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Youngjin Lee

Title: Associate Professor

Department: Learning Technologies

College: College of Information

Curriculum Vitae

Curriculum Vitae Link

Education

  • PhD, University of Illinois at Urbana-Champaign, 2003
    Major: Education
    Specialization: Educational Computing
  • MEd, Seoul National University, 1996
    Major: Science Education
  • BS, Seoul National University, 1994
    Major: Earth Science

Current Scheduled Teaching

LTEC 6950.436Doctoral DissertationSpring 2025
LTEC 6510.001Introduction to Research in Learning TechnologiesSpring 2025
LTEC 6510.430Introduction to Research in Learning TechnologiesSpring 2025
LTEC 6900.436Special Problems in Learning TechnologiesSpring 2025
LTEC 3260.420Web AuthoringSpring 2025
LTEC 5420.420Web AuthoringSpring 2025
LTEC 5702.420Applications of Artificial Intelligence in Learning AnalyticsFall 2024
LTEC 3530.420Data CommunicationsFall 2024 Syllabus
LTEC 6950.436Doctoral DissertationFall 2024

Previous Scheduled Teaching

LTEC 5610.001Analysis of Research in Learning TechnologiesSpring 8W2 2024 SPOT
LTEC 6510.030Introduction to Research in Learning TechnologiesSpring 2024 SPOT
LTEC 5310.020Human Computer InteractionFall 2023 SPOT
LTEC 6500.030Introduction to Quantitative Research in Learning TechnologiesFall 2023 SPOT
LTEC 6950.736Doctoral DissertationSummer 10W 2023
LTEC 6950.736Doctoral DissertationSpring 2023
LTEC 6510.030Introduction to Research in Learning TechnologiesSpring 2023 SPOT
LTEC 3260.020Web AuthoringSpring 2023 Syllabus SPOT
LTEC 5420.020Web AuthoringSpring 2023 SPOT
LTEC 5610.020Analysis of Research in Learning TechnologiesFall 8W2 2022 SPOT
LTEC 6950.706Doctoral DissertationFall 2022
LTEC 6950.736Doctoral DissertationFall 2022
LTEC 6800.031Special Topics in Learning TechnologiesFall 2022 SPOT
LTEC 6950.736Doctoral DissertationSummer 10W 2022
LTEC 5610.020Analysis of Research in Learning TechnologiesSpring 8W2 2022 SPOT
LTEC 6511.020Analysis of Research in Learning TechnologiesFall 2021 SPOT
LTEC 6511.030Analysis of Research in Learning TechnologiesFall 2021 SPOT
LTEC 6511.040Analysis of Research in Learning TechnologiesFall 2021 SPOT
LTEC 6950.706Doctoral DissertationFall 2021
LTEC 6950.736Doctoral DissertationFall 2021
LTEC 6950.756Doctoral DissertationFall 2021
LTEC 6514.001Seminar on Advanced Research Topics in Learning Technologies and Information SciencesFall 2021 SPOT
LTEC 6514.030Seminar on Advanced Research Topics in Learning Technologies and Information SciencesFall 2021 SPOT
LTEC 6950.736Doctoral DissertationSummer 10W 2021
LTEC 6950.756Doctoral DissertationSummer 10W 2021
LTEC 5421.020Advanced Web and Media DevelopmentSpring 2021 SPOT
LTEC 5421.026Advanced Web and Media DevelopmentSpring 2021 SPOT
LTEC 5610.020Analysis of Research in Learning TechnologiesSpring 8W2 2021 SPOT
LTEC 6950.706Doctoral DissertationSpring 2021
LTEC 5610.020Analysis of Research in Learning TechnologiesFall 8W2 2020 SPOT
LTEC 5610.080Analysis of Research in Learning TechnologiesFall 8W2 2020 SPOT
LTEC 6950.706Doctoral DissertationFall 2020
LTEC 6514.001Seminar on Advanced Research Topics in Learning Technologies and Information SciencesFall 2020 SPOT
LTEC 6514.030Seminar on Advanced Research Topics in Learning Technologies and Information SciencesFall 2020 SPOT
LTEC 6950.706Doctoral DissertationSummer 10W 2020
LTEC 6950.706Doctoral DissertationSpring 2020
LTEC 6480.020Research SeminarSpring 2020
LTEC 6900.706Special Problems in Learning TechnologiesSpring 8W2 2020
LTEC 6800.030Special Topics in Learning TechnologiesSpring 2020
LTEC 6800.040Special Topics in Learning TechnologiesSpring 2020
LTEC 5510.020Technology Based Learning EnvironmentsSpring 2020
LTEC 5510.080Technology Based Learning EnvironmentsSpring 2020
LTEC 6514.001Seminar on Advanced Research Topics in Learning Technologies and Information SciencesFall 2019 SPOT
LTEC 6514.030Seminar on Advanced Research Topics in Learning Technologies and Information SciencesFall 2019 SPOT
LTEC 6514.040Seminar on Advanced Research Topics in Learning Technologies and Information SciencesFall 2019 SPOT

