For decades, ecologists have taught ecological principles using examples from textbooks, published papers, and personal research. The advent of new modes of data collection, dissemination, analysis and visualization create new opportunities for the way we teach ecology. The availability of vast ecological data repositories and live-streaming data services now allow students to conduct their own scientific inquiries with rich, high quality data, and to develop their own mental constructs of ecological phenomena across scales well beyond their capacity to collect their own data. This organized oral session explores the ways that the data revolution can revolutionize ecology education, especially in the context of ESA’s recently endorsed Four-Dimensional Ecology Education (4DEE) framework. That framework recommends that ecology be taught by integrating four dimensions, including Core Ecological Concepts, Human-Environment Interactions, Ecology Practices, and Cross Cutting Themes. One of the six listed practices is Quantitative Reasoning (QR) and computational thinking in ecology, including statistics, data sense making (using Big Data, meta-analysis, visualization), computation skills, modeling, and informatics. A number of challenges and opportunities emerge when considering how this practice can be integrated with the other dimensions of the 4DEE framework. For instance, by elevating the importance of integrating the human dimension in the teaching of ecology, we need to consider ways to help students plan experiments, collect and analyze data and use computational models to address human/environment interactions to understand and help environmental problems. As a result, students need to learn how to integrate sociological data with ecological data to decide how to approach implementation of real-world environmental solutions. The presentations in this Organized Oral session will explore various perspectives and examples of teaching and learning this ecological practice in a number of education contexts. Each talk emphasizes the challenges and opportunities for integrating data sense-making with other practices (e.g., the natural history approach, communication) and other 4DEE dimensions (e.g., human/environment interactions, core ecological concepts). Data collection and analysis will be discussed from different scales, forms of obtaining data and how to integrate multiple types of data into teaching the study of 21st century environmental issues.