Reputable scholars are developing typologies of ignorance for different reasons including philosophizing about ignorance as well as understanding ignorance within professions, the scientific endeavour, and women's health (discussed herein). These four agnotological typologies (i.e., the study of ignorance) proved useful for revealing and…

We propose an innovative, effective, and data-agnostic method to train a deep-neural network model with an extremely small training dataset, called VELR (Voting-based Ensemble Learning with Rejection). In educational research and practice, providing valid labels for a sufficient amount of data to be used for supervised learning can be very costly…

Using cognitive diagnostic modeling (CDM), this study identified subtypes of mathematics learning disability (MLD) based on children's numerical skills and examined the language and spatial precursors of these subtypes. Participants were 99 MLD children and 420 low achievers identified from 1839 Finnish children (966 boys) who were followed from…

Multimodal imaging studies targeting preschoolers and low-functioning autism spectrum disorder (ASD) patients are scarce. We applied machine learning classifiers to parameters from T1-weighted MRI and DTI data of 58 children with ASD (age 3-6 years) and 48 typically developing controls (TDC). Classification performance reached an accuracy,…

In online courses, discussion forums play a key role in enhancing student interaction with peers and instructors. Due to large enrolment sizes, instructors often struggle to respond to students in a timely manner. To address this problem, both traditional machine learning (ML) (e.g., Random Forest) and deep learning (DL) approaches have been…

Many educational and psychological studies have shown that the development of students is generally step-by-step (i.e. ordinal development) to a specific level. This study proposed a novel longitudinal learning diagnosis model with polytomous attributes to track students' ordinal development in learning. Using the concept of polytomous attributes…

This study analyzed the influence of rhetoric in the endorsement text on the willingness of the crowd to participate in citizen science projects. Four categories of endorsers were studied: professors, students, industrial researchers, and amateur researchers. Using 1243 endorsement texts from 543 citizen science projects as the corpus, the effects…

Purpose: This article provides a tutorial introduction to ordinal pattern analysis, a statistical analysis method designed to quantify the extent to which hypotheses of relative change across experimental conditions match observed data at the level of individuals. This method may be a useful addition to familiar parametric statistical methods…

A text semantic classification is an essential approach to recognizing the verbal intention of online learners, empowering reliable understanding, and inquiry for the regulations of knowledge construction amongst students. However, online learning is increasingly switching from static watching patterns to the collaborative discussion. The current…

Development dyslexia (DD) is a common language disorder, that significantly affects children. Despite having ordinary intelligence, dyslexic people struggle with reading, writing, and comprehension in their native tongue. It is still unclear whether dyslexic kids have difficulties with visuo-spatial working memory. Using meta-analysis, this gap…

The last few years have witnessed an upsurge in the number of studies using Machine and Deep learning models to predict vital academic outcomes based on different kinds and sources of student-related data, with the goal of improving the learning process from all perspectives. This has led to the emergence of predictive modelling as a core practice…

This study aims to conduct a comparative study of Bagging and Boosting algorithms among ensemble methods and to compare the classification performance of TreeNet and Random Forest methods using these algorithms on the data extracted from ABIDE application in education. The main factor in choosing them for analyses is that they are Ensemble methods…

In education, machine learning (ML), especially deep learning (DL) in recent years, has been extensively used to improve both teaching and learning. Despite the rapid advancement of ML and its application in education, a few challenges remain to be addressed. In this thesis, in particular, we focus on two such challenges: (i) data scarcity and…

For nearly half a century now, Garner interference has been serving as the gold standard measure of dimensional interaction and selective attention. But the mechanisms that generate Garner interference are still not well understood. The current study proposes a novel theory that ascribes the interference (and dimensional interaction in general) to…

For 25 years, the National Science Foundation's Alliances for Graduate Education and the Professoriate (AGEP) program has been supporting efforts to broaden participation and meaningfully diversify the Science, Technology, Engineering, and Mathematics (STEM) postdoctoral and faculty ranks. To examine the structures and strategies carried out by…