Adaptive Learning Experiences Research Articles

Artificial intelligence in medical problem-based learning: opportunities and challenges

Abstract Problem-based learning (PBL) in medical education has encountered challenges affecting both teachers and students. The integration of artificial intelligence (AI) into PBL may provide potential solutions to these challenges. This paper aims to discuss the potential advantages of AI, where we found these merits of AI have the potential to improve the quality of PBL lessons. It is also important to pay attention to ethical guidelines and other limitations of AI in PBL lessons as well. Examples of interactions with AI chatbots are provided to demonstrate its application possibility. It is recommended to try using AI in PBL lessons, making it more adaptable for the PBL classroom. Future research should further explore the capabilities of AI, with the goal of developing a more personalized and adaptive learning experience within PBL.

PURE: a Prompt-based framework with dynamic Update mechanism for educational Relation Extraction

Traditional education systems obscure the diverse interconnections inherent within subject knowledge, thus failing to meet the current demand for personalized and adaptive learning experiences. Recent advances have explored various relation extraction techniques to construct educational knowledge graphs that integrate dispersed subject knowledge into a unified framework. However, educational conceptual entities are far more abstract and intricate compared to their real-world equivalents, and these techniques primarily focus on static knowledge, overlooking the dynamic nature of knowledge in practical learning and application scenarios. To address these issues, we propose a Prompt-based framework with dynamic Update mechanism for educational Relation Extraction (PURE). This framework embraces a prompt-tuning strategy and employs a more appropriate MacBERT-large model to encode the instances wrapped by prompt templates. Furthermore, we construct an instance-relation database that serves as an external knowledge base of our framework. A dynamic instance-relation update mechanism is proposed to refine the database, thus enhancing the accuracy of PURE in predicting new triples. We conduct experiments on a Data Structure course relation extraction dataset and three public datasets. The experimental results demonstrate that PURE achieves significant improvements and outperforms several state-of-the-art baselines in efficiency of extraction and utilization of educational information. Comparable performance is achieved even in more complex biomedical relation extraction, validating its robustness and applicability to other domains.

Challenges and Opportunities of Artificial Intelligence Adoption in Islamic Education in Indonesian Higher Education Institutions

This article aims to explore the challenges and opportunities of integrating Artificial Intelligence (AI) in Islamic education within Indonesian Higher Education Institutions (IHEIs). Using qualitative interviews with scholars, the study examines the complexities involved in reconciling AI’s personalized learning potential with traditional Islamic pedagogical methods, which emphasize the teacher's central role in fostering holistic spiritual and moral student development. It addresses ethical concerns such as data privacy, algorithmic bias, and transparency, underscoring the need for equitable AI systems that align with Islamic ethical principles. Additionally, the research highlights the digital divide as a significant barrier to AI adoption, urging stakeholders to invest in improved infrastructure, digital literacy, and teacher training. Despite these challenges, scholars acknowledge AI’s potential to enhance educational quality by enabling more adaptive learning experiences, streamlining administrative processes, and fostering collaboration and innovation across IHEIs. The study emphasizes the need for a balanced and culturally sensitive approach, one that empowers educators and respects Islamic values, thereby ensuring that AI is not only a tool for learning enhancement but also one that preserves the integrity of traditional Islamic teachings. Finally, the research advocates for further exploration into contextually relevant AI tools, innovative pedagogical strategies, and collaborative frameworks to shape a future in which AI and Islamic education harmoniously support each other, enriching students' learning experiences without compromising core values.

