Modeling reading comprehension processes is a critical task for Learning Analytics, as accurate models of the reading process can be used to match students to texts, identify appropriate interventions, and predict learning outcomes. This paper introduces an improved version of the Automated Model of Comprehension, namely version 4.0. AMoC has its…

Educational institutions are increasingly investing into digital delivery, acquiring new devices, and employing novel software and services. The rising costs associated with maintenance, in combination with increasing redundancy of older technologies, presents multiple challenges. While lesson content itself may not have changed, the educational…

This article presents an instructional technology-based cycle model intended to support and facilitate the teaching and learning of mathematics, particularly calculus. The study used quantitative methods with quasi-experimental research that uses non-randomised assignments of the study group that are categorised into experimental and control…

Many individuals with autism experience challenges using language in social contexts (i.e., pragmatic language). Characterizing and understanding pragmatic variability is important to inform intervention strategies and the etiology of communication challenges in autism; however, current manual coding-based methods are often time and labor…

The rationality and the effectiveness of classroom teaching behavior directly influence the quality of classroom instruction. Analyzing teaching behavior intelligently can provide robust data support for teacher development and teaching supervision. By observing verbal and nonverbal behaviors of teachers in the classroom, valuable data on…

This study investigates user satisfaction with e-learning systems in higher education institutions, examining the perspectives of students, lecturers, and elearning officers and heads of the department of Information Technology as key informants. A total of 375 student respondents from Diploma, Bachelor, and Masters levels, 51 lecturers, and 15…

Purpose: The purpose of this study was to further evaluate an eight-step partner instructional model developed by Kent-Walsh and McNaughton that has been demonstrated to improve implementation quality and fidelity among adults in clinical and educational settings who support the use of augmentative and alternative communication (AAC) for…

We propose that machine-learned computational models (MLCMs), in which the model parameters and perhaps even structure are learned from data, can complement extant approaches to the study of text and discourse. Such models are particularly useful when theoretical understanding is insufficient, when the data are rife with nonlinearities and…

Purpose: Research in communication sciences and disorders frequently involves the collection of clusters of observations, such as a series of scores for each individual receiving treatment over the course of an intervention study. However, little discipline-specific guidance is currently available on the subject of building and interpreting…

This study extends the understanding of the process of teachers' technology adoption by investigating the dynamic nature of the adoption process. We propose a nonhomogeneous hidden Markov model that reveals the dynamics of teachers' adoption over time and examines the impact of internal and external factors, including experiences, interventions,…

Since MOOC is suffering high dropout rate, researchers try to explore the reasons and mitigate it. Focusing on this task, we employ a composite model to infer behaviors of learners in the coming weeks based on his/her history log of learning activities, including interaction with video lectures, participation in discussion forum, and performance…

As higher education institutions develop fully online course programs to provide better access for the non-traditional learner, there is increasing interest in identifying students who may be at risk of attrition and poor performance in these online course programs. In our study, we investigate the effectiveness of an online orientation course in…

To succeed in STEM, students need to learn to use visual representations. Most prior research has focused on conceptual knowledge about visual representations that is acquired via verbally mediated forms of learning. However, students also need perceptual fluency: the ability to rapidly and effortlessly translate among representations. Perceptual…

Connecting data and chance is fundamental in statistics curricula. The use of software like TinkerPlots can bridge both worlds because the TinkerPlots Sampler supports learners in expressive modeling. We conducted a study with elementary preservice teachers with a basic university education in statistics. They were asked to set up and evaluate…

As two teacher educators, we conducted a collegial action research study and investigated how collaborative lesson preparation and reflection that focused on prospective teachers' thinking supported our perspectives on teaching and learning. We conducted this action research to provide more equal education opportunities to the prospective teachers…