Many psycholinguistic studies examine how people parse sentences in isolation; however, years of work in discourse processing have shown that sentence-level interpretations are influenced at some stage by discourse-level information. Evidence over the past 20 years remains mixed as to the temporal dynamics of such top-down interactions. In…

The search for relevant scientific articles is a crucial step in any research project. However, the vast number of articles published and available online in digital databases (Google Scholar, Semantic Scholar, etc.) can make this task tedious and negatively impact a researcher's productivity. This article proposes a new method of recommending…

This paper has designed a professional and practical SIMD computer mathematical model based on the SIMD physical machine model combined with the variable addition method. Furthermore, the model is applied in image collection, processing, and display operations, and a SIMD data parallel image processing system is finally established by absorbing…

Background and Context: We replicated and expanded on previous work about how well students learn dynamic programming, a difficult topic for students in algorithms class. Their study interviewed a number of students at one university in a single term. We recruited a larger sample size of students, over several terms, in both large public and…

Computational thinking (CT) is becoming increasingly important as a learning content. Subject-integrated approaches aim to develop CT within other subjects like mathematics. The question is how exactly CT can be integrated and learned in mathematics classrooms. In a case study involving 12 sixth-grade learners, CT activities were explored that…

Design education includes many pursuits that deal with creativity, thinking and visual communication techniques in the learning process. This study aims to create a participatory learning algorithm based on a location, while measuring the spatial impact through an emergent situation. The exemplified issue is determined as fire that emerged due to…

Before they even talk, infants become sensitive to the speech sounds of their native language and recognize the auditory form of an increasing number of words. Traditionally, these early perceptual changes are attributed to an emerging knowledge of linguistic categories such as phonemes or words. However, there is growing skepticism surrounding…

Algorithmic decision-making systems such as Learning Analytics (LA) are widely used in an educational setting ranging from kindergarten to university. Most research focuses on how LA is used and adopted by teachers. However, the perspective of students and parents who experience the (in)direct consequences of these systems is underexplored. This…

Aim/Purpose: The purpose of this study is to review and categorize current trends in student engagement and performance prediction using machine learning techniques during online learning in higher education. The goal is to gain a better understanding of student engagement prediction research that is important for current educational planning and…

Despite the growing use of large language models (LLMs) in educational contexts, there is no evidence on how these can be operationalized by students to generate custom datasets suitable for teaching and learning. Moreover, in the context of network science, little is known about whether LLMs can replicate real-life network properties. This study…

Self-regulated learning is an essential skill that can help students plan, monitor, and reflect on their learning in order to achieve their learning goals. However, in situations where there is a lack of effective feedback and recommendations, it becomes challenging for students to self-regulate their learning. In this paper, we propose an…

As algorithmic decision making is increasingly deployed in every walk of life, many researchers have raised concerns about fairness-related bias from such algorithms. But there is little research on harnessing psychometric methods to uncover potential discriminatory bias inside decision-making algorithms. The main goal of this article is to…

Computer science development, especially machine learning, is a thriving innovation essential for education. It makes the process of teaching and learning more accessible and manageable and also promotes equality. The positive influence of machine learning can also be felt in Islamic studies, particularly in Hadith studies. This literature review…

The artificial intelligence methods might be applied to see through the education problems, and make effective prediction and decision. The transformation from data to decision are inseparable from the learning analytics. In order to solve the dynamic multi-objective decision problems, a decision learning algorithm is designed to analyze the…

The study investigates the potential of anxiety clusters in predicting programming performance in two distinct coding environments. Participants comprised 83 second-year programming students who were randomly assigned to either a block-based or a text-based group. Anxiety-induced behaviors were assessed using physiological measures (Apple Watch…