Studi Literatur: Pengembangan Bahan Ajar Bahasa yang Menarik untuk Anak Sekolah Dasar dengan Menggunakan Worksheet Interaktif

Language learning at the elementary school level requires an approach that is able to attract students' interest, while building basic language skills that are effective and meaningful. One innovative approach in the digital era is the use of interactive worksheets, which offer a dynamic and adaptive learning experience. This article aims to examine several studies related to the development of interactive worksheet-based language teaching materials aimed at increasing student motivation, participation and in-depth understanding. The method used is a literature study, which includes collection, analysis and synthesis of various relevant research regarding the effectiveness of interactive worksheets in increasing student engagement in the elementary school environment. The results of the literature review show that interactive worksheets can provide several significant benefits, including supporting various student learning styles, stimulating language exploration, and encouraging critical thinking skills. In addition, the findings show that interactive worksheets provide flexibility for teachers in adapting learning materials to students' needs and interests. The main challenges in implementing interactive worksheets include the need for adequate technological facilities and increasing teacher competence in designing interactive and effective teaching materials.

Gamifying Learning with AI: A Pathway to 21st-Century Skills

ABSTRACT This systematic review examines how gamification and artificial intelligence (AI) can converge to foster essential 21st-century skills like creativity, collaboration, and critical thinking in education. The review followed the main PRISMA statement guidelines, resulting in 175 articles for qualitative content analysis and bibliometric network visualization using VOSviewer. Key findings emerged: 1) Priority skills included creativity, collaboration, communication, and critical thinking. 2) Gamification enhances motivation, engagement, and skill acquisition via game elements. 3) AI personalizes learning experiences, provides feedback, and adapts gamified content. 4) Social interactions in virtual gamified environments promote collaboration. Gamification taps into motivational aspects of games, while AI enables personalized, adaptive learning experiences. Together, they offer innovative strategies for transforming education into an engaging, personalized process for developing vital competencies. This review provides valuable insights for teachers, instructional designers, and policymakers seeking to prepare students for future challenges through leveraging gamification and AI in fostering 21st-century skills.

Learning for an uncertain future: artificial intelligence a challenge for Pakistani education system in the era of digital transformation

PurposeThe rapid advancement of AI in education brings both significant challenges and opportunities. In Pakistan, where the educational system is facing numerous issues, AI integration has raised significant concerns. Therefore, this study aims to explore the challenges AI poses to the Pakistani education system in the era of digital transformation.Design/methodology/approachA focus group was conducted with 13 participants, including educators and heads of departments from universities located in Rawalpindi and Islamabad. Thematic analysis was used to generate themes from the data.FindingsThe study findings indicated that AI integration in education can provide personalized and adaptive learning and teaching experiences by bridging the educational divide through easy access to quality education. Participants also highlighted the anxieties related to the digital divide as a great challenge for Pakistan. The integration of AI and automation in education is also raising concerns about job displacement for educators.Originality/valueIt highlighted that the integration of AI into the educational system can also bring both challenges and opportunities. To tackle these issues, potential strategies such as professional development and training programs to develop AI literacy among educators need to be introduced.

The Influence of Artificial Intelligence Tools on Student Performance in e-Learning Environments: Case Study

This study investigated the impact of AI-powered personalized learning tools on the academic performance and perceptions of pre-service student teachers enrolled in the Educational Technology course, a compulsory component of the Professional Postgraduate Diploma in Teaching program at Ajman University. A quasi-experimental design was employed with 55 students in the experimental group and 55 in the control group. The experimental group utilized AI-powered tools within the Moodle platform, while the control group received traditional instruction. Pre- and post-tests, along with a rubric-based assessment and a questionnaire, were administered to assess performance, knowledge retention, critical thinking, motivation, and engagement. Statistical analysis revealed significant differences between the groups, favoring the experimental group in terms of academic performance and knowledge retention. Additionally, students in the experimental group demonstrated higher levels of critical thinking, motivation, and engagement. These findings underscore the transformative potential of AI-powered personalized learning tools in teacher education. By integrating AI into educational practices, institutions can revolutionize e-learning by providing personalized instruction, intelligent tutoring, automated grading, and adaptive learning experiences. This can enhance student engagement, improve learning outcomes, and reduce the workload of educators. Ultimately, AI empowers institutions to create more effective and inclusive learning environments that cater to the diverse needs of students and prepare them for the future.

