Intelligent assessment, the core of any AI-based educational technology, is defined as embedded, stealth and ubiquitous assessment which uses intelligent techniques to diagnose the current cognitive level, monitor dynamic progress, predict success and update students' profiling continuously. It also uses various technologies, such as learning…

Background: Within the context of the Special Interest Research Group (SIRG) on Persons with Profound Intellectual and Multiple Disabilities (PIMD), researchers often discuss the methodological problems and challenges they are confronted with. The aim of the current article was to give an overview of these challenges. Methods: The challenges are…

This article characterizes and reflects on the possible uses of early warning systems (hereafter, EWS) in the region as effective tools to support educational pathways, whenever they identify risks of dropout, difficulties for the achievement of substantive learning, and the possibility of organizing specific actions. This article was developed in…

Ten years after the announcement of the "rise of the super experiment" at Educational Data Mining 2012, challenges to implementing "internet scale" educational experiments often persist for educational technology providers, especially when they seek to test substantive instructional interventions. Studies that deploy and test…

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…

The proliferation of vast quantities of available datasets that are large and complex in nature has challenged universities to keep up with the demand for graduates trained in both the statistical and the computational set of skills required to effectively plan, acquire, manage, analyze, and communicate the findings of such data. To keep up with…

Big international assessment organisations like Cambridge Assessment have long held considerable amounts of data. When text is produced digitally, we can do more with it. Surprisingly to many, there have been examples of automatic scoring of extended writing for around 20 years, though what works well in one context may not be applicable in all…

Increasingly, students training in the biological sciences depend on a proper grounding in biological statistics, data science and experimental design. As biological datasets increase in size and complexity, transparent data management and analytical methods are essential skills for undergraduate biologists. We propose that using the software R…

New technologies, including artificial intelligence (AI), enablers of big data analysis, blockchain data systems, robotics, and drones are transforming marketing. Marketing education has adapted over the last 120 years driven by changes in marketing technology that have helped shape the courses taught. Marketing educators are facing challenges in…

Mixed methods surveys using multilingual assistants in areas without clear pre-defined sampling units are often difficult to manage and unpredictable, thereby threatening data quality. More so when such surveys are executed in unfamiliar territories where cultural and language barriers prevent direct communication between the principal researcher…

Due to rapid advancements in our ability to collect, process, and analyze massive amounts of data, it is now possible for educational institutions to gain new insights into how people learn (Kumar, 2013). E-learning has become an important part of education, and this form of learning is especially suited to the use of big data and data analysis,…

Home visiting is an important component of the early childhood (EC) landscape. However, states often fail to prioritize home visiting data when developing their early childhood integrated data systems (ECIDS). Home visiting represents a range of services, models, and programs, each with different data requirements, so integrating the data can be…

Industry demand for talented analytics professionals has created a significant increase in degree programs (e.g., MS in Analytics) around the globe. Many of these programs incorporate experiential learning in the curriculum to foster a deeper understanding. This article focuses on the value and challenges in implementing experiential learning in…

Reproducibility crises have arisen in psychology and other behavioral sciences, spurring efforts to ensure research findings are credible and replicable. Although reforms are occurring at professional levels in terms of new publication parameters and open science initiatives, the credibility and reproducibility of undergraduate research deserves…

The process of data analysis provides, undoubtedly, some of the major challenges facing organizations during the implementation of interventions in emergencies. The challenges are primarily due to the lack of direct access to beneficiaries and the rapidly evolving nature of emergencies. This paper outlines how Plan International's Making Ghanaian…