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Factors That Lead to Misbehaviour in Class According to Students’ Perception at UiTM Seremban 3 Using Multiple Linear Regression (MLR) Analysis

This study was conducted to describe the factors that lead to misbehaviour in class according to students’ perception in University Technology Mara (UiTM) Seremban 3. 372 students were surveyed regarding their perception of the factors that lead to misbehaviour in class. There are five factors that the researchers want to study, which are the lecturer’s personality, student’s lifestyle, influence from social media, students’ time management, and facilities. These five variables were chosen to determine the factors that lead to misbehaviour in class which is the main objective. To achieve the main objective of this study, Multiple Linear Regression (MLR) analysis will be used to come out with the result. Results show that three factors lead to misbehaviour in class. These factors are the lecturer’s personality, influence from social media and students’ time management. Other than that, there are several methods to achieve other research objectives. The Spearman correlation method was used to analyse the relationship between the factors that affect the students’ perceptions of misbehaviour in class. The analysis shows that the relationship for lecturer’s personality has a moderate positive relationship. In contrast, the other four factors, such as students’ lifestyle, influence from social media, students’ time management and facilities, have a weak positive relationship with students’ perception of misbehaviour in class. Moreover, the Kruskal Wallis test was used to identify the final objective, identifying the differences in students’ perceptions between different faculties in UiTM Seremban 3. The result shows that all students in the three faculties have the same perceptions of factors leading to misbehaviour in class. In conclusion, this study helps higher education organisations identify what makes students misbehave in class. Based on the results, organizations may know how to decrease misbehaviour cases among students. For these students, the administration needs to focus on the lecturer’s personality, influence from media social, and students’ time management in reducing the misbehaviour problem.


1.
Introduction How do you feel if you are surrounded by people misbehaving in class? Nowadays, student misbehaviour is one of the most frequent problems globally, especially in schools and universities [1]. According to [2], this problem also happens in one of the universities in Malaysia, which is the University Technology Mara (UiTM). One of the challenges that the education environment needs to improve is to make sure that the behaviours of students are under control. In UiTM Seremban 3, the administration also faces the same problem with students' misbehaviour in class. However, there is little information or studies on students' behaviour, especially on campus. The researchers know that UiTM has many students compared to other universities, which means severe misbehaviour problems happen.
Behaviour can be defined as what people do at their own risk and their natural act, especially in response to their environment [3]. People can observe behaviour, and everyone has their behaviour [4]. In this study, the researchers want to study the factors that lead to misbehaviour in class. According to [5], misbehaviour is an adverse movement that people always do that makes other people uncomfortable. Misbehaviour can happen not only in higher-educational institutions but also in other places [6].
Students' misbehaviour can make the study environment stressful, negatively affecting the lecturers' and students' feelings because of the destructive behaviour in class [6]. Good behaviour is the thing that all lecturers want. Good behaviour is a necessary condition for an effective learning environment between lecturers and students. The outcome of good behaviour in a learning environment will positively impact their lives as students [7] where misbehaviour cannot grow in their surroundings. The administration needs to find the factor that leads to misbehaviour of students in class. Accordingly, this study has the following three objectives: 1. To determine the relationship between lecturer's personality, student's lifestyle, influence from social media, students' time management, facilities and students' perception towards misbehaviour in class. 2. To determine the factors that lead to misbehaviour in class according to students' perceptions. 3. To identify if there is a significant difference among the Faculty of Computer and Mathematical Sciences (FSKM), the Faculty of Administrative Science and Policy Study (FSPPP) and the Faculty of Sport Science and Recreation (FSR) in students' perception towards misbehaviour in class.

