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29THE ROLE OF ARTIFICIAL INTELLIGENCE IN IMPROVING THE QUALITY OF STUDENT LEARNING PROCESS
Sayfullayeva N.J.
Gulistan state university, student https://doi.org/10.5281/zenodo.12596677
Abstract. Artificial intelligence (AI) technology has become integral to student learning in the digital era. This article investigates the role of AI in improving the quality of the student learning process, focusing on personalization of learning, adaptive evaluation, and learning data analysis. This research uses a qualitative research approach. The research design adopted is a case study, which allows us to understand the implementation of artificial intelligence in student learning deeply. The research population and sample were 100 students at the Indonesian Technocrat University in Lampung province, Indonesia. The research results show that implementing AI in education has great potential to increase learning effectiveness, inclusiveness and efficiency. This confirms that adopting AI technology can significantly strengthen students' academic performance and prepare them to face future challenges.
Keywords: artificial intelligence, student learning, personalization of learning, adaptive evaluation, data analysis.
INTRODUCTION
The concept of student learning in Indonesia includes a variety of approaches that adapt to this country's cultural, social and economic context. Traditionally, learning in Indonesia has often been more lecturer-centred, with a more didactic teaching approach, but with the times and the influence of globalization, there has been a paradigm shift towards learning that is more student-oriented (Khan et al., 2021; Vincent-Lancrin & Van der Vlies, 2020). A more interactive, collaborative and student-centred learning approach is currently increasingly gaining attention in various higher education institutions in Indonesia. Students are expected to be active in the learning process, involved in discussions, collaborative projects, and problem-solving as part of efforts to develop critical, creative, and analytical thinking skills needed in an increasingly complex world of work. The use of technology in learning is also increasingly widespread, although there are still challenges related to infrastructure and accessibility (Bates et al., 2020; Gocen & Aydemir, 2020). The concept of student learning in Indonesia continues to develop along with the demands of the times and global paradigm changes in education, with continuous efforts to improve the quality of learning to prepare students to become competent and highly competitive members of society.
Improving the quality of the learning process has a central role in advancing the education system and forming an academically and professionally competent generation. The quality of the learning process includes various elements, ranging from the use of innovative teaching methods to the availability of adequate supporting resources (Bhatia et al., 2020; Gonzalez-Calatayud et al., 2021). By improving the quality of the learning process, educational institutions can create an environment that stimulates creativity, strengthens understanding of concepts, and encourages lifelong learning.
The demand for relevant expertise and skills is growing along with the times and global dynamics, so improving the quality of the learning process becomes increasingly important. A
quality learning process prepares students to face challenges in the academic world and equips them with the practical skills needed in the rapidly changing world of work. Improving the quality of the learning process also has positive implications for society as a whole by producing individuals who are more educated, competitive, and able to contribute positively to social, economic and cultural development. Investment and efforts to continuously improve the quality of the learning process are strategic steps in building a brighter and more sustainable future for the country and society (Hwang et al., 2020; Tapalova & Zhiyenbayeva, 2022).
Improving the quality of the learning process also significantly reduces disparities in educational access and outcomes, and by ensuring that all students have equal access to quality education and effective learning processes, we can reduce disparities in academic achievement between social, economic, and social groups, and geographical. This not only creates a fairer opportunity for all individuals to achieve academic success but also has the potential to reduce inequalities in access to economic and social opportunities (Ahmad et al., 2021; Kuleto et al., 2021).
Improving the quality of the learning process plays a key role in preparing future generations to face complex challenges, such as technological change, environmental issues, and other global challenges. Providing relevant, inclusive education oriented towards problem-solving can equip students with the adaptation and critical thinking skills needed to deal with unexpected changes and lead innovation in various fields (Fitria, 2021; Igbokwe, 2023). Improving the quality of the learning process is not only about improving academic results but also about preparing individuals to become competitive future leaders who contribute positively in responding to global challenges.
Technological developments, especially artificial intelligence (AI), have significantly impacted the world of education, especially in increasing the effectiveness of the learning process. AI has the potential to transform traditional learning paradigms into more adaptive, personalized, and efficient experiences. With its ability to quickly analyze data and generate relevant patterns and recommendations, AI can help teachers and educational institutions in various aspects of learning, from personalizing the curriculum to providing timely feedback to students. AI technology also enables independent and data-driven learning, where students can learn independently using digital learning platforms tailored to their needs and learning styles (Hwang et al., 2020; Tapalova & Zhiyenbayeva, 2022).