Unveiling the Dynamic Mechanisms of Generative AI in English Language Learning: A Hybrid Study Based on fsQCA and System Dynamics.

The burgeoning development of generative artificial intelligence (GenAI) has unleashed transformative potential in reshaping English language education. However, the complex interplay of learner, technology, pedagogy, and contextual factors that shape the effectiveness of GenAI-assisted language learning remains underexplored. This study employed a novel mixed-methods approach, integrating qualitative comparative analysis (QCA) and system dynamics (SD) modeling, to unravel the multi-dimensional, dynamic mechanisms underlying the impact of GenAI on English learning outcomes in higher education. Leveraging a sample of 33 English classes at the Harbin Institute of Technology, the QCA results revealed four distinct configurational paths to high and low learning effectiveness, highlighting the necessary and sufficient conditions for optimal GenAI integration. The SD simulation further captured the emergent, nonlinear feedback processes among learner attributes, human-computer interaction, pedagogical practices, and ethical considerations, shedding light on the temporal evolution of the GenAI-empowered language-learning ecosystem. The findings contribute to the theoretical advancement of intelligent language education by constructing an integrative framework encompassing learner, technology, pedagogy, and context dimensions. Practical implications are generated to guide the responsible design, implementation, and optimization of GenAI in English language education, paving the way for learner-centric, adaptive learning experiences in the intelligence era.

Analyzing the Impact of Learning Technology on the Quality of Education in Schools: Potential and Risks

This research examines the impact of learning technologies on the quality of education in schools, focusing on the potential and associated risks. In the digital era, the integration of technology in the teaching and learning process is becoming increasingly important. This research method uses a qualitative approach with literature study techniques to analyze and understand the impact of learning technology on the quality of education. Learning technology contributes significantly to improving the quality of education in schools, both in terms of accessibility and quality of learning processes. Technology allows students to access a wide range of information sources and learning materials and supports more flexible and interactive learning. With educational apps, learning videos and online platforms, students can study independently outside of school hours and adapt learning to their own style and pace. This helps to create a more personalized and adaptive learning experience, which results in increased student motivation and understanding of the material. However, the application of technology in education also brings a number of risks that need to be taken seriously. One of the main risks is that students' dependence on technological devices can reduce their ability to think critically and solve problems independently. This implies that schools and governments need to develop policies that support the effective application of technology, including teacher training in integrating technology with the curriculum, provision of adequate infrastructure, and efforts to ensure equal access for all students.

Unlocking the power of immersive learning: The FAIRI instructional design proposition for adaptive immersive virtual reality

Immersive Virtual Reality (IVR) is a promising tool for providing immersive and adaptive learning experiences by simulating realistic work environments and gathering data on learner's interactions to offer personalized instructional content. However, IVR-supported instruction presents unique challenges due to its heightened immersion, including managing the learner's cognitive load and self-regulation. Incorporating adaptivity into IVR can mitigate these challenges by regulating the complexity of the virtual environment, reducing cognitive strain, and maintaining learner focus through real-time feedback for both learners and instructors. However, recent reviews highlight the underutilization of adaptivity within IVR research, making it difficult to inform the design of adaptive IVR instruction.This paper proposes FAIRI, an instructional design for adaptive IVR in domain-specific training. FAIRI synthesizes recent IVR research relevant to the design of adaptivity for IVR through a purposive literature review, guided by the instructional design elements of the Four-Component Instructional Design-model (4C/ID) and Intelligent Tutoring Systems (ITS). The instructional design elements of the 4C/ID-model and ITS are evaluated for their potential viability and further refined for adaptive IVR-supported instruction based on recent IVR studies. Two key design principles are identified for adaptive IVR: limiting IVR to tasks that benefit from its heightened realism and leveraging its adaptive features to manage the intensity of the experience. Additionally, the application of FAIRI's design principles and elements are demonstrated through a forklift operator training case in IVR. FAIRI aims to catalyse further research into adaptivity for IVR by proposing and aligning promising instructional design elements for adaptive IVR instruction.

