This study aims to analyze the factors influencing the typology of Turkic words to examine the specifics of the way students learn Turkic languages in higher education institutions. A hypotheticdeductive, survey, and comparative method was used for the study. Results showed that the learners have trouble constructing oral discourse and do not…

Cognitive presence is a core construct of the Community of Inquiry (CoI) framework. It is considered crucial for deep and meaningful online-based learning. CoI-based real-time dashboards visualizing students' cognitive presence may help instructors to monitor and support students' learning progress. Such real-time classifiers are often based on…

Self-regulated learning (SRL) theory comprises cognitive, metacognitive, and affective aspects that enable learners to autonomously manage their learning processes. This article presents a systematic literature review on the measurement of SRL in digital platforms, that compiles the 53 most relevant empirical studies published between 2015 and…

In order to make informed instructional decisions, teachers need psychological knowledge about relational categories. We conducted two 2 x 2 experiments to examine effective designs for learning relational categories in the context of teacher education. In both experiments, a blocked compared to an interleaved example format was more beneficial…

In this article Antti Moilanen assesses criticisms of Wolfgang Klafki's model of exemplary teaching made by Meinert Meyer and Hilbert Meyer and by Chi-Hua Chu. "Exemplary teaching" is a style of discovery-based teaching in which students study concrete examples of general principles in such a way that they acquire transferable knowledge…

Concepts contain rich structures that support flexible semantic cognition. These structures can be characterized by patterns of feature covariation: Certain features tend to cluster in the same items (e.g., "feathers," "wings," "can fly"). Existing computational models demonstrate how this kind of structure can be…

This paper explores the efficacy of ChatGPT, a generative artificial intelligence in educational contexts, particularly concerning its potential to assist students in overcoming academic challenges while highlighting its limitations. ChatGPT is suitable for solving general problems. When a student comes across academic challenges, ChatGPT may…

In classification learning of artificial stimuli, participants learn the perfectly diagnostic dimension better than the partially diagnostic dimensions. Also, there is a strong preference for a unidimensional categorization based on the perfectly diagnostic dimension. In a different experimental procedure, called array-based classification task,…

Categorization researchers have long debated the possibility of multiple category-learning systems. The need persists for paradigms that dissociate explicit-declarative category-learning processes (featuring verbalizable category rules) from implicit-procedural processes (featuring stimulus-response associations lying beneath declarative…

The challenge posed by algebra story problems creates a significant hurdle for many students, transcending both the mathematical content of the problem and the specific instructional background received. This study offers a distinctive contribution to the existing literature by focusing on the cognitive conditions essential for comprehension in…

This research is part of the Artificial Intelligence Virtual Trainer (AI-VT) project which aims to create a system that can identify the user's skills from a text by means of machine learning. AI-VT is a case-based reasoning learning support system can generate customized exercise lists that are specially adapted to user needs. To attain this…

The quest for determining the degree of learning difficulty associated with different types of categories has been instrumental in our understanding of human categorization behavior and, more broadly, human generalization. For instance, we now know that the topological nature of the dimensions (e.g., whether these are integral or separable) that…

In a range of settings, human operators make decisions with the assistance of automation, the reliability of which can vary depending upon context. Currently, the processes by which humans track the level of reliability of automation are unclear. In the current study, we test cognitive models of learning that could potentially explain how humans…

With the advent of technological advancement in learning, such as context-awareness, ubiquity and personalisation, various innovations in teaching and learning have led to improved learning. This research paper aims to develop a system that supports personalised learning through adaptive content, adaptive learning path and context awareness to…

In this article, we investigate a systematic workflow that supports the learning engineering process of formulating the starting question for a conversational module based on existing learning materials, specifying the input that transformer-based language models need to function as classifiers, and specifying the adaptive dialogue structure,…