This research article explores the potential of leveraging cutting-edge technologies, specifically educational data mining (EDM) and simulation, to enhance authentic learning experiences in educational settings. Authentic learning is an instructional approach that emphasizes real-world application of knowledge and skills, promoting deep understanding and transferability. While the integration of technology in education has shown promising results, the use of authentic tasks and assessment methods has remained a challenge. To bridge this gap, this study proposes the adoption of educational data mining and simulation technologies to support authentic learning.
Drawing from cognitive science principles, the use of educational data mining can provide valuable insights into students’ learning processes and outcomes. By analyzing large-scale educational datasets, patterns and trends can be identified to inform instructional design and identify students’ strengths and weaknesses. This enables educators to tailor instruction and assessment to meet individual learners’ needs, fostering authentic learning experiences.
Furthermore, simulation technologies offer a dynamic and interactive platform for students to engage with authentic tasks and scenarios. Simulations can replicate real-world contexts, allowing learners to apply their knowledge and skills in a safe and controlled environment. Through simulation, students can experiment, make decisions, and experience the consequences of their actions, enhancing their understanding and critical thinking abilities.
By integrating educational data mining and simulation technologies, authentic learning can be scaffolded and supported in various educational domains. The article discusses the potential benefits and challenges of adopting these technologies and provides examples of successful implementations. Additionally, ethical considerations related to data privacy and student well-being are addressed, ensuring responsible use of these technologies.
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