Random encouragement designs evaluate treatments that aim to increase participation in a program or activity. These randomized controlled trials (RCTs) can also assess the mediated effects of participation itself on longer term outcomes using a complier average causal effect (CACE) estimation framework. This article considers power analysis…

Background: The study focuses on the need to optimise assessment scales for support needs in individuals with intellectual and developmental disabilities. Current scales are often lengthy and redundant, leading to exhaustion and response burden. The goal is to use machine learning techniques, specifically item-reduction methods and selection…

Existing toolkits for analyzing movement dynamics in animal ecology primarily focus on individual or group behavior in habitats without predefined boundaries, while methods for studying human activity often cater to bounded environments, such as team sports played on defined fields. This leaves a gap in tools for modeling and analyzing human group…

The study intended to describe profiles of three achievement emotions (enjoyment, boredom, anxiety), their associations with each other and with control-value appraisals within the framework of the control-value theory. A total of 2002 Chinese university EFL students from 11 universities in China participated in the questionnaire survey.…

This study explored how caregiver-reported executive functioning domains, assessed by the BRIEF2 at baseline, predicted behavioral challenges reported by caregivers using the CBCL six months later. The sample included 94 youth with Down syndrome, aged 6 to 18 years. Results of hierarchical regression analyses revealed that, after controlling for…

This study aimed to develop a prediction model to classify students based on their academic procrastination tendencies, which were measured and classified as low and high using a self-report tool developed based on the students' assignment submission behaviours logged in the learning management system's database. The students' temporal learning…

Predictive analytics is widely used in various domains, including education, to inform decision-making and improve outcomes. However, many predictive models are proprietary and inaccessible for evaluation or modification by researchers and practitioners, limiting their accountability and ethical design. Moreover, predictive models are often opaque…

Choosing a field of study (study major) is challenging for prospective students. However, little research has examined factors measured prior to enrollment to predict motivation and well-being in a specific study major. Based on literature on affective forecasting and person-environment fit, prospective students' well-being forecast could be such…

Since the introduction by Kermack and McKendrick in 1927, the Susceptible-Infected-Recovered (SIR) epidemic model has been a foundational model to comprehend and predict the dynamics of infectious diseases. Almost for a century, the SIR model has been modified and extended to meet the needs of different characteristics of various infectious…

It is no surprise that concern for the future is on the rise. Several catastrophes obscure our future(s) imaginary, such as climate change, a global pandemic, racial inequality, and political polarization. Students are feeling a disconnect between what they learn in classrooms and the futures that populate their media platforms. Futures literacies…

Many studies have linked quality in early childhood education and care [ECEC] to school performance, but the mechanisms of how ECEC process quality affects children in ways that lead to improved school performance is unclear. In this study on 7431 children in Norway, we test the hypothesis that the relation between process quality in ECEC and…

This study investigates infants' neural and behavioral responses to maternal ostensive signals during naturalistic mother-infant interactions and their effects on object encoding. Mothers familiarized their 9- to 10-month-olds (N = 35, 17 females, mainly White, data collection: 2018-2019) with objects with or without mutual gaze, infant-directed…

Knowledge tracing (KT) for evaluating students' knowledge is an essential task in personalized education. More and more researchers have devoted themselves to solving KT tasks, e.g., deep knowledge tracing (DKT), which can capture more sophisticated representations of student knowledge. Nonetheless, these techniques ignore the reconstruction of…

Given the extensive use of online learning in educational settings, Knowledge Tracing (KT) is becoming increasingly essential. KT primarily aims to predict a student's future knowledge acquisition based on their past learning activities, thus enhancing the efficiency of student learning. However, the effective acquisition of dynamic and evolving…

Designing and constructing pedagogical tests that contain items (i.e. questions) which measure various types of skills for different levels of students equitably is a challenging task. Teachers and item writers alike need to ensure that the quality of assessment materials is consistent, if student evaluations are to be objective and effective.…