In this paper, we describe a course project in which teams of undergraduate students propose and execute an end-to-end analytics project to solve a real-world problem. The project challenges students to implement machine learning, optimization, simulation, or a combination of these three techniques on real-world data that they collect. A…

In many collegiate level statistics courses, the focus of the learning outcomes is often on the analysis of data after it has been collected. Students are provided with clean data sets from previous studies to practice statistical analysis, but receive little to no application as to the amount of time and effort that goes in to collecting good…

Water analysis is an excellent interdisciplinary topic for project-based learning. An undergraduate course was designed to engage the senior undergraduate chemistry students in a real-life experience. In this course, students developed methodologies based on published American Society for Testing and Materials (ASTM) methods for the measurement of…

There is considerable evidence that 'active learning' strategies are more efficacious than traditional 'passive learning' methods (e.g. lecture). Presented here is a small group active learning project developed for undergraduate social psychology students. The activity involves carrying out and reporting the results of a structured demonstration…

An undergraduate-level Computational Chemistry project was incorporated initially into a Physical Chemistry course and then into the laboratory curriculum in the subsequent application. Before the introduction of the project, the lectures covered quantum chemistry, spectroscopy, and kinetics while simultaneously including computational chemistry…

Implementing collaborative action research (CAR) is recognized as an effective strategy for transforming professional practice through evidence-based methods. How can CAR be carried out online, and how is data collected through digital methods? This case study will address these aspects in the context of a CAR, international professional…

The increasing use of massive data requires effective teaching strategies for business analytics. The discipline combines analytical skills, information technology, and business-domain knowledge, and is challenging to teach to business students. This research demonstrates that business undergraduate students can benefit from an experiential…

The Student Participation Observation Tool (SPOT) is a web-based classroom observation protocol developed for higher education STEM courses and based on research on evidence-based practices. The low-inference and objective nature of the SPOT and visual outputs make it an optimal tool for teaching professional development. The SPOT allows novice…

This paper describes the evolution of "recognition of need for data" and "strategical thinking", two types of thinking identified by Wild and Pfannkuch in their Framework for Statistical Thinking in Empirical Enquiry, as well as its relevance for math teacher professional development. The research was carried out with ten…

The California Blackworm ("Lumbriculus variegatus") is a freshwater segmented worm species that has been used by biology instructors as a model system for inquiry-based student investigations. The blackworm dorsal blood vessel pulsation rate is easily quantified. Moreover, this species can facilitate the study of neuromuscular…

Despite their increasingly widespread adoption in post-secondary education, scholars and practitioners know very little about the impact of digital data displays on instructors' sense-making and academic planning. In this manuscript, I report the results of comparative case studies of five different introductory physics instructors at three…

In an increasingly data-driven world, large volumes of fine-grained data are infiltrating all aspects of our lives. The world of education is no exception to this phenomenon: in classrooms, we are witnessing an increasing amount of information being collected on learners and teachers. Because educational practitioners have so much contextual and…

Through a multi-year, national calculus study, researchers have recently identified seven characteristics of successful college calculus programs. We identified these seven characteristics by visiting five doctoral-granting mathematics departments with successful calculus programs and uncovering the common traits among them. These seven traits…

The abundance of freely available, scientific big data sets can facilitate discovery-based authentic science projects saving time, money, and effort. This is especially true of remotely sensed data, as there is global coverage of Earth's surface spanning several decades that can be used for a multitude of applications. In this article, I present…

This paper reflects on an attempt to introduce smartphones into a blended learning context and highlights several methodological considerations relevant to the collection of mobile data. While mixed methods are now common, using this approach for investigating the challenges of mobile data collection is not as common. This study employed a mixed…