Student Learning Behavior Research Articles

Mining the English application learning patterns of college students based on time series clustering

As a convenient learning tool in the We Media era, mobile apps have been paid more and more attention by college students because of their accompanying timeliness and practicality. With the increasing number of English learning apps, many such apps provide college students with new ways to obtain learning resources and diversified learning modes. The related research in the field of mobile-assisted language learning at home and abroad has developed over nearly 20 years, basically following the route from theory to application in practice, but there have been few process studies on learners’ individual language skill learning behaviors based on mobile platform data. In this study, the time series clustering method was adopted, and the learning behavior of college students in an English vocabulary learning app in China was selected for data mining. Firstly, taking the “single-day memorization amount” as the measurement index, the memorization records of college students in the whole use cycle were extracted and processed into trajectory data, and the KmL algorithm was used to cluster the trajectory of the memorization amount in the time series. According to the intra-class average trajectory, the characteristics of learning behavior changes among the different college students are summarized, and two learning modes are depicted. Secondly, through the experimental analysis, it was found that adopting the English learning model three weeks before an exam can effectively stimulate college students and improve their willingness to learn and continue using the app.

PERAN GURU BIMBINGAN DAN KONSELING TERHADAP PERILAKU BELAJAR SISWA KELAS IX SMP NEGERI 1 SIDOHARJO

Guidance and counseling is a school component that provides counseling services to students. One of the duties of the guidance and counseling teacher/counselor is to help develop students' potentials in a positive direction, including having good study habits. The purpose of this study was to investigate the influence of the guidance and counseling teacher's role on the learning behavior of class IX students at SMP Negeri 1 Sidoharjo. The method used is quantitative with a correlation approach. From the simple linear regression statistical test with SPSS which was carried out, the result was that the correlation value (R) was 0.129. From this output, the coefficient of determination (R square) is 0.17, which implies that the effect of the independent variable (the role of the guidance and counseling teacher) on the dependent variable (learning behavior) is 1.7%, the calculated F value = 2.227, with a significance level of > 0.05, so it can be concluded that there is no influence of the role of the counseling teacher on student learning behavior. Thus, the first hypothesis in this study can be rejected.

The influence of a digital clinical reasoning test on medical student learning behavior during clinical clerkships

Recently, a new digital clinical reasoning test (DCRT) was developed to evaluate students’ clinical-reasoning skills. Although an assessment tool may be soundly constructed, it may still prove inadequate in practice by failing to function as intended. Therefore, more insight is needed into the effects of the DCRT in practice. Individual semi-structured interviews and template analysis were used to collect and process qualitative data. The template, based on the interview guide, contained six themes: (1) DCRT itself, (2) test debriefing, (3) reflection, (4) practice/workplace, (5) DCRT versus practice and (6) ‘other’. Thirteen students were interviewed. The DCRT encourages students to engage more in formal education, self-study and workplace learning during their clerkships, particularly for those who received insufficient results. Although the faculty emphasizes the different purposes of the DCRT (assessment of/as/for learning), most students perceive the DCRT as an assessment of learning. This affects their motivation and the role they assign to it in their learning process. Although students appreciate the debriefing and reflection report for improvement, they struggle to fill the identified knowledge gaps due to the timing of receiving their results. Some students are supported by the DCRT in exhibiting lifelong learning behavior. This study has identified several ways in which the DCRT influences students’ learning practices in a way that can benefit their clinical-reasoning skills. Additionally, it stresses the importance of ensuring the alignment of theoretical principles with real-world practice, both in the development and utilization of assessment tools and their content. Further research is needed to investigate the long-term impact of the DCRT on young physicians’ working practice.

Analysis and Application of The Mining Process to Identify Student Learning Behaviour On The Use of E-Learning After The Covid-19 Pandemic

SMK Telkom Malang is a vocational high school in the field of Technology and Information Technology that implements technological advances and developments in the system, distance learning. E-learning is one of the learning media supported by computer and internet technology, which contains learning content. Student learning behavior in machine learning or E-Learning has a strong relationship in its use. The higher the quality of the application of learning in machine learning or E-Learning, the higher the achievement in obtaining data on student learning behavior in the use of e-learning recorded in the event log. This research uses Disco and ProM tools using the Heuristic Miner. Heuristic Miner is used because it is most suitable for handling process mining on event logs from Learning Management System because heuristic miners can express event logs well and reveal main events recorded in event logs and are able to handle data that has noise. The use of Petri Net in ProM tools helps in analyzing the process model to provide an overview of student learning behavior towards e-learning the actual Result of heuristic miner can model the event log into the process model well, seen from the average fitness of the RPL majors shows a value of 0.970.

