Li Xu
- Professor, College of Applied Science and Technology
- Member of the Graduate Faculty
- (520) 458-8278
- UNIVERSITY OF ARIZONA SOUTH
- SIERRA VISTA, AZ 85635-0000
- lxu@arizona.edu
Biography
I am a professor in Computer Science at the University of Arizona South. I attended Shandong University in China as an undergraduate, and the University of Science and Technology of China for a MS in Computer Science. I obtained my PhD in Computer Science at Brigham Young University. In 2003, I became a faculty member at the University of Arizona South. My research interests include computational thinking, programming, data management, machine learning, and computer science education.
Degrees
- Ph.D. Computer Science
- Brigham Young University, Provo, Utah, United States
- M.S. Computer Science
- University of Science and Technology in China, Hefei, Anhui, China
- B.S. Computer Science
- Shandong University, Jinan, Shandong, China
Work Experience
- University of Arizona South (2016 - Ongoing)
- University of Arizona South (2009 - 2016)
- University of Arizona South (2003 - 2009)
Awards
- Best Graduate Honor
- Shandong University, China, Fall 1994
- 2023 CUES Distinguished Fellow
- Summer 2023
- Verified Cerficate on Completing "Probability-The Science of Uncertainty and Data"
- MITx, an online learning initiative of the Massachusetts Institute of Technology, Fall 2022
- Take a Bow: Meet our Honorees
- Fall 2021
- Superior Faculty Award
- University of Arizona South, Fall 2013
- UA South Superior Faculty Award
- Fall 2013
- Scholarship for Managing the Academic Career for Faculty Women at Undergraduate Computer Science and Engineering Institutions Workshop
- ACM Women, Fall 2011
- Educator Scholarship
- 2005 ACM SIGPLAN International Conference on Object-Oriented Programming, Systems, Languages and Applications (OOPSLA 2005), Fall 2005
Interests
Teaching
Computational thinking and doing, programming languages, operating systems, compilers and system software, object oriented programming and design, system programming and UNIX, database systems, artificial intelligence, data structures, etc.
Research
Computer Science education, database systems, computational thinking and doing.
Courses
2024-25 Courses
-
Computational Thinking & Doing
APCV 320 (Fall 2024) -
Data Analysis & Visualization
APCV 361 (Fall 2024)
2023-24 Courses
-
Computational Thinking & Doing
APCV 320 (Summer I 2024) -
Data Fluency for All
APCV 303 (Summer I 2024) -
Computational Thinking & Doing
APCV 320 (Spring 2024) -
Data Analysis & Visualization
APCV 361 (Spring 2024) -
Data Analysis & Visualization
APCV 361 (Fall 2023) -
Mobile Device Programming
CSCV 381 (Fall 2023)
2022-23 Courses
-
Computational Thinking & Doing
APCV 320 (Summer I 2023) -
Database Design
CSCV 460 (Summer I 2023) -
Computational Thinking & Doing
APCV 320 (Spring 2023) -
Data Analysis & Visualization
APCV 361 (Spring 2023) -
Data Analysis & Visualization
APCV 361 (Fall 2022) -
Mobile Device Programming
CSCV 381 (Fall 2022)
2021-22 Courses
-
Computational Thinking & Doing
APCV 320 (Summer I 2022) -
Database Design
CSCV 460 (Summer I 2022) -
Data Analysis & Visualization
APCV 361 (Spring 2022) -
Prin Operating Systems
CSCV 452 (Spring 2022) -
Data Analysis & Visualization
APCV 361 (Fall 2021) -
Mobile Device Programming
CSCV 381 (Fall 2021)
2020-21 Courses
-
Computational Thinking & Doing
APCV 320 (Summer I 2021) -
Database Design
CSCV 460 (Summer I 2021) -
Computational Thinking & Doing
APCV 320 (Spring 2021) -
Prin Operating Systems
CSCV 452 (Spring 2021) -
Compilers+Systems Sftwr
CSCV 453 (Fall 2020) -
Data Analysis & Visualization
APCV 361 (Fall 2020) -
Mobile Device Programming
CSCV 381 (Fall 2020)
2019-20 Courses
-
Computational Thinking & Doing
INFV 320 (Summer I 2020) -
Database Design
CSCV 460 (Summer I 2020) -
Database Design
CSCV 460 (Spring 2020) -
Prin Operating Systems
CSCV 452 (Spring 2020)
2018-19 Courses
-
Computational Thinking & Doing
INFV 320 (Summer I 2019) -
Mobile Device Programming
CSCV 381 (Summer I 2019) -
Database Design
CSCV 460 (Spring 2019) -
Introduction to Informatics
INFV 310 (Spring 2019) -
Prin Operating Systems
CSCV 452 (Spring 2019) -
Compar Programming Lang
CSCV 372 (Fall 2018) -
Compilers+Systems Sftwr
CSCV 453 (Fall 2018) -
Independent Study
CSCV 499 (Fall 2018)
2017-18 Courses
-
Mobile Device Programming
CSCV 381 (Summer I 2018) -
Database Design
CSCV 460 (Spring 2018) -
Independent Study
CSCV 499 (Spring 2018) -
Senior Capstone
INFV 498 (Spring 2018) -
Web Programming
CSCV 337 (Spring 2018) -
Compar Programming Lang
CSCV 372 (Fall 2017) -
Compilers+Systems Sftwr
CSCV 453 (Fall 2017) -
Computational Thinking & Doing
INFV 320 (Fall 2017) -
Independent Study
CSCV 399 (Fall 2017) -
Internship
INFV 393 (Fall 2017)
2016-17 Courses
-
Database Design
CSCV 460 (Summer I 2017) -
