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…

Statistical knowledge is required for students in a range of disciplines. However, there are limited educator resources that exist for applying statistics to solve real-world problems. This investigation provides one approach to teaching statistics using entrepreneurial-minded learning (as a way to connect real-world applications and value…

Drawing upon the social network theory and social cognitive theory, this research proposes a model that assesses team performance from the mediating aspect of knowledge application, which represents a team's learning process whereby an effective retrieval mechanism enables the team to access knowledge. In the model, team performance relates to…

As universities around the world have begun to use learning management systems (LMSs), more learning data have become available to gain deeper insights into students' learning processes and make data-driven decisions to improve student learning. With the availability of rich data extracted from the LMS, researchers have turned much of their…

Unfolding models are frequently used to develop scales for measuring attitudes. Recently, unfolding models have been applied to examine rater severity and accuracy within the context of rater-mediated assessments. One of the problems in applying unfolding models to rater-mediated assessments is that the substantive interpretations of the latent…

Social sciences expose many cognitively complex, highly qualified, or fuzzy problems, whose resolution relies primarily on expert judgement rather than automated systems. One of such instances that we study in this work is a reflection analysis in the writings of student teachers. We share a hands-on experience on how these challenges can be…

Students often complain that the content of their studies is not practice-oriented enough because they do not recognize the importance of theory. This theory-practice problem has long been discussed in teacher education. Explicit research on religious education (RE) is only just beginning. This article tries to evince some connectors between…

Research has shown the importance of dealing with real-life issues and of enabling student encounters with complexity in chemistry education in order to increase student participation. Therefore, this study aims to analyse how complexity evolves in students' discussions and how this complexity relates to aspects of tentativeness in chemistry. In…

This research paper seeks to explore a newly proposed model to assist public educational systems with properly integrating digital technology into their currently practiced teaching and learning processes. Digital learning has been adopted for the past two decades under various forms of internet-based learning, such as online learning, e-learning,…

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…

A rich body of empirically grounded results and a solid theory base have often been viewed as signs of a mature discipline. Many disciplines have frequently debated what they should accept as legitimate kinds of theories, the proper roles of theory, and appropriate reference disciplines. Computing education research (CER) in particular has seen a…

School attendance and absenteeism are critical targets of educational policies and practices that often depend heavily on aggregated attendance/absenteeism data. School attendance/absenteeism data in aggregated form, in addition to having suspect quality and utility, minimizes individual student variation, distorts detailed and multilevel…

While formal early career mentoring is considered significant for faculty success, few universities have instituted programmatic mid-career mentoring. We review the reasons mid-career mentoring is important especially for under-represented (URM) faculty and consider the ways the entrenched model of one-on-one mentoring can fail URM faculty. We…

Computer-Supported Collaborative Learning is a promising innovation that ameliorates tutoring through modern technologies. However, the way of recommending collaborative activities to learners, by taking into account their learning needs and preferences, is an important issue of increasing interest. In this context, this paper presents a framework…

Learning interaction activities are the key part of tracking and evaluating learning behaviors, that plays an important role in data-driven autonomous learning and optimized learning in interactive learning environments. In this study, a big data set of learning behaviors with multiple learning periods is selected. According to the instance…