Exploration of the development path of university thinking and political education in the background of Internet

Abstract The effective development of Civic Education work in colleges and universities can promote the cultivation of high-quality talents. Starting from Internet information technology, this paper constructs a digital platform for Civic Education work, in which Shannon’s theory and balanced power allocation are used to optimize channel transmission and enhance the loading speed of Civic Education resources. The XGBoost algorithm is used to effectively cluster students’ learning behaviors as a way to help Civic Education workers understand students’ learning behaviors in Civic Education. The results show that the average response time is 0.327s, and the maximum throughput is 11849.478 bytes/sec. The prediction accuracy of the XGBoost algorithm for student learning behavior is 4.65%, 9.79%, and 21.79% higher than that of LR, RF, GBM, and Stacking classification models, respectively. 9.79%, 21.41%, and 13.5%, respectively. This shows that the university’s thinking and political education work can be developed through the direction of the digital Internet platform, which in turn provides a new research path for the reform and innovation of thinking and political education work.

Research on the development of digitalization of art education in the era of big data technology

Abstract Exploring the digital development of art education can effectively enhance students’ creativity in art design. This paper constructs a digital teaching platform for art education based on big data technology and analyzes student learning behavior data in the teaching platform. For student learning behavior with a new Hawkes process for data extraction, the decomposition of the student learning effect is realized by data encoder, event-level decoder and course-level decoder. Performance tests and art teaching effect analysis were conducted for the platform built in this paper. From the performance test, the throughput of the test interface is 580 when the server CPU is maintained at about 26%, memory is maintained at about 48.62%, and load is maintained at about 4.7. From the teaching effect, the four dimensions of students’ creativity changes had significant differences; namely, the p-values of adventurousness, curiosity, imagination, and challenge were 0.189, 0.247, 0.076, and 0.425, respectively. This indicates that the digital teaching platform for art education built by using big data technology can effectively enhance students’ creativity and also provide a new direction for the digital development of art education.

Study on the optimization of the cultivation path of finance professionals in universities in the digital era

Abstract The rapid development of big data technology is bound to affect the development direction of finance majors in colleges and universities and put forward new challenges to the cultivation of talents. This paper first analyzes the data mining concept, process as well as methods and selects the clustering analysis method, K-means algorithm, and NMF algorithm of big data technology. Secondly, data pre-processing is carried out for students’ learning behavior, learning evaluation, and professional ability data, which makes the subsequent data mining results more reliable. Finally, the judgment matrix is constructed for the training of college finance professionals, and the consistency test of the matrix is carried out to form the absolute indexes of the primary indexes and the relative weight values of the secondary indexes, and the absolute weights of the secondary indexes are obtained through calculation, which finally forms the weights about the student learning behavior, learning evaluation and professional competence evaluation indexes. The learning percentages of student learning clusters are: 16.1%, 19.3%, 30.1%, 34.4%. The innovation and collaboration ability of finance students has been improved, and the deep processing feedback ability of financial knowledge content has been strengthened. Thus, the wide application of big data technology provides a new path for the training of finance professionals in colleges and universities.

Research on the construction and reform path of online and offline hybrid English teaching model based on time series

Abstract With the widespread use of blended English teaching, the teaching model has become increasingly rigid and needs to be reformed. This paper proposes an analytical model of student learning behavior under blended English teaching based on big spatiotemporal data and constructs a structure of offline and online student learning behavior. The DWT-FCM clustering method for learning behaviors is constructed by using a similar distance based on time series instead of Euclidean distance in the traditional fuzzy C-mean algorithm. The maximum information coefficient was used to analyze the correlation between learning behaviors and grades based on MI. the DWT-FCM algorithm divided learning behaviors into five clusters, where the discussion number of cluster 0 reached an average of 45.2, which was 3.2 times higher than that of cluster 1. Cluster 4 has an average number of task completions of only 1.88, which will skip almost the entire course taken. The correlations of the number of task completion, course video progress, and assignment evaluation scores are all highly correlated, with correlation coefficients reaching 0.884 and 0.825, respectively. This study suggests the influence of learning characteristics on English performance in a blended teaching model, which can effectively guide the reform of the blended English teaching model.

Effectiveness of Gamification in Enhancing Learning and Attitudes: A Study of Statistics Education for Health School Students.

