A version of the classic rotationally resolved infrared (IR) spectrum of a diatomic molecule experiment has been developed using the POGIL framework to more fully engage students in the collection, modeling, analysis, and interpretation of the data. An analysis of the experimental protocol reveals that the POGIL approach actively engages students…

This resource has been written specifically for higher education practitioners who are interested in improving students' learning experiences through the process of researching their own practice. We use the term 'higher education practitioners' to describe all who work in universities and who have a stake in students' learning experiences.…

This study examines physical education (PE) curriculum development in an elementary school. Our goal was to understand the daily construction of a curriculum. We sought to analyse the theoretical and methodological framework and documents that a PE teacher uses each day while putting a curriculum into practice (lived curriculum). The data…

The study used earliest available student data from a flagship university in the southeast United States to build data mining models like logistic regression with different variable selection methods, decision trees, and neural networks to explore important student characteristics associated with retention leading to graduation. The decision tree…

In light of the emergence of statistical analysis techniques based on data mining in education sciences, and the potential they offer to detect non-trivial information in large databases, this paper presents a procedure used to detect factors linked to academic achievement in large-scale assessments. The study is based on a non-experimental,…

The purpose of this study is to provide an account of teacher perception of core practice tasks in data use, particularly data interpretation. Data interpretation is critical to professional practice in planning instructional adjustments for student learning. This is a case study of four elementary teachers who provide numerous task-specific…

The growth in the availability of longitudinal data--data collected over time on the same individuals--as part of program evaluations has opened up exciting possibilities for evaluators to ask more nuanced questions about how individuals' outcomes change over time. However, in order to leverage longitudinal data to glean these important insights,…

Communities, Cameras, and Conservation (CCC) is the most exciting and valuable program the author has seen in her 30 years of teaching field science courses. In this citizen science project, students and community volunteers collect data on mountain lions ("Puma concolor") at four natural areas and public parks along the Front Range of Colorado.…

Two basic data sources required for research studies have been secondary and primary. Secondary data collection helps the researcher to provide relevant background to the study and are, in most cases, available for retrieval from recorded sources. Primary data collection requires the researcher to venture into the field where the study is to take…

Durkheim's nineteenth-century analysis of national suicide rates dismissed prior concerns about mortality data fidelity. Over the intervening century, however, evidence documenting various types of error in suicide data has only mounted, and surprising levels of such error continue to be routinely uncovered. Yet the annual suicide rate remains the…

In the modern world, higher education is transitioning from enrollment mode to recruitment mode. This shift paved the way for institutional research and policy making from historical data perspective. More and more universities in the U.S. are implementing and using enterprise resource planning (ERP) systems, which collect vast amounts of data.…

The Office of Planning, Research and Evaluation (OPRE), a unit within the Administration for Children and Families (ACF), is responsible for advising the Assistant Secretary for Children and Families on increasing the effectiveness and efficiency of programs to improve the economic and social well-being of children and families. In collaboration…

Although most school districts and schools are routinely involved in data collection, they do not typically use the data they collect in a systematic fashion to identify strengths and weaknesses and develop improvement strategies. One reason for the lack of data use is the perception that the data are being collected for someone else's purposes.…

Data-mining technology's predictive modeling was applied to enhance the prediction of enrollment behaviors of admitted applicants at a large state university. (Contains 4 tables and 6 figures.)

In the Philadelphia Public Schools, a computer system called Data to Success has been created to assess student progress prior to end-of-year testing. The five-stage system allows a school to influence teacher decisions, identify student warning signs, and monitor important trend and analysis information throughout the school year. (MLH)