(c)
Figure 1. The Hierarchy of Artificial Intelligence in Educational
AI can be used to improve learning evaluation through assessment automation systems or predictive analysis to identify areas that require additional attention. The integration of AI technology in learning has great potential to create a more dynamic, inclusive and adaptive learning environment, which allows every student to achieve their learning potential optimally, as the results of previous research explain the data as follows:
Implementation. (a) The Dimension of System Development, (b) The Dimension of Extraction, and (c) The Dimension of Application Source: (Teng et al., 2023)
While AI technology promises major advances in learning, several issues need to be addressed to optimize its effectiveness. One of them is challenges related to infrastructure and technological accessibility, especially in areas that are less developed or have limited resources. Data privacy and security issues are also a concern, with potential risks of use of students' personal data and privacy breaches. There is also a need for adequate training for educators to use AI technology effectively in the learning process and a better understanding of how this technology can be well integrated into existing curricula and teaching methodologies. While AI technology offers much potential to improve learning effectiveness, research is needed to address the issues associated with its implementation and use in diverse educational contexts. This research aims to investigate how artificial intelligence (AI) technology can be applied in the context of higher education in Indonesia to increase the effectiveness and quality of the student learning process. 1. Basic concepts about Artificial Intelligence (AI) and Machine Learning Artificial Intelligence (AI) and Machine Learning are two basic concepts that are the backbone of the development of modern technology. Artificial Intelligence refers to the ability of a machine or computer to imitate or perform behavior that, if performed by a human, would require intelligence (Bhatia et al., 2020; Gocen & Aydemir, 2020). This concept involves the development of algorithms that enable computers to complete tasks that typically require human intelligence, such as natural language understanding, decision-making, and pattern recognition. Machine Learning is a branch of AI that focuses on developing algorithms and models that allow computers to learn from data without being explicitly programmed. Computers can identify hidden patterns in data, make predictions, and make decisions automatically based on the experience gained from the data (Ouyang et al., 2022).
Machine learning techniques include supervised, unsupervised, and reinforcement learning. The combination of the basic concepts of AI and machine learning has opened the door to various revolutionary applications, from autonomous cars to virtual assistants, that fundamentally change how we interact with technology and the world around us. As knowledge and technology continue to develop in this field, the potential to improve human life and solve complex challenges in various fields is ever greater.
Artificial Intelligence (AI) also includes natural language processing, facial recognition, computer vision, and knowledge modelling concepts. Natural language processing allows computers to understand, interpret, and respond to human language in a human-like way. This enables more efficient information retrieval, language translation, and intuitive human-machine interactions. Facial recognition and computer vision allow computers to identify and analyze objects, patterns or features in images or videos; this has a wide range of applications, from security and facial detection to object recognition in autonomous cars.
Knowledge modelling allows computers to represent knowledge and concepts in forms that machines can understand and manipulate, such as ontologies and knowledge bases. By integrating
the basic concepts of AI and machine learning with other technologies, such as big data and cloud computing, we can develop more sophisticated and complex solutions to solve problems in various fields, including health, finance, energy, and the environment.
2. Studies on the Implementation of AI in Global Education and in Developing Countries
Previous research studies on the implementation of artificial intelligence (AI) in global
education and developing countries have provided valuable insights into various aspects of the use of this technology in educational contexts. One study explores the effectiveness of an AI-based adaptive learning system in improving student academic achievement by adjusting material and level of difficulty based on individual abilities; another study is explained in the following paragraph:
The study by Yang et al. (2021)—"Human-centered artificial intelligence in education: Seeing the invisible through the visible"—investigates the impact of using an adaptive learning system supported by artificial intelligence on improving students' academic achievement. Study findings show significant improvements in academic achievement and student engagement and a reduction in the gap between high- and low-performing students.
The study by (Sun et al., 2021) - " Design of Online Intelligent English Teaching Platform Based on Artificial Intelligence Techniques", this research highlights the effectiveness of using AI chatbots as a learning support tool that can provide personalized and instant learning assistance
to students. The study results showed increased material understanding and student engagement using chatbots.
A study by (Huang et al., 2021) - " A Review on Artificial Intelligence in Education" focuses on applying data analysis and artificial intelligence in providing timely feedback to students and teachers. The study findings highlight the benefits of adapting curriculum and teaching approaches based on individual needs and classroom dynamics.
A study by (L. Chen et al., 2020) - " Artificial Intelligence in Education: A Review", this research explores the impact of using artificial intelligence based educational games in motivating students, increasing engagement, and strengthening understanding of critical concepts. The study results show that AI-based educational games can effectively facilitate interactive and fun learning.
The study (Arun, 2021) - " Potential of Artificial Intelligence for Transformation of the Education System in India." this research highlights the unique challenges faced in implementing artificial intelligence technology in educational contexts in developing countries. This study provides insight into the critical role of technology infrastructure and training for educators in addressing these challenges.
These findings consistently confirm that with the right strategy and strong commitment from stakeholders, implementing AI in education has great potential to improve access, quality, and relevance of education worldwide.