Gamification is the use of game design elements in non-game contexts. It is considered a student-centered instructional design to motivate student learning and academic behavior. In this study, the effects of gamification on learning statistics (hypothesis testing issue) and attitude toward statistics in comparison with the common e-learning approach were investigated. The students' experience and critical elements of gamification on learning statistics were assessed, too. In a before and after trial, in a census manner, 64 health faculty students of Guilan University of Medical Sciences, Rasht, Iran, non-randomly were assigned to the intervention (n=42) and control (n=22) groups. Learning activities were gamified in the intervention group, while the control group received traditional problem-solving in the learning management system. Narrative, avatar, level, point, progress bar, scoreboard, challenge and feedback elements were used in the game experience. The implementation of gamification was applied based on Landers' theory of gamified content. Valid and reliable Persian version of the Survey Attitude toward Statistics questionnaire measured the students' attitude before and after the intervention. The EGameFlow questionnaire and a valid and reliable researcher-made exam measured the users' experience of gamified content and learning hypothesis testing after the intervention. The independent samples T-test, analysis of covariance and the partial eta-squared effect size were calculated by SPSS software, version 26. Compared to the control group, the intervention group had a more positive attitude toward learning difficulty (moderate partial eta-squared 0.099), value and cognitive competency (weak partial eta-squared=0.01 and 0.05). Learning between the two groups was not different (P=0.522). There was a significant correlation between learning and the students' perceived experience with feedback (r=0.583, P<0.001), concentration (r=0.509, P=0.005), and challenge (r=0.421, P=0.023) of the gamified content. It suggests using gamification on learning statistics while optimizing the design with more focus on the feedback, challenge and concentration elements.

Student Learning Behavior Recognition Incorporating Data Augmentation with Learning Feature Representation in Smart Classrooms.

A robust and scientifically grounded teaching evaluation system holds significant importance in modern education, serving as a crucial metric that reflects the quality of classroom instruction. However, current methodologies within smart classroom environments have distinct limitations. These include accommodating a substantial student population, grappling with object detection challenges due to obstructions, and encountering accuracy issues in recognition stemming from varying observation angles. To address these limitations, this paper proposes an innovative data augmentation approach designed to detect distinct student behaviors by leveraging focused behavioral attributes. The primary objective is to alleviate the pedagogical workload. The process begins with assembling a concise dataset tailored for discerning student learning behaviors, followed by the application of data augmentation techniques to significantly expand its size. Additionally, the architectural prowess of the Extended-efficient Layer Aggregation Networks (E-ELAN) is harnessed to effectively extract a diverse array of learning behavior features. Of particular note is the integration of the Channel-wise Attention Module (CBAM) focal mechanism into the feature detection network. This integration plays a pivotal role, enhancing the network's ability to detect key cues relevant to student learning behaviors and thereby heightening feature identification precision. The culmination of this methodological journey involves the classification of the extracted features through a dual-pronged conduit: the Feature Pyramid Network (FPN) and the Path Aggregation Network (PAN). Empirical evidence vividly demonstrates the potency of the proposed methodology, yielding a mean average precision (mAP) of 96.7%. This achievement surpasses comparable methodologies by a substantial margin of at least 11.9%, conclusively highlighting the method's superior recognition capabilities. This research has an important impact on the field of teaching evaluation system, which helps to reduce the burden of educators on the one hand, and makes teaching evaluation more objective and accurate on the other hand.

Building Mathematics Learning through Inquiry Using Student-Generated Data: Lessons Learned from Plan-Do-Study-Act Cycles

This paper describes how plan-do-study-act cycles engaged a classroom mentor teacher and student teacher in a professional collaboration that resulted in two inquiry activities for high-school geometry classes. The PDSA cycles were carried out in four high school geometry classes, each with 30 to 35 students, in a mid-Atlantic urban school district in the U.S. The four geometry classes were co-taught by the second and third authors of this paper. The data consisted of classroom documents (e.g., activity prompts, tasks), classroom observations, student feedback about activities, and monthly PDSA reports. The PDSA cycles had a direct effect on the professional learning of the teachers. The resultant classroom activities used a data collection approach to engaging students in inquiry to learn about trigonometry functions and density. Student learning behaviors were noticeably improved during these activities compared with traditional mathematics instruction. We concluded that the data collection sequence provided an accessible entry point for students to begin scientific inquiry in mathematics. The process opened the conceptual space for students to develop curiosity about mathematical phenomena and to explore their own research questions. The use of culturally relevant topics was especially compelling to students, and the open-ended nature of these exploratory activities allowed students to see mathematics through their own cultural lenses.

