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15МЕТОД ОЦЕНКИ ЗНАНИЙ УЧАЩИХСЯ, ОСНОВАННЫЙ НА ПОВЕДЕНИИ В
ЭЛЕКТРОННОЙ УЧЕБНОЙ СРЕДЕ
Юсупов Давронбек Фирнафасович
Урганский государственный педагогический институт
Рузимбоева Севара Нурмат кизи
Ургенчский государственный университет
Электронное обучение, или электронное обучение, становится все более популярным как метод предоставления образования учащимся. Одной из проблем электронного обучения является эффективная оценка знаний учащихся. В отличие от традиционных классов, учителя физически не находятся в одной комнате с учениками, что затрудняет оценку их поведения и вовлеченности. В этом эссе мы рассмотрим метод оценки знаний учащихся, основанный на поведении в электронной среде обучения.
Ключевые слова: электронное обучение, электронная образовательная среда, студенческие знания, поведение, оценка, вовлеченность.
THE METHOD OF EVALUATING STUDENT KNOWLEDGE BASED ON BEHAVIOR IN AN ELECTRONIC LEARNING ENVIRONMENT
Electronic learning, or e-learning environment, has become increasingly popular as a method of delivering education to students. One challenge with e-learning is how to assess student knowledge effectively. Unlike traditional classrooms, teachers are not physically present in the same room as students, which makes it difficult to evaluate their behavior and engagement. In this essay, we will explore the method of evaluating student knowledge based on behavior in an electronic learning environment.
Keywords: electronic learning, e-learning, student knowledge, behavior, evaluation, engagement.
ELEKTRON O'QUV MUHITIDAGI HATTI-HARAKATLAR ASOSIDA TALABALAR
BILIMINI BAHOLASH USULI
Elektron ta'lim yoki elektron ta'lim talabalarga ta'lim berish usuli sifatida tobora ommalashib bormoqda. Elektron ta'lim bilan bog'liq muammolardan biri talabalar bilimini qanday samarali baholashdir. An'anaviy sinflardan farqli o'laroq, o'qituvchilar talabalar bilan bir xonada jismonan mavjud emas, bu ularning xatti-harakati va faolligini baholashni qiyinlashtiradi. Ushbu maqolada biz elektron ta'lim muhitida talabalarning xatti-harakatlariga asoslangan bilimlarini baholash usulini o'rganamiz.
Kalit so'zlar: elektron ta'lim, elektron ta'lim muhiti, talaba bilimi, xatti-harakati, baholash, faollik.
Introduction: The rapid development of technology has brought about significant changes in the education sector. Electronic learning, also known as e-learning, has become increasingly popular as a method of delivering education to students. E-learning provides students with the opportunity to learn at their own pace and in their own time, using electronic devices and online resources. However, the challenge with e-learning is how to assess student knowledge effectively. Unlike traditional classrooms, teachers are not physically present in the same room as students, which makes it difficult to evaluate their behavior and engagement. In this essay, we will explore the method of evaluating student knowledge based on behavior in an electronic learning environment.
Related Work: The use of electronic learning environments has gained popularity in recent years, and numerous studies have been conducted to evaluate the effectiveness of e-learning. One study conducted by [1] found that e-learning can be just as effective as traditional classroom instruction when designed appropriately. The study highlighted the importance of engagement and interaction in e-learning, which are critical components in evaluating student knowledge based on behavior.
Another study by [2] explored the use of learning analytics to evaluate student performance in e-learning environments. The study found that learning analytics can be used to monitor and evaluate student behavior, including participation, engagement, and mastery of the subject matter. The study also highlighted the importance of providing feedback to students based on their performance, which is an essential component of evaluating student knowledge based on behavior in e-learning .[3]-[6]
Overall, these studies suggest that evaluating student knowledge based on behavior in e-learning is a critical component of effective e-learning. [7]-[12] By monitoring and evaluating student behavior, teachers can assess student engagement, participation, and mastery of the subject matter, providing valuable insights into the student's learning process. These studies also highlight the importance of providing feedback to students based on their performance, which is essential for improving student knowledge and engagement in e-learning environments.[13]
Methods of Evaluating Student Knowledge in E-Learning: Assessing participation: One method of evaluating student knowledge in e-learning is to assess their participation. Participation can be measured by analyzing the frequency and quality of a student's contributions to online discussions, group work, and individual assignments. Teachers can also use tools such as polls, surveys, and quizzes to assess student participation and engagement.
