With the vigorous development of intelligent campus construction, great changes have taken place in the development of information technology in colleges and universities from the previous digital to intelligent development. In the teaching process, the analysis of students' classroom learning has also changed from the previous manual observation…

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…

All chemistry students must develop competency in analyzing and making sense of data. However, there are many difficulties that chemistry students may experience while analyzing data. Many students may not use relevant prior knowledge to aid in making sense of data, or they may not form conclusions using all the data provided. Additionally, prior…

Data Analytics has grown dramatically in importance and in the level of business deployments in recent years. It is used across most functional areas and applications, some of the latter including market campaigns, detecting fraud, determining credit, identifying assembly line defects, health services and many others. Indeed, the realm of…

Based on a brief analysis of the current situation of university education management and research on intelligent algorithms, this article constructs a university education management system based on big data. For the clustering and prediction modules in higher education management, corresponding algorithms are used for optimization design. A…

Medical simulations allow trainees to work within teams to develop their self-regulated learning (SRL) and socially-shared regulated learning (SSRL) skills (Bransen et al., 2022). Both skillsets help to better prepare medical trainees for the multifaceted challenges inherent in clinical practice. SRL skills are imperative in empowering learners to…

In this study, we introduced a cross-classified multidimensional nominal response model (CC-MNRM) to account for various response styles (RS) in the presence of cross-classified data. The proposed model allows slopes to vary across items and can explore impacts of observed covariates on latent constructs. We applied a recently developed variant of…

The education faculty aims to assess departmental effectiveness by analyzing the relationship between service levels, output variables, and input variables. This objective is coupled with the formulation of faculty development strategies tailored to enhance efficiency while accommodating individual professionals' unique requirements and…

This paper describes an innovative approach for teaching the challenges in the management of data warehouse development. The approach contains lecture material providing conceptual background about the management of data warehouse development, a simulation game supporting experiential learning, and a post-play debriefing to support synthesis of…

With recent advances in artificial intelligence (AI), machine learning (ML) has been identified as particularly useful for organizations seeking to create value from data. However, as ML is commonly associated with technical professions, such as computer science and engineering, incorporating training in the use of ML into non-technical…

This study introduces a modular teaching framework for business data analytics (BDA) curricula and programs. The framework integrates gamification features of the SAP business processes, ERPsim Games, and SAP data warehousing into the experiential learning of BDA curricula. The pedagogical practices of deploying the framework in an undergraduate…

This work focuses on simulation, design, development, and evaluation of a visual Learning Analytics (LA) tool -- Real-time Educational AI-powered Classroom Tool (REACT) -- to support educators' data-driven decision-making. The educational institutions face one of the biggest challenges, such as predicting student performance, detecting undesirable…

Understanding scientific phenomena requires learners to construct mental models of causal systems. Simulation-based discovery learning offers learners the opportunity to construct mental models and test them against the behavior of a simulation. The purpose of this study was to investigate sequential patterns of learner actions and utterances…

Anecdotal evidence suggests that students with quantitative business majors (e.g., finance, accounting, data analytics, economics) outperform students from less quantitatively rigorous majors (e.g., management, human resource management, marketing) on a business simulation game at a mid-sized, southeastern, public, AACSB accredited university. We…

This paper details the anticipated impact of synthetic "big" data on learning analytics (LA) infrastructures, with a particular focus on data governance, the acceleration of service development, and the benchmarking of predictive models. By reviewing two cases, one at the sector-wide level (the Jisc learning analytics architecture) and…