ការប្រើប្រាស់វិធីសាស្រ្តបង្រៀននិងរៀនតាមបែបរិះរក ក្នុងមុខវិជ្ជាគណិតវិទ្យាថ្នាក់ទី៣ ដើម្បីជំរុញការរៀនសកម្ម

Teaching methods play an important role in the teaching-learning process as they help students have the opportunity to build knowledge through active learning and improve their learning outcomes. Based on the experience of the researchers' past internships and teaching practicum, about 70% of the students did not participate actively in class. Students were often inactive during class hours without responding to teachers or expressing themselves. Students often sat quietly, took notes, and did not engage in any activities. Recognizing the significance of an Inquiry-Based Learning (IBL), this study aims to measure its effects on students' active learning, particularly on Grade 3 students’ learning outcomes in mathematics. The analysis of the data from 22 Grade 3 students revealed that the use of IBL motivated students to participate in learning actively in terms of objective identification, lessons, materials, teacher activities, teaching methods, student learning behavior, satisfaction with learning activities, and interests in learning. In addition, IBL seems to improve students’ learning outcomes. The students’ mean scores for the pre-test were 1.88 and 8.47 for the post-test. Thus, using IBL could make students more active learners and help promote their learning outcomes.

Exploration of factors affecting changes in student learning behavior: A systematic literature review

&lt;span lang="EN-US"&gt;The general learning behavior has a major impact on the psychological and mental adjustment of students to learn. Therefore, this study reviews relevant studies on the factors causing changes in student learning behavior. The review used PRISMA, so several stages were carried out to filter and collect relevant information. The results of the synthesis revealed 19 broad factors influencing student learning behavior. Furthermore, these factors can be seen in more detail in four main groupings: i) Student learning behavior in the classroom; ii) Student learning behavior outside the classroom; iii) Student learning motivation; and iv) Student learning behavior results. Student learning behavior in the classroom is influenced by motivation, reflection, learning satisfaction, and learning activities. Meanwhile, student learning behavior outside the classroom is influenced by technology, independent learning abilities, learning resources, learning environment, and students’ internal conditions. The final result showed that students with a positive learning environment consistently acquire good knowledge in achieving learning objectives. There are many challenges in forming good student learning behavior. Therefore, this study benefits the education experts, counselors, teachers, parents, and the learning environment by increasing student motivation and satisfaction in learning to minimize the negative impact of changes in student learning behavior.&lt;/span&gt;

The Influence of Association on Changes in Student Learning Behavior at SMA Negeri 6 Pekanbaru

This research was written against the backdrop of the existence of a phenomenon of changes in student learning behavior caused by the association of students at SMA Negeri 6 Pekanbaru. Changes in learning behavior such as students skipping study, unplugging, smoking, not paying attention to the teacher while studying and others. Based on this phenomenon, the authors are interested in conducting research with the aim of finding out whether there is social influence on changes in student learning behavior at SMA Negeri 6 Pekanbaru. The location of this research was conducted at SMA Negeri 6 Pekanbaru. The research method used is quantitative with data collection techniques, namely questionnaires (questionnaire), observation, interviews and documentation. Based on the results of statistical calculations, Tcount (12.782) Ttable (2.012) means that Ha is accepted. Based on the results of the linear regression equation, the equation is Y = -3.895 + 1.138X, meaning that if association (X) increases by 1, then changes in learning behavior (Y) increase by 1.138. So it can be concluded from the results of the T test that there is an influence of variable X on variable Y, meaning that Ha is accepted, namely: there is an influence on changes in student learning behavior at SMA Negeri 6 Pekanbaru.

Minat Membaca dalam Upaya Meningkatkan Perilaku Belajar Siswa pada Mata Pelajaran Pendidikan Agama Buddha dan Budi Pekerti

This study aims to improve the learning behavior of 7th grade students of SMP Smaratungga Ampel. The research method used in this research is quantitative research method, while the research approach used is a causal approach. The subject of this research was Buddhist students in grade 7 of SMP Smaratungga Ampel, totaling 10 people, data collection techniques in the form of data obtained directly from the field (primary data) by distributing questionnaires or questionnaires to respondents. Primary data was obtained by researchers by distributing questionnaires to respondents totaling 10 people. The results of this study indicate that the results of data analysis with the simple linear regression formula obtained the amount of R square 0.814, thus meaning that 81.4% of Buddhist education learning behavior in 7th grade students of Smaratungga Ampel Junior High School is influenced by reading interest while the remaining 18.6% is influenced by other factors not included in the regression equation. Thus it can be concluded that interest in reading can improve the learning behavior of 7th grade Buddhist students of Smaratungga Ampel Junior High School.

