Articles

The Role of Self-Regulated Learning in Mediating the Relationship between Smartphone Usage Intensity and High School Students’ Academic Motivation

/in /by

Digital technology has made smartphones an essential part of students’ lives. Although smartphones can aid learning, excessive use can distract students and decrease their engagement in learning. A quantitative method with a mediation model for a correlational design using multiple linear regression analysis was used in this study. The purpose of this study is to explain the role of self-regulated learning in mediating the relationship between smartphone usage intensity and academic motivation of high school students. A total of 395 high school students were randomly selected from the high school student population. The scales used for data collection included a smartphone usage intensity scale, a self-regulated learning scale, and an academic motivation scale. The research results show that 1) the intensity of smartphone use significantly affects self-regulated learning by 30.3%, 2) academic motivation significantly affects self-regulated learning by 20.8%, and 3) self-regulated learning significantly affects the intensity of smartphone use and academic motivation. Followed by an F regression value of 15.392. An Rsquared value of 0.073 indicates that self-regulated learning contributes 70.3% to the intensity of smartphone use and academic motivation. Smartphone use intensity and academic motivation are considered significant predictors of the variation in selfregulated learning among high school students. The pattern of smartphone use and the level of academic learning drive influence students’ ability to independently plan, monitor, and evaluate their learning process.

The Impact of Study Habits on Academic performance: A Meta-Analysis

/in /by

This meta-analysis investigates the relationship between students’ study habits and their academic performance across a range of educational levels and cultural settings. The study synthesizes findings from fifteen empirical studies selected through a systematic review of academic databases. These studies employed various research methodologies, including quantitative, qualitative, and mixed-method designs. They examined the impact of behaviors such as time management, note-taking, goal setting, and self-testing on academic outcomes. The analysis reveals a positive association between effective study habits and academic performance. However, the strength of this relationship varies depending on factors such as educational level, cultural background, gender, learning environment, and institutional support. While many studies report a significant correlation, others show weak or non-significant results, highlighting the complexity of this relationship and the influence of contextual variables. This meta-analysis underscores the importance of integrating structured study skills training into educational programs and developing targeted interventions tailored to students’ individual needs and learning contexts. The findings contribute to a deeper understanding of how study behaviors affect academic success and offer practical implications for educators, academic advisors, and policymakers aiming to enhance student learning outcomes.

Approaching the ASSURE Model and Proposing a Teaching Process for Mathematics Using AI Chatbots Combined with Gamification in a Self-Regulated Learning Framework

/in /by

The ASSURE model is a method for designing and implementing lessons developed to optimize the teaching and learning process, particularly in integrating educational technologies. This model assists teachers in creating highly flexible lessons, enabling students to acquire knowledge more effectively through the use of technology and modern teaching methods. AI Chatbots facilitate the automation of responses and support personalized learning for students, while gamification provides an engaging learning environment that helps students develop critical thinking and problem-solving skills in mathematics through the incorporation of game elements. Research findings indicate that the combination of AI Chatbots and gamification in teaching can enhance students’ learning of mathematics, while also increasing engagement and motivation. This paper approaches the ASSURE model and proposes a teaching process utilizing AI Chatbots combined with gamification in a self-regulated learning framework, aiming to guide teachers in organizing mathematics instruction in a scientific and effective manner.

Design of Knowledge Flow According to the Approach of Self-Regulation Learning for Teaching Maths on Chatbot

/in /by

Each student has different skills, interests, and learning paces in a classroom. If each student has a personal tutor to support learning according to their ability, it will improve the quality of teaching and no student will be left behind. In reality, no school has enough teachers to support individual learning, but each teacher has to handle many students in the same class. Therefore, an AI Chatbot that acts as a “virtual teacher” next to a real teacher can do that. AI Chatbot can support individual students in a friendly, interesting environment and provide knowledge depending on their cognitive level. Learning with AI Chatbot also helps students feel more interested and motivated with new learning methods. Instead of teachers providing information and knowledge for students to remember and apply, AI Chatbot will help learners build and create their knowledge through interactions and experiences. Besides providing answers to learners’ queries, Chatbots can provide step-by-step instructions to achieve teaching goals for specific lessons. In this article, the authors based on the applications of AI Chatbot in teaching to present a teaching scenario using AI Chatbot to teach mathematics with a self-regulated learning orientation for primary school students. Specifically, the authors have built a scenario for the “Millimeter” lesson in the Mathematics, 3rd Grade according to three phases of self-regulated learning: forethought, performance and self-reflection.

Lived Experiences of Grade – 11 Stem Students in Mathematics Using Modular Distance Learning

/in /by

This qualitative study explored the lived experiences of Grade – 11 STEM students in mathematics using modular distance learning. With the aim of understanding the challenges, coping strategies, support systems, emotional factors, and perceived advantages associated with this learning modality, the research design employed a phenomenological approach. Data collection involved one-on-one interviews with 12 participants, and thematic analysis was utilized to identify common themes. The findings revealed challenges in understanding complex topics, managing the modular structure, and dealing with distractions and connectivity issues. Participants adapted through self-regulated learning, utilization of online resources, and independent learning strategies. The study highlighted the importance of teacher and parental support, effective guidance, and the promotion of positive emotional experiences. The advantages identified include access to information, flexible time management, and autonomous exploration of resources. The implications of these findings would contribute to the design and implementation of educational interventions, addressing challenges, and enhancing distance learning experiences. The study concluded by offering recommendations for educators, policymakers, and researchers to optimize distance learning programs and support student success.