Enhancing Novice Programming Education through AI-Driven Mentorship and Project-Based Learning

This study examined AI-powered problem-based learning (PBL) in social studies, focusing on knowledge acquisition, critical thinking, and adoption factors. Using qualitative methods, interviews were conducted with teachers and students engaged in AI-mediated PBL activities. Findings revealed that AI-powered PBL enhanced students’ conceptual understanding in social studies by fostering interactive, context-rich learning experiences, while students exhibited stronger critical thinking and analytical abilities when working with real-world problems and historical case studies guided by AI tools. Participants emphasized that AI-enhanced PBL increased motivation and engagement through personalized feedback and adaptive learning paths. Barriers to broader implementation included limited technological access, inadequate teacher training, and concerns regarding data privacy, and teachers expressed the need for professional development to effectively integrate AI into their teaching practices. Institutional backing and clear policy guidelines were identified as essential for sustaining these innovations. The study underscored the importance of culturally and pedagogically aligning AI tools with social studies curricula to ensure they promote critical inquiry and cultural awareness. Recommendations include targeted teacher training, equitable access to technology, and the creation of culturally sensitive AI resources, aiming to maximize the transformative potential of AI-powered PBL while addressing adoption and implementation challenges. Overall, the research contributes to growing discussions on AI in education and highlights its promise for enriching social studies instruction by supporting critical thinking, engagement, and cultural awareness, ultimately cultivating globally conscious citizens prepared for complex, interconnected societies.

Digital skills, particularly programming, have become a vital prerequisite for succeeding in today’s work life. Developing those skills is, however, a challenging task, as it requires perseverance, effort, and practice. To teach coding, individualized tutoring adapted to the novice programmers’ state of knowledge has evolved as the most promising learning strategy. However, offering sufficient learning support while practicing coding tasks is a challenge due to resource constraints. Following a three-cycle design science research approach, we developed a chatbot-based digital tutor that can support novice programmers using individualized, automated conversations based on adaptive learning paths and in-depth code analyses. In this article, we present the final version of the digital tutor software and report the findings of introducing it in a field setting over two entire lecture periods. We show that digital tutors can effectively provide individualized guidance in moments of need and offer high learning satisfaction in a long-term learning setting. This article expands the state of research by presenting insights into how students interact with a digital tutor over an entire lecture period. This also provides insights on how to design digital tutors for developing skills.

So far, the learning process has only focused on improving learning outcomes but has not provided guidance on students' creative talents in being creative during lectures, so that students cannot develop their creativity to the fullest. This study aims to determine the results of implementing innovative learning with the Project Based Learning (PjBL) model in growing and increasing student creativity in Anti-Corruption Education courses. The research method used is descriptive method with a qualitative approach in which the data is obtained from observations and interviews with a descriptive analytical or critical analytical style, namely examining the primary ideas regarding the scope of the problem that are believed by relevant secondary ideas. The results of this study concluded that the implementation of innovative learning with the PjBL model can grow and increase student creativity, so that it is effectively used in the learning process of Anti-Corruption Education courses. In addition, students can take an active role in preventing corrupt behavior on campus and society.

This review paper explores the transformative potential of AI-powered eLearning platforms specifically tailored for front-end development and aspiring entrepreneurs. It begins by highlighting the significant advancements in AI technologies that facilitate personalized learning experiences and enhance educational outcomes. The importance of front-end development skills in today's digital landscape, particularly for entrepreneurial success, is underscored. The paper examines the design features of AI-powered eLearning platforms, emphasizing the need for adaptive learning paths, real-time feedback, and interactive content delivery. Furthermore, it discusses the customization of courses to meet the unique needs of aspiring entrepreneurs, integrating technical and business skills, and leveraging AI for mentorship and networking opportunities. The paper also addresses the technical and ethical challenges associated with AI in education, including data integration, scalability, bias, and privacy concerns. Future trends such as VR/AR, advanced analytics, and blockchain integration are explored, providing a glimpse into the evolving landscape of AI in eLearning. The review concludes with implications for educators and developers, highlighting the need for continuous innovation and the balance between AI-driven automation and human interaction. This comprehensive analysis underscores the immense potential of AI-powered eLearning in revolutionizing education for front-end development and entrepreneurship.. Keywords: AI-powered Elearning, Front-End Development, Personalized Learning, Entrepreneurship Education, Adaptive Learning Paths

