Integrating the use of large datasets into our teaching provides critical and unique opportunities to build students' skills and conceptual knowledge. Here, we discuss the core components needed to develop effective activities based on large datasets, which align with the 5E learning cycle. Data-based activities should be structured around a…

The research sought to study potential efficiency in course design and execution using Constructive Alignment, and then classroom workflow grounded in eduScrum based on the Agile Project Framework of Scrum for graduate classes in managerial analytics. The research measured performance based on the Scrum concept of Velocity, defined as the rate of…

The field of "learning design" studies how to support teachers in devising suitable activities for their students to learn. The field of "learning analytics" explores how data about students' interactions can be used to increase the understanding of learning experiences. Despite its clear synergy, there is only limited and…

Educational inclusion aims to support all students through instructional and contextual designs that promote learning. Educators are assigned the task of teaching an increasingly neurodiverse population with varying neurological processes and perceptions. Traditional school-based settings are designed for individuals with less neurodivergence,…

This paper proposes the theoretical context for a course development framework to address the specific needs and challenges of teaching and learning in interdisciplinary studies (IDS). User-centred design (UCD) principles are used for this development process. Traditional course development frameworks provide a helpful guide in terms of setting…

This study aims to investigate problem-solving with dataset (PSWD) as a computational thinking learning implementation as reflected in academic publications. Specifically, the purpose is to specify the scope of PSWD, which overlaps with the data literacy, thinking with data, big data literacy, and data-based thinking concepts in the literature.…

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…

This paper provides a comprehensive overview of the research on the application of artificial intelligence (AI) in primary education to explore its potential to enhance teaching and learning processes. Through a systematic review of the relevant literature, this study identifies key areas in which AI can significantly impact primary education and…

Humans have always been lured by the idea that they can use data to understand a phenomenon and make predictions about it. Learning analytics, in this sense, promise to understand and optimize learning and the environments in which it occurs by collecting data from learners and learning contexts. In this regard, this study systematically examines…

Artificial Intelligence (AI) and robotics are likely to have a significant long-term impact on higher education (HE). The scope of this impact is hard to grasp partly because the literature is siloed, as well as the changing meaning of the concepts themselves. But developments are surrounded by controversies in terms of what is technically…

Student engagement is regarded as a critical educational outcome. However, it has proven to be elusive to educators within technical domains, such as marketing research and analytics, which has inspired the exploration of experiential course design elements. Client-sponsored projects (CSPs) have become a popular tactic to meet this objective in…

This article presents an evaluation of edCrumble, a blended learning authoring tool for teachers. The tool visually represents learning designs and integrates data analytics to scaffold teacher design decisions. In addition to assessing the usability of edCrumble using Usability Metric for User Experience questionnaire, analyses of participant…

The purpose of this article is to describe a multidisciplinary approach implemented in teaching public policy analysis at university level. The approach fuses (a) contextual policy analysis with (b) bivariate and multivariate analysis techniques and (c) data analytics skills to improve the learners' competence to conduct "decisional"…

In this study, we held a 12-hour workshop focused on training the Data-Driven Learning (DDL) approach for in-service Chinese teachers aiming to implement this pedagogy in Mandarin Chinese classrooms in the future. We analyzed data from a postworkshop questionnaire to understand how the individual-level traits of Chinese teachers (such as their…

Use of online learning systems, such as learner dashboards, is increasing in university chemistry courses. Learning analytics can support student learning by providing feedback on concept mastery. This paper investigated how student use of a chemistry learner dashboard might be increased through class structure, instructor practice, and dashboard…