- Title: Applied Linear Algebra
- Section: A
- Instructor: Dr. Alex John Quijano
- Office: Buckley Center 279
- Email: quijano@up.edu
MTH 202 with a grade of C- or higher or permission of instructor.
In-person lectures and discussions will occur synchronously during their scheduled time on Monday, Wednesday, and Friday. Our lectures will typically consist of traditional lectures in the first 20 to 30 minutes of class, then followed by mini-activities in a form of group work, discussions, or worksheets.
The course schedule and location is:
- Section A: MWF 10:20 AM - 11:15 AM, Franz Hall 018
This course uses the following two textbooks - which is free to access - for optional reading and practice.
Click on the link to access the resources.
Nicholson WK (2018). Linear algebra with applications, Open Edition, edition. Lyryx. [pdf]
Boyd S, Vandenberghe L (2018). Introduction to applied linear algebra:, vectors, matrices, and least squares. Cambridge university press. [pdf]
The syllabus, tentative topics schedule, assignments, and all other class materials are posted on the course website.
You can access the course website at mth-342a-sp24. The website can also be viewed in Teams.
We will be using Teams as the main real-time communication tool for general announcements, question-answering discussions, and direct messages. I added you to the Teams page already, so you just need to log in using your UP credentials. If not, then send a request when you log in. Let me know if you need any assistance.
The Teams for this course is MTH-342-sp24.
Note that most of the content can be accessed in Teams which includes the course website, Gradescope, and Cloud Computing.
My UP email is quijano@up.edu.
If you prefer communicating through email, note that I have set up an email filter for this course, and you must put the “MTH 342” keyword in your subject line.
It is easy for me to get notice of your email if you put the keyword in the subject line. Concise and specific messages are helpful, so I know how I can best help you.
All assignments and feedback must be submitted through Gradescope. You are already listed in Gradescope for this course using your UP email. The gradescope website can also be access through Teams.
Please register on Gradescope using your UP email address to access assignments. The Gradescope entry code for this course is 8EWE42.
Note that you may submit your assignments physically in-person if you prefer. I will scan and upload your assignments to Gradescope.
We will be using a computational tool (R or Python) for the semester project and some assignments. These tools are free and open-source. We will use the Posit Cloud service, an online computing environment.
Create a free account at Posit Cloud Sign-Up using your UP email. Note that you must use your UP email for me to add you into the course’s workspace in Posit Cloud. You will receive an email inviting you into the workspace at the first week of the semester. Once you are in the workspace, you can create your own project environment with either R or Python.
R or Python instructions and materials will be provided ad hoc.
Note that the Posit Cloud computing service is free for you but it is metered by computation hours. Please only use the service for course related computations.
The advantage of cloud computing is that you don’t need to worry about installation and updates, and I can fix any errors remotely. If you are interested in doing your own computation on your own machine, you can install R or Python environments yourself through R Studio or Jupyter.
This course delves into the practical applications of linear algebra across various disciplines. Students will explore fundamental concepts such as systems of linear equations, matrices, determinants, vector spaces, linear transformations, eigenvalues, and eigenvectors. Additionally, the course covers basic numerical algorithms for matrix computations. The course goes beyond theoretical foundations to address real-world challenges in applied mathematics, engineering, physics, biology, or other scientific disciplines. Through an applied and project-based approach, students will develop a comprehensive understanding of how linear algebra plays a crucial role in solving complex problems and optimizing processes across diverse fields. Emphasis will be placed on practical problem-solving, encouraging students to apply theoretical knowledge to real-world scenarios. This course equips students with valuable skills applicable to a broad spectrum of industries and research areas, fostering a multidisciplinary perspective.
By the end of the semester, you will be able to:
Upon completion of the course, you will be able to:
Dr. Alex John Quijano
- Walk-in Monday to Thursday at 4:00 PM - 5:00 PM, Buckley Center 279
- One-to-One, Buckley Center 279 or in Teams
Click on the link to sign-up for a 15-minute session.
