Retrospective confidence refers to the phenomenological experience of the level of certainty that retrieved information is, in fact, correct. Retrospective confidence judgments are examined across a range of sub-disciplines in psychology from perception to memory research, and in education and legal applications. This paper focuses on…

Amidst ongoing technological and social change, this article explores the implications for critical education that result from a data-driven model of digital governance. The article argues that traditional notions of critique which rely upon the deconstruction and analysis of texts are increasingly redundant in the age of datafication, where the…

As a prominent aspect of modeling learners in the education domain, knowledge tracing attempts to model learner's cognitive process, and it has been studied for nearly 30 years. Driven by the rapid advancements in deep learning techniques, deep neural networks have been recently adopted for knowledge tracing and have exhibited unique advantages…

Learning interaction activities are the key part of tracking and evaluating learning behaviors, that plays an important role in data-driven autonomous learning and optimized learning in interactive learning environments. In this study, a big data set of learning behaviors with multiple learning periods is selected. According to the instance…

With the emergence of short video and the development of mobile internet, short video software, such as TikTok and Kwai, has emerged. Based on the semantic understanding technology of teaching short videos, a teaching management platform was built to push healthy and positive short video for students' content in a targeted way. Taking the 21st…

This paper investigates the intersection of big data and philosophy of education by considering big data's potential for addressing learning via a holistic process of coming-to-know. Learning, in this sense, cannot be reduced to the difference between a pre- and post-test, for example, as it is constituted at least as much by qualities of…

Personalized education--the systematic adaptation of instruction to individual learners--has been a long-striven goal. We review research on personalized education that has been conducted in the laboratory, in the classroom, and in digital learning environments. Across all learning environments, we find that personalization is most successful when…

This systematic review is built on the seminal work by the New London Group in 1996. Few endeavours have synthesized findings of empirical studies pertaining to the effects and challenges of multiliteracies practices in various schooling and geographical contexts. Through a five-point Likert scale and a deductive and inductive thematic analysis,…

With the emergence of the Industrial Revolution 4.0, modern technologies such as cloud computing, artificial intelligence, and big data are profoundly transforming the education ecosystem. The development of education is not only faced with huge challenges but also contains rare opportunities. New concepts such as deep learning, adaptive learning,…

The early elementary school years are widely understood to be critical to a child developing a strong foundation for future academic success. Children arrive at kindergarten from diverse settings and experiences, and not all of them are "kindergarten ready." Kindergarten readiness refers to the skills and abilities needed to succeed in…

We study learning outcome prediction for online courses. Whereas prior work has focused on semester-long courses with frequent student assessments, we focus on short-courses that have single outcomes assigned by instructors at the end. The lack of performance data and generally small enrollments makes the behavior of learners, captured as they…

The metaverse is rapidly reshaping our understanding of education, yet identifying the public's beliefs, emotions and sentiments towards its adoption in education remains largely uncharted empirically. Grounded in the Technology Acceptance Model (TAM) and Digital Diffusion Theory (DOI), this paper aims to fill this gap using a big-data approach…

This article is a revised version of the keynote presented at LAK '16 in Edinburgh. The article investigates some of the assumptions of learning analytics, notably those related to behaviourism. Building on the work of Ivan Pavlov, Herbert Simon, and James Gibson as ways of "learning as a machine," the article then develops two levels of…

We examine the challenges of teaching probability through the use of modelling. We argue how an integrated modelling approach might facilitate a coordinated understanding of distribution by marrying theoretical and data-oriented perspectives and present probability as more connected to the social lives of modern-day students. Research is, however,…

Personalized learning has become the most notable application of big data in primary and secondary schools in the United States. The combination of big data and adaptive technological platforms is heralded as a revolution that could transform education, overcoming the outdated classroom model, and realizing the progressive vision of…