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Reflection and goal-setting are interrelated processes in well-established educational theories to promote in-depth self-reflection and self-regulated learning. Prior studies have considered reflection to be an important antecedent for meaningful goal-setting. Yet, there lacks empirical evidence to shed light on how students' abilities to reflect inform their abilities to set goals. Hence, in the present study, we aimed to quantify the connection between students' retrospective reflection and their subsequent goal-setting, and derive more in-depth insights to benefit educators in their teaching to promote deeper reflection, more specific goal-setting and better self-regulation. To this end...

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The use of computational tools to predict academic success has become increasingly popular. Machine learning algorithms, trained on past study histories, have been shown to provide valid predictions. However, knowing about biases and unfairness in algorithms, one should take a closer look at these predictions. This paper explores the extent to which the predictive accuracy of academic success varies between specific groups of students, focusing on traditional and non-traditional students (NTS), who have not acquired a higher education entrance qualification at school. In a case study the study compares several popular algorithms and their prediction quality, and investigates whether...

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Retaining learner engagement is a major challenge in online learning environments, which is even more intensified with learning spaces increasingly built by combining resources from multiple independent sources. Narrative-centric learning experience has been found to improve learner engagement by several researchers. Towards this end, we propose an AI-based approach that generates auxiliary learning content called narrative fragments which are interspersed into the learning pathways to create interactive learning narratives. The proposed approach consists of the automatic generation of two types of narrative fragments– overviews of the learning pathway segments and reflection...

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This research explored the typologies of self-regulated learners in an asynchronous online Chemistry I (OCI) course of an undergraduate active learning program. Student readiness and capability regarding self-regulated learning (SRL), the activity logs in the learning management system, and academic achievement were collected to investigate behavioral sequences of different typologies of learning self-regulation. Seventeen students who took OCI in the 2019 school year were recruited for the study. Through learning analytics for the 3965 behavioral codes, the study generated three key results. First, hierarchical cluster analysis classified two typologies of self-regulated online learners:...

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Massive Open Online Courses (MOOCs) are a type of Learning Management Systems (LMSs), but it seems that the influence of the instructor in these systems is minimal or simply lacking. These systems present the learning content and materials to all learners attending the course in the same way and fail to offer individualized instruction that recognizes the individual differences and needs of the learners. It is reported that such problems can be eliminated by making the new generation intelligent learning systems. However, there is still an ongoing search for making such systems intelligent and a conceptual discussion concerning them. Integrating an intelligent tutoring system (ITS) with...

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The benefits of artificial intelligence (AI)-enabled language models, such as ChatGPT, have contributed to their growing popularity in education. However, there is currently a lack of evidence regarding the perception of ChatGPT, specifically among design students. This study aimed to understand the product design (PD) and user experience design (UXD) students' views on ChatGPT and focused on an Indian university. The study employed a survey research design, utilizing questionnaires as the primary data collection method. The collected data (n = 149) was analyzed using descriptive statistics (i.e., frequency, percentage, average, and standard deviation (SD). Inferential statistics (i.e., one...

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This study aimed at developing an instructional tool for the artificial intelligence education of young students, and used learning analytics to identify the sequential learning behavioral patterns of students during the process of learning with the instructional tool. The instructional experiment took 9 weeks. The first stage of the course was 5 weeks spent on individual learning of MIT App Inventor and Personal Image Classifier. The second stage was 4 weeks spent on cooperative learning to make a robot car and play a computational thinking board game. In the second stage, the students worked in pairs to make the robot car. Finally, they played the computational thinking board game with...

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This study highlights the potential of fine-tuned ChatGPT (GPT-3.5) for automatically scoring student written constructed responses using example assessment tasks in science education. The application of ChatGPT in research and academic fields has greatly enhanced productivity and efficiency. Recent studies on ChatGPT based on OpenAI's generative model GPT-3.5 proved its superiority in predicting the natural language with high accuracy and human-like responses. GPT-3.5 has been trained over enormous online language materials such as journals and Wikipedia; however, direct usage of pre-trained GPT-3.5 is insufficient for automatic scoring as students do not utilize the same language as...

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This study explores the perception of artificial intelligence (AI)-based Chatbots, specifically Open AI's ChatGPT use, among physics students in four universities in Ghana, Jordan, and the United States. We utilized a survey instrument adapted from the Technology Acceptance Model (TAM) to elicit responses from 804 students. TAM constructs: Perceived Usefulness (PU), Perceived Ease of Use (PEU), Subjective Norms (SN), Attitude Towards Technology Use (ATU), Behavioral Intention (BI), and User Behavior (UB) were assessed. We also assessed perceptions of ethical use (EU) and student learning outcomes (SLO) using a Structural Equation Model (SEM) approach. A measurement model had good fit...

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This paper introduces the design and development of a framework that integrates a large language model (LLM) with a retrieval-augmented generation (RAG) approach leveraging both a knowledge graph and user interaction history. The framework is incorporated into a previously developed adaptive learning support system to assess learners’ code, generate formative feedback, and recommend exercises. Moreover, this study examines learner preferences across three instructional modes: adaptive, Generative AI (GenAI), and hybrid GenAI–adaptive. An experimental study was conducted to compare the learning performance and perception of the learners, and the effectiveness of these three modes using four...

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