completed by Friday and at least one response to a fellow student’s post is
completed by Sunday. Both the post and response demonstrate critical thinking (i.e.,
are more substantive than just, “Yes”, “No”, “I agree”, or “Interesting”). Length is not a
factor; one well written paragraph may be sufficient. Just make sure to explain your
reasoning and pull in at least one concept from that week’s lectures or readings.
4 Same as above, EXCEPT either post or response fails to demonstrate critical thinking.
3 Initial post is completed, but response to fellow student is not.
OR
Completed what would have been a 5-point post, but turned it in late (within 5 days).
2 Completed what would have been a 4-point post, but turned it in late (within 5 days).
0 No post completed within allowed time.

3. Weekly Quizzes (30%)
Each week an online quiz is available for students to use to test their understanding of key concepts covered in the
lectures and readings. The quizzes, which consist of multiple choice questions, are designed primarily for learning
rather than assessment, so each quiz may be taken twice. Students should allow time to take the quiz, review what
was missed and then retake the quiz. Students can complete them any time before the end of the week.
Semantic Analysis Methods (SAMs) (40%)
Beginning in Week 5, students will look at a different tool each week which performs a specific semantic analysis task.
Each week, students will receive instructions on how to access the tool and a series of questions to use to evaluate the
tool’s performance. Students will turn in a written document approximately 2-3 pages long which demonstrates
critical thinking and addresses these questions. Screenshots taken while using the tool may also be required. These
evaluations will be graded primarily on effort and thoughtfulness. It is expected that students performing this task
appropriately will receive the full points. IMPORTANT NOTE: Although these assignments are not designed to be
time-consuming or technically difficult, it is recommended that students attempt these assignments early in the
week in case difficulties arise. The instructor will do his best to address these difficulties as soon as he is made
aware of them, but requests for assistance made on Saturdays and Sundays may be difficult to accommodate.
GRADING RUBRIC for SEMANTIC ANALYSIS METHODS (SAMs)
Points Explanation
Followed instructions and demonstrated effort
2 Assignment is completed on-time and includes screenshots (if required)
2 Overall, paper demonstrates critical thinking and reasoning
Specific questions were addressed in student’s paper
2 1. High-level description of how tool works
2 2. Is the tool truly semantic?
2 3. Evaluation of results
2 4. Business value and Knowledge Life Cycle
2 5. Impact on Semantic Landscape
Format and professionalism (4 pts)
2 The final paper submitted is approximately 2-3 pages in length, double spaced.
2 The final paper is grammatically correct and error-free.
Modeling a Semantic Solution (30%)
During Weeks 14 and 15, students will complete a longer assignment in which they will identify a business problem or
process that can either be solved or enhanced by adopting a semantic solution. Students will explain the problem or
process and justify why the semantic analysis method/tool they have chosen is the most appropriate choice for the
given task. This should include an analysis of the costs, risks, and benefits of adopting the solution. Students will then
sketch out a high-level description of how the semantic analysis method would work. This sketch should include a
description of how a human being would go about the task and a discussion of what inputs the semantic analysis
method/tool would require, an overview of how the method/tool works (such as machine learning techniques), and
what outputs it would generate. Finally, students should identify what benchmarks will be used to determine
whether the semantic solution has performed successfully.
The final paper should be approximately 6-8 pages in length, double spaced. Students are highly encouraged to begin
thinking about the business problem/process and semantic method/tool they will write about no later than Spring
Break. Please feel free to run your ideas by the instructor at any point during the course if you are unsure whether or
not they are an appropriate topic for the paper.

4. GRADING RUBRIC for MODELING A SEMANTIC SOLUTION ASSIGNMENT
Points Explanation
Identification of problem and justification of solution, cost/benefit analysis (25 pts)
10 Student identified and explained a business problem or process that can either be solved
or enhanced by adopting a semantic solution
10 Student justified why the semantic analysis method/tool chosen is the most appropriate
choice for the given task
5 Costs, risks, and benefits of adopting the solution were considered in the student’s
analysis
High-level sketch of how the semantic analysis method would work (25 pts)
5 Sketch included a description of how a human being would go about the task being
modeled
5 Sketch included a discussion of what inputs the semantic analysis method/tool would
require
5 Sketch included an overview of how the method/tool works (such as machine learning
techniques)
5 Sketch included a discussion of what outputs the method/tool would generate
5 Student identified what benchmarks will be used to determine whether the semantic
solution performed successfully
Format and professionalism (10 pts)
5 The final paper submitted is approximately 6-8 pages in length, double spaced.
5 The final paper is grammatically correct and error-free.
How to Submit Assignments:
All assignments should be submitted through the ASSIGNMENT DROPBOX tool on the course Blackboard Learn
website. Please submit only one file for each assignment- preferred formats are WORD and PDF. If there are
multiple files, zip (compress) it and submit the file. Please do not use Google Docs.