My walk-in help hours start week 2. Note that you can bring a fellow student with you when you sign-up for a session. Just click the “Add Guests” link when you sign-up, and add in your fellow student’s UP email. If you need more than 15 minutes, you can book at least two consecutive sessions.
Students can get academic assistance through Learning Commons tutoring services and workshops. The Co-Pilot peer tutoring program provides students with opportunities to work with other students to get help in writing, math, group projects, and other courses. Schedule an appointment to meet with a Co-Pilot (tutor) by visiting the Learning Commons website. Students can also meet with a Co-Pilot during drop-in hours. Check the Learning Commons website or drop by the Learning Commons in BC 163 to learn more about their services. Find a tutor at the Learning Commons to get support on your academic journey.
Appointment-based tutoring accepts appointments starting week 1 and sessions start week 2. Visit the Math Resource Center website to sign-up for an appointment. Drop-in tutoring is Monday to Thursday, 3:00 PM - 7:00 PM in BC 163 and starts week 2. Check the Math Resource Center website or drop by the center for more information.
It is strongly recommended that you attend the walk-in help hours or set up a one-to-one meeting with the me if you feel like you are falling behind during our in-person class activities, or if you just need to clarify concepts discussed in class. In order to be more productive during a one-to-one meeting (or the walk-in help hours), these are three recommendations before you come in:
Note that these are recommendations so that you can get the most out of the help hours allocated for you. If you just want to come in and chat about something else, feel free to do so. If the dedicated time for one-to-one meeting does not work for you, send me a message to set up an appointment.
I expect you to participate in the class through lectures, discussion, labs, and other engagements. I also expect you to make use of opportunities to get help outside of class (help hours, Teams, email, tutoring) if you need help. Concise and specific messages are the most helpful so I know how I can best help you.
Students are encouraged to participate in discussions with their peers (or each other) regarding homework and other assignments. However, each student must take responsibility and ownership of their work and submit their work individually.
Student work products for this course may be used by the University for educational quality assurance purposes.
Learning mathematics takes hard work, thinking what you have learned, and making changes to your understanding. Students will be assessed on their proficiency in mathematics, and they will have opportunities to demonstrate their proficiency, revise their work and reflect on their learning.
This course follows the standards-based grading system which focuses on the mastery of specific learning standards. It is more accurate and motivating than traditional grading systems, and can help to create a more equitable learning environment. Here are some of the key features of this type of grading:
Each assignment will be graded according to the general grading guide detailed below. Each student will be given feedback on their assignment and learning process to improve their performance. Note that each assignment has its own rubric guided by these general guidelines and the assignment’s learning objectives.
Given the following categorical grade, the student’s work is able to:
| Grade | Rubric Description |
|---|---|
| Outstanding (O) |
Demonstrate full understanding of material, clearly and concisely explains concepts, applies them to solve problems correctly and efficiently, and may extend concepts to new situations. |
| Excellent (E) |
Show approximate understanding of material, may have made minor errors but can correct them and explain reasoning, solves problems correctly, and may need more time or practice for efficiency. |
| Acceptable (A) |
Show some understanding of material but makes errors, can solve some problems, may need help with more difficult ones, need to work on problem-solving skills and reasoning needed. |
| Needs Improvement (NI) |
Show potential but needs more work, made a lot of errors or unable to solve any problems, need to work on understanding material and problem-solving skills. |
| Needs Major Improvement (NMI) |
Little understanding of material and some parts are incomplete or missing. Made many errors, unable to solve any problems, need to work on understanding material from the ground up. |
| Incomplete (I) |
No work submitted or blank. |
Note that these are categorical grades (not scores)
| Assignment | Rank | Grade | A | B | C | D |
|---|---|---|---|---|---|---|
| Project Phases | 1 | O | 70% | - | - | - |
| E | - | 60% | - | - | ||
| A | - | - | 50% | - | ||
| NI | - | - | - | 40% | ||
| Homeworks | 2 | O | 100% | - | - | - |
| E | - | 90% | - | - | ||
| A | - | - | 80% | - | ||
| NI | - | - | - | 70% | ||
| Worksheets | 3 | Completed | 90% | 80% | 70% | 60% |
The above table shows the percent of given assignments. These percentages are minimum requirements for each letter grade. The rank determines the importance of each assignment where 1 means high rank and 3 means low rank.
