Determinants of academic stress amongst engineering students

Abstract

BACKGROUND:

Academic stress is one of the active research domains in engineering institutions. As it can result in ill health of students, it is important to monitor the level of academic stress in students.

OBJECTIVE:

The objective of this study was to determine the academic stress factors in the engineering universities in Punjab state of India. This study also aimed to check the determinants of academic stress.

METHODS:

The data was collected through a questionnaire survey conducted on engineering students of two different universities. The collected data out of 400 surveys is subjected to factor analysis and ANOVA.

RESULTS:

Factor analysis revealed various factors that influence the academic stress. It was also found that the academic stress in students is most influenced by Engineering Streams and Nature of Universities.

CONCLUSIONS:

The study projected the effects of Academic Stress on Gender, Age, Engineering Streams, Nature of Universities.

Keywords

Gender age engineering streams nature of universities questionnaire

1 Introduction

Stress embodies the experience of emotions or bodily strain. Stress may be experienced in two ways i.e. emotional or physical. Emotional stress tends to be found there where the situations perceived by people are tough and intriguing. So far, physical stress is concerned, is the reaction of the body due to various triggers. The pain experienced after surgery is an example of physical stress. Physical stress frequently contributes to emotional stress, which leads to physical stress (e.g., cramps in stomach). There is a participation of ‘control’ and ‘tension reduction’ in stress management which takes place in stressful situations by making emotional and physical changes. Stress affected students may resort to take drugs and alcohol making them socially isolated and self-harm [1, 2]. In order to know how much change takes place, it is important to know the level of stress and the dire need for attaining change. These thoughts were reverberated by Bernstein et al. [3] and Auerbach and Grambling [4].

2 Stress

The word “stress” was first introduced in the fields by distinguished endocrinologist, Hans Selye, and was popularly used in the seventeenth century and derived from Latin word to mean “Hardship”, “Strait”, “Adversity” or “Affliction.” Selye suggested that stress is simply the rate of wear and tear in the body [5]. His concept of stress at that time was a physiological one and throughout his life the psychological component of the phenomenon of stress was not so much ignored by him, as placed in a secondary, and to some degree, less important place in the total picture of human stress.

As per to the transactional model, when the person comprehends an external demand as broadening his or her capability to deal with, stress is believed to take place. Thus, whether stress is experienced by an individual is determined by personal valuation of the demand nature, resources available and human skills, and presumed results. Recognition and dealing with individual differences are the goals of this approach [6]. Academic stress has been studied extensively as an important factor in college student adjustment [7, 8]. In general, college-related stress has been found to be inversely related to academic performance among traditional undergraduates [9 –11].

Thus, it is important to examine the stress level of engineering students, the reasons for its increase and focus on methods to manage stress. Mechanisms that explains why students perform badly under stress include “hyper vigilance” (excessive alertness to a stressful situation resulting in panic - for example, over studying for an exam) and “premature closure” (quickly choosing a solution to end a stressful situation–for example, rushing through an exam).

Thus, this has attracted the attention of many researchers to examine the factors leading to stress among engineering students.

2.1 Causes of stress

The various causes of stress are explained in the following sections.

2.2 Academic stress

Engineering curriculum is associated with continuous evaluation system, focusing on assignments, quizzes, presentations, projects along with regular written semester exams. Suri & Sharma found that there is a significant relationship between discipline and e-learning attitude of students as depicted by previous researches [12]. These researches lay emphasis on the role of department in learning and satisfaction level of students. Academic institutions have priorities and quite different from non-academic activities. Therefore, one would experience the difference in symptoms, causes, and consequences of stress. Stress is very common in college going students. Their struggle for survival academically, professionally makes them to lead stressful life. They have work hard to achieve their goals. There is a lot of pressure on the students to learn more than past generations and how they learn it. They experience stress from regular academic work, moreover it is too difficult for them to manage stress generated from these workloads and challenging tasks.

Academic stressors include overload of assignments, peer competition, poor relationships with teachers [13]; grade competition [14]; inadequate resources to perform academic work [15] and fear of academic failure [16].

