HINTS Lab
HINTS Lab
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Rui Zhi
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Adaptive, Immediate Feedback (AIF) for Novice Programmings
Example-based Feedback
Crescendo: Engaging Students to Self-Paced Programming Practices
Step Tutor: Supporting Students through Step-by-Step Example-Based Feedback
A Comparison of the Quality of Data-driven Programming Hint Generation Algorithms
Design and Evaluation of Instructional Supports for Novice Programming Environments.
Evaluating the Effectiveness of Parsons Problems for Block-based Programming
Exploring the Impact of Worked Examples in a Novice Programming Environment
One minute is enough: Early Prediction of Student Success and Event-level Difficulty during a Novice Programming Task
Toward Data-Driven Example Feedback for Novice Programming
Exploring Instructional Support Design in an Educational Game for K-12 Computing Education
Reducing the State Space of Programming Problems through Data-Driven Feature Detection
Evaluation of a Data-driven Feedback Algorithm for Open-ended Programming
Hint Generation Under Uncertainty: The Effect of Hint Quality on Help-Seeking Behavior
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