Faculty incivility and learning engagement are examined in this study using locus of control (LOC) as moderator. A survey on 321 college students from Chandigarh (UT), India, was conducted. The data was analyzed using Smart PLS4. By demonstrating locus of control as a moderating factor between faculty incivility and learning engagement, findings supported the predicted hypotheses. Learning engagement was significantly impacted by faculty incivility. Further, LOC has a favorable impact on learning engagement. At low LOC there is highest impact of faculty incivility on learning engagement. However high LOC dampens faculty incivility and learning engagement relationship. Study results sheds light on ways to lessen the detrimental impact of faculty incivility on students’ learning process
Behavior that disrupts a peaceful and collaborative learning environment is termed as classroom incivility (Feldmann, 2001). An environment of disrespect for one another in educational institutes can be fostered by both students and teachers. Learning environment could be severely harmed by uncivil behavior on the part of faculty and students. Braxton et al. (2011) observed that incivility phenomenon has gotten worse because students are not blamed for such behavior. Instead, they focus on the rude behaviors of the faculty members toward the students in the classroom, such as being late for classes and absence, offensive humor, demeaning remarks, public humiliation, and other various forms of insults.
Since the majority of incivility research focuses on the causes and consequences of workplace incivility (Schilpzand et al., 2016). Various studies have focused on figuring out what causes faculty incivility (FI) and how it affects students' perceptions and the consequences of those perceptions (Caza & Cortina, 2007). Even though incivility is primarily linked to organizations, it has recently been expanded to encompass conflictual relationships outside of the traditional dyadic between managers and employees. For example, manager-customer relationships and work-family conflict are examples of conflict that may arise from managers acting in an uncivil manner at work. The study of incivility has been expanded to encompass instances of incivility that occur in higher education as well (Lim & Lee, 2011).
2.1 Faculty Incivility
Students claimed that incivility from the teachers had an impact on their physical and mental health (Clark, 2008). Using an interpretative qualitative research approach, the study examined perceptions of faculty over incivility in nursing education about its probable causes and solutions. Four categories were identified through a narrative analysis: student disruptions in and out of class, teacher’s uncivil conduct, and potential reasons for uncivil behavior in nursing education (Clark & Springer, 2007).
2.2 Locus of Control
The key work on social learning theory gave rise to the locus of control (Rotter, 1966). The construct was given the full name Locus of Control of Reinforcement by Rotter.
It has been discovered that internal locus of control orientation and achievement are correlated. Academic performance, learning qualities have all been studied in relation to LOC. Students with self-confidence in knowledge and abilities can succeed quickly and receive excellent grades. defined as “The locus of control is a dimension of personality; it helps to explain one's traits and behavior”(Rotter, 1966). Students' cognitive, emotional, and behavioral responses in academic success and in and outside of the classroom contexts are significantly correlated with locus of control (Chubb et al., 1992).
2.3 Learning Engagement
Numerous scholars have attempted to conceptualize "student engagement," which is a multidimensional idea. Student engagement has been extensively studied. In earlier decades, researchers have given it a great deal of attention (Reschly & Christenson, 2022). As per Fredricks et al.(2004) there are three characteristics of involvement—behavioral, cognitive, and emotional—combine to form student engagement. Participation in extracurricular activities, attendance, school-related behavior, and learning contributions are all examples of behavioral student involvement.
Perceived academic task relevance and use of fundamental cognitive processes for the conception of multidimensional notions are a part of the cognitive framework (Wang & Eccles, 2012). The final element is the way students feel about their classes and schools; their emotional component includes how they interact with their teachers and peers.
2.4 Faculty Incivility and Learning engagement
Incivility interrupts the learning process, causes financial waste, and causes mental and physical strain(Bai et al., 2020). Classroom incivility and learning engagement have been discovered to have a negative correlation (Malodia & Butail, 2023). Learning engagement is negatively and significantly impacted by classroom incivility(Cahyadi et al., 2021; Ramadhany & Anggraeni, 2022). Students who are disengaged are more likely to become disinterested in their studies, to not establish intellectual connections with their teachers and peers, and to act uncivil as a result (Cicotti, 2012).
2.5 LOC and Learning Engagement
LOC significantly impacts both learning outcomes and behavioral intentions (Yang et al., 2017). Locus of control was not substantially correlated with either accomplishment or retention (Tobin & Capie, 1982). Both intrapersonal and interpersonal religious commitment were major pathways from LOC to academic involvement (Chukwuorji et al., 2018).