Literature Review
Misbehaviour is a matter of concern for all people, especially in educational organizations, because misbehaviour will affect all aspects, especially in producing high-quality students who can fulfil the requirements of high-quality graduates. In this study, the lecturer's personality is one of the factors that this research wants to study. Based on previous research, 1500 students have been taken as respondents for this research, and the results show that lecturers have a relationship with students. In this study, Pearson correlation was used [8]. Another research by [9] indicates a significant but moderate relationship between lecturers and students. Regarding students' lifestyles, the previous research [10] shows that 30.7 per cent of the respondents who participated in the research suffer from resistance to falling asleep. This problem may affect the students' behaviour towards their learning process.
Furthermore, other research [11] that studied influence from social media found that social media usage among students negatively influences students' behaviour in selected universities in Pakistan. Further investigation found that social media has changed how people, including university students, communicate and interact throughout their learning process at university [12].
In terms of students' time management, it affects individuals' overall performance and achievements [13]. Another finding by [13] found that time management causes students' misbehaviour in class. Students always complain that they do not have enough time to complete all the homework or tasks their lecturers or teachers give to them. According to research done by [14], more than ten minutes of learning were lost because of students' behaviour problems. Other than that, students' time spent on unnecessary things will influence them with bad behaviour, which has adverse effects on their academic performance [15]. There was a study about Total Learning Environment Assessment (TLEA), and the study found that discipline or behaviours are significantly related to TLEA, including facilities [16]. Another finding in terms of facilities factor is research done by [17] who claims that the facility design will impact students' achievement, behaviour, class attendance and teacher retention.

Research Design
This study aims to determine the factors that lead to misbehaviour in class according to students' perception at UiTM Seremban 3. Hence, the cross-sectional design was used in this research. The theoretical framework used in this study is shown in figure 1.

Population
The target population for this research were active and full-time students in UiTM Seremban 3. After excluding the students who take additional semesters and non-full-time students, the total students from three faculties were 5243 students. The sample was chosen from the population. The population for this study is shown in table 1.

Sample Size
The sample size is chosen accordingly based on the population of 5243 students. The margin error used in this study is 0.05, following the previous research that used the same population: students from higher educational institutions [18]. For this research, stratified sampling, which is categorized in probability technique, was used. The population was divided into several faculties, which were FSKM, FSR and FSPPP. The formula and calculation of sample size and sampling technique are shown in equations 1 and 2. = 1 + ( ) 2 (1) where n = Corrected Sample Size, N = Population Size = 5243 Students e = Margin error = 0.05

Sampling Technique and Sample Selected
In this study, stratified sampling was used. The population was divided into several faculties, which are FSKM, FSR and FSPPP. Then, simple random sampling was conducted to select the sample in this study. The selection was chosen from three different faculties, which were FSKM, FSR and FSPPP. The calculation for sample size found that 106 students were selected from FSKM out of 1499 students, 55 students were chosen from FSR out of 775 students, and 211 students were chosen from FSPPP out of 2969 students. The number of samples for each faculty are shown in table 2.

Research Instrument and Data Collection Method
A questionnaire was used in this study. The questionnaire was adapted from various previous studies. It consists of two-part, which are Part A and Part B. In Part A, which contains demographics, the respondents need to answer eight different questions about their background. Moreover, the questions were also to identify the respondents' perceptions about misbehaviour in class. Part B is provided in the questionnaire to identify the students' perception towards the factors of misbehaviours in class. In Part B, there are six sections, and every section has five different questions which use the Likert scale from strongly disagree, disagree, agree and strongly agree. In this study, Google Forms were used to collect the data from respondents. The questionnaires were distributed through social media platforms such as WhatsApp, Telegram, Facebook and Instagram. The questionnaire about the independent variable for lecturer's personality and student's lifestyle were adapted from [8], [10], [24] and [25]. Meanwhile, the questionnaire for the independent variable influence from social media, faculties, and time management is adapted from research [26] and [27]. The questionnaire about the dependent variable was adapted from [9].