Published Intellectual Contributions

    Book Chapter

  • Hsu, Y., Meyen, E., Lee, Y. (2018). Understanding emotional analytics for student engagement: An instructional visual design perspective. Student-centered virtual learning environments in higher education. 70-102. Hershey, PA,
  • Conference Proceeding

  • Carter, E.S., Cockerham, D.P., Lee, Y. (2024). Gamification in the Undergraduate Chemistry Course: A Systematic Review. Society for Information Technology & Teacher Education International Conference. 1808–1811. Waynesville, NC, Association for the Advancement of Computing in Education (AACE). https://www.learntechlib.org/primary/p/224214/
  • Journal Article

  • Goodman, A., Lee, Y., Elieson, S., Knezek, G. (2024). Using self-regulated learning theory and learning analytics to identify explanatory variables affecting learning outcomes in online/hybrid undergraduate calculus. Journal of Computers in Mathematics and Science Teaching. 42 (2) 125-154. Waynesville, NC, Association for the Advancement of Computing in Education.
  • Lee, Y. (2023). The effect of course format change on learning behaviors and performance of students. International Journal on E-Learning. 22 (2) 159-176. Waynesville, NC, Association for the Advancement of Computing in Education.
  • Lee, Y. (2022). Identifying prerequisite courses in undergraduate biology using machine learning. Journal of Data Science. (1-16) 1–16.
  • Wang, X., Lee, Y., Lin, L., Mi, Y., Yang, T. (2021). Analyzing instructional design quality and students’ reviews of 18 courses out of the Class Central Top 20 MOOCs through systematic and sentiment analyses. The Internet and Higher Education. 50 100810.
  • A, L., Lee, Y. (2020). College students' perception of pleasure in learning: Designing gameful educational gamification. International Journal on E-Learning. 19 (2) 93–123.
  • Lee, Y. (2019). Estimating student ability and problem difficulty using Item Response Theory (IRT) and TrueSkill. Information Discovery and Delivery. 47 (2) 67-75.
  • Gu, P., Lee, Y. (2019). Promoting students' motivation and use of SRL strategies in the Web-based mathematics learning environment. Journal of Educational Technology Systems. 47 (3) 391-410.
  • Lee, Y. (2018). Effect of uninterrupted time-on-task on students’ success in Massive Open Online Courses (MOOCs). Computers in Human Behavior. 86 174-180.
  • Lee, Y. (2018). Using Self-Organizing Map (SOM) and clustering to investigate problem solving patterns in the Massive Open Online Course (MOOC): An exploratory study. Journal of Educational Computing Research. 57 (2) 471-490.
  • Lee, Y. (2017). Modeling students’ problem solving performance in the computer-based mathematics learning environment. International Journal of Information and Learning Technology. 34 (5) 385-395.
  • Sullivan, D.K., Goetz, J.R., Gibson, C.A., Mayo, M.S., Washburn, R.A., Lee, Y., Ptomey, L.T., Donnelly, J.E. (2016). A virtual reality intervention (Second Life) to improve weight maintenance: Rationale and design for an 18-month randomized trial. Contemporary Clinical Trials. 46 77–84.
  • Lee, Y. (2016). Predicting students' problem solving performance using Support Vector Machine. Journal of Data Science. 14 231–244.
  • Lee, Y. (2015). Analyzing log files to predict students’ problem solving performance in a computer-based physics tutor. Educational Technology & Society. 18 (2) 225–236.
  • Lee, Y. (2015). Developing iPad-based physics simulations that can help people learn Newtonian physics concepts. The Journal of Computers in Mathematics and Science Teaching. 34 (3) 299–325.
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Overall
Summative Rating
Challenge and
Engagement Index
Response Rate

out of 5

out of 7
%
of
students responded
  • Overall Summative Rating (median):
    This rating represents the combined responses of students to the four global summative items and is presented to provide an overall index of the class’s quality. Overall summative statements include the following (response options include a Likert scale ranging from 5 = Excellent, 3 = Good, and 1= Very poor):
    • The course as a whole was
    • The course content was
    • The instructor’s contribution to the course was
    • The instructor’s effectiveness in teaching the subject matter was
  • Challenge and Engagement Index:
    This rating combines student responses to several SPOT items relating to how academically challenging students found the course to be and how engaged they were. Challenge and Engagement Index items include the following (response options include a Likert scale ranging from 7 = Much higher, 4 = Average, and 1 = Much lower):
    • Do you expect your grade in this course to be
    • The intellectual challenge presented was
    • The amount of effort you put into this course was
    • The amount of effort to succeed in this course was
    • Your involvement in course (doing assignments, attending classes, etc.) was
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