The percentages in the table are not set in stone. I will evaluate your overall performance, including your self-assessments, when making decisions. I will never raise the standards outlined in the table, but I may round down the minimum percentages to help you succeed.
Decisions about +/- cutoffs will be based on two things: your performance on the final project presentation and your overall achievements.
You can submit your assignments physically or online through Gradescope. If you decide to submit online, your work can be hand-written or typed, but must be uploaded as a single pdf file. If you had handwritten your answers/solutions on a physical paper, make sure to label it properly and please scan your document using a scanner app for clarity. Suggestions: “Adobe Scan” for Android or iOS.
There will be worksheets for each non-project week. The purpose of the worksheets is for in-class group work and activities. The group members must submit their completed worksheet individually by end-of-class or end-of-day. Worksheets are graded mostly on completion, and partially on correctness. Your name must exist in your worksheet and the names of your collaborators.
Homework is assigned every week and due every Friday by end-of-day, except for project weeks. You must do and submit your homework individually. Homework is graded mostly on correctness and completion.
You can revise your homework for an up-grade, meaning - for example - a grade of “NI” can be up-graded to “A”.
Here are the qualifications and requirements for homework revisions:
Here are the rules for homework revisions:
This course is focused on applying linear algebra concepts to science or engineering fields, such as data analysis, probability and statistics, and machine learning. Thus, the course requires you to complete a semester-long project that is specific and guided.
The project is an individual expository analysis that demonstrates a comprehensive understanding of the theory of linear algebra and how it applies in the practice of your chosen science or engineering field. An expository analysis project typically involves exploring and presenting a topic related to the application of linear algebra concepts in real-world scenarios.
Every semester is unique and topics can very each semester. See the Project section in the class website for more details on the project topics.
The general timeline of the project is done in four phases:
Each phase has its own specific tasks of the same chosen topic, and due date on when these tasks should be done. You must submit a written report by the time you present, and present that report to me in each phase. The one-to-one presentation allows you to demonstrate your understanding of your project verbally and receive valuable feedback. It is administered mostly in dialog style. The presentation is only ten to fifteen minutes.
As a student in this course, the table below outlines the criteria used to assess the abilities demonstrated in each phase. The final report and presentation will be evaluated comprehensively.
| Project Criteria | Description |
|---|---|
| Content Knowledge | Demonstrates a deep understanding of linear algebra concepts relevant to the project. Shows proficiency in applying mathematical principles to solve real-world problems. |
| Clarity and Organization | Presents the project in a clear and organized manner. The flow of ideas is logical, and information is presented in a structured format. |
| Methodology | Describes the methodology used to approach and solve the problem. Provides clear and concise explanations of the steps taken, including any mathematical techniques or algorithms applied. |
| Critical Thinking | Demonstrates critical thinking by analyzing the problem thoroughly, exploring alternative solutions, and justifying the chosen approach. Considers the implications of the results and potential improvements. |
| Presentation Skills | Delivers a well-prepared and engaging presentation. Speaks clearly, maintains good eye contact, and effectively uses visual aids if applicable. Captures the audience’s attention and conveys complex ideas in an accessible manner. |
| Completeness | Addresses all aspects of the project requirements. Includes relevant data, calculations, and explanations. Does not leave any critical components unanswered. |
| Adherence to Guidelines | Follows the guidelines provided for the project. Meets any specified formatting requirements, word limits, and submission deadlines. |
| Peer Evaluation (Phase 4 Only) | Participates actively in the peer evaluation process. Provides constructive feedback on peers’ projects, highlighting strengths and suggesting areas for improvement. Fairly assesses contributions of team members if applicable. |
Here are the rules for the project phase presentations:
The grade you will receive for the project phases are a breakdown of the above criteria with detailed feedback.
