The success of online learning relies on college students' self-regulated learning. The common visualizations (e.g., presentation learning behaviors' frequency and duration) are widely used to enhance online self-regulated learning. But most college students still have difficulty in accurately understanding their learning patterns and…

Math anxiety can significantly impair student learning outcomes. This is often due to a lack of self-regulated learning (SRL), leading to a reliance on external guidance. This systematic literature review aimed to increase existing knowledge on the role of SRL in reducing students' mathematics anxiety and to assess its impact on improving learning…

With the development of teaching theory, teaching workers gradually realize the importance of reading ability. Based on the development of new literature, this paper analyzes the relationship between students' reading ability and curriculum training through models. Combined with teaching cases, this paper integrates network-based learning…

This paper proposes a computer-aided teaching model using knowledge graph construction and learning path recommendation. It first creates a multimodal knowledge graph to illustrate complex relationships among knowledge. Learning elements and sequences are then used to form time sequences stored as directed graphs, supporting flexible path…

Writing high-quality procedural texts is a challenging task for many learners. While example-based learning has shown promise as a feedback approach, a limitation arises when all learners receive the same content without considering their individual input or prior knowledge. Consequently, some learners struggle to grasp or relate to the feedback,…

This paper presents the design of a personalized learning agent powered by the Agentic RAG technique. The agent can interpret learners' queries and autonomously decide which tools should be used to generate the most suitable response. When the learner shares an Open Educational Resource (OER) they wish to learn from, the agent first breaks the…

Academically talented students with autism, also known as twice-exceptional students with autism (2eASD), are increasingly identified in school. These students present challenges to educators who attempt to plan and implement successful instructional opportunities, as teachers' knowledge and use of evidence-based practices (EBPs) for students…

This study investigated the feasibility and effectiveness of using a flipped classroom (FC) approach to combine self-regulated learning (SRL) instruction and out-of-class eLearning activities in a two-year reading intervention program to facilitate students' learning of classical Chinese reading. A total of 352 junior secondary students from three…

Purpose: This study aimed to analyze audiovisual speech perception strategies in children with dyslexia, specifically addressing difficulties in phonological processing and reading. Our objective was to investigate the impact of different training programs (phonetic and visual) on learning and assess individual differences in strategy preferences…

Background/purpose: This study examines integrating the VARK learning style model into Learning Management Systems (LMS) to create more personalized learning experiences. The VARK model classifies the learners as Visual, Auditory, Reading, Writing, or Kinesthetic, enabling tailored instructional strategies. Materials/methods: By employing an…

There have been many studies about the effectiveness of differentiated instruction in promoting student-centered learning. However, most of these studies have focused on primary and secondary education. There is hardly any research about its application and effectiveness in higher education settings. Furthermore, there is a need to identify the…

By creating specific prompts, educators can harness the power of AI models to generate tailored content, provide instant feedback, and simulate real-world scenarios for deeper learning engagement. Whether it's creating personalized lesson plans, generating creative writing prompts, or assisting with problem-solving exercises, generative AI creates…

This study aims to produce a more personalized recommendation system for online learning using multicriteria in collaborative filtering and data from the Binus Online Learning repository as a knowledge base. The study uses forecasting (regression) and consists of three stages: (1) collecting data on the results of the learning process; (2) adding…

This qualitative case study proposes a pedagogy to support the academic success of students from historically excluded groups (HEGs), e.g. first-generation students, low-income students, and Students of Color, who are struggling academically. We adopted a 'student-ready' approach (McNair et al. 2016), which foregrounds institutional responsibility…

This study investigates the impact of AI-assisted language learning (AIAL) strategies on cognitive load and learning outcomes in the context of language acquisition. Specifically, the study explores three distinct AIAL strategies: personalized feedback and adaptive learning, interactive exercises with speech recognition, and intelligent tutoring…