Analyzing learning outcomes: Another method of evaluating student knowledge in e-learning is to analyze their learning outcomes. Learning outcomes can be measured by assessing the students' mastery of the subject matter through assessments such as exams, quizzes, and assignments. Learning outcomes can also be measured by evaluating the student's ability to apply the knowledge learned in real-world scenarios.
Monitoring online behavior: A third method of evaluating student knowledge in e-learning is to monitor their online behavior. This involves tracking the student's online activity to determine their level of engagement and to identify any potential issues that may be affecting their performance. [9]Online behavior can be monitored using tools such as learning analytics, which provide insights into the student's activity and performance.
Advantages and Disadvantages of Evaluating Student Knowledge Based on Behavior in E-Learning:
Advantages: Evaluating student knowledge based on behavior in e-learning provides teachers with a comprehensive view of the student's performance. It allows teachers to assess the student's engagement, participation, and mastery of the subject matter.[8] This method also provides valuable insights into the student's learning process, allowing teachers to tailor their teaching methods to better meet the needs of individual students.
Disadvantages: One disadvantage of evaluating student knowledge based on behavior in e-learning is that it may not provide a complete picture of the student's performance. It may not account for external factors that may be affecting the student's performance, such as technical issues or personal problems. Additionally, this method may not be suitable for all students, as some may prefer to learn independently without constant monitoring and evaluation.
Future Work: As e-learning continues to evolve, there is a need for further research to explore new and innovative methods of evaluating student knowledge based on behavior in electronic learning environments. Some potential avenues for future work in this area include:
Integration of artificial intelligence (AI) and machine learning (ML) techniques: AI and ML can be used to develop predictive models that can identify student behavior patterns and provide personalized feedback to students based on their performance. These techniques can also be used to analyze large amounts of data collected from e-learning platforms to provide insights into student behavior and performance. For example, AI and ML can be used to identify students who are at risk of falling behind in their coursework, and provide early interventions to help these students stay on track.
Use of virtual and augmented reality technologies: Virtual and augmented reality technologies can be used to create immersive learning environments that simulate real-world scenarios. These technologies can provide a more engaging and interactive learning experience for students, allowing teachers to assess student knowledge based on behavior in a more realistic and comprehensive way. For example, virtual reality simulations can be used to assess students' critical thinking skills and problem-solving abilities, while augmented reality technologies can be used to provide students with real-time feedback on their performance.
Integration of social learning and collaboration tools: Social learning and collaboration tools, such as online discussion forums, wikis, and social media platforms, can be used to facilitate collaborative learning and assess student knowledge based on behavior. For example, online discussion forums can be used to assess students' ability to articulate their ideas and engage in meaningful discussion with their peers. Wikis can be used to assess students' ability to collaborate on group projects and produce high-quality work. Social media platforms can be used to assess students' ability to communicate effectively and engage with a broader community of learners.
Use of game-based learning: Game-based learning can be used to create a more engaging and interactive learning experience for students, while also providing teachers with valuable insights into student behavior and performance. For example, game-based learning can be used to assess students' problem-solving skills, decision-making abilities, and ability to work collaboratively with others. Games can also be used to provide students with instant feedback on their performance, allowing them to adjust their learning strategies accordingly. Development of new assessment methods: As e-learning continues to evolve, there is a need for new and innovative assessment methods that can capture the full range of student knowledge, skills, and abilities. Some potential assessment methods include the use of portfolios, performance-based assessments, and open-ended assessments. These assessment methods can provide teachers with a more comprehensive view of student knowledge based on behavior, allowing them to assess not only what students know, but also how they apply their knowledge in real-world situations. Overall, the future of evaluating student knowledge based on behavior in electronic learning environments is bright, with numerous opportunities for innovation and advancement. As e-learning continues to gain popularity and become more integrated into traditional educational settings, it is important for educators and researchers to continue exploring new and innovative ways of assessing student knowledge and promoting engagement and learning.
