Kun Li

Educational Technology Specialist

Duke University

Biography

I design and develop online courses with subject matter experts in higher education. I work on educational data mining projects. I conduct research based on learning sciences and instructional design models.

My research interests include applying theories in learning science into real education settings, self-regulated learning in online environments and designing engaging personalized learning experiences for all learners.

Interests

Increasing learner motivation
Promoting self-regulated learning
Designing engaging learning environment

Education

Ph.D. in Instructional Technology

Ohio University
M.Ed. in Computer Technology Education

Ohio University
B.Sc. in Computer Science

Xidian University, China

Publications

More Publications

Kun Li, Dorian A. Canelas (2019). Learners’ Perceptions and Experiences of Two Chemistry MOOCs: Implications for Teaching and Design. American Journal of Distance Education.

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Kun Li (2019). MOOC learners’ demographics, self-regulated learning strategy, perceived learning and satisfaction: A structural equation modeling approach. Computers & Education.

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Kun Li, David R. Moore (2018). Motivating students in Massive Open Online Courses (MOOCs) using the Attention, Relevance, Confidence, Satisfaction (ARCS) model. Journal of Formative Design in Learning.

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Kun Li, John M. Keller (2018). Use of the ARCS model in education: A literature review. Computers & Education.

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Kun Li, Kent Darr, Fei Gao (2018). Enriching classroom learning through a microblogging-supported activity. E-Learning and Digital Media.

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Kun Li (2017). Motivational design in chemistry MOOCs: Applying the ARCS model. Online approaches to chemical education.

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Heather B. Shapiro, Clara H. Lee, Noelle E. Wyman Roth, Kun Li, Mine Çetinkaya-Rundel, Dorian A. Canelas (2017). Understanding the massive open online course (MOOC) student experience: An examination of attitudes, motivations, and barriers. Computers & Education.

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Kun Li, Kim Manturuk (2017). Pathways for affective learning in Massive Open Online Courses. Educause Review.

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Kun Li, Yanju Li, Teresa Franklin (2016). Preservice Teachers’ Intention to Adopt Technology in Their Future Classrooms. Journal of Educational Computing Research.

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Kun Li, Niamboue Bado, Jamie Smith, David Moore (2013). Blogging for teaching and learning: An examination of experience, attitudes, and levels of thinking. Contemporary Educational Technology.

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Talks

Reconsidering instructional design with Web 2.0 technologies

Mar 6, 2012

SITE International Conference

Teaching

Technology Applications in Education
- In College of Education at Ohio University
- As the teacher of record for three quarters
- A series of Web 2.0 tools to pre-service teachers
- Applications in the classroom
- Implemented engaging learning activities.
Learning sciences theories for a communication course
- In Physical Therapy Division at Duke University
- As the topic instructor
- Information processing theory and cognitive load theory
- Instructional videos in a flipped class mode
- Designed application and higher level assessment.

Contact

kl195@duke.edu
311 Trent Drive, Duke University, Durham 27710, USA