The study investigates automated and controlled cognitive processes that occur when university students read multiple documents (MDs). We examined data of 401 students dealing with two MD sets in a digital environment. Performance was assessed through several comprehension questions. Recorded log data gave indications about students' time…

It is known that bilingualism may cause some specific problems with the articulation of sounds and errors in reading and writing when acquiring linguistic skills. The paper presents the results and conclusions related to the use of the Warnke method in improving the phonological competence of a bilingual girl aged seven, which learned two…

Greer and Mark's (2016) paper suggested and reviewed different methods for evaluating the effectiveness of intelligent tutoring systems such as Propensity score matching. The current study aimed at assessing the effectiveness of automated personalized feedback intervention implemented via the Student Advice Recommender Agent (SARA) in a first-year…

Progress monitoring is used to assess a student's performance during the early stages of literacy development. Computerized progress monitoring systems are capable of scoring some progress monitoring measures automatically. However, other measures, such as those involving writing or sign language, are typically scored manually, which is…

With the vast number of apps and the complexity of their features, it is becoming challenging for teachers to select a suitable learning app for their courses. Several evaluation frameworks have been proposed in the literature to assist teachers with this selection. The iPAC framework is a well-established mobile learning framework highlighting…

Curriculum-based measurement of oral reading fluency (CBM-R) is widely used across the United States as a strong indicator of comprehension and overall reading achievement, but has several limitations including errors in administration and large standard errors of measurement. The purpose of this study is to compare scoring methods and passage…

Kaggle is a data modeling competition service, where participants compete to build a model with lower predictive error than other participants. Several years ago they released a simplified service that is ideal for instructors to run competitions in a classroom setting. This article describes the results of an experiment to determine if…

Globalizations across organizations are impacted by economic, political, legal, security, social, cultural, ecological, and technological dimensions among others. This paper presents the readings from relevant articles and studies pertaining to the relationship between technology and its dimensions with globalization. Globalization and…

The Artificial Intelligence (AI)-driven automated decision-making support system has been heralded as a considerable workforce replacement in the near future by automating mundane repetitive tasks and eliminating time-consuming support tasks in all disciplines (Park & Glenn, 2017). Even though a number of practical hurdles in the field of the…

Systematic reviews are a cornerstone of today's evidence-informed decision making. With the rapid expansion of questions to be addressed and scientific information produced, there is a growing workload on reviewers, making the current practice unsustainable without the aid of automation tools. While many automation tools have been developed and…

"Learning-in-action" depends on interactions with learning content, peers and real world problems. However, effective learning-in-action also depends on the extent to which students are "active-in-thinking," making meaning of their learning experience. A critical component of any technology to support active thinking is the…

Designing good multiple choice questions (MCQs) for education and assessment is time consuming and error-prone. An abundance of structured and semi-structured data has led to the development of automatic MCQ generation methods. Recently, ontologies have emerged as powerful tools to enable the automatic generation of MCQs. However, current question…

Recent advances in computational linguistics and the social sciences have created new opportunities for the education research community to analyze relevant large-scale text data. However, the take-up of these advances in education research is still nascent. In this paper, we review the recent automated text methods relevant to educational…

Purpose: Data mining algorithms using electronic health records (EHRs) are useful in large-scale population-wide studies to classify etiology and comorbidities (Casey et al., 2016). Here, we apply this approach to developmental language disorder (DLD), a prevalent communication disorder whose risk factors and epidemiology remain largely…

We have used an unsupervised machine learning method called latent Dirichlet allocation (LDA) to thematically analyze all papers published in the Physics Education Research Conference Proceedings between 2001 and 2018. By looking at co-occurrences of words across the data corpus, this technique has allowed us to identify ten distinct themes or…