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…

Objectives: Java is a popular programming language for use in computing education, but it is difficult to get a wide picture of the issues that it presents for novices; most studies look only at the types or frequency of errors. In this observational study, we aim to learn how novices use different features of the Java language. Participants:…

Interactive learning environments can generate massive learning behavior data and the support of learning behavior big data can ensure the completeness of data analysis and robustness of relationship verification. In this study, learning behaviors are divided into training set and testing set, BP neural network and recurrent Elman network are…

There is a broad impetus across policy and institutional domains to expand public engagement and involvement with emerging technology research and innovation. Yet innovative theory, methods, and practices to critically explore algorithmic system controversies and democratic possibilities are still in nascent form. In this paper, we bring together…

This paper examines ways in which the ethics of data-driven technologies might be (re)politicised, particularly where educational institutions are involved. The recent proliferation of principles, guidelines, and frameworks for ethical 'AI' (artificial intelligence) have emerged from a plethora of organisations in recent years, and seem poised to…

In this article, we investigate the community-driven science happening organically in elite athletics as a means of engaging a community of learners--collegiate athletes, many of whom come from underrepresented groups--in STEM. We aim to recognize the data literacy practices inherent in sports play and to explore the potential of "critical…

The COVID-19 pandemic prompted a sudden rethinking of how music was taught and learned. Prior to the pandemic, the web-based digital audio workstation Soundtrap emerged as a leading platform for creating music online. The present study examined the growth of Soundtrap's usage during the COVID-19 pandemic. Using machine-learning methods, we…

Data visualization is an important tool for communicating research results. This manuscript discusses a method that instructors can use to introduce political science students to visualizations and discusses strategies that instructors can share with students about how to create high-quality visualizations. These strategies can help students make…

The authors provide novice teachers with a step-by-step introduction to linguistic analysis, a tool to identify gaps between English learners' proficiency levels and the language demands of their coursework in the content areas.

The University of Missouri Kansas City (UMKC) is an urban research university with a special emphasis on fostering diversity. In 2021, the Center for Advancing Faculty Excellence created a Faculty Fellows program to develop comprehensive resources and support in four areas: teaching and learning, service and engagement, research and creativity,…

Social media platforms are rich and dynamic spaces where individuals communicate on a person-to-person level and to broader audiences. These platforms provide a wealth of publicly available data that can shed light on the lived experiences of people from numerous clinical populations. Twitter can be used to examine individual expressions and…

The priority goals of the development of Czech higher education include ensuring the quality of its activities, improving the availability and relevance of flexible forms of education, and increasing efficiency in teaching and research. Several professional articles evaluated educational efficiency, but the proposed models did not include…

This research aims to build economic research skills and stimulate students' interest in the local economy through data-based undergraduate research in entry-level economics courses. The authors developed two assignments and one student survey assessing students' learning outcomes and implemented them in two introductory-level classes from fall…

The Cross Industry Standard Process for Data Mining (CRISP-DM) framework was developed in the 1990s and has been widely used as the most relevant and comprehensive leading principle for conducting analytics projects. Despite the wide acceptance and adoption of the CRISP-DM framework, the current business analytics discipline often focuses on the…

Challenges in the measurement of racial disparities in school discipline are a significant barrier to identifying policy and programmatic reforms that are effective at closing gaps. This article reviews key measurement issues and presents a set of empirical analyses as an illustrative case study. Specifically, we reframe the interpretation of…