Few data-driven approaches are available to estimate the risk of conclusion change in systematic review updates. We developed a rule-based approach to automatically extract information from reviews and updates to be used as features for modelling conclusion change risk. Rules were developed to extract relevant information from published Cochrane…

A thematic evaluation of data journalism courses resulted in a typology that parses the field and offers guidance to educators. At the center is pattern detection, preceded by data acquisition and cleaning, and followed by data representation. The typology advances academic understanding by offering a precise conceptualization that distinguishes…

In some universities, there is a significant population of first year chemistry students who enter the system with very little prior knowledge of the subject. This, coupled with preconceived ideas of subject difficulty, necessitates that the introduction of key concepts is carried out in a nonthreatening, engaging, simplistic, and efficacious…

We explore how different components of an Automatic Short Answer Grading (ASAG) model affect the model's ability to generalize to questions outside of those used for training. For supervised automatic grading models, human ratings are primarily used as ground truth labels. Producing such ratings can be resource heavy, as subject matter experts…

Growth mixture models (GMMs) are a popular method to uncover heterogeneity in growth trajectories. Harnessing the power of GMMs in applications is difficult given the prevalence of nonconvergence when fitting GMMs to empirical data. GMMs are rooted in the random effect tradition and nonconvergence often leads researchers to modify their intended…

In this approach, formulae-based mnemonics by using the classification of negative charge (localized or delocalized) have been highlighted by innovative and time economic way to enhance interest of students' who belong to paranoia zone of chemistry for the prediction of hybridization state of carbon atom containing negative charge (one or more)…

This paper explores the effect of using multitask learning for abstractive summarization in the context of small training corpora. In particular, we incorporate four different tasks (extractive summarization, language modeling, concept detection, and paraphrase detection) both individually and in combination, with the goal of enhancing the target…

The growth of computer-based testing over the last two decades has motivated the creation of innovative item formats. It is often argued that technology-enhanced items (TEIs) provide better measurement of test-takers' knowledge, skills, and abilities by increasing the authenticity of tasks presented to test-takers (Sireci & Zenisky, 2006).…

This article draws on the ongoing discussion in some European countries about whether and how non-religious worldviews and pupils should be included in religious education (RE). This discussion lacks empirical knowledge about the specific learning conditions of these pupils in RE -- a desideratum that this article addresses. Building on a…

This paper examines recent lexical expansion in New Zealand Sign Language (NZSL) in the context of change in the status of the language and ongoing contact with other (spoken and signed) languages. We categorised 917 new signs documented in the past five years according to their source, semantic field, and sign formation mechanism(s), both…

This study was conducted to compare the efficacy of Lecture-Based-Learning (LBL) and Cooperative-Learning (CL) in teaching 'classification of living things' to Senior High School (SHS) students in Tamale, Northern Region, Ghana. The study was conducted in two SHSs using two science classes offering Biology during the 2020-2021 academic year. A…

U.S. elementary schools administer reading screeners to identify students in need of remedial instruction. However, the administration of additional assessments comes with a cost. It is unclear the extent to which multiple types of reading screeners warrant the increase in resources that could be used for instruction. This study compared…

Automating the classification of instructional strategies from a large-scale online tutorial dialogue corpus is indispensable to the design of dialogue-based intelligent tutoring systems. Despite many existing studies employing supervised machine learning (ML) models to automate the classification process, they concluded that building a…

A key feature of embodied education is the participation of the learners' body and mind with the environment. Yet, little work has been done to review the state of embodied education with Artificial Intelligence (AI). The goal of this systematic review is to examine the state of human and AI's triad engagement in education, that is the mind, body,…

This study explores integrating industry-crowdsourced projects within capstone courses of a 4-year Bachelor of Science program at an accredited American university. A unique business consulting model was developed for the final year course, aligning students with 16-weeks industry projects that reflected their academic goals and the program's…