The pedagogical insights of mathematics teachers integrating artificial intelligence in rural upper primary schools of Namibia

This paper presents a qualitative intervention study that explores the pedagogical experiences of mathematics teachers integrating Artificial Intelligence (AI) technologies into teaching mathematics in rural upper primary schools in Namibia. The Technological Pedagogical Content Knowledge (TPACK) framework, which intersects teachers’ understanding of technology integration with pedagogical techniques and subject matter knowledge, was adopted for the study. The research involved 13 mathematics teachers selected through purposive sampling. Data collection included two sharing circle discussions, lesson observations, and semi-structured interviews. A thematic analysis approach was employed to interpret the collected data. The findings reveal a diverse range of AI tools used by the selected teachers, such as Geogebra, Khan Academy, Virtual Tutors, and various problem-solving mobile applications, including Photomath, Mathway, and Microsoft Math Solver. These AI resources were noted for enhancing the visualisation of mathematical concepts, providing adaptive learning experiences, and promoting independent, paced learning that supports learners' learning styles. Teachers reported a marked improvement in learners’ comprehension and problem-solving abilities attributable to AI integration. Despite the benefits of AI in education, challenges remain, particularly in rural areas. Key issues include inadequate infrastructure, limited access to devices, and the need for ongoing teacher training in technological pedagogical content knowledge. Additionally, the lack of culturally relevant AI technologies hinders effective AI-supported learning in diverse contexts. Greater investment in localised AI educational tools is needed to achieve equitable and effective learning outcomes.

AI Tutors vs. Human Instructors: Perceptions of Higher Education Students in Hungary and Spain

Integrating AI-powered tutoring systems in higher education represents a significant advancement in educational technology, offering personalized and adaptive learning experiences. This study investigates the perceptions and expectations of higher education students in Hungary and Spain regarding AI tutors. Despite extensive research on the technological efficacy of AI systems, there is limited understanding of student attitudes in these specific cultural contexts. This research aims to fill this gap by exploring student expectations, satisfaction levels, and perceived benefits of AI tutors compared to human instructors. To achieve this, a validated questionnaire was administered to 184 higher education students from Hungary and Spain, capturing data on various dimensions of their expectations. The study's findings indicate that students appreciate the adaptability and continuous guidance provided by AI tutors, with Hungarian students showing higher overall expectations compared to their Spanish counterparts. These insights suggest that AI tutoring systems can enhance the learning experience by addressing individual student needs more effectively. The implications of this study are significant for higher education institutions seeking to integrate AI technologies.

Language learning technologies: A review of trends in the USA and globally

This review provides a succinct overview of the comprehensive review on language learning technologies, exploring key trends in both the United States and global contexts. The review delves into the transformative impact of technology on language education, examining emerging trends that shape the landscape of language learning methodologies. In recent years, language learning technologies have witnessed a remarkable evolution, revolutionizing traditional approaches to language education. This review critically analyzes trends in language learning technologies, focusing on their applications, effectiveness, and implications for language learners, with a specific emphasis on both the United States and global perspectives. The exploration of language learning technologies in the United States reveals a dynamic landscape characterized by innovative tools, platforms, and methodologies. From interactive language apps to virtual reality language immersion experiences, the USA has been at the forefront of adopting cutting-edge technologies to enhance language acquisition. The review assesses the success and challenges of these technologies in diverse educational settings, shedding light on their integration into formal education systems and informal learning environments. On a global scale, the review provides insights into how language learning technologies are shaping language education practices across different countries and regions. It examines the adoption of technology in diverse cultural and linguistic contexts, exploring the effectiveness of digital language learning resources in overcoming linguistic barriers and promoting multilingualism. Key trends identified in the review include the rise of artificial intelligence-driven language tutors, the gamification of language learning, and the increasing emphasis on personalized, adaptive learning experiences. Additionally, the review explores the impact of technology on fostering cultural competence and global communication skills, essential components of language proficiency in the interconnected world. The findings of this review contribute to a deeper understanding of the current state of language learning technologies, offering valuable insights for educators, policymakers, and researchers. By examining trends in the USA and globally, the review provides a comprehensive perspective on the role of technology in shaping the future of language education, paving the way for informed decisions and advancements in language learning methodologies.