Mobile Device Programming
CSCV 381 (Summer I 2017) -
Computational Thinking & Doing
INFV 320 (Spring 2017) -
Database Design
CSCV 460 (Spring 2017) -
Senior Capstone
INFV 498 (Spring 2017) -
Compar Programming Lang
CSCV 372 (Fall 2016) -
Independent Study
INFV 399 (Fall 2016) -
Prin Operating Systems
CSCV 452 (Fall 2016)
2015-16 Courses
-
Database Design
CSCV 460 (Summer I 2016) -
Internship
INFV 393 (Summer I 2016) -
Mobile Device Programming
CSCV 381 (Summer I 2016) -
Analysis Discrete Struct
CSCV 345 (Spring 2016) -
Computational Thinking & Doing
INFV 320 (Spring 2016) -
Independent Study
CSCV 399 (Spring 2016) -
Independent Study
CSCV 499 (Spring 2016) -
Senior Capstone
INFV 498 (Spring 2016)
Scholarly Contributions
Journals/Publications
- Xu, L. (2015). Learning Computational Thinking Online: A Student-Centered, Participatory Approach. Computer Science Education & Computer Science Research Journal, 11.More infoWing[1] proposed Computational Thinking (CT) as a fundamental skill to everyone. In this paper, we present a study of an online course development that aimed to facilitate a student-centered, participatory approach to learn CT. Through the online class, we intended to teach CT systematically, explicitly, and deliberately. Our course-offering data shows that students effectively learned Computer Science (CS) concepts and techniques as mental tools for them to develop CT skills. During the learning process, students were motivated, challenged, and involved. Despite the reported challenges, the learning outcomes were positive---our result shows the online learning provided a unique opportunity to promote CT to undergraduate students across disciplines. [1]J.Wing.Computationalthinking.CommunicationsoftheACM,49(3),33-35, March 2006.
Proceedings Publications
- Xu, L. (2023). Use Community Problem-Solving to Engage All Students in Computational and Statistical Thinking. In CTE-STEM 2023.
- Xu, L., & Brown, S. (2023). Exploring Sense of Belonging in Online Post-Traditional Students. In EdMedia + Innovate Learning 2023.
- Xu, L. (2022). Integrating Online CURE to Engage Students in Computational and Statistical Thinking. In The 33rd annual conference of the Society for Information Technology and Teacher Education (SITE 2022).More infoProgram accreditation documents and employer requirements have verified that undergraduate students in STEM need to develop higher-order thinking and meta-cognitive skills in problem solving. In our institution, faculty identified Computational Thinking (CT) and Statistical Thinking (ST) as critical cognitive dispositions students need to adopt in our Applied Computing curriculum. However, historically students shy away from computation and statistics education. Moreover, in our institution, due to the various backgrounds of transferring students we serve and the online course deliveries we use to offer courses in Applied Computing, the transition from previous institutions to our college and study online can prove challenging to engage students into effective and productive learning. Course-based Undergraduate Research Experience (CURE) provides an effective approach to engage students into more active learning (Kuh, 2008), support students to accomplish learning outcomes and persistence (Freeman et al., 2014), and improve graduation rates and retention in STEM majors. This paper presents a course design that integrates CURE into an online course in Applied Computing. The paper addresses what topics to cover based on a course topic framework and how to achieve student learning outcomes. Additionally, the presentation also describes five effective strategies to facilitate teaching CT and ST, and get students involved into the CURE project development.
- Xu, L. (2020, April). Identifying Effective Teaching Strategies for Engaging Students on Learning Operating Systems. In The Society for Information Technology & Teacher Education (SITE 2020).
- Xu, L. (2020, May). Teaching Computational Thinking to Applied Science Majors: What and How. In International Conference of Computational Thinking Education 2020 (CTE2020).More infoThe paper was accepted. The acceptance letter is attached.
- Xu, L. (2018, June 25-29). Identifying Strategies for Teaching Computational Thinking by Problem Solving and Self-Awareness. In EdMedia 2018.
- Xu, L. (2018, March 26-30). A closer look at promoting and teaching computational thinking. In SITE 2018.
- Xu, L. (2016, November/Fall). Reflective Analysis on Teaching and Learning Computational Thinking Online. In E-Learn 2016.
- Xu, L., & Simon, F. (2016, 3/Spring). Computational Thinking In Problem Solving and Writing -How We Can Help K-12 Teachers. In SITE 2016.More infoThe paper was published in SITE 2016 Proceedings. Also, I was invited to extend the paper to publish in AACE Journals.
