In today's university era, reforming the English teaching model has become a major research topic for researchers. Based on this, this paper adopts a hierarchical and progressive model construction method to further explore the reform model of university English teaching in the context of educational ecology. First, this paper discusses the…

In the era of artificial intelligence (AI), big data (BD), and digital transformation (DT), analytics students should gain the ability to solve business problems by integrating various methods. This teaching brief illustrates how two such methods--Bayesian analysis and Markov chains--can be combined to enhance student learning using the Analytics…

Background and Context: Assessing team members' indivdiual contributions to software development projects poses a key problem for computing instructors. While instructors typically rely on subjective assessments, objective assessments could provide a more robust picture. To explore this possibility, In a 2020 paper, Buffardi presented a…

This article describes experiences with teaching process data analytics and machine learning, including in: (1) a joint undergraduate/graduate course for students in chemical and mechanical engineering and engineering management; and (2) an undergraduate chemical engineering concentration in process data analytics. The article also describes…

Faculty teaching data analytics at undergraduate level are often faced with the tension created by student under-preparedness, the demands of the course, and time constraints. How do faculty close this gap? In this paper, we propose the use of flow diagramming as an accessible method for interpreting regression analyses, in ways that are time…

Programmatic advertising has come to dominate the landscape of digital media planning. To prepare ad majors for their future careers in the industry, it is essential to teach students programmatic buying and provide them with hands-on experience. In this article, the authors present their approach of integrating teaching programmatic buying into a…

The poor level of engagement in learning mathematics is primarily caused by ineffective methods of instruction. Therefore, the purpose of this study was to investigate how context-based problem-posing and solving instructional approaches influence students' engagement in learning data handling using a concurrent embedded quasi-experimental…

This research delves into the global understanding of smart education from various perspectives, including expert viewpoints, policy dimensions, public datasets, and visions of equity and inclusion. Multiple webinars have revealed that the concept of smart education with a shared vision of quality education in the age of AI is being understood by…

Data-handling, processing, and analysis skills are an integral part of a chemist's skill set and, more generally, are highly sought by employers. We report a self-directed workshop to develop and advance these key skills using the popular spreadsheet program Microsoft Excel. Making use of its accessible user interface, various contextualized…

This article examines the social utility of the concept, 'data literacy'. Recent developments in the processes of datafication challenge long-held assumptions about privacy and the role of both state and commerce in individual lives. Typically, these have been addressed through: "regulatory" legal constraints underwritten by the nation…

The constantly growing offering of online learning materials to students is making it more difficult to locate specific information from data pools. Personalization systems attempt to reduce this complexity through adaptive e-learning and recommendation systems. The latter are, generally, based on machine learning techniques and algorithms and…

Maps are a primary method of displaying statistical data that comes from a geographical frame. Maps are esthetically appealing and make it easier to identify geographic patterns in a dataset. However, few introductory statistical texts and courses explicitly present maps as a way to display data. In this article, we will present examples of…

Intelligent Tutoring systems (ITSs) and Intelligent Learning Environments (ILEs) have been developed and evaluated over the last 40 years. Recent meta-analyses show that they perform well enough to act as effective classroom assistants under the guidance of a human teacher. Despite this success, they have been criticised as embodying a retrograde…

One of the challenges that science teachers face is the lack of strategy/method to train students in data collection and developing analytical skills, which are pre-requisites to resolve socio-scientific problems and an important element in scientific literacy. In this activity, the SWOT analysis proposed by the Stanford Research Institute in the…

With the rapid development of science and technology in recent years, the application areas of fuzzy logic have also gained speed. Fuzzy logic is a frequently preferred approach in the educational process, and it can be said that scientific publications on this topic have recently gained momentum in the literature. In this context, the present…