Research on Cooperative Learning in College English Listening Course Empowered by Digital Intelligence

With the rapid development of information technology and the continuous integration of the global economy, the digital era has arrived, which has had a profound impact on educational models. The introduction of the digitally empowered cooperative learning model in college English listening course not only enriches teaching methods but also enhances students' independent learning abilities and teamwork skills. This research paper delves into the integration of digital intelligence in the enhancement of cooperative learning within college English listening course. The study aims to explore the impact of digital tools and technologies on the efficiency and effectiveness of English listening instruction, focusing on the collaborative learning process among students. The research underscores the trans-formative potential of digital intelligence in empowering cooperative learning in college English listening course. By leveraging the strengths of technology, educators can create more interactive, adaptive, and student-centered learning experiences that enhance language proficiency and prepare students for the demands of the digital age.

Digital Pedagogy Philosophy: Building Critical Awareness of The Role of Technology in Education

Technology integration in education raises the need for a philosophical foundation that guides the use of technology in learning contexts. The philosophy of digital pedagogy is an approach that provides an ethical basis and values that guide the application of technology in the educational process. This paper aims to explore the relationship between digital pedagogical philosophy, critical consciousness, and the role of technology in shaping contextual and adaptive learning experiences. This research uses a hermeneutic approach to describe the reality of Digital Pedagogical Philosophy in building critical awareness of the role of technology in education. This method involves elements of interpretation and description in analyzing and understanding the implications and significance of technology integration in the learning context. The philosophy of digital pedagogy provides a foundation for integrating technology into learning to support the formation of critical, creative, and responsible individuals. Critical awareness of the role of technology in education creates a deeper understanding of the challenges and opportunities faced in the digital environment. This approach can increase student interaction with course material, increase understanding of concepts, and promote critical thinking.

Unlocking Potential: Key Factors Shaping Undergraduate Self-Directed Learning in AI-Enhanced Educational Environments

This study investigates the factors influencing undergraduate students’ self-directed learning (SDL) abilities in generative Artificial Intelligence (AI)-driven interactive learning environments. The advent of generative AI has revolutionized interactive learning environments, offering unprecedented opportunities for personalized and adaptive education. Generative AI supports teachers in delivering smart education, enhancing students’ acceptance of technology, and providing personalized, adaptive learning experiences. Nevertheless, the application of generative AI in higher education is underexplored. This study explores how these AI-driven platforms impact undergraduate students’ self-directed learning (SDL) abilities, focusing on the key factors of teacher support, learning strategies, and technology acceptance. Through a quantitative approach involving surveys of 306 undergraduates, we identified the key factors of motivation, technological familiarity, and the quality of AI interaction. The findings reveal the mediating roles of self-efficacy and learning motivation. Also, the findings confirmed that improvements in teacher support and learning strategies within generative AI-enhanced learning environments contribute to increasing students’ self-efficacy, technology acceptance, and learning motivation. This study contributes to uncovering the influencing factors that can inform the design of more effective educational technologies and strategies to enhance student autonomy and learning outcomes. Our theoretical model and research findings deepen the understanding of applying generative AI in higher education while offering important research contributions and managerial implications.