Singh & Singh highlighted that there were significant differences among school, college and university level sports persons on almost all traits of personality, except dominance [17]. Jacobs et al. suggested that the Wii Fit exercise should be considered by occupational therapists as a potential occupation of weight control in undergraduate students to improve performance [18]. Wii Fit exercise uses a unique platform peripheral called the Wii Balance Board, on which the player stands during exercise. This features yoga, strength training, aerobics, and balance games. For the present study, the components of academic activity considered include: curriculum and instruction; team work; assessment and placement. Ramayah, Yeap & Ignatius revealed that extrinsic motivation, reciprocal relationships, sense of self-worth and subjective norm are vital determinants of an academician’s attitude towards knowledge sharing [19]. The present study attempts to find out which of these aspects are creating stress among management students. The components of academics taken include curriculum and instruction, team work, assessment and placement.

2.3 Personal stress

Personal stress is due to anxiety among the students. Such stress can be due to personal accountabilities at home, in relationships, and at workplace. Family “well-being” includes steady and affectionate relationships, satisfaction in domestic responsibilities, child fosterage, and growth of family members with thorough mental and physical health. Any factor that distorts this leads to personal stress.

2.4 Financial stress

Financial stress is due to fairly extensive reasons. High career financial aspirations may cause financial stress. Peer comparisons of placement offers and nature of job, the reputation of organizations offering placements matter much in financial stress. However, the present research covers only academic stress.

3 Population and sampling

The entire research activity was segregated into two phases of research:

Phase 1 (Selection of Population)

The engineering students as population were selected as while teaching it was observed that the students in engineering have to undergo heavy academic stress.

Sample size determination

The present study has covered a total of four engineering streams from two different universities. As per calculations the minimum sample size was 246 so 400 sample population was used.

Initial study was conducted on 400 Engineering students (who volunteered), from four streams i.e. Civil, Computer, Electronics and Communication and Mechanical Engineering in the age group of 18 to 22 years. They were selected from two state universities of engineering (one private and other government as mentioned above). The details are shown through Tables 1 and 2. These two universities are rated high in state and national rankings.

Table 1
Details of the subjects

Type of university Trade Females Males Total

Government University of Engineering Civil Engineering 6 44 50

Computer Engineering 28 22 50

Electronics and Communication Engineering 18 32 50

Mechanical Engineering 2 48 50

Private University of Engineering Civil Engineering 2 48 50

Computer Engineering 22 28 50

Electronics and Communication Engineering 26 24 50

Mechanical Engineering zero 50 50

104 296 400

Type of university	Trade	Females	Males	Total
Government University of Engineering	Civil Engineering	6	44	50
	Computer Engineering	28	22	50
	Electronics and Communication Engineering	18	32	50
	Mechanical Engineering	2	48	50
Private University of Engineering	Civil Engineering	2	48	50
	Computer Engineering	22	28	50
	Electronics and Communication Engineering	26	24	50
	Mechanical Engineering	zero	50	50
		104	296	400

Phase 2 (Selection of Sample)

The stratified random sampling technique was used to choose the respondents. The students were short-listed based on their self-observation reported, as well in the interview about exhibiting stress.

The group of 400 students were classified on basis of age <20 years (84),=20 years (134) and > 20 years (182), gender males (296) and females (104), type of family nuclear (300) and joint (100)Religion Hindu (291), Sikh (108) and others (1).

After gaining permission from ethical committee for conducting this study, the respondents from both the groups were also requested to sign a consent form.

3.1 Demographic profile of respondents

Demographic characteristics of respondents un-dertaken in the present study were gender, age, engineering streams and nature of university vise distribution of respondents. Table 2 represents the demographic characteristics of the respondents.

