MOOCs might be an important organization way to realize the online learning process. Online technology and sharing technology enable MOOCs to realize the adaptive scheduling of learning resources, as well as the independent construction of learning sequences. At the same time, it also generates a large number of complex learning behaviors. How to…

"Applications" of knowledge symbolically and structurally "codify" thinking, often displacing the human who is relegated to passive, routine reproduction of operations and left with no space or time to understand or question the relations underlying the processes. This is both mirrored and augmented by the schematic narrowing…

This dissertation is about a particular style of research. The philosophy of this style is that in order to scientifically understand deep learning, it is fruitful to investigate what happens when neural networks are trained on simple, mathematically well-defined tasks. Even though the training data is simple, the training algorithm can end up…

There are two main approaches to how statistical patterns are extracted from sequences: The transitional probability approach proposes that statistical learning occurs through the computation of probabilities between items in a sequence. The chunking approach, including models such as PARSER and TRACX, proposes that units are extracted as chunks.…

Kolb's experiential learning cycle is typically applied in short-term, episodic snapshots of time, while understating the implications of continual, longer-term learning. This fixed-frame, episodic usage may diminish the knowledge that learners bring into an educational experience and the continued shaping of knowledge through future experiences.…

Purpose: This study aims to understand how practitioners use their insights in software development models to share experiences within and between organizations. Design/methodology/approach: This is a qualitative study of practitioners in software development projects, in large-, medium- or small-size businesses. It analyzes interview material in…

Collaborative learning provides learners with significant opportunities to collaborate on solving problems and creating better products. There has been a growing utilization of adaptive and intelligent systems to support productive learning while promoting collaborative practices. One of the core capabilities of these adaptive and intelligent…

Deep learning techniques are being unified for decision support in various applications. However, it remains challenging to train robust deep learning models, due to the inherent insufficient labeled data that is usually time-consuming and labor-intensive. Self-supervised learning is a feature representation learning paradigm to learn robust…

This study investigated the relationships between academic self-discipline, self-control and management, meaningful learning self-awareness, and generative artificial intelligence (GAI) acceptance among 597 teacher candidates at nine Turkish universities. A serial mediation model was proposed, hypothesizing that academic self-discipline influences…

The author has been influenced throughout his time in mathematics education by the work of Caleb Gattegno. Gattegno made extensive use of the word awareness whereas much educational literature from a psychological perspective talks about memory (for example, Justicia-Galiano, MartÌn-Puga, Linares & Pelegrina, 2017). This has, amongst other…

Interpreting a seemingly simple function word like "or," "behind," or "more" can require logical, numerical, and relational reasoning. How are such words learned by children? Prior acquisition theories have often relied on positing a foundation of innate knowledge. Yet recent neural-network-based visual question…

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…

Within the commognitive perspective, ritual and explorative routines are used in a very particular way to distinguish students' routines according to whether they are driven by social reward or by generating a substantiated narrative. Explorative routines in this theorisation may refer not to inquiry-based activity but to the result of a student's…

Student performance is affected by their knowledge which changes dynamically over time. Therefore, employing recurrent neural networks (RNN), which are known to be very good in dynamic time series prediction, can be a suitable approach for student performance prediction. We propose such a neural network architecture containing two modules: (i) a…

The extraction of cooccurrences between two events, A and B, is a central learning mechanism shared by all species capable of associative learning. Formally, the cooccurrence of events A and B appearing in a sequence is measured by the transitional probability (TP) between these events, and it corresponds to the probability of the second stimulus…