All file names should contain your last name (e.g., dolan1.pdf, dolan1.doc, or dolan1.zip). If you have trouble
submitting a file, please email me through the course website's email.
GRADING
Final grading will be based on the sun of all graded coursework on a basis of 0-100%. More specifically: A 95-
100 | A- 92-94.9 | B+ 88-91.9 | B 82-87.9 | B- 80-81.9| C+ 78-79.9 | C 72-77.9 | C- 70-71.9 | D 60-69.9 | F <60
Graduate student standards:
• A= demonstrate superior performance through critical thinking, exemplary product, positive and
supportive interactions with colleagues, and sustained active participation across course activities.
• B= average on all assignments; this graduate standard indicates that the work was well done, complete,
met stated criteria, represents a strong professional effort, and was turned in on time.
COURSE POLICIES AND PROCEDURES
• A week starts on Monday and finishes on Sunday. Each week the learning materials will be available on
Blackboard Learn on the Sunday before the week starts.
• Assignments of each week are due at the end of Sunday of the week. For example, Week one
assignments are due at the end of Sunday (at your local time).
• Assignments of a learning module can be submitted any time before the due day. It is encouraged that
you submit earlier than the due day in order to get feedback earlier.
• Where no arrangements have been made to take an Incomplete, failure to complete any course
requirement will result in a course grade of C or lower, regardless of the grades received in other
components.
• Attending in all classes and participating in discussions in classes and through the Blackboard Learn
site are expected. Excused absences are those that are approved by the university (illness, death of
immediate family, religious observance, etc.) and deemed acceptable by the instructor. If possible, you
must talk to the instructor beforehand for all excused absences. If an emergency or illness occurs, have

5. someone notify the course instructor as soon as possible--even if you are out of town. Too little
participation is sufficient cause to lower the final course grade. Exceptions will be made for
emergencies and other extenuating circumstances provided they are verified by appropriate
documentation that is received no later than one week after the absence(s).
Communication Policy:
• Both in-class emails and general Discussion Board on Blackboard Learn can be used to communicate
between the students and the instructor, and among students. Alternative email of the instructor at
mzeng@kent.edu can also be used, but please note that sometimes kent.edu email system will filter out
emails without noticing the receiver. It is not guaranteed that your email will be read if sent to this
alternative email address.
• To discuss a grade, write an email or arrange for a private meeting in which you identify the sources of
your concern. It is important to bring with you to that meeting the relevant materials (e.g. marked
papers). Except for extraordinary circumstances, no appeal for an individual assignment or project will
be considered later than two weeks after the graded assignment was returned. For final grades, no
appeal will be considered after the last day of the month the semester ends.
Policy on LATE SUBMISSIONS:
• Any late submission (within 5 days) will receive a 50% deduction of the grade for that week. No
submissions will be accepted 5 days past the assignment’s due date unless the instructor grants an
extension.
Student Conduct & Netiquette:
Taking an online course and corresponding via the Internet presents communicators with a challenging task. It
is important to remember several points of etiquette that will smooth communication between students and
instructors.
• Read first, Write later. It is important to read all posts or comments of students and instructors within
the course discussion before personally commenting to prevent repeating commentary or asking
questions that have already been answered.
• Avoid language that may come across as strong or offensive. Language can be easily misinterpreted in
written communication. Review your written communication to make sure that outsiders reading it
would not be offended then post the statement. Humor and sarcasm may easily be misinterpreted as
well, so try to be as matter-of-fact and professional as possible.
• Follow the language rules of the Internet. Do not write using all capital letters, because it will appear as
shouting. Also, the use of emotions can be helpful when used to convey nonverbal feelings ; ).
• Consider the privacy of others'. Ask permission prior to giving out a classmate's email address or other
information.
• If possible, keep attachments small. If it is necessary to send pictures, change the size to an acceptable
250kb or less.
• No inappropriate material. Do not forward virus warnings, chain letters, jokes, etc. to classmates or
instructors. The sharing of pornographic material is forbidden.