- Czerkawski, B. C., & Xu, L. (2012, June). Computational Thinking and Educational Technology. In ED-MEDIA 2012.
- Ding, Y., Xu, L., & Embley, D. W. (2009, March). A Model of World Wide Web Evolution. In WebSci'09: Society On-Line.
- Xu, L. (2013, October). Applying Online Learning Components to Foster Learning Operating Systems. In E-Learn 2013.
- Xu, L. (2015, October). An Online Learning Approach to Teaching Mobile Application Development. In World Conference on E-Learning (ELearn 2015).More infoThe recent steadily growing revenue and jobs in mobile application development led us to examine the traditional Computer Science (CS) curriculum we used and revise the curriculum for students to develop skills required in mobile computing. In this paper, we present an online class that supported students to conduct self-directed and hands-on learning on mobile device programming. Even though there are quite a few published research works that addressed course development on mobile application development, very few publications approached online course development on the subject. Our case study describes the course learning objectives, the programming platform, the course topics, the pedagogical methods we used to develop the course as well as the characteristics our course design has, and the two course delivery experiences that took place in summers 2014 and 2015. The course delivery experiences were positive, which shows that the online course was well accepted by students. The case study reveals that online learning provides a unique opportunity to improve CS course accessibility, and supports students to develop skills to secure quality employment and commit to life-long learning.
- Xu, L., & Czerkawski, B. C. (2012, October). Designing Online Course Components to Infuse Computational Thinking in Computer Science. In E-Learn 2012.
- Xu, L., & Simon, F. (2014, March). Combining Teacher Professional Development on Computational Thinking with Writing and Problem Solving. In SITE 2014.
- Xu, L. (2014, June). Adopting a Phenomenographic Study to Design and Implement Teaching Object-Oriented Programming and Design Online. In EdMedia 2014.
Presentations
- Xu, L., & Brown, S. (2023). Examination of Sense of Belonging in Online Post-Traditional Students: What Matters and How to Foster Connections?. OCC Accelerate 2023.
- Xu, L. (2020, August). Teaching Computational Thinking to Applied Science Majors: What and How. The Fourth International Conference on Computational Thinking Education 2020.
- Xu, L. (2019, June). Computational Thinking with Programming. UA Yuma Teacher Training Week. Yuma: UA Yuma.More infoI did a computational thinking presentation in 2018 to a group of teachers in Yuma. In summer 2019, I was invited again to present and extend the topic on comptuatinal thinking with programming.
- Xu, L. (2018, June 4-8). What is Computational Thinking?. WESTERNCATS-GADSDEN Teacher Training. San Luis Technical Institute, Yuma, Arizona.More infoThe presentation introduces computational thinking, which is a higher-level thinking to teachers in K-12. In addition to address concepts in computational thinking, the presentation also used a programming language Scratch to show case how to teach computational thinking to students in K-12.
- Xu, L. (2018, March). A Closer Look at Promoting and Teaching Computational Thinking. SITE 2018. Washington, DC.
- Xu, L. (2015, June). Learning Computational Thinking Online: A Student-Centered, Partic- ipatory Approach. the 11th Annual Computer Science Education and Computer Science Conference (CSECS 2015).
- Xu, L. (2015, October). An Online Learning Approach to Teaching Mobile Application Development. World Conference on E-Learning in Corporate, Government, Healthcare, Higher Education (E-Learn 2015).
- Xu, L. (2014, June). Adopting a Phenomenographic Study to Design and Implement Teaching Object-Oriented Programming and Design Online. EdMedia 2014.
- Xu, L. (2014, March). Combining Teacher Professional Development on Computational Thinking with Writing and Problem Solving. SITE 2014.
- Xu, L., Simon, F., & Holland, L. (2014, February). Infusing Computational Thinking and Data Analysis for Teaching Improvement. i3 Grant Teacher's Professional Development Workshop. Sierra Vista, Arizona: i3 Grant, Southern Arizona Writing Project.
Creative Productions
- Xu, L. (2019. Humans, Machines, and Virtual Reality. UA Sierra Vista Campus: UA CAST and City of Sierra Vista.More infoI strongly believe that the CS educators should be responsible to engage the public audience and promote computing education across K-12. In particular, I am very interested at developing creative activities to engage the public audience and inspire them to think computationally. According to a report titled ``K-12 Computer Science Framework" by ACM, the computationally literate creators are ``proficient in the concepts and practices of computer science." To equip students with the required skills, it is necessary to successfully promote CS and computational participation to K-12 students, which would only happen when students understand and are able to identify how computing is relevant to their everyday life. To promote computational participation, in spring 2019 I worked diligently with a team of UA South faculty and staff to discuss and research engaging/inspiring topics and tools to promote computing. In particular, I did research on tools including Scratch, Ozobot, LittleBits and Virtual Reality. Based on my search, I gave presentations and delivered program demos and creative activities to two group of kids in summer 2019.