Educators and researchers have analyzed various image data acquired from teaching and learning, such as images of learning materials, classroom dynamics, students' drawings, etc. However, this approach is labour-intensive and time-consuming, limiting its scalability and efficiency. The recent development in the Visual Question Answering (VQA)…

Educational process mining aims (EPM) to help teachers understand the overall learning process of their students. Although deep learning models have shown promising results in many domains, the event log dataset in many online courses may not be large enough for deep learning models to approximate the probability distribution of students' learning…

Background: When learning causal relations, completing causal diagrams enhances students' comprehension judgements to some extent. To potentially boost this effect, advances in natural language processing (NLP) enable real-time formative feedback based on the automated assessment of students' diagrams, which can involve the correctness of both the…

This paper examines the enactment of feedback in Massive Open Online Courses (MOOCs), focusing on analytics dashboards. Building on scholarship that recognizes data practices as entangled and 'messy', the paper problematizes the model of the feedback loop that assumes that analytics dashboards 'feed back' data to instructors and/or learners…

We design a generative adversarial network (GAN)-based pencil drawing learning system for art education on large image datasets to help students study how to draw pencil drawings for images and scenes. The system generates a pencil drawing result for a natural image based on GAN. The GAN network is trained on pencil drawing big datasets containing…

In order to learn the mappings from words to referents, children must integrate co-occurrence information across individually ambiguous pairs of scenes and utterances, a challenge known as cross-situational word learning. In machine learning, recent multimodal neural networks have been shown to learn meaningful visual-linguistic mappings from…

Instruction in many STEM domains heavily relies on visual representations, such as graphs, figures, and diagrams. However, students who lack representational competencies do not benefit from these visual representations. Therefore, students must learn not only content knowledge but also representational competencies. Further, as learning…

Big Data Technology (BDT) and Analytics have gained immense recognition in recent years. BDT plays an essential role in various sectors. This study intends to provide a review of BDT in the education sector which includes analyzing, predicting learner's results based on behavior patterns, assessing their performance regularly. Education…

Recent research on learning analytics dashboards has focused on designing user interfaces that offer various forms of "visualization guidance" (often referring to notions such as "data storytelling" or "narrative visualization") to teachers (e.g., emphasizing data points or trends with colour and adding annotations),…

In educational applications, "Knowledge Tracing" (KT) has been widely studied for decades as it is considered a fundamental task towards adaptive online learning. Among proposed KT methods, Deep Knowledge Tracing (DKT) and its variants are by far the most effective ones due to the high flexibility of the neural network. However, DKT…

The article describes a pre-experimental research study that focuses on learning objects. Web objects that capture the attention of users and that characterize the content of a website were examined. The main goal was to identify the most relevant design of three web objects by using the eye-tracking tool Areas of Interest and feedback questioning…