Table 2
Demographic characteristics of respondents

Demographic characteristics Classification No. Percentage %

Age <20 years 84 21

=20 years 134 33.5

>20 years 182 45.5

Gender Male 296 74

Female 104 26

Engineering stream Civil Engineering 50 + 50 25

Computer engineering 50 + 50 25

Electronics and Communication Engineering 50 + 50 25

Mechanical Engineering 50 + 50 25

Nature of University Thapar University (Private) 200 50

Punjabi University (Government) 200 50

Demographic characteristics	Classification	No.	Percentage %
Age	<20 years	84	21
	=20 years	134	33.5
	>20 years	182	45.5
Gender	Male	296	74
	Female	104	26
Engineering stream	Civil Engineering	50 + 50	25
	Computer engineering	50 + 50	25
	Electronics and Communication Engineering	50 + 50	25
	Mechanical Engineering	50 + 50	25
Nature of University	Thapar University (Private)	200	50
	Punjabi University (Government)	200	50

4 Survey instrument

For the short-listed students, the Stress level was assessed with the help of a self structured questionnaire. Questionnaire comprised of personal data form, which includes the basic information of the respondents such as age; stream; university; gender; religion; and type of family. There were 34 questions on Academic Stress (Appendix I). Respenose method was through Rating each factor on Likert’s 5 point scale by ticking (√) on one of the five boxes where 1 meant least priority and 5 was highest priority.

4.1 Reliability and validity

A pilot study was conducted for pre-testing of questionnaire on a group of 54 respondents for checking the reliability and validity of the questionnaire. Valuable suggestions of academicians and researchers were incorporated and some of questions were reframed for satisfying the research objectives. The details of the final questionnaire are provided in Appendix I. The questionnaire was validated by the academicians and researchers. It possessed a good validation score (3.7 on a scale of 5). The changes suggested by experts were incorporated in the questionnaire. Some questions were deleted and at same time, some were rephrased. Reliability applies to a measure when similar results were obtained over time and across situations. The details of reliability of different sections have been reported through Table 3.

Table 3
Reliability statistics

S. no. Items Factor name Cronbach alpha

1. 34 Academic stress 0.913

S. no.	Items	Factor name	Cronbach alpha
1.	34	Academic stress	0.913

Hence the questionnaire was found to be valid and reliable to be used for further analysis.

5 Hypotheses development

Effort was made to compare academic stress based on gender, age, engineering streams, nature of university. Accordingly, the following hypotheses have been framed:

H_1a: There is a significant difference in the academic stress based on gender.

H_text1b: There is a significant difference in the academic stress based on age.

H_1c: There is a significant difference in the academic stress based on engineering streams.

H_1d: There is a significant difference in the academic stress based on nature of university.

6 Results

ANOVA was used to test the hypotheses and for intergroup comparisons post-hoc Tukey was used.

The results of factor analysis as shown through Table 4 which highlighted that based on factor analysis seven factors emerged. These seven factors explained 51.126 % of variation. The first factor viz. AS-1 Examination Stressors had Eigen Value 9.881 and explained 9.881 % of variation. The first two items, viz. i.) AS19: Concern about results after examinations and ii.) AS17: Examination syllabus is too heavy in some subjects loaded heavily on first factor signifying higher importance than other factors. The composite reliability is 0.845 and Average variance extracted is 0.501. This suggests high construct reliability for this factor.

Table 4
Factor analysis for identification of factors affecting academic stress

Factor name Items Factor loading Eigenvalue % of variance C AVE CR

AS-1: Examination Stressors AS19: Concern about results after examinations 0.752 9.881 9.881 9.881 0.501 0.845

AS17: Examination syllabus is too heavy in some subjects 0.723

AS16: Exam papers are tough 0.717

AS20: Tendency to ‘day-dream’ when trying to study 0.712

AS21: Study periods are often too short for me to get ‘warmed up’ and concentrated 0.620

AS18: Worrying about the examinations 0.608

AS-2: Inadequate Teaching Interaction AS10: Lack of opportunity to meet teachers 0.683 8.839 8.839 18.721 0.529 0.769

AS11: Slow in getting along with the curriculum 0.673

AS7: Inadequate query handling by teacher 0.667

AS14: Lack of case studies to support teaching and learning 0.500

AS31: Less placement opportunity provided by the institute 0.500

AS-3: Lack of Outreach Opportunities AS29: Inadequate lab space 0.724 8.751 8.751 27.471 0.546 0.774

AS27: Not able to grasp the subject matter 0.673

AS34: Unfavorable location of placement 0.654

AS26: Unable to discuss academic failures with parents 0.603

AS-4: Inadequate Learning Orientation AS2: Lack of concentration during study hours 0.698 7.616 7.616 35.087 0.514 0.730