Here is how you can sign-up for a one-to-one project phase presentation:
- ALA Project Phase Presentation
Click on the link to sign-up for a 15-minute session.
Your reports can be revised and must present those revisions to me on the next Project Phase. Revisions allows you to have your project phases up-graded, meaning - for example - a grade of “NI” can be up-graded to “A”.
Here are the qualifications for phase revisions:
Here are the rules for phase revisions:
You can make-up your phase presentations due to extenuating circumstances. Please let me know if you can’t make it to a phase presentation day. If you missed a phase presentation day, please let me know as soon as possible to discuss the next steps.
Here are the rules of make-up project phase presentations:
Here is how you can sign-up for a make-up project phase presentations:
- ALA Make-Up Project Phase Presentation
Click on the link to sign-up for a 15-minute session.
The final project phase (Phase 4) requires you to present your work to the entire class and possibly guests - this includes a peer review worksheet that must be submitted in class. Previous Phase revisions are not allowed during finals week.
The final presentations are on:
- Section A: May 1, Th 10:30 PM - 12:30 PM, Franz Hall 018
You can cancel your appointments, but it is strongly recommended that you cancel 12 hours before your scheduled time so that other students can schedule when a spot opens. You can reschedule for a different day and time if you need to.
Please try to show-up to any of your appointments. If you have extenuating circumstances, please let me know as soon as possible to discuss next steps.
Attendance is not tracked. However, participation is highly recommended. You are expected to actively participate in this class. Participation includes coming to class on time, being prepared, being willing to ask questions and share ideas, setting up study groups outside of class, attending tutoring sessions, posting helpful resources online, and contributing to the Teams discussion channels. Group and individual presentations of ideas is a suggested component of participation.
Generally, students are expected to attend all class sessions according to the instructor’s direction. Students who feel unwell should NOT attend class in person. These students should inform their instructor as soon as possible.
Should the instructor need to miss class, the course may be temporarily conducted remotely. Should the instructor be unable to teach for an extended period of time, the respective department or unit will find a substitute to continue the course.
You are expected to turn in all completed assignments on time. Circumstances that may disallow you to turn in your work on time - such as a medical reason - are understandable. Please let me know if you are unable to submit your work and have missed the deadline way beyond its original posted date. Because every assignment is an important aspect of your learning in this class, we will discuss when you will turn in the assignment as well as decide upon an acceptable consequence for your turning it in late. I am committed to successfully helping you learn from this course.
In the study of natural and mathematical sciences, often perceived as objective disciplines aimed at understanding the world, it is crucial to recognize the historical biases embedded within these fields, stemming from a limited set of privileged populations. Acknowledging the potential existence of overt and covert biases within the course, I emphasize that science is a human endeavor necessitating the incorporation of diverse experiences in the pursuit of knowledge and skill. Valuing every student irrespective of background, origin, race, religion, ethnicity, sexual orientation, disability status, etc., I am committed to fostering an inclusive climate throughout the course. Encouraging open communication about concerns or challenges, I assure confidentiality, except for instances of academic integrity violations or sexual harassment, which are legally mandated to be reported. Within our classroom, diversity and individual differences are celebrated as strengths, and the use of mathematics as an analytical tool to challenge power, privilege, and oppression is supported. It is our collective responsibility to create a welcoming space where ideas can be challenged while maintaining respect for individuals.