The Effect Of Adaptive Learning Experience (Adlx) On Mathematics Learning Outcomes Of High School Students In Grade Xi Based On Learning Motivation

This study aims to analyze the effect of the use of ADLX (Adaptive Learning Experience) on the mathematics learning outcomes of grade XI high school students by considering learning motivation. Using a quasi-experimental method with a non-equivalent control group design, this study involved several 11th grade high school students in X City who were divided into two groups: an experimental group using ADLX and a control group using conventional methods. The research instruments include mathematics learning outcome tests and learning motivation questionnaires validated by experts. The data were analyzed using the variance analysis technique (ANOVA) to test the hypothesis. The results showed significant differences in mathematics learning outcomes between the experimental and control groups, with the experimental group using ADLX showing better results. The data analysis also revealed that learning motivation interacted significantly with ADLX use, suggesting students with high learning motivation benefited more from ADLX use than students with low learning motivation. In general, students report that their learning motivation is influenced by the material's relevance to their daily lives and interactive and engaging teaching approaches. The use of ADLX, which involves hands-on experience and real-life examples, is considered effective in increasing understanding and motivation for learning math. This shows that the contextual learning approach is to improve students' understanding of mathematics. The conclusion of this study is that the use of ADLX can improve the mathematics learning outcomes of high school students in grade XI, especially for students with high learning motivation. These findings emphasize the importance of integrating adaptive technology in learning and the need for strategies to increase student learning motivation to achieve optimal learning outcomes.

Impact of Artificial Intelligence on Learning Management Systems: A Bibliometric Review

The field of artificial intelligence is drastically advancing. This study aims to provide an overview of the integration of artificial intelligence into learning management systems. This study followed a bibliometric review approach. Specifically, following the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) statement, 256 documents from the Scopus and Web of Science (WoS) databases over the period of 2004–2023 were identified and examined. Besides an analysis of the documents within the existing literature, emerging themes and topics were identified, and directions and recommendations for future research are provided. Based on the outcomes, the use of artificial intelligence within learning management systems offers adaptive and personalized learning experiences, promotes active learning, and supports self-regulated learning in face-to-face, hybrid, and online learning environments. Additionally, learning management systems enriched with artificial intelligence can improve students’ learning outcomes, engagement, and motivation. Their ability to increase accessibility and ensure equal access to education by supporting open educational resources was evident. However, the need to develop effective design approaches, evaluation methods, and methodologies to successfully integrate them within classrooms emerged as an issue to be solved. Finally, the need to further explore education stakeholders’ artificial intelligence literacy also arose.

Automated English Teaching System Through Deep Belief Network for Human-Computer Interaction Experience

This paper presented the integration of Human-Computer Interaction (HCI) with the Automated Teaching Belief Network (ATBN) to enhance automated English teaching experiences. The proposed ATBN model implemented the Deep Belief Network for the estimation of the factors related to the HCI to promote the experience of the users. The ATBN model uses the deep learning model for the classification in English Teaching. Through the capabilities of deep learning and HCI principles, the ATBN system offers personalized and adaptive learning experiences tailored to individual student needs. The proposed ATBN model estimates the features in English teaching to improve the performance of the Students through HCI model. Simulation analysis expressed that proposed ATBN model improves the pre-test and post-test score by +15 for the English Teaching. The classification values are achieved with accuracy value of 94.8% with minimal loss of 0.12. The assessment of student performance through pre-test and post-test score is improved by 15 for the beginner, intermediate and advanced level. The findings expressed that proposed ATBN model achieves the higher teaching test performance for the HCI language level through the belief network those significantly improves the user experience.

The Role of Technology in Modern Language Education

This article explores the transformative role of technology in modern language education, highlighting the significant advancements over the past thirty years. It begins with an overview of traditional language teaching methods and their limitations, followed by a discussion on the integration of the Internet, which has revolutionized access to language learning resources and facilitated virtual classrooms. The article delves into the impact of Artificial Intelligence (AI), particularly its recent widespread adoption since 2022, in creating personalized and adaptive learning experiences. It also examines interactive and immersive technologies such as Virtual Reality (VR) and Augmented Reality (AR), which provide engaging, real-world practice scenarios. Additionally, the benefits and challenges of technology in language education are analyzed, supported by case studies and testimonials. The article concludes by exploring emerging trends and the need for a balanced approach between traditional methods and technological advancements to create effective and inclusive language learning environments.