Conclusion: Evaluating student knowledge based on behavior in e-learning is an effective method of assessing student performance in an electronic learning environment. It allows teachers to assess the student's engagement, participation, and mastery of the subject matter, providing valuable insights into the student's learning process. However, this method may not provide a complete picture of the student's performance and may not be suitable for all students. As technology continues to develop, it is essential to explore new and innovative methods of evaluating student knowledge in e-learning to ensure that students receive a comprehensive and effective education.
REFERENCES:
1. L. Pham, Y. B. Limbu, T. K. Bui, H. T. Nguyen, and H. T. Pham, "Does e-learning service quality influence e-learning student satisfaction and loyalty? Evidence from Vietnam," International Journal of Educational Technology in Higher Education, vol. 16, no. 1, 2019, doi: 10.1186/s41239-019-0136-3.
2. A. M. Maatuk, E. K. Elberkawi, S. Aljawarneh, H. Rashaideh, and H. Alharbi, "The COVID-19 pandemic and E-learning: challenges and opportunities from the perspective of students and instructors," J Comput High Educ, vol. 34, no. 1, 2022, doi: 10.1007/s12528-021-09274-2..
3. G. Clarebout, H. Horz, and J. Elen, "The use of support devices in electronic learning environments," Comput Human Behav, vol. 25, no. 4, 2009, doi: 10.1016/j.chb.2008.07.004.
4. S. Alyahya and A. Aldausari, "An electronic collaborative learning environment for standardized tests," Electronic Journal of e-Learning, vol. 19, no. 3, 2021, doi: 10.34190/ejel.19.3.2167.
5. J. GRAHAM, "CASE-BASED LEARNING IN AN ELECTRONIC LEARNING ENVIRONMENT.," Perspectives of Innovations, Economics & Business, vol. 14, no. 4, 2014.
6. T. Consiglio and G. C. Van Der Veer, "Electronic learning environments - Worlds behind screens," in ACM International Conference Proceeding Series, 2013. doi: 10.1145/2501907.2501940.
7. H. A. El-Sabagh, "Adaptive e-learning environment based on learning styles and its impact on development students' engagement," International Journal of Educational Technology in Higher Education, vol. 18, no. 1, 2021, doi: 10.1186/s41239-021-00289-4.
8. M. A. Almaiah, A. Al-Khasawneh, and A. Althunibat, "Exploring the critical challenges and factors influencing the E-learning system usage during COVID-19 pandemic," Educ Inf Technol (Dordr), vol. 25, no. 6, 2020, doi: 10.1007/s10639-020-10219-y.
9. Ю. Д. Фирнафасович, "ИНФОРМАТИКА ФАНИНИ У^ИТИШНИ НЕЙРОТАРМО^ ТЕХНОЛОГИЯСИ АСОСИДА ТАШКИЛ КИЛИБ ТАЛАБАЛАРНИ ФАОЛЛАШТИРИШ МЕТОДИКАСИ," pp. 2181-1717, 2021, doi: 10.53885/edinres.2021.25.64.100.
10. L. Kester, P. Kirschner, and G. Corbalan, "Designing support to facilitate learning in powerful electronic learning environments," Comput Human Behav, vol. 23, no. 3, 2007, doi: 10.1016/j.chb.2006.10.001.
11. M. G. Jones, "Creating Electronic Learning Environments : Games , Flow , and the User Interface," Proceedings of Selected Research and Development Presentations at the National Convention of the Association for Educational Communications and Technology (AECT), 1998.
12. D. Bylieva, J. C. Hong, V. Lobatyuk, and T. Nam, "Self-regulation in e-learning environment," Educ Sci (Basel), vol. 11, no. 12, 2021, doi: 10.3390/educsci11120785.
13. D. Al-Fraihat, M. Joy, R. Masa'deh, and J. Sinclair, "Evaluating E-learning systems success: An empirical study," Comput Human Behav, vol. 102, 2020, doi: 10.1016/j.chb.2019.08.004.