3. Review of Research Related to the Role of AI in Improving the Quality of Student Learning Processes in Various Contexts
A review of research related to the role of artificial intelligence (AI) in improving the quality of student learning processes has revealed various interesting findings in various educational contexts, such as research conducted by (X. Chen et al., 2022; Dai et al., 2020; Yu & Guo, 2023). These studies have demonstrated that implementing AI technology in the learning process can significantly impact student effectiveness, engagement and learning outcomes. Several
studies in higher education contexts highlight the use of AI-based adaptive learning systems that can tailor curriculum and teaching methods to each individual, enabling more personalized and effective learning experiences.
Other research explores the application of AI chatbots as learning aids that can provide instant support to students in completing assignments or understanding course material (Alam, 2022; Y. Chen et al., 2023). These studies also highlight the role of data analytics and artificial intelligence in providing timely feedback to students, enabling the adoption of more responsive and effective learning strategies. In various educational contexts, such as in developing countries, research has also highlighted unique challenges and opportunities in adopting AI technologies, including issues of technology accessibility and the need for educators to be trained. Through a review of these studies, we can gain a better understanding of the potential and obstacles of AI implementation in improving the quality of student learning processes, as well as find opportunities for further development in this area (X. Chen et al., 2020; Seo et al., 2021).
This research uses a qualitative research approach. The research design adopted is a case study, which allows us to gain a deep understanding of the implementation of artificial intelligence in the student learning process. The research population and sample were 100 students at the Indonesian Technocrat University in Lampung province, Indonesia. The approach used is qualitative research with a case study design. The study population consisted of all students at the Indonesian Technocrat University. At the same time, the sample was chosen purposively by considering variations in study programs and level of involvement in learning using artificial intelligence. The main research instrument is in-depth interviews with students involved in the learning process using AI and lecturers and administrators involved in implementing AI technology at the university. The participatory observation was also carried out to gain a direct understanding of how AI technology is applied in the daily learning process within the Indonesian Technocrat University. The data collection procedure involves the sample identification stage, preparing the interview approach, observation schedule, and primary data collection. Data from interviews and observations will be analyzed using a thematic approach to identify patterns, themes and trends related to the role of AI in improving the quality of student learning processes at the Indonesian Technocrat University.
RESULTS AND DISCUSSION 1. The Role of AI in Improving the Quality of Student Learning Process
Artificial intelligence (AI) provides new possibilities for personalizing learning in unprecedented ways. With advanced data analysis and fast processing, AI can gather information about learning preferences, student progress, and individual learning styles accurately and timely. This information allows AI systems to design learning experiences tailored to each student's unique needs. AI can recommend learning materials that suit students' interests and level of understanding, present material in the most effective format based on individual learning styles, and adjust the difficulty level of assignments or exercises according to each student's abilities.
Source: data proceed
AI can provide immediate, personalized feedback to students about their performance, help them understand their strengths and weaknesses, and provide recommendations to improve their understanding. Using AI technology to personalize learning, educators can create an adaptive and inclusive learning environment where students receive the right attention according to their needs
and potential. In this way, AI opens the door to a more effective, efficient and individual focused learning approach, helping each student reach their optimal learning potential.
The application of AI in personalized learning can also utilize predictive analysis technology to identify complex learning behavior patterns. By utilizing historical data and student learning responses to learning materials, AI can predict potential learning difficulties in the future and take preventive action. The results of using AI in learning are presented in the following table:
Table 1. Learning activity data using AI applications
No AI Platforms/Applications Frequency of Use (Per week) Types of Learning Activities supported
1 Google Classroom Five times Assignment and Collection of Assignments
2 Duolingo Three times Foreign Language Learning
3 Khan Academy Four times Independent learning and tutorials
4 Quizizz Two times Evaluations and quizzes
5 Coursera One time Online course-based learning
Source: data proceed
Artificial intelligence (AI) technology has been used in the learning process at the Indonesian Technocrat University. AI platforms or applications such as Google Classroom, Duolingo, Khan Academy, Quizizz, and Coursera have been implemented with varying frequencies of use per week. Interpretation of the results of this data shows that the use of AI technology in learning at the university is extensive. The significant frequency of use shows that these AI platforms have an important role in supporting various learning activities, such as assignments, assignment collection, independent learning, tutorials, evaluations, and online course-based learning.
AI can identify students at risk of having difficulty understanding certain material and provide additional help or appropriate reading material before the problem becomes more serious. AI can dynamically adjust learning plans, provide challenges appropriate to a student's level of progress, or provide additional help by monitoring learning progress in real-time. The application of AI in personalized learning not only helps students understand the material better but can also prevent learning setbacks and improve retention of information in the long term, showing that AI is not only a powerful learning tool but also a valuable partner for educators in facilitate effective and sustainable learning for all students.
