Eric Wiebe


Professional Title: 
Associate Professor
About Me (Bio): 
Dr. Eric Wiebe is an Associate Professor of Science and Technology Education at North Carolina State University. His primary interest is in the use of graphics as a tool for communicating and learning scientific and technical information. Applications in this research includes exploring the cognitive basis of learning via multimedia instructional materials, evaluating technology as a vehicle for communication and learning technical, engineering and scientific information, and promoting graphics literacy and the application of scientific visualization in secondary and post-secondary education. He is also interested in the design and evaluation of instructional materials, especially the interaction with learners and the medium of delivery. Dr. Wiebe holds a Ph.D. in Psychology from North Carolina State University.
Citations of DRK-12 or Related Work (DRK-12 work is denoted by *): 
  • Aksit, O. & Wiebe, E. (December 2019; online). Exploring force and motion concepts in middle grades using computational modeling: A classroom intervention study. Journal of Science Education and Technology. doi: 10.1007/s10956-019-09800-z*
  • Lytle, N., Cateté, V., Boulden, D., Dong, Y., Houchins, J., Milliken, A., Isvik, A., Bounajim, D., Wiebe, E., & Barnes, T. (July, 2019). Use, Modify, Create: Comparing Computational Thinking Lesson Progressions for STEM Classes. In 24th Annual Conference on Innovation and Technology in Computer Science Education (ITiCSE 2019). Aberdeen, Scotland UK. ACM. doi: 10.1145/3304221.3319786*
  • Zakaria, Z., Wiebe, E., Boulden, D., Tsan, J., Vandenberg, J., Lynch, C. & Boyer, K. (June, 2019). Collaborative Talk Across Two Pair-Programming Configurations. In International Conference on Computer Supported Collaborative Learning (CSCL 2019). Lyon, France.*
  • Wiggins, J., Min, W., Mott, B., Wiebe, W., Boyer, K. E., & Lester, J. (June, 2019). Take the Initiative: Mixed-Initiative Dialogue Policies for Pedagogical Agents in Game-Based Learning Environments. Proceedings of the 20th International Conference on Artificial Intelligence in Education (AIED ’19).*
  • Wiebe, E., London, J., Aksit, O., Mott, B., Boyer, K. E., & Lester, J., (February, 2019). Development of a Lean Computational Thinking Abilities Assessment for Middle Grades Students. In Proceedings of the 50th ACM Technical Symposium on Computer Science Education (pp. 456-461). ACM. doi: 10.1145/3287324.3287390*
North Carolina State University (NCSU)

The project will provide the opportunity for upper elementary students to learn computer science and build strong collaboration practices. Leveraging the promise of virtual learning companions, the project will collect datasets of collaborative learning for computer science in diverse upper elementary school classrooms; design, develop, and iteratively refine its intelligent virtual learning companions; and generate research findings and evidence about how children collaborate in computer science learning and how best to support their collaboration with intelligent virtual learning companions.

Concord Consortium

This project will develop and test a digital monitoring tool that will enable teachers to track student learning within a digital learning system and quickly adjust classroom instructional strategies to facilitate learning. The tool will be developed for use with an existing digital curriculum for high school genetics.

North Carolina State University (NCSU)

This project enhances elementary students' engagement in and learning of science through visual communication skills using student-generated graphics in science notebooks. The products include two professional development modules for each grade level 2–5 that explicitly teach specific forms of graphical representation used in science, how these representations complement written and numeric information, and how teachers can promote the thoughtful reflection and discussion of these representations in small-group and whole-class settings.

North Carolina State University (NCSU)

The project designs and implements technologies that combine artificial intelligence in the form of intelligent tutoring systems with multimedia interfaces (i.e., an electronic science notebook and virtual labs) to support children in grades 4-5 learning science. The students use LEONARDO's intelligent virtual science notebooks to create and experiment with interactive models of physical phenomena.