Digital Transformation of Education

InVis: An EDM Tool for Graphical Rendering and Analysis of Student Interaction Data

In S. Gutierrez-Santos & O. C. Santos (Eds.), EDM 2014 Extended Proceedings: Workshop Proceedings of the 7th International Conference on Educational Data Mining. London, United Kingdom: CEUR-WS.

Snag'em: Graph Data Mining for a Social Networking Game

In S. Gutierrez-Santos & O. C. Santos (Eds.), EDM 2014 Extended Proceedings: Workshop Proceedings of the 7th International Conference on Educational Data Mining. London, United Kingdom: CEUR-WS.

Evaluation of Logic Proof Problem Difficulty Through Student Performance Data

In S. Gutierrez-Santos & O. C (Eds.), EDM 2014 Extended Proceedings: Workshop Proceedings of the 7th International Conference on Educational Data Mining. London, United Kingdom: CEUR-WS.

Extracting temporal features using BCIpy

Proceedings of the Workshop on Utilizing EEG Input in Intelligent Tutoring Systems. Presented at the Intelligent Tutoring Systems (ITS2014), Honolulu, Hawaii.

Use and development of entertainment technologies in after school STEM program

SIGCSE '14: Proceedings of the 45th ACM technical symposium on Computer science education, 163–168.

Balancing physical and cognitive challenge: A study of players psychological responses to exergame play

Nickel, A., Barnes, T., Payton, J., & Wikstrom, E. (2014, April 3). Presented at the Foundations of Digital Games, Fort Lauderdale, FL.

Part of the game: Changing level creation to identify and filter low quality user-generated levels

Hicks, A., Cateté, V., & Barnes, T. (2014, April 3). Presented at the Foundations of Digital Games (FDG2014), Fort Lauderdale, FL.

Exploring differences in problem solving with data-driven approach maps

Educational Data Mining, 76–83.

Generating hints for programming problems using intermediate output

Educational Data Mining, 92–98.

Exploration of student's use of rule application references in a propositional logic tutor

Educational Data Mining, 249–252.

Reflections from a computational service learning trip to Haiti

The Journal of Computing Sciences in Colleges, 29(3), 43–50.

Can Diagrams Predict Essay Grades?

In Intelligent Tutoring Systems (pp. 260–265).

When Is Tutorial Dialogue More Effective Than Step-Based Tutoring?

In Intelligent Tutoring Systems (pp. 210–219).

Making games and apps in introductory computer science (abstract only)

Proceedings of the 45th ACM technical symposium on Computer science education - SIGCSE '14. Presented at the the 45th ACM technical symposium.

An investigation of the interrelationships between motivation, engagement, and complex problem solving in game-based learning.

Educational Technology & Society, 17(1), 42–53.

The influence of information technology self-leadership on product and process innovation.

Journal of Leadership and Management, 1(2), 95–109.

Metacognition

Cambridge Handbook of the Learning Sciences, 2nd Edition, 63–87.

When is tutorial dialogue more effective than step-based tutoring?

Intelligent tutoring systems, its 2014, 8474, 210–219.

Survival analysis on duration data in intelligent tutors

Intelligent tutoring systems, its 2014, 8474, 178–187.

Note-taking within MetaTutor: Interactions between an intelligent tutoring system and prior knowledge on note-taking and learning

Educational Technology Research and Development: ETR & D, 62(5), 507–528.