One challenging issue in improving the teaching and learning methods in MOOCs is to construct potential knowledge graphs from massive learning resources. Therefore, this study proposes knowledge graphs driving online learning behaviour prediction and multi-learning task recommendation in MOOCs. Based on the knowledge graphs supported by…

The objective of question generation from knowledge graphs (KGQG) is to create coherent and answerable questions from a given subgraph and a specified answer entity. KGQG has garnered significant attention due to its pivotal role in enhancing online education. Encoder-decoder architectures have advanced traditional KGQG approaches. However, these…

In recent years, knowledge tracing (KT) within intelligent tutoring systems (ITSs) has seen rapid development. KT aims to assess a student's knowledge state based on past performance and predict the correctness of the next question. Traditional KT often treats questions with different difficulty levels of the same concept as identical…

Reading comprehension requires readers to connect ideas within and across texts to produce a coherent mental representation. One important factor in that complex process regards the cohesion of the document(s). Here, we tackle the challenge of providing researchers and practitioners with a tool to visualize text cohesion both within (intra) and…

Reading comprehension is key to knowledge acquisition and to reinforcing memory for previous information. While reading, a mental representation is constructed in the reader's mind. The mental model comprises the words in the text, the relations between the words, and inferences linking to concepts in prior knowledge. The automated model of…

Theories of discourse argue that comprehension depends on the coherence of the learner's mental representation. Our aim is to create a reliable automated representation to estimate readers' level of comprehension based on different productions, namely self-explanations and answers to open-ended questions. Previous work relied on Cohesion Network…

Scholars interested in the function of language in mathematical learning often draw on Vygotsky, whose early work on word meaning has shaped many research studies. However, near the end of a rather short life, Vygotsky heavily critiqued his own previous work and began to sketch a radical theory revision, which overturns much of what he had done…

The evaluation of text complexity is an important topic in education. While this objective has been addressed by approaches using lexical and syntactic analysis for decades, semantic complexity is less common, and the recent research works that tackle this question rely on machine learning algorithms that are hardly explainable and are not…

While education increasingly relies on social media technologies to provide richer learning experiences, the rigid and course-centric design of curricula still imposes a challenge for students to construct meaningful connections between social media and formal learning. Building on the knowledge graphs' potential to establish semantic links among…

Academic grades in assessments are predicted to determine if a student is at risk of failing a course. Sequential models or graph neural networks that have been employed for grade prediction do not consider relationships between course descriptions. We propose the use of text mining to extract semantic, syntactic, and frequency-based features from…

The current theories suggest the fundamental role of semantic memory in creativity, mediating bottom-up (divergent thinking) and top-down (fluid intelligence) cognitive processes. However, the relationship between creativity, intelligence, and the organization of the semantic memory remains poorly-characterized in children. We investigated the…

We compared the ability of three different contextual models of lexical semantic memory (BEAGLE, Latent Semantic Analysis, and the Topic model) and of a simple associative model (POC) to predict the properties of semantic networks derived from word association norms. None of the semantic models were able to accurately predict all of the network…

This study investigates representational code-switching (RCS) by considering three high school students' communications in the process of comparing and contrasting pairs of representations (e.g., equation and graph) in the context of rational functions. Supporting this study is research in the realms of students interacting with mathematical…

Curricula often lack metadata to characterize the relatedness of concepts. To investigate automatic methods for generating relatedness metadata for a mathematics curriculum, we first address the task of identifying which terms in the vocabulary from mathematics word problems are associated with the curriculum. High chance-adjusted interannotator…

Mapping the knowledge formations of language teachers within their pedagogic practices is underresearched, particularly for subject English, a multi-faceted, elusively defined discipline. Deeper knowledge of the pedagogy of subject English teachers is critical, especially within South African education, given the socio-economic power of English in…