This article discusses scientific discovery learning with computer simulations of conceptual domains. It reviews the effectiveness and efficiency of discovery learning in simulation environments and identifies problems learners may encounter. The article also explores how simulations can be combined with instructional support to overcome these problems. Scientific discovery learning is a self-directed, constructivist approach where learners infer characteristics of a model through experimentation. Computer simulations are suitable for this type of learning as they allow learners to interact with a model and observe outcomes. The article discusses different types of simulations, including conceptual and operational models, and their use in learning. It also examines the challenges learners face in discovery learning, such as generating hypotheses, designing experiments, interpreting data, and regulating learning. The article concludes that while simulations can be effective, they require instructional support to help learners overcome the challenges of discovery learning. The study highlights the importance of structured environments, planning, and monitoring in successful discovery learning. The article also discusses the role of domain knowledge and the need for learners to have prior knowledge to effectively engage in discovery learning. Overall, the article emphasizes the importance of combining simulations with instructional support to enhance learning outcomes in scientific discovery learning.This article discusses scientific discovery learning with computer simulations of conceptual domains. It reviews the effectiveness and efficiency of discovery learning in simulation environments and identifies problems learners may encounter. The article also explores how simulations can be combined with instructional support to overcome these problems. Scientific discovery learning is a self-directed, constructivist approach where learners infer characteristics of a model through experimentation. Computer simulations are suitable for this type of learning as they allow learners to interact with a model and observe outcomes. The article discusses different types of simulations, including conceptual and operational models, and their use in learning. It also examines the challenges learners face in discovery learning, such as generating hypotheses, designing experiments, interpreting data, and regulating learning. The article concludes that while simulations can be effective, they require instructional support to help learners overcome the challenges of discovery learning. The study highlights the importance of structured environments, planning, and monitoring in successful discovery learning. The article also discusses the role of domain knowledge and the need for learners to have prior knowledge to effectively engage in discovery learning. Overall, the article emphasizes the importance of combining simulations with instructional support to enhance learning outcomes in scientific discovery learning.