NOTE: The instructor reserves the right to remove posts that are not collegial in nature and/or do not
meet the Online Student Conduct and Etiquette guidelines listed above.

6. COURSE OUTLINE/SCHEDULE
Tentative Schedule (Content may be adjusted based on the feedback and progress of the participants)
Week #
1st day
of the
week
Course Contents
Pre-class 1/09
About the course
Short Bio on General Discussion Board
- 1/16 Martin Luther King, Jr. Day - No Class
1 1/17
Lesson 1. Semantics and Course Overview
• Semantics Defined
• Knowledge and Semantics
• Revised View of Knowledge Pyramid
Assignments: Quiz: (10.0), Discussion Post (5.0)
2 1/23
Lesson 2. Semantics and Knowledge Architecture
• Enterprise and Knowledge Architecture
• People Data Model and Knowledge Components
• Knowledge Based Applications
Assignments: Quiz: (10.0), Discussion Post (5.0)
3 1/30
Lesson 3. The Semantic Landscape
• History of Semantic Technologies
• What Makes an Application Semantic
• Semantic Web and Semantic Web Stack
Assignments: Quiz: (10.0), Discussion Post (5.0)
4 2/06
Lesson 4. Modeling a Semantic Solution
• Understanding the Problem
• Software Development Life Cycle
• Deep Dive into Semantic Search
Assignments: Quiz: (10.0), Discussion Post (5.0)
5 2/13
Lesson 5. Natural Language Processing
• Linguistics and Levels of Language
• Disambiguation Tasks
• Part of Speech Tagging
Assignments: Quiz: (10.0), Discussion Post (5.0); SAM1.0: (20.0)
6 2/20
Lesson 6. Pure Word Extraction
• Concepts vs. Words
• Context and Meaning
• Grammatical Tagging of Concepts
Assignments: Quiz: (10.0); Discussion Post (5.0); SAM2.0: (20.0)
7 2/27
Lesson 7. Grammar-Based Extraction
• Concept Extraction Basics
• Grammatical Concepts
• Use of Concept Extraction for Knowledge Management
Assignments: Quiz: (10.0); Discussion Post (5.0); SAM3.0: (20.0)
8 3/06
Lesson 8. Rule-Based Concept Extraction
• Concept Extraction vs. Classification
• Knowledge Sources as Rule Sets
• Uses of Rule Based Concept Extraction for Knowledge
Assignments: Quiz: (10.0); Discussion Post (5.0); SAM4.0: (20.0)
9 3/13
Lesson 9. Rule-Based Classification, Part 1
When You Have a Scheme to Work With
• Supervised vs. Unsupervised Methods
• Differentiation of Processes and Scheme Development
• Distinction between Classification and Indexing

7. Assignments: Discussion Post (5.0); Quiz: (10.0)
10 3/20
Lesson 10. Rule-Based Classification, Part 2
• Subject Classification
• Geographical Classification
• Sentiment Classification
• Security Level and Risk Classification
Assignments: SAM5.0 (20.0)
_ 3/27 Spring Break – No Class
11 4/03
Lesson 11. Clustering, aka Dynamic Categorization
• Statistical Methods Used in Clustering
• Concept of Similarity
• Selecting Variables
• Validation of Clusters
Assignments: Quiz: (10.0); Discussion Post (5.0); SAM6.0: (20.0)
12 4/10
Lesson 12. Automated Summarization
• Modeling the Human Process
• Professional Rules for Abstracting
• Frequency of Concepts Extraction
• Cue Phrases, Important or Exclusion Phrases
• Differentiation of Text Summarization and Text Generation
Assignments: Quiz: (10.0); Discussion Post (5.0); SAM7.0: (20.0)
13 4/17
Lesson 13. Text Generation
• Human Authoring Processes
• Document Planning
• Content and Structures
• Text Microplanning
Assignments: Quiz: (10.0); Discussion Post (5.0); SAM8.0: (20.0)
14 4/24
Lesson 14: Sentiment Analysis
• Machine Learning
Assignments: Begin Modeling a Semantic Solution Assignment: (60.0)
15 5/01
Lesson 15. Recommender Systems
• Machine Learning
Assignments: Finish Modeling a Semantic Solution Assignment: (60.0)
End 5/06 All Assignments must be turned in by this date.