AS3: Difficulty in memorizing and retention of lectures 0.672

AS1: Lack of interest in some subjects 0.588

AS9: Lack of confidence in the class 0.536

AS-5: Lack of Interest AS24: Enjoyment of loafing (spending time ideally), ‘bull- seasons’ (amusing and illogical use of words) interferes with my study 0.773 6.812 6.812 41.899 0.501 0.716

AS23: Too tired, sleepy and restless to study efficiently 0.693

AS25: Dislike of certain courses and teachers interferes with getting good results 0.552

AS-6: Problems of Interaction AS22: Missing important points while taking notes in class 0.622 4.878 4.878 46.777 0.403 0.508

AS15: Lack of interactive sessions in class 0.546

AS-7: Poor Time Management i. AS12: Unable to complete the assignment in time 0.703 4.349 4.349 51.126 0.405 0.562

ii. AS6: Personal hesitation to ask questions in class 0.544

Factor name	Items	Factor loading	Eigenvalue	% of variance	C	AVE	CR
AS-1: Examination Stressors	AS19: Concern about results after examinations	0.752	9.881	9.881	9.881	0.501	0.845
	AS17: Examination syllabus is too heavy in some subjects	0.723
	AS16: Exam papers are tough	0.717
	AS20: Tendency to ‘day-dream’ when trying to study	0.712
	AS21: Study periods are often too short for me to get ‘warmed up’ and concentrated	0.620
	AS18: Worrying about the examinations	0.608
AS-2: Inadequate Teaching Interaction	AS10: Lack of opportunity to meet teachers	0.683	8.839	8.839	18.721	0.529	0.769
	AS11: Slow in getting along with the curriculum	0.673
	AS7: Inadequate query handling by teacher	0.667
	AS14: Lack of case studies to support teaching and learning	0.500
	AS31: Less placement opportunity provided by the institute	0.500
AS-3: Lack of Outreach Opportunities	AS29: Inadequate lab space	0.724	8.751	8.751	27.471	0.546	0.774
	AS27: Not able to grasp the subject matter	0.673
	AS34: Unfavorable location of placement	0.654
	AS26: Unable to discuss academic failures with parents	0.603
AS-4: Inadequate Learning Orientation	AS2: Lack of concentration during study hours	0.698	7.616	7.616	35.087	0.514	0.730
	AS3: Difficulty in memorizing and retention of lectures	0.672
	AS1: Lack of interest in some subjects	0.588
	AS9: Lack of confidence in the class	0.536
AS-5: Lack of Interest	AS24: Enjoyment of loafing (spending time ideally), ‘bull- seasons’ (amusing and illogical use of words) interferes with my study	0.773	6.812	6.812	41.899	0.501	0.716
	AS23: Too tired, sleepy and restless to study efficiently	0.693
	AS25: Dislike of certain courses and teachers interferes with getting good results	0.552
AS-6: Problems of Interaction	AS22: Missing important points while taking notes in class	0.622	4.878	4.878	46.777	0.403	0.508
	AS15: Lack of interactive sessions in class	0.546
AS-7: Poor Time Management	i. AS12: Unable to complete the assignment in time	0.703	4.349	4.349	51.126	0.405	0.562
	ii. AS6: Personal hesitation to ask questions in class	0.544

C: Cumulative variance; AVE: Average variance extracted; CR: Composite reliability.

The second factor AS-2 Inadequate Teaching Interaction explained 8.839 % of variation. i.) AS10: Lack of opportunity to meet teachers and ii.) AS11: Slow in getting along with the curriculum loaded high on this factor. Average variance extracted is 0.529 and composite reliability is 0.769, well above acceptable range.

The next factor viz. AS-3 Lack of Outreach opportunities explained 8.751 % of Variation. The first two items, viz. i.) AS29: Inadequate lab space and ii.) AS27: Not able to grasp the subject matter loaded high on this factor. The Composite reliability is 0.774 and Average variance extracted is 0.546.

The fourth factor is AS-4 Inadequate Learning Orientation. It had four items and item i) AS2: Lack of concentration during study hours and Item ii) AS3: Difficulty in memorizing and retention of lectures are important. The composite reliability is 0.730 and average variance extracted is 0.514 are both in acceptable range.