The University of Portland strives to make its courses and services fully accessible to all students. Students are encouraged to discuss with their instructors what might be most helpful in enabling them to meet the learning goals of the course. Students who experience a disability are also encouraged to use the services of the Office for Accessible Education Services (AES), located in the Shepard Academic Resource Center (503-943-8985). If you have an AES Accommodation Plan, you should meet with your instructor to discuss how to implement your plan in this class. Requests for alternate location for exams and/or extended exam time should, where possible, be made two weeks in advance of an exam, and must be made at least one week in advance of an exam. Also, if applicable, you should meet with your instructor to discuss emergency medical information or how best to ensure your safe evacuation from the building in case of fire or other emergency. All information that students provide regarding disability or accommodation is confidential. All students are responsible for completing the required coursework and are held to the same evaluation standards specified in the course syllabus.
The University of Portland is a diverse academic community of learners and scholars who are dedicated to freely sharing ideas and engaging in respectful discussion of those ideas to discover truth. Such pursuits require each person, whether student or faculty, to present truthfully our own ideas and give credit to others for the ideas that they generate. Thus, cheating on exams, copying another student’s assignment, including homework, or using the work of others without proper citation are some examples of violating academic integrity.
Especially for written and oral assignments, students have an ethical responsibility to properly cite the authors of any books, articles, or other sources that they use. Students should expect to submit assignments to Turnitin, a database that ensures assignments are original work of the student submitting. Each discipline has guidelines for how to give appropriate credit, and instructors will communicate the specific guidelines for their discipline.
The use of artificial intelligence (AI) tools such as ChatGPT without attribution also constitutes plagiarism. Students must cite any AI-generated text and ideas and disclose any activities (e.g. brainstorming, editing, translating, etc.) for which AI was employed. Students are expected to demonstrate sound judgment in discerning when and how to utilize AI ethically across their academic work, upholding standards of citation, originality, and integrity. The misuse of AI to shortcut academic requirements will be considered a breach of academic integrity. Students who have questions about when and how to use AI should talk with their instructor.
In your written work for this course, you must cite all sources of information that you use, whether they are direct quotes, paraphrases, or summaries. The style of citation that you use should be consistent throughout your paper. The citation styles for this course are APA or CSE.
If you are unsure which citation style to use, please consult with me. You can also find more information about APA and CSE style in the Clark Library citation guidelines: libguides.up.edu/cite
Plagiarism is the act of using someone else’s work without giving them credit. It is a serious academic offense that can result in a failing grade or even expulsion from school. By following these guidelines, you can help to avoid plagiarism and ensure that your work is properly cited.
Anyone may sometimes experience problems with their mental health that interfere with academic experiences and negatively impact daily life. If you or someone you know experiences mental health challenges at UP, please contact the University of Portland Wellness Center in the lower level of Orrico Hall (down the hill from Franz Hall and near Mehling Hall) at 503-943-7134 or wellness@up.edu. Their services are free and confidential. In addition, confidential phone counseling is available at the Pilot Helpline by calling 503-943-7134 and pressing 3. The University of Portland Campus Safety Department (503-943-4444) also has personnel trained to respond sensitively to mental health emergencies at all hours. Remember that getting help is a smart and courageous thing to do - for yourself, for those you care about, and for those who care about you.
The University of Portland is committed to fostering a safe and respectful community free from all forms of violence. Violence of any kind, and in particular acts of power-based personal violence, are inconsistent with our mission. Together, all UP community members must take a stand against violence. Learn more about what interpersonal violence looks like, campus and community resources, UP’s prevention strategy, and what we as individuals can do to assist on the Green Dot website, www.up.edu/greendot. Further information and reporting options may be found on the Title IX website, www.up.edu/titleix.
The University of Portland is a community dedicated to the investigation and discovery of processes for thinking ethically and encouraging the development of ethical reasoning in the formation of the whole person. Using information ethically, as an element in open and honest scholarly endeavors, involves moral reasoning to determine the right way to access, create, distribute, and employ information, including: considerations of intellectual property rights, fair use, information bias, censorship, and privacy. More information can be found in the Clark Library’s guide to the Ethical Use of Information at libguides.up.edu/ethicaluse.