Students who experienced workplace loneliness had lower levels of student engagement conditioned to internal LOC. Learning engagement would therefore be present for the student with a high internal LOC (Singh et al., 2020). Students with a high internal LOC would take responsibility for their performance and accepted criticism for their scores and lack of effort in the class (Hopkins et al., 2020).
2.6 Moderating effect of Locus of Control
In a study, it was found that student disrespect had a higher detrimental effect on learner engagement when there was low LOC (Cahyadi et al., 2021).
Figure 1. Conceptual model
2.7 Hypotheses
H1: Faculty incivility negatively and significantly impacts learning engagement.
H2: LOC positively and significantly impacts learning engagement.
H3: LOC moderates faculty incivility and learning engagement relationship.
3.1 Sampling
Population consisted in this study are students of Chandigarh's public and private colleges. For the objective of gathering data, eleven colleges in Chandigarh were approached and simple random sampling technique was opted. After deleting inactive responses and outliers, 321 responses in total were taken into account for the analysis. It had 130 females (40%) and 191 males (60%) in total. The sample consisted of 66 (20%) postgraduate students and 255 (80%) undergraduate students. The survey was completed by 206 (64%) students from public institutions and 115 (36%) students from private colleges. In 2024, the data was gathered between July and September.
3.2 Research Instruments
Five-point Likert Workplace Incivility Scale (WIS) with twelve items developed by (Cortina et al., 2001) was used in this study to measure faculty incivility. Alpha for faculty incivility was 0.958. The seven-point nine items Likert student Version (UWES-S) scale developed by (Schaufeli et al., 2002) was used to measure learning engagement. There are three dimensions of the measure. First dimension is Vigor, second is dedication, and third is absorption. Cronbach’s Alpha for learning engagement was 0.861. The six point eight items Likert scale developed by (Levenson, 1981) was used in this study to measure LOC. Cronbach’s Alpha for LOC was 0.893. Cronbach Alpha should be or greater than 0.70 (Nunnally, 1978). The alpha values for all the subscales used for the study were found to be more than 0.70.
Table 1. Variables and scales
Variables |
Likert Scale |
Items |
Author |
Cronbach's Alpha |
Faculty Incivility |
Five Point |
12 |
Cortina et al., 2001 |
0.958 |
Learning Engagement |
Seven Point |
17 |
Schaufeli et al., 2002 |
0.861 |
Locus of Control |
Five Point |
24 |
Levenson, 1981 |
0.893 |
4.1 Common method bias
The model is free from of common method bias Common method bias as VIF values are less than 3.33 (Kock,2015).
Table 2. Variance Inflation Factor (VIF)
|
VIF |
FI -> LE |
1.231 |
LOC -> LE |
1.051 |
LOC x FI -> LE |
1.176 |
|
|
4.2 Measurement model
Measurement model evaluated construct’s validity and reliability. Item in model has a factor loading with minimum permissible value 0.50 or more (Hair et al., 2010). Loading more than 0.70 is preferred (Hair et al., 2019). Between 0.40 and 0.70 outer loadings should only be discarded if doing so raises the AVE or CR values above suggested level (Hair et al., 2017). Since the results for the construct were already below the suggested threshold, the item (LE7, Loading=0.173) has been deleted from the current study as it would have significantly decreased the composite reliability and AVE (see Table 3).
Cronbach's alpha and CR values for both are above permissible value of 0.70 (Wasko & Faraj, 2012). So, There is strong reliability if value is above 0.70 (Henseler et al., 2016). Since AVE was more than 0.500, convergent validity was determined to be satisfactory. Discriminant validity was established comparing correlations of latent variable with square root of AVE (Fornell & Larcker, 1981). Also, correlations' HTMT ratio is below 0.85 (Henseler et al., 2015) (see Table 3, 4 & 5).
