According to decades of research in educational psychology, learning is a social process that is enhanced when it happens in contexts that are familiar and relevant. But because of the skyrocketing popularity of data science, today we often work with students coming from an abundance of academic concentrations, professional, and personal…

Educational process mining aims (EPM) to help teachers understand the overall learning process of their students. Although deep learning models have shown promising results in many domains, the event log dataset in many online courses may not be large enough for deep learning models to approximate the probability distribution of students' learning…

Using simulation approaches when conducting randomization tests for comparing two groups in the context of experimental studies has been promoted as a beneficial approach for supporting student learning of statistical inference. Many researchers have suggested that the data production process in simulations for the randomization test intuitively…

This paper explores the potential of using Chat Generative PreTrained Transformer (ChatGPT), a powerful language model, as an innovative tool to enhance education in the classroom. Drawing from firsthand experience, this paper demonstrates how ChatGPT can be integrated into the teaching and learning process of statistics and data analytics…

Data visualization is a complex matter and so is teaching it in the context of engineering and data science. Even more challenging is teaching in a midst of once in a century pandemic. In this paper, we show the results of a workshop conducted with second-year students on a university degree in data science, which took place in the context of…

The growing use of generative AI (GenAI) has sparked discussions regarding integrating these tools into educational settings to enrich the learning experience of teachers and students. Self-regulated learning (SRL) research is pivotal in addressing this inquiry. One prevalent manifestation of GenAI is the large-language model (LLM) chatbot,…

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…

The general growth in public affairs programs offering hybrid and online courses to reach a wide variety of students, along with the necessity of doing so during a global health pandemic, calls for an investigation of best practices in teaching public affairs statistics and research-oriented courses. These courses often require the use of a…

The age of big data drives the need for emerging technologies to enable scalable analytics on massive, rapidly generated, and varied data. It requires "data scientists" with deep knowledge of managing the six Vs of big data: volume, velocity, variety, volatility, veracity, and value. As a result of this trend, new analytical tools are…

This study focused on statistical investigation tasks designed by preservice teachers. Participants designed a statistical investigation task as a culminating summative assessment after completing modules on teaching and learning statistics. Our study examined the designed tasks to identify their strengths as well as areas of needed improvement.…

The use of technology for teaching and learning has created a paradigm shifting in learning environments and learning process, and also the paradigm shifting has also affected the assessment processes. In addition to these, online environments provide more opportunities to assess of the learners. In this study, the Adaptive Mastery Testing (AMT)…