All aspects of life are connected to the internet in the industrial revolution 4.0 era. All information can be accessed quickly and easily without regard for space, distance, or time. Students can learn with anything, anywhere, and at any time. Lecturers are not the only source of information. Today's online learning environment makes it challenging to incorporate project-based learning in order to produce usable products. Project-based learning is a type of learning that applies to both online and offline learning environments. This research aims to create a viable and effective hybrid project-based learning environment that will improve learning outcomes. The ADDIE model is used to develop products. An expert validated the feasibility model, and the effectiveness model was validated using independent t-test samples and the SPSS program. Based on the results of expert assessment, the following feasibility results are known: (1) expert assessment related to learning model of 96.87%; (2) expert assessment related to learning materials of 95.34%; and (3) expert assessment related to learning design of 97.39%. Experts gave an overall rating of 95.78%. As a result, a value of 96.53% was obtained from all expert trials. The findings indicate that hybrid project-based learning is both feasible and effective in terms of enhancing learning outcomes. Hybrid Project-Based Learning (HPjBL) provides numerous benefits to students and educators. Academic research is increasingly supporting the use of HPjBL to engage students, reduce absenteeism, enhance collaborative learning skills, and boost academic performance.

Morphology learning in higher education is important to improve students' understanding in determining words and correct word formation. This study aims to describe the application of Project-based learning in morphology learning, material on morphological and morphophonemic processes in texts. The method used is descriptive qualitative which combines classroom observation methods and document analysis of learning outcomes. The research participants were 15 students from the Indonesian Language Education Study Program, Universitas PGRI Adi Buana Surabaya, class of 2024, selected through a purposive sampling method. The project type was to identify morphological and morphophonemic processes in texts. The assessment used was a scored process assessment with criteria. The results of the study indicate that student learning outcomes using Project-Based Learning (PjBL) are successful, this can be seen in the student's score. The use of Project-Based Learning is effective in this learning because students will contribute to each other in analyzing texts that undergo morphological and morphophonemic processes. Based on these findings, it can be suggested that the use of Project-Based Learning is effective but does not rule out the possibility of using more diverse, interactive, and fun methods. The results of this study provide an important contribution in improving learning outcomes using Project-Based Learning (PjBL).

This study aims to analyze the effectiveness of the Project-Based Learning (PBL) model in internalizing the value of gotong royong (mutual cooperation) in English learning among class X OTKP students at SMKS Kristen Tomosa 2. It also explores the experiences, interactions, and perceptions of both students and teachers during the learning process. Using a qualitative approach with descriptive analysis, the study employed instruments such as observation sheets, interviews, and documentation to gather data. The findings reveal that the PBL model significantly enhanced collaboration among students and deepened their understanding of English learning materials. Through project activities, students learned to work together, share responsibilities, and engage in positive interactions, which facilitated the internalization of the gotong royong value. The project activities encouraged teamwork and mutual support, contributing to the development of students' social character. In conclusion, the PBL model proved effective in promoting both academic achievement and the internalization of cultural values such as gotong royong. The study highlights the potential of PBL as a tool for fostering cooperation, improving learning outcomes, and shaping students’ social character in the classroom. Future research could explore its impact on other aspects of character development and academic skills.

This systematic review analyzes research on the application of Large Language Models (LLMs) to enhance the quality of learner support in the context of university autonomy. The study aims to evaluate the current applications of LLMs in providing personalized and adaptive learning paths, identify ethical challenges, and analyze the role of prompt engineering and human-in-the-loop supervision. The research method involves a systematic analysis of scientific works published up to mid-2024. The findings indicate that LLMs significantly enhance personalized feedback and adaptive tutoring, thereby promoting self-regulated learning and student engagement. However, challenges related to feedback accuracy and ethical issues persist, requiring robust governance frameworks. The conclusion emphasizes that effective LLM integration requires combining technological power with pedagogical expertise and human oversight to optimize the educational experience and successfully support autonomous learners.

Learning systems can potentially transform education and training by allowing educators to encourage behavioural changes and internalization of concepts in learners. This paper introduces such an AI-powered model for a personalized learning system, building on our success of hand-curated learning paths to support individualized education. We utilize a network science approach as a construct to create an environment that is supportive of an individualized learning process, presenting an AI-powered framework. This framework is informed by student and faculty interactions with two custom created learning systems, experiences that shaped goals and expectations of the proposed AI-powered method since 2018. This paper contributes to advancing the conversation around AI-powered learning systems and personalizing educational experiences. Our AI-powered model engages learners in their educational journey through individualized and adaptive learning paths, while meeting each learners’ specific learning outcomes. We conclude with open research problems that surfaced from this vision.

