As artificial intelligence (AI) technologies are increasingly pervasive in our daily lives, the need for students to understand the working mechanisms of AI technologies has become more urgent. Data modeling is an activity that has been proposed to engage students in reasoning about the working mechanism of AI technologies. While Computational…

In this study, we used multivariate decoding methods to study processing differences between canonical (montring and count) and noncanonical finger numeral configurations (FNCs). While previous research investigated these processing differences using behavioral and event-related potentials (ERP) methods, conventional univariate ERP analyses focus…

Computational thinking (CT) is considered to be a critical problem-solving toolkit in the development of every student in the digital twenty-first century. Thus, it is believed that the integration of deeper learning in CT education is an approach to help students transfer their CT skills beyond the classroom. Few literature reviews have mapped…

In this opinion piece, we explore the idea that GenAI has the potential to fundamentally disrupt computer science education (CSE) by drawing insights from 10 pedagogical and cognitive theories and models. We highlight how GenAI improves CSE by making educational practices more effective and requires less effort and time, and all at a lower cost,…

Deeper learning (DL) is firmly rooted in learning science and computer science. However, a dearth of review studies has probed its trajectory in DL in foreign languages (DLFL). Utilizing SSCI from the Web of Science Core Collection, we employ Citespace and Vosviewer to analyze the scientific knowledge graph of DLFL literature. Our analysis…

As part of a broader information literacy agenda, academic libraries are interested in advancing algorithmic literacy. Folk theories of algorithmic decision-making systems, such as recommender systems, can provide insights into designing and delivering enhanced algorithmic literacy initiatives. Users of the Spotify music recommendation systems…

Preventing humans from committing errors is a crucial aspect of man-machine interaction and systems of computer assistance. It is a basic implication that those systems need to recognise errors before they occur. This paper reports an exploratory study that utilises eye-tracking technology and automated face recognition in order to analyse test…

In many evolving systems, inputs can be derived from both human observations and physical sensors. Additionally, many computation and analysis tasks can be performed by either human beings or artificial intelligence (AI) applications. For example, weather prediction, emergency event response, assistive technology for various human sensory and…

The order of problems presented to students is an important variable that affects learning effectiveness. Previous studies have shown that solving problems in a blocked order, in which all problems of one type are completed before the student is switched to the next problem type, results in less effective performance than does solving the problems…

Computational models will play an important role in our understanding of human higher-order cognition. How can a model's contribution to this goal be evaluated? This article argues that three important aspects of a model of higher-order cognition to evaluate are (a) its ability to reason, solve problems, converse, and learn as well as people do;…

An intensive, naturalistic study tracked one six year old's learning for six months and more. The study was inspired by the hope that with concepts of Artificial Intelligence and sufficiently detailed observation, the path of knowledge development could be described through observing significant learning experiences. Included is a reasonably…