Hubungan Kompetensi Pedagogik Guru dengan Perubahan Perilaku Belajar Siswa Beragama Buddha

This study aims to measure how important pedagogical competence is in addressing student learning behavior at SMP Negeri 2 Susukan. This research is a quantitative research with a correlational approach, namely research that aims to find out whether or not there is an influence or relationship between two or more variables, and if there is a relationship, how big the relationship is. To collect data the researcher distributes questionnaires to students. This study involved 15 students. The results of the data analysis show a strong relationship between teacher pedagogical competence and student learning behavior.

Improving self-directed learning ability of medical students using the blended teaching method: a quasi-experimental study

BackgroundSelf-directed learning (SDL) is one of the most important abilities for medical students in terms of their future clinical medical practice. During the blended teaching process, teachers can design a variety of learning activities to cultivate students’ SDL abilities. This study aimed to assess the differences between the SDL abilities of medical students using blended and traditional didactic teaching.MethodsThis study included 239 medical students from eight administrative classes. The students were divided into two groups: (1) the experimental group (EG), which included 119 students from four administrative classes, and (2) the control group (CG), which included 120 students from the remaining four classes. From February to July 2022, blended teaching methods were applied to the EG group, and SDL abilities were assessed in comparison to the CG group receiving traditional didactic teaching methods.ResultsAt the end of the semester, significant differences (p < 0.05) were observed between EG and CG in all six SDL ability factors. Furthermore, when k-means cluster analysis was used to analyze the learning behavior of students in the EG after classifying them as comprehensive, interactive, and passive types, significant differences were observed in all six Self-directed learning factors of students with the comprehensive type, whereas significant differences were observed in four factors (setting learning goals and plans, self-monitoring and regulation, information processing, and communication and cooperation) of students with the interactive type. For students with passive type, only one factor of SDL (information processing) showed significant improvement. There were on differences between comprehensive, interactive, and passive types of CG.ConclusionThe blended teaching approach is better than the conventional didactic teaching for cultivating clinical medical students’ SDL abilities.

DEEP MIND MAPPING MODEL IMPLEMENTATION DEVELOP CHILD CREATIVITY

&lt;p style="margin: 0cm 0.65pt 0pt 0cm; text-align: justify;"&gt;&lt;span style="letter-spacing: -0.05pt; font-family: 'Cambria','serif'; font-size: 12pt; mso-ascii-theme-font: major-latin; mso-hansi-theme-font: major-latin;"&gt;Children's creativity is a potential that must be developed through the educational process. This study aims to describe the implementation of the mind mapping model in developing children's creativity in akidah akhlak lessons. This study uses a qualitative approach with a descriptive study method. The background of this research is in SDN 068003. Observation techniques, interviews, and document studies are three research data acquisition techniques. Then, the data were analyzed using an interactive analysis model, through the steps of data collection, data sorting, data presentation, and drawing conclusions. The results of this study indicate that the application of the mind mapping model makes it easier for educators during the thematic learning process, because it stimulates students to develop their creativity based on the spirit of group learning. Likewise, there are obstacles in implementing the learning model, namely the low focus of students in group activities, difficulties for teachers to control student learning behavior, and some students like to disturb their friends.&lt;/span&gt;&lt;/p&gt;

Study on the Evaluation Method of Blended Learning Effect Based on Multiple Linear Regression Analysis

With the development of information technology, blended learning has been widely used in the education field, and the evaluation of blended learning effect has become one of the research hotspots. Taking the automobile theory course as an example, a blended learning process with online and offline is designed, and the main learning behaviors that affect learning effect are analyzed. By extracting data on the main learning behaviors of students during the learning process, correlation and linear regression methods are used to analyze the influencing factors of blended learning effect, and a linear regression prediction model is established. The results show that students' online testing, classroom performance, unit testing, feature assessment, and experimental performance are key indicators for predicting learning performance. According to the analysis of influencing factors of blended learning, the countermeasures and suggestions for improving the effect of blended learning are proposed.

LOW MOTIVATION TO LEARN IN MUHAMMADIYAH JUNIOR HIGH SCHOOL STUDENTS, SOUTH PAGARALAM DISTRICT DUE TO THE INFLUENCE OF SOCIAL MEDIA

This research is based on the background that there are still students who do not understand the use of social media well so that it has an impact on student learning behavior at school. This affects student learning outcomes in schools that are less than satisfactory because social media is not used for learning but is more used as a place of entertainment. Based on this, this study will reveal how the influence of the use of social media on learning behavior. Social media is a communication area that is used more today, whether in terms of work, relationships and other matters. The existence of social media makes it easier for someone to communicate, faster and more affordable, all human activities become easier. Social media also has a weakness, namely users who do not have limits or control themselves will be complacent, and negligent in other matters. Based on the results of this study, it can be understood that excessive use of social media will greatly affect student learning behavior at school.