Engaging students in creating high-quality novel content, such as educational resources, promotes deep and higher-order learning. However, students often lack the necessary training or knowledge to produce such content. To address this gap, this paper explores the potential of incorporating generative AI (GenAI) to review students' work and…

Predictive analytics are increasingly pervasive in higher education. However, algorithmic bias has the potential to reinforce racial inequities in postsecondary success. We provide a comprehensive and translational investigation of algorithmic bias in two separate prediction models--one predicting course completion, the second predicting degree…

Amalgamating generative artificial intelligence (Gen AI), Bloom's taxonomy and critical thinking present a promising avenue to revolutionize assessment pedagogy and foster higher-order cognitive skills needed for learning autonomy in the domain of self-directed learning. Gen AI, a subset of artificial intelligence (AI), has emerged as a…

The literature until 2020 has forecasted a significant uptake of learning analytics (LA) to support learning design in higher education. However, there remain only a few investigations into teachers' course design practices and their perspectives on LA as a tool to support their design practices. This paper presents findings from an examination of…

With the widespread use of learning analytics (LA), ethical concerns about fairness have been raised. Research shows that LA models may be biased against students of certain demographic subgroups. Although fairness has gained significant attention in the broader machine learning (ML) community in the last decade, it is only recently that attention…

Purpose: In spite of the popularity of learning analytics (LA) in higher education institutions (HEIs), the success rate and value gained through LA projects is still little and unclear. The existing research on LA focusses more on tactical capabilities rather than its effect on organizational value. The key questions are what are the expected…

Learning analytics (LA) has been widely adopted in research on education. However, most studies in the area have conducted LA after computer-supported collaborative learning (CSCL) activities rather than during CSCL. To address this problem, this study proposed a LA-based real-time feedback approach based on a deep neural network model to improve…

Feedback is a crucial component of student learning. As advancements in technology have enabled the adoption of digital learning environments with assessment capabilities, the frequency, delivery format, and timeliness of feedback derived from educational assessments have also changed progressively. Advanced technologies powered by Artificial…

In this paper, CiteSpace is used to conduct metrological and visual analysis of the core journals of blended learning research (2003-2021) collected by the China National Knowledge Infrastructure (CNKI). The results show that the number of studies on blended learning in China is increasing year by year, which indicates that the research on blended…

Game-based learning has received increasing attention in recent years as it could help improve pupils' motivation, self-efficacy, and achievement. Technological innovations like learning analytics (LA) and GBL offer pedagogical support for teachers. GBL could significantly support pupils' learning as a learning approach compared to conventional…

This study aims to use LMS log data to suggest a way to understand CoI constructs. Students' interactions in Moodle components were weighted for indicators of cognitive, teaching and social presences. Traces reflecting students' online interactions were obtained from the Moodle LMS and analyzed through learning analytics techniques. The data is…

Purpose: Enculturation is a central and defining idea within socioculturally minded research that informs the design of school learning environments. Now, three decades since the idea has emerged in the field, the authors believe it is time to reflect on it because of several ambiguities that have emerged from its use, which is the purpose of this…

Practice in real-world settings exhibits many idiosyncrasies of scheduling and duration that can only be roughly approximated by laboratory research. Here we investigate 39,157 individuals' performance on two cognitive games on the Lumosity platform over a span of 5 years. The large-scale nature of the data allows us to observe highly varied…

Machine learning algorithms that automatically score scientific explanations can be used to measure students' conceptual understanding, identify gaps in their reasoning, and provide them with timely and individualized feedback. This paper presents the results of a study that uses Hebrew NLP to automatically score student explanations in Biology…

Purpose: The purpose of this study is to set up an evaluation model to predict massive open online courses (MOOC) learning performance by analyzing MOOC learners' online learning behaviors, and comparing three algorithms -- multiple linear regression (MLR), multilayer perceptron (MLP) and classification and regression tree (CART).…