Table 3. Measurement Model
Factors |
Indicators |
Loadings |
Alpha |
CR |
AVE |
VIF |
||||
Measurement Model Assessment at First Order |
||||||||||
Faculty Incivility |
FI1 |
0.813 |
0.958 |
0.963 |
0.686 |
2.735 |
||||
FI2 |
0.831 |
2.958 |
||||||||
FI3 |
0.833 |
3.139 |
||||||||
FI4 |
0.844 |
3.491 |
||||||||
FI5 |
0.841 |
3.442 |
||||||||
FI6 |
0.833 |
2.908 |
||||||||
FI7 |
0.714 |
2.252 |
||||||||
FI8 |
0.892 |
4.848 |
||||||||
FI9 |
0.815 |
3.222 |
||||||||
FI10 |
0.777 |
2.565 |
||||||||
FI11 |
0.861 |
3.606 |
||||||||
FI12 |
0.867 |
|
|
|
3.884 |
|||||
Vigor |
LE1 |
0.664 |
0.840 |
0.882 |
0.555 |
1.551 |
||||
LE2 |
0.705 |
1.68 |
||||||||
LE3 |
0.766 |
1.756 |
||||||||
LE4 |
0.758 |
1.988 |
||||||||
LE5 |
0.812 |
2.126 |
||||||||
LE6 |
0.756 |
1.685 |
||||||||
Dedication |
LE8 |
0.855 |
0.904 |
0.933 |
0.777 |
4.848 |
||||
LE9 |
0.914 |
3.222 |
||||||||
LE10 |
0.908 |
3.007 |
||||||||
LE11 |
0.846 |
2.225 |
||||||||
Absorption |
LE12 |
0.778 |
0.883 |
0.909 |
0.626 |
2.1 |
||||
LE13 |
0.836 |
2.477 |
||||||||
LE14 |
0.726 |
1.775 |
||||||||
LE15 |
0.751 |
1.962 |
||||||||
LE16 |
0.827 |
2.125 |
||||||||
LE17 |
0.822 |
1.972 |
||||||||
Measurement Model Assessment at Second Order |
||||||||||
Learning Engagement
Internal Locus of Control
External Locus of Control |
VI |
0.869 |
0.861
0.914 |
0.915
0.945 |
0.781
0.851 |
1.97 |
||||
DE |
0.922 |
2.593 |
||||||||
AB |
0.859 |
2.256 |
||||||||
IS
POS
CS |
0.899
0.929
0.939 |
2.887
3.592
3.187 |
||||||||
|
|
|
|
|
|
|
||||
Measurement Model Assessment at Third Order |
||||||||||
Locus of Control |
Internal
External |
0.963
0.936 |
0.893 |
0.948 |
0.902 |
2.86
2.86 |
||||
Source: (Survey Data SMART PLS4 Results)
CR= Composite Reliability, AVE= Average Variance Extracted, VIF= Variance Inflation Factor
Table 4. Cross Loadings
|
01. CI |
02. VI |
03. DE |
04. AB |
LOC |
CI1 |
0.813 |
-0.176 |
-0.275 |
-0.129 |
0.21 |
CI2 |
0.831 |
-0.136 |
-0.235 |
-0.078 |
0.171 |
CI3 |
0.833 |
-0.175 |
-0.244 |
-0.137 |
0.128 |
CI4 |
0.844 |
-0.117 |
-0.289 |
-0.096 |
0.188 |
CI5 |
0.841 |
-0.075 |
-0.25 |
-0.084 |
0.201 |
CI6 |
0.833 |
-0.165 |
-0.236 |
-0.091 |
0.195 |
CI7 |
0.714 |
-0.074 |
-0.127 |
-0.035 |
0.241 |
CI8 |
0.892 |
-0.158 |
-0.273 |
-0.12 |
0.197 |
CI9 |
0.815 |
-0.084 |
-0.169 |
-0.073 |
0.189 |
CI10 |
0.777 |
-0.094 |
-0.198 |
-0.104 |
0.153 |
CI11 |
0.861 |
-0.132 |
-0.277 |
-0.115 |
0.185 |
CI12 |
0.867 |
-0.173 |
-0.318 |
-0.14 |
0.141 |
LE1 |
-0.132 |
0.664 |
0.464 |
0.359 |
0.121 |
LE2 |
-0.101 |
0.705 |
0.47 |
0.419 |
0.106 |
LE3 |
-0.143 |
0.766 |
0.446 |
0.385 |
0.21 |
LE4 |
-0.056 |
0.758 |
0.418 |
0.469 |
0.211 |
LE5 |
-0.156 |
0.812 |
0.587 |
0.597 |
0.205 |
LE6 |
-0.131 |
0.756 |
0.638 |
0.583 |
0.218 |
LE8 |
-0.213 |
0.633 |
0.855 |
0.591 |
0.137 |
LE9 |
-0.303 |
0.638 |
0.914 |
0.666 |
0.145 |
LE10 |
-0.303 |
0.585 |
0.908 |
0.684 |
0.144 |
LE11 |
-0.229 |
0.556 |
0.846 |
0.695 |
0.152 |
LE12 |
-0.077 |
0.508 |
0.583 |
0.778 |
0.121 |
LE13 |
-0.094 |
0.476 |
0.583 |
0.836 |
0.171 |
LE14 |
0.005 |
0.381 |
0.468 |
0.726 |
0.189 |
LE15 |
0.05 |
0.467 |
0.493 |
0.751 |
0.19 |
LE16 |
-0.151 |
0.624 |
0.673 |
0.827 |
0.174 |
LE17 |
-0.212 |
0.532 |
0.677 |
0.822 |
0.163 |
IS |
0.176 |
0.208 |
0.11 |
0.158 |
0.899 |
CS |
0.213 |
0.256 |
0.196 |
0.238 |
0.939 |
POS |
0.203 |
0.217 |
0.131 |
0.17 |
0.929 |
Source: (Survey Data SMART PLS4 Results)
Table 5. Discriminant Validity by Fornell-Larker and HTMT
|
CI |
VI |
DE |
AB |
LOC |
CI |
VI |
DE |
AB |
LOC |
CI |
0.828 |
|
|
|
|
|
|
|
|
|
VI |
-0.164 |
0.745 |
|
|
|
0.171 |
|
|
|
|
DE |
-0.302 |
0.683 |
0.881 |
|
|
0.308 |
0.777 |
|
|
|
AB |
-0.127 |
0.639 |
0.749 |
0.791 |
|
0.135 |
0.717 |
0.816 |
|
|
LOC |
0.211 |
0.243 |
0.153 |
0.201 |
0.950 |
0.229 |
0.267 |
0.167 |
0.224 |
|
Source: (Survey Data SMART PLS4 Results)
4.3 Structural model
It depicts paths hypothesized in conceptual model. Structural model is based on R2, Q2 and significance of paths.
