MTH008 Syllabus

Author

Jiaye Xu

1 Course Information

  • MTH008 Multivariable Calculus for Science and Engineering – Spring 2026

    • Class-Group Code: MTH008 G14 & G16

    • 课程名称：多元微积分 (理工类)

  • Instructor: Dr. Jiaye Xu (徐嘉烨)

  • Lecture Time:

    • G14 Tuesday 11:00 a.m. - 12:50 p.m., Friday 11:00 a.m. - 12:50 p.m.

    • G16 Tuesday 3:00 - 4:50 p.m., Thursday 1:00 - 2:50 p.m.

  • Location: SIP-FB 396. (基础楼396)

  • Office Hours: Thursday 3:00 - 5 p.m, Friday 1:00 - 3:00 p.m.

2 Textbooks

D. Varberg, E. Purcell, S. Rigdon. Calculus Early Transcendentals. Pearson Education Asia Limited, 2018.

N.B. Please check the Learning Mall Core page for further details of the syllabus. And the PDF file Teaching Plan for MTH008 under the section of MHT008 Module Handbook on the course page is the final version of teaching schedule.

3 Assessment

  1. Course Works (25%): Weekly Assignments (1.5% * 10) + Online Assignments (5% * 2)

  2. Midterm (15%): Week 7

  3. Final Exam (60%)

4 Outline of Lectures

Week and Lecture Suggested Reading Lecture Notes
Week 1 sec. 11.1 - 11.3 Chapter 11 Geometry in Space and Vectors
Week 2 sec 11.4 - 11.6
Week 3

sec 11.8;

sec12.1-12.2

 Chapter 12 Derivatives for Multivariable Functions
Week 4

sec 12.3 -12.4;

sec 12.6
Week 5

sec 12.5, 12.7;

sec 12.8
Week 6 D1 D1 lecture is flexible due to holiday. Lecture Notes on Introduction to Data Science.
Week 6 D2 sec 12.9
Week 7 sec 13.1 - 13.3 Chapter 13 Multiple Integrals
Week 8

sec 13.4;

sec 13.6 - 13.7
Week 9 D1 sec 11.9, sec 13.8
Week 9 D2 D2 lecture is flexible due to holiday. Lecture Notes on Introduction to Data Science.
Week 10 D1 sec 13.9, 14.1
Week 10 D2 sec 9.1 - 9.2 Chapter 9 Infinite Sequences
Week 11

sec 9.3 - 9.4;

sec 9.5
Week 12 sec 9.6 - 9.8
Week 13

sec 9.9;

review

5 Why Calculus Courses?

  • Compulsory Course: Pre-Major, 5 Credits.

  • Solid Foundation for Domain Science: down the road of math courses, differential equations, probability, statistics, mathematical modelling. Toolkit for the domain science, engineering, data science, business, economics, social sciences etc.

  • Rigorous Scientific Training and Problem Solving Techniques: Stay strong!

6 Learning Resources

  • Textbook: Pre-class reading, browse; Post-class reading, thoroughly.

  • In-Class Notes: Derivations, examples, sketching graphs etc. are shown manually on board in the lecture. Chalk-n-Talk works in math education.

  • Learning Mall Core: Lecture notes of the current semester.

  • Online Resources: There are loads of learning material out there.

    • Lecture videos from self-learning/teaching platforms, e.g., MIT OCW, 3B1B, Coursera, Khan Academy;

    • Lecture videos with Chinese subtitle on, say, Bilibili. Math problems could be, in essence, English problems. Be aware of the terminologies in English and math notations!

  • Practice Problems: homework, problem sets in textbook. Learn by doing!

  • Get Help: Group Study, Office Hours. Learn by explaining!

7 Academic Integrity

This is REALLY important! Please read this document XJTLU Academic Integrity Policy carefully. And remember that: No Copying or Collusion!