The article "Scientific Discovery Learning with Computer Simulations" by Ton de Jong and Wouter R. van Joolingen reviews the effectiveness and efficiency of discovery learning in simulation environments, highlighting the challenges learners face and proposing instructional support strategies to overcome these issues. Discovery learning, a constructivist approach, emphasizes active learner engagement and problem-solving. Computer simulations, which can be conceptual or operational, are particularly suited for this type of learning. However, learners often struggle with hypothesis generation, experiment design, data interpretation, and learning regulation. The authors identify specific problems such as the tendency to choose safe hypotheses, inefficient experimentation, and difficulty interpreting data. They also discuss various instructional support measures, including direct access to domain knowledge, hypothesis generation support, experiment design hints, prediction tools, and regulatory processes like planning and monitoring. Studies show that combining simulations with these supports can enhance learning outcomes, though the effectiveness varies depending on the complexity of the simulation and the learners' prior knowledge. The article concludes by emphasizing the need for structured and guided approaches to support learners in scientific discovery learning.The article "Scientific Discovery Learning with Computer Simulations" by Ton de Jong and Wouter R. van Joolingen reviews the effectiveness and efficiency of discovery learning in simulation environments, highlighting the challenges learners face and proposing instructional support strategies to overcome these issues. Discovery learning, a constructivist approach, emphasizes active learner engagement and problem-solving. Computer simulations, which can be conceptual or operational, are particularly suited for this type of learning. However, learners often struggle with hypothesis generation, experiment design, data interpretation, and learning regulation. The authors identify specific problems such as the tendency to choose safe hypotheses, inefficient experimentation, and difficulty interpreting data. They also discuss various instructional support measures, including direct access to domain knowledge, hypothesis generation support, experiment design hints, prediction tools, and regulatory processes like planning and monitoring. Studies show that combining simulations with these supports can enhance learning outcomes, though the effectiveness varies depending on the complexity of the simulation and the learners' prior knowledge. The article concludes by emphasizing the need for structured and guided approaches to support learners in scientific discovery learning.