The advancement of Natural Language Processing (NLP) technology has significantly impacted the methods of foreign language education, including Japanese. This study aims to analyze the implementation of NLP-based technology in enhancing the efficiency and effectiveness of Japanese language learning for non-native learners. Using a literature review and content analysis approach, this article examines various educational applications that utilize NLP features such as automatic feedback, pronunciation training, and real-time syntactic and semantic analysis. The findings suggest that NLP can enrich the learning experience by offering personalized support and adaptive learning paths. However, challenges such as cultural context limitations and dependency on native-speaker-oriented data remain. This research provides insights and recommendations for curriculum developers and educational technology designers in optimizing NLP-based tools for Japanese language instruction.

This study explores the use of artificial intelligence technology to build an adaptive learning system to promote the innovation of college English teaching. By integrating natural language processing, deep learning, and recommendation algorithms, a multidimensional adaptive learning framework for college English is constructed that provides personalized support in various skills. By designing comparative teaching experiments and collecting learning behavior data, the effectiveness of the model is systematically evaluated. Experiments show that the system can significantly improve the utilization rate of teaching resources, learning efficiency, and interactive experience. Students who use the system have made remarkable progress in vocabulary mastery, writing ability, and oral expression, and their satisfaction is high. Students with different learning styles and levels can get adaptive learning paths and real-time feedback. The adaptive learning system driven by artificial intelligence shows good applicability and popularization potential in college English teaching.

This study developed a computer-assisted language learning system based on English syntactic structure using long short-term memory (LSTM) network. Through dynamic learning models and adaptive learning paths, personalized and efficient learning experiences were provided, aiming to address the shortcomings of traditional systems and improve learners’ mastery of syntactic structure. The system processed language sequence data by designing an LSTM model, combined with a dynamic adjustment mechanism and real-time feedback system, to achieve dynamic adjustment of personalized learning content and difficulty. Based on data-driven teaching strategies, teaching methods were continuously optimized and learning outcomes were improved by collecting and analyzing learning data. The experimental results of this study indicated that the system had significant effects in improving learners’ mastery of syntactic structures, overcoming the limitations of traditional computer-assisted language learning systems. In the experiment, 120 English learners were selected and divided into an experimental group and a control group, using the system developed in this study and the traditional system, respectively. After the experiment, learners in the experimental group significantly improved their mastery of syntactic structures, with their scores jumping from 70 to 94, while those in the control group increased from 68 to 85. The percentage of correct learning increased from 75% to 94% in the experimental group and from 73% to 86% in the control group. The study shows that the computer-assisted language learning system is effective in improving the mastery of syntactic structures.

This study aims to determine the process and results of the application of the Project Based Learning (PjBL) learning model in improving learning outcomes in the Prose course in the English Language and Literature Department of UIN Alauddin Makassar. This study uses a Research and Development (R&D) approach with stages simplified into three stages: preliminary study, model development, and model evaluation. Data analysis was carried out at each stage. The results of the study indicate that the application of the PjBL model in learning to write short story texts has a positive impact on the learning activities of students and lecturers. There was an increase in students' writing skills in five assessment aspects: paragraph content, paragraph organization, vocabulary, language use, and mechanics. In phase I, the average student score reached 85 with a sufficient category and 88% completeness. In phase II, there was an increase in the quality of writing skills with an average score of 90 and a good category and the percentage of completeness remained at 88%. These findings indicate that the PjBL model is effective in improving students' short story writing skills, especially through a project-based approach that allows students to be actively and creatively involved in the literature learning process.

Project-based learning in programming classes – the effect of open project scope on student motivation and learning outcome

Enhancing student engagement and conceptual understanding in chemistry requires innovative and interactive learning materials. This study aims to develop and evaluate a flipbook module based on Project-Based Learning (PjBL) for chemical bonding content. The research adopted the 4D development model—Define, Design, Develop, and Disseminate—focusing on content validity, student responses, and effectiveness in improving learning outcomes. Expert evaluations confirmed the module’s high validity, and student feedback indicated strong approval in terms of content, presentation, and language. The module also demonstrated moderate effectiveness in enhancing students' conceptual understanding, as shown by learning gains. These findings suggest that the PjBL-based flipbook module is feasible, pedagogically appropriate, and positively received, making it a valuable resource for supporting active and student-centered chemistry learning in high school settings.