POGIL Undergraduate Chemistry, Mumbai, India
Description
The dataset offers a comprehensive analysis of feedback from a Process-Oriented Guided Inquiry Learning (POGIL) activity, encompassing quantitative and qualitative insights into participant experiences. It evaluates confidence in understanding key concepts, identifies challenges with worksheets, and assesses the contribution of activities to learning and skill development. Feedback highlights participant struggles with theoretical questions, numerical problems, graph interpretation, and equation formulation, while also emphasizing the progression of skills from the start to the end of the activity. The dataset captures reflections on group collaboration, critical thinking moments, and suggestions for worksheet improvement, offering a detailed view of the learning process. Additionally, it evaluates the skill and responsiveness of instructors in areas such as communication, time management, and the ability to engage students. Insights into how students used worksheets for exam preparation reveal the relevance of these materials in enhancing recall and application of concepts. This data has numerous applications, including curriculum enhancement, activity design, and assessment support, by helping educators refine worksheets, align activities with learning objectives, and create assessment-linked materials. It also offers actionable feedback for professional development, enabling instructors to address their strengths and areas for growth. For researchers, the dataset serves as a valuable resource for studying active learning methods like POGIL, providing insights into learning barriers, group dynamics, and collaboration. It can inform cross-disciplinary studies, instructional design, and comparative research, contributing to broader explorations of inquiry-based learning. Furthermore, the data's qualitative depth allows for a nuanced understanding of student experiences, enabling other researchers to explore the relationship between teaching strategies, worksheet design, and learning outcomes. This dataset is particularly useful for benchmarking studies in STEM education and tracking the impact of changes in activity design over time. By facilitating a deeper understanding of effective teaching practices, the dataset can be leveraged for both immediate pedagogical improvements and long-term research contributions, providing a foundation for enhancing active learning techniques across diverse educational settings.