2. Analysis of student performance data before and after implementation
AI technology can increase the efficiency, accessibility and flexibility of learning, and its impact on student learning at the Indonesian Technocrat University may be very positive. Students can access learning materials more easily and follow learning according to their rhythm and preferences. AI platforms can provide timely and personalized feedback in learning, helping students understand the material better and improving their academic performance; these results can be seen in the following data:
Student Performance Data Before and After Implementation
86
70
84
82 80
78
76
74
72
Before AI Implementation
After AI Implementation
"Average Exam Score "Average Assignment Score" Average Project Score
Figure 2. Student Performance Data Before and After Implementation
Source: data proceed
Based on student performance data before and after the implementation of artificial intelligence technology, there has been a significant increase in student learning achievement. Before implementation, the average scores for exams, assignments, and projects were 75, 80, and 78, respectively. After the implementation of AI technology, there was a quite striking increase, where the average exam score rose to 82, the Average assignment value increased to 85, and the average project score also increased to 83. This shows that the adoption of AI technology in learning at the Indonesian Technocrat University has positively impacted student academic performance. This increase indicates that AI technology has helped students understand learning material better, provide more timely feedback, and increase the overall effectiveness of the learning process.
The application of artificial intelligence (AI) in learning evaluation and timely feedback has a revolutionary impact on understanding and improving the learning process. Through in-depth data analysis, AI can automatically evaluate student performance in various aspects of learning, including material comprehension, engagement, and academic progress. With advanced algorithms, AI can identify patterns in student responses and provide relevant feedback instantly. AI systems can analyze students' responses to exam questions or practice exercises, highlight areas of weakness or confusion, and provide recommendations to improve their understanding. The application of AI in learning evaluation and timely feedback not only provides deep insight into student learning progress but also enables real-time adjustments to instruction, ensuring that each student receives support appropriate to their needs and ability level; this makes AI a very valuable tool in increasing the effectiveness and relevance of learning in this digital era.
3. Challenges and Opportunities
Adopting artificial intelligence (AI) technology in the context of Indonesian education faces several challenges that need to be identified and overcome. One of the main challenges is the equal availability of infrastructure and technological accessibility throughout Indonesia. Even though AI technology offers the potential to improve the quality of learning, many regions in Indonesia still have limited internet access or adequate technological facilities; this can create a digital divide between urban and rural areas and between educational institutions with different financial capabilities.
Another challenge is the knowledge and skills needed to integrate AI technology into learning. Many educators may need to fully understand the potential of AI technology or be untrained in using AI tools to improve the learning process. Investment in teacher training and professional development is needed to ensure they can effectively utilize AI technology in their teaching. It is important to consider data privacy and security when adopting AI technology in education. AI technology often involves collecting and analysing students' data, so clear policies and strong data privacy protection are needed. Appropriate measures must be implemented to prevent data misuse and security breaches when using AI technology in educational settings. Strategic steps can be taken to overcome barriers to adopting AI technology in Indonesian education by identifying these challenges, including investment in technology infrastructure, training and professional development of teachers, and developing policies that pay attention to data privacy and security.
Using artificial intelligence (AI) in student learning brings various opportunities and significant long-term benefits. One of its main potentials is better personalization of learning. AI technology can analyze individual students' learning patterns and preferences, making it possible to provide learning materials tailored to each student's needs and level of understanding; this can increase the effectiveness of learning and help students reach their maximum potential.
The use of AI in learning can also increase the accessibility and inclusivity of education. With adaptive learning algorithms, AI technology can help students with special needs or different learning styles stay engaged and successful. This opens the door to a more inclusive education and ensures that every student has equal opportunities to learn and develop. Another long-term benefit is increased efficiency in teaching and assessment. AI systems can take over administrative tasks and handle evaluations automatically, freeing up faculty time and energy to focus on direct interactions with students and individual mentoring, enabling more efficient use of human resources and strengthening relationships between students and faculty.
The use of AI also opens up opportunities for innovation in curriculum design and learning method development, and with advanced data analysis, AI technology can provide valuable insights into learning trends, student needs, and potential improvements in the learning process, allowing educational institutions to make informed decisions, smarter in developing relevant and effective educational programs. Using AI in the student learning process promises extensive long-term opportunities and benefits. Educational institutions can create more adaptive, inclusive and effective learning environments and prepare students to face the challenges and opportunities in an increasingly connected and rapidly changing society by wisely exploiting the potential of this technology.
Based on the research analysis and discussion results, the role of artificial intelligence (AI) technology significantly impacts the quality of the student learning process. By applying AI in various aspects of learning, such as personalized learning, adaptive evaluation, and learning data analysis, educational institutions can create learning environments that are more effective, inclusive, and responsive to individual student needs. This research confirms that adopting AI technology can strengthen student academic performance, increase educational accessibility, and help educational institutions prepare students to face the demands of an increasingly connected and complex society.
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