UNIVERSITY AND SCHOOL POLICIES
UNIVERSITY AND SCHOOL POLICIES
[required info]
SPECIAL NOTES for Course Syllabi
(1) REGISTRATION REQUIREMENTS
Every class has its own schedule of deadlines and considerations. To view the add/drop schedule and other important dates
for this class, go to the Students Tools and Courses tab in FlashLine and choose either View or Print Student Schedule. To
see the deadlines for this course, click on the CRN or choose the Drop or Add a Course link and click on the green clock next
to the course under Registration Deadlines.
(2) TECHNOLOGICAL COMPETENCIES
Students must be familiar with basic computer operations (e.g., copying and printing files, moving among directories and
subdirectories), logging on to a network, creating and establishing connections to the Internet (i.e.,: modem, Wi-Fi, etc.),
using the Internet to access and interact with course software, uploading and downloading files, accessing audio and video
course contents and using word processing, presentation, and spreadsheet software programs .

8. (3) STUDENTS WITH DISABILITIES
University policy 3342-3-01.3 requires that students with disabilities be provided reasonable accommodations to ensure
their equal access to course content. If you have a documented disability and require accommodations, please contact the
instructor at the beginning of the semester to make arrangements for necessary classroom adjustments. Please note, you
must first verify your eligibility for these through Student Accessibility Services (contact 330-672-3391 or visit
www.kent.edu/sas for more information on registration procedures).
(4) POLICY ON INCOMPLETE, NF AND SF GRADES. PER THE GRADUATE CATALOG:
IN
NF
The mark IN (Incomplete) may be given to students who—due to extenuating circumstances—are unable to
complete the required work between the course withdrawal deadline and the end of classes. The timeline shall be
adjusted appropriately for summer sessions and flexibly scheduled courses.
To be eligible, undergraduate students currently must be earning a minimum D grade, and graduate students
currently must be earning a minimum C grade. Appropriate documentation is required to support the extenuating
circumstance. The student or university-approved designee must initiate the request for the IN mark from the
instructor, and it is the responsibility of the student to arrange to make up the incomplete work.
Instructors are required to complete and submit an Incomplete Mark Contract to their department chair/school
director at the time grades are assigned. This form includes justification for awarding the Incomplete, describes the
work to be completed for the course and specifies the grade to be assigned if the work is not completed (default
grade). A copy of the Incomplete Mark Contract is provided to the student.
The IN mark is not counted in the computation of grade point averages; when the work is completed, an
appropriate grade will be assigned based on the instructor’s evaluation of the work submitted and a new grade
point average computed.
Unless the course is completed or an extension is granted, the IN mark automatically will lapse to the default grade
designated on the Incomplete Mark Contract at the earliest of one of the following: (1) the default date designated
on the Incomplete Mark Contract; or (2) at the end of one semester for undergraduate courses, at the end of three
consecutive terms for graduate courses and after 90 calendar days for College of Podiatric Medicine courses.
The mark NF (Never Attended–Fail) denotes that the student neither attended any class session nor formally
withdrew from the course. The NF mark counts as an F grade (zero quality points) in computing grade point
averages. In the case of undergraduate courses taken pass/fail, the NF mark will be changed to a Z (fail) grade.
SF The mark SF (Stopped Attending–Fail) denotes that the student stopped attending the course and did not formally
withdraw. The SF mark counts as an F grade (zero quality points) in computing grade point averages and must be
accompanied by a date of last attendance in the course. Faculty who cannot determine the exact date of last
attendance may use the date of the last academic activity in which students participated. In the case of
undergraduate courses taken pass/fail, the SF mark will be changed to a Z (fail) grade.
(5) CHEATING AND PLAGIARISM
Cheating and plagiarism constitute fraudulent misrepresentation for which no credit can be given and for which
appropriate sanctions are warranted and will be applied. The university affirms that acts of cheating and plagiarism by
students constitute a subversion of the goals of the institution, have no place in the university and are serious offenses to
academic goals and objectives, as well as to the rights of fellow students. Both cheating and plagiarism are prohibited and
may result in failing the class and ultimately dismissal from the program. One area that many students may not realize as
cheating is the following. "Using a substantial portion of a piece of work previously submitted for another course or
program to meet the requirements of the present course or program without notifying the instructor to whom the work is
presented."
Per university policy 3-01.8, "Plagiarize" means to take and present as one's own a material portion of the ideas or words of
another or to present as one's own an idea or work derived from an existing source without full and proper credit to the
source of the ideas, words, or works.
[For the complete policy and procedure, please visit Kent State Policy # 3-01.8 Administrative policy regarding student
cheating and plagiarism.]

