Mining problems and exploring rules are the key problems in the learning process, and also the difficulties in education big data. Therefore, taking learning behavior as the research objective, this study demonstrates the collaborative training method of multi view learning interaction process driven by big data, so as to realize the tendency…

The use of e-learning services is growing in different contexts, especially in the COVID-19 pandemic. This study aims to examine students' acceptance of and intention to use Learning Management Systems (LMSs) for university education in Brazil using the extended technology acceptance model, unified theory of acceptance and use of technology…

Computational models of child language development can help us understand the cognitive underpinnings of the language learning process, which occurs along several linguistic levels at once (e.g., prosodic and phonological). However, in light of the replication crisis, modelers face the challenge of selecting representative and consolidated infant…

Personalized computer-based tutoring demands learning systems and applications that identify and keep personal characteristics and features for each individual learner. This is achieved by the technology of student modeling. One prevalent technique of student modeling is stereotypes. Furthermore, individuals differ in how they learn. So, the way…

Academic advising plays an important role in students' decision-making in higher education. Data-driven methods provide useful recommendations to students to help them with degree completion. Several course recommendation models have been proposed in the literature to recommend courses for the next semester. One aspect of the data that has yet to…

A data-driven model where individual learning behavior is a linear combination of certain stylized learning patterns scaled by learners' affinities is proposed. The absorption of stylized behavior through the affinities constitutes "building blocks" in the model. Non-negative matrix factorization is employed to extract common learning…

The use of realistic visualizations has gained considerable interest due to the proliferation of virtual reality equipment. This review is concerned with the theoretical basis, technical implementation, cognitive effects, and educational implications of using realistic visualizations. Realism can be useful for learners, but in several studies,…

Adaptive E-learning platforms provide personalized learning process relying mainly on learning styles. The traditional approach to find learning styles depends on asking learners to self-evaluate their own attitudes and behaviors through surveys and questionnaires. This approach presents several weaknesses including the lack of self-awareness of…

Purpose: The general goal of this paper is to help educators understand the importance of MOOC training to school teachers and their hypothetical value for predicting the use of teaching strategies in the face-to face-classroom teaching. With this purpose, the study is guided by two research questions: (1) Are there different patterns of…

LibGuides are an essential resource in academic libraries. Although librarians use LibGuides primarily as instructional tools there is little discussion about the application of pedagogical and learner-centered design principles to the design of LibGuides. Current research focuses almost exclusively on issues of usability, resulting in best…

In this paper we use historic score-reporting records and test-taker metadata to inform data-driven recommendations that support international students in their choice of undergraduate institutions for study in the United States. We investigate the use of Structural Topic Modeling (STM) as a context-aware, probabilistic recommendation method that…

Stimuli that capture the central tendency of presented exemplars are often preferred--a phenomenon also known as the classic beauty-in-averageness effect. However, recent studies have shown that this effect can reverse under certain conditions. We propose that a key variable for such ugliness-in-averageness effects is the category structure of the…

This study tested two cognitive models, learning styles and dual coding, which make contradictory predictions about how learners process and retain visual and auditory information. Learning styles-based instructional practices are common in educational environments despite a questionable research base, while the use of dual coding is less…

Although infants begin learning about their environment before they are born, little is known about how the infant brain changes during learning. Here, we take the initial steps in documenting how the neural responses in the brain change as infants learn to associate audio and visual stimuli. Using functional near-infrared spectroscopy (fNRIS) to…

It is a hard task to strike a balance between extents of control a learner exercises and the amount of guidance, active or passive, afforded by the learning environment to guide, support, and motivate the learner. Adaptive systems strive to find the right balance in a spectrum that spans between self-control and system-guidance. They also concern…