Method of Analysis
This study has been analysed using the Cronbach Alpha for the pilot study. Based on the rule of thumb of Cronbach Alpha, all the values of each variable are in range, respectable and very good. The Spearman correlation was used to measure the relationship strength between the independent and dependent variables to achieve the first objective. For the second objective, the researchers have to find factors that lead to misbehaviour in class. The multiple linear regression was applied in this analysis. There are three selection methods in multiple linear regression: stepwise regression, forward and backward elimination method. In this study, the backwards elimination method is used following the previous research that had the same study population, which are students itself applied this method [19]. For the final objective, the third objective, Kruskal Wallis Test, was undertaken to achieve the third objective, which is to identify any significant difference between FSKM, FSPPP and FSR students towards factor misbehaviour in class. The Kruskal Wallis Test was used to analyse the difference between two or more groups. If the p-value is less than 0.05, it can be concluded that there is a significant difference between the groups and the independent variable. This study also uses two types of nonparametric tests: spearman correlation and Kruskal Wallis test. These two non-parametric tests were used because the Likert scale for Spearman correlation and Kruskal Wallis test was used since the two groups did not follow the normality assumptions. Both methods chosen is based on journals by [22] and [23], respectively. Table 3 Table 4 shows that the value of R-square for the general regression model is 0.254. Thus, it can be concluded that 25.4 per cent of the total variation in students' perception towards misbehaviour in class is explained by the lecturer's personality, influence from social media, and student's time management, while other factors explain another 74.6 per cent. Based on table 4, the regression model is significant since the p-value is 0.0001, less than 0.05. Based on table 5, all variables are significant, in which the p-value is less than 0.05. Furthermore, it shows that the lecturer's personality, influence from social media, and student's time management are significant. This is because the p-value for these three independent variables is less than 0.05. All the variables in the model are significant. The final model was chosen since all the variables were significant and all the assumptions were met. It can be concluded that three factors lead to misbehaviour in class according to students' perception: lecturer's personality, influence from social media, and student's time management. There are two variables: student's lifestyle and facilities that are not the factors since these variables are not significant.  Figure 2. The final theoretical framework of perception towards misbehaviour in class among UiTM Seremban 3 students.

Comparison Students' Perception Towards Misbehaviour in Class and Between Faculties
The last objective is to identify the significant difference of the faculties towards misbehaviour in class, FSKM, FSR and FSPPP with the dependent variable. The Kruskal Wallis test was used to determine the significant difference between the faculties. Based on table 6, the p-value of the Kruskal Wallis is equal to 0.102, where it fails to reject the null hypothesis because the p-value of the test is more than alpha with a=0.05. This can be concluded that there is no significant difference between faculties towards the students' perception that leads to misbehaviour in class. Thus, all the students in UiTM Seremban 3 have the same perception of factors that lead to destructive behaviour in class.

Conclusion
Misbehaviour among university students is a serious problem nowadays. The first objective result shows that the relationship between the lecturer's personality and students' perception toward misbehaviour in class has a moderate positive relationship which is lecturers contribute to the behaviour of their students. This result is also supported by previous research that concludes a significant but moderate relationship between lecturers and students [9]. In this study, only three factors out of five are substantial. three factors lead to misbehaviour in class. The administration of UiTM Seremban 3 needs to focus on these three factors to overcome the misbehaviour problem. According to previous research, the same finding has also found that social media usage among students negatively influences students' behaviour in selected universities [11]. The previous study with the same result [15] concludes that students' time spent doing unnecessary things will influence them with bad behaviour and its harmful effects on academic performance. In terms of lecturer's personality, their previous study that comes out with same results with this study which is the personality of the lecturers is the main factor that leads to low performance and misbehaviour students [21]. Moreover, all the students in the three faculties have the same perception of factors that lead to misbehaviour in class. Moreover, the most significant limitation of this study was that it was conducted during the COVID-19 pandemic, in which the data itself takes a long time to gain. Also, this research needs a long time to finish because there is no face-to-face meeting between the researchers and the respondents.

Recommendations
For this research, only 25.4 per cent of the total variation is explained by the factors. Based on this result, future researchers can identify other factors that might be presented more than the factors used in this study. Other factors that can be used for future research are students' personalities or students' family problems. This research can also be used for different places and relevant factors for the places or locations. Hence, this research needs to be updated for other research factors in line with time flow.