Source: (Survey Data SMART PLS4 Results)
Table 6. Direct Relationships
Hypotheses |
Path coefficients |
SD |
t values |
p values |
Decision |
|
H1: FI -> LE |
-0.217 |
0.060 |
3.608 |
0.000 |
Accepted |
|
H2: LOC -> LE |
0.281 |
0.062 |
4.537 |
0.000 |
Accepted |
|
H3: LOC x FI -> LE |
-0.159 |
0.069 |
2.307 |
0.021 |
Accepted |
|
R2 LE= 0.156
|
Q2 LE=0.124
|
|
|
|
|
|
Abbreviations: BI-bias corrected confidence interval; FI- faculty incivility; LOC- locus of control; LE- learning engagement
The goodness of model is established by R2 value (Peñalver et al., 2018). Value of R2 ought to be equal or more than 0.1 (Falk & Miller, 1992). R2 values are greater than 0.1, as indicated in Table 6. Thus, it has established predictive capacity. Moreover, Q2 proves the endogenous constructs' predictive significance. Model predictive significance is shown by a Q2 above 0. Hypotheses testing is summarized in Table 6.
LE was significantly impacted by FI (β = -0.217, t=3.608, p < .05), thereby supporting H1. Moreover, significant association was established in LOC and LE (β = 0.281, t=2.307, p < .05), therefore, supporting H2. Also, LOC moderates FI and LE relationship (β = -0.159, t=2.307, p < .05), therefore supporting H3.
Figure 2. Moderation
Source: (Derived from Jeremy Dawson’s Excel Sheet)
Where, FI=Faculty Incivility, LOC= Locus of Control, LE= Learning Engagement
At low locus of control there is highest impact of faculty incivility on learning engagement. However high LOC dampens the faculty incivility and learning engagement relationship.
Three hypotheses were framed and tested. All the hypotheses were supported. The study results showed that faculty incivility negatively impacts learning engagement. The study examined whether faculty incivility impacts learning engagement or not, and further LOC moderates this relationship or not. Study also examined the relationship between LOC and learning engagement. Results showed that faculty incivility impacts learning engagement negatively. There was a significant association established between LOC and learning engagement. Moderation results showed that at low locus of control there is more faculty incivility and it impacts their learning engagement. It shows students with high LOC are able to cope up with faculty incivility and there was no impact of it on their learning. However high LOC dampens faculty incivility and learning engagement relationship.
Implications of the study
This study made some useful recommendations for fostering civility in classroom, such as how to successfully respond to and handle uncivil behavior. Incivility has been recognized as a real issue in education. The educators must understand that incivility in the classroom negatively impacts student's capacity to learn. In addition, there must be strict disciplinary measures that give teachers and students a way to handle uncivil behavior in the classroom. This approach consists of having open conversations, promoting mutual respect, and enforcing strict laws against rude conduct.
Limitations
Despite its contributions and ramifications, this research has certain limitations also. In this study, respondents were students only. This study only identified uncivil behavior experienced from the perspective of students. Teacher’s perspective might be different. Further studies needed to examine teacher’s perspective also. The scope of the study only included public and private colleges of Chandigarh, India. Further studies can explore other geographical areas with large sample size. Further, longitudinal study on these variables might give more clear results.