9. (6)ATTENDANCE POLICY
In-person Class Attendance
Classes are conducted on the premise that regular attendance is expected. The individual instructor has both the
responsibility and the prerogative for managing student attendance. If students anticipate an absence, they should consult
with the instructor individually. In the event the absence was due to illness or injury, verification from the medical
professional treating the illness or injury should be presented to the instructor.
Online Attendance Policy
Online courses are conducted on the premise that regular attendance (students logging into the Blackboard Learn learning
management system) is expected. The number of logins or length of time students spend in the online course may vary on a
daily, weekly, or monthly basis depending on participation requirements listed in the course syllabus. Attendance is
therefore measured both by virtual presence in the online course and satisfying the specific criteria for course participation.
If students anticipate an absence from the online course due to technical or medical reasons, they should consult with the
instructor individually. In the event the absence was due to illness or injury, verification from the medical professional
treating the illness or injury should be presented to the instructor.
(7) WITHDRAWAL
Withdrawal from any or all courses is permitted through the 10th
week of the semester (or the prorated deadline for flexibly
scheduled courses – see schedule course detail). After that time, students are considered to be committed to all remaining
courses and must complete them. Students will use FlashFAST via FlashLine to withdraw from one or more courses by the
deadline. If students are unable to complete the term because of extreme circumstances that first occur after the deadline,
they should consult their college or campus dean’s office. Any course withdrawal(s) processed after the second week of the
fall or spring semester (or prorated deadline for summer or flexibly scheduled courses) will appear on the students’
academic record with an administrative mark of W. For more information on the W mark, please refer to Grading Policies
and Procedures in the University Catalog. Any applicable tuition credit (policy published on the Office of the Bursar
website) is determined by the date the transaction is processed on FlashFAST. Course withdrawal does not negate a
student’s financial obligation, and students will be held responsible for all balances due to the university.
(8) PREFERRED CITATION STYLE FOR ASSIGNMENTS
The official citation style for SLIS assignments is APA. The required manual is the Publication Manual of the American
Psychological Association, 6th ed. (Washington, DC: APA, 2009). Students should refer to this style guide for formatting,
structure and design of the written format of papers and assignments where citation is necessary. The Kent State University
Library provides a good resource for this style as well: http://libguides.library.kent.edu/apa
(9) NOTICE OF MY COPYRIGHT AND INTELLECTUAL PROPERTY RIGHTS.
Any intellectual property displayed or distributed to students during this course (including but not limited to visual aids,
notes, quizzes, examinations) by the professor/lecturer/instructor remains the intellectual property of the
professor/lecturer/instructor. This means that the student may not distribute, publish or provide such intellectual property
to any other person or entity for any reason, commercial or otherwise, without the express written permission of the
professor/lecturer/instructor.
(10) STATEMENT ON NONDISCRIMINATION, HARASSMENT AND SEXUAL VIOLENCE POLICIES AND PROCEDURES (from
University Counsel):
KSU policy 5-16 prohibits unlawful discrimination and harassment based on race, color, religion, gender, sexual orientation,
national origin, ancestry, disability, genetic information, age, military status, or veteran identity. Gender-based
discrimination also includes sexual harassment, sexual misconduct, stalking and intimate partner violence. Please report
any violation of this policy to the Office of Compliance, Equal Opportunity, and Affirmative Action at 330-672-2038,
or aa_eeo@kent.edu.
(11) M.L.I.S. PORTFOLIO
M.L.I.S. students with the catalog year of 2016‐2017 and beyond are required to complete LIS 60280
Master’s Portfolio in Library and Information Science in the last semester of their program. This course will result in the
creation of a portfolio that showcases the student’s work from the courses they have taken at SLIS and aligns them with
program learning outcomes and professional standards. As you complete this course, consider your assignments to see if
they help you demonstrate any of the following M.L.I.S. program learning outcomes. If so, the assignment will be one that
you will want to include in the creation of your portfolio class.

10. Graduates of this program will be able to:
1. Apply the field's foundational theories, principles, values, ethics and skills to everyday practice.
2. Critique and synthesize research and identify appropriate research methodologies to solve
problems in the field.
3. Analyze and engage in the changing cultural, educational and social roles and responsibilities of
librarians/information professionals and the environments they work in within the global
society.
4. Evaluate systems and technologies relevant to a particular information context.
5. Identify needs and connect individuals and communities with information that engages and
empowers them.
Option for instructors: In addition, instructors may want to point to a specific assignment they may consider to be a good
candidate to address certain program learning outcomes.