The fifth factor is AS-5 Lack of Interest. It has three items. The First item viz. i.) AS24: Enjoyment of loafing (spending time ideally), ‘bull- seasons’ (amusing and illogical use of words) interferes with my study had highest loading of 0.773 followed by ii.) AS23: Too tired, sleepy and restless to study efficiently with loading of 0.693. This factor explains 6.812 % of Variance. The average variance extracted is 0.501 and Composite reliability is 0.716.

AS-6: Problems of Interaction had two items only viz. i.) AS22: Missing important points while taking notes in class with item loading of 0.622; and ii.AS15: Lack of interactive sessions in class. The average variance extracted is 0.403 and Composite reliability is.508. The values are comparatively low, but are important and hence included for further examination.

AS-7: Poor Time Management also had two items, viz. i.) AS12: Unable to complete the assignment in time has loading of 0.703 and ii.) AS6: Personal hesitation to ask questions in class having a lower loading of 0.544. The average variance extracted is 0.405 and composite reliability is 0.562. The values are comparatively low, but are important for further examination, hence retained.

ANOVA results (Table 5) reflect that there is a significant difference in perception of respondents in only one of the seven factors influencing academic stress based on gender groups (male and female) considered for analysis. This is: AS-4: Inadequate learning orientation but for other six factors i.e. AS-1: Examination stressors, AS-2: Inadequate teaching interaction, AS-3: Lack of outreach opportunities, AS-5: Lack of interest, AS-6: Problems of interaction, AS-7: Poor time management, the results didn’t reflect significant difference on academic stress with respect to gender grouping. This shows there is a similarity of perception of the respondents on the academic stress based on gender grouping.

Table 5

ANOVA results factors influencing academic stress based on gender

		Sum of squares	df	Mean square	F	Sig.
AS-1 Examination Stressors	Between groups	0.213	1	0.213	0.280	0.597
	Within groups	302.598	398	0.760
	Total	302.811	399
AS-2 Inadequate Teaching Interaction	Between groups	0.220	1	0.220	0.343	0.558
	Within groups	255.311	398	0.641
	Total	255.531	399
AS-3 Lack of Outreach Opportunities	Between groups	0.811	1	0.811	1.127	0.289
	Within groups	286.298	398	0.719
	Total	287.109	399
AS-4 Inadequate Learning Orientation	Between groups	2.988	1	2.988	4.183	0.041^*
	Within groups	284.343	398	0.714
	Total	287.331	399
AS-5 Lack of Interest	Between groups	0.014	1	0.014	0.020	0.887
	Within groups	284.891	398	0.716
	Total	284.905	399
AS-6 Problems of Interaction	Between groups	0.406	1	0.406	0.459	0.499
	Within groups	352.188	398	0.885
	Total	352.594	399
AS-7 Poor Time Management	Between groups	0.152	1	0.152	0.147	0.702
	Within groups	411.626	398	1.034
	Total	411.777	399

^***p < 0.001; ^**p < 0.01; ^*p < 0.05 [df: Degrees of freedom; F: F ratio; Sig: Significance].

Thus, the hypothesis H_1a: there is a significant difference in the academic stress with respect to the different gender groups has been rejected.

ANOVA results shown through Table 6 reflect that there is a significant difference in only one of the seven factors influencing academic stress based on age groups considered for analysis. This is: AS-1: Examination stressors, but for AS-2: Inadequate teaching interaction, AS-3: Lack of outreach opportunities, AS-4: Inadequate learning orientation, AS-5: Lack of interest, AS-6: Problems of interaction and AS-7: Poor time management, the results didn’t reflect significant difference on academic stress with respect to age grouping. This shows there is a similarity of perception of the respondents on the academic stress based on age grouping.

Table 6

ANOVA results factors influencing academic stress based on age

		Sum of squares	df	Mean square	F	Sig.
AS-1 Examination Stressors	Between groups	10.949	2	5.475	7.447	0.001^**
	Within groups	291.861	397	0.735
	Total	302.811	399
AS-2 Inadequate Teaching Interaction	Between groups	0.991	2	0.496	0.773	0.462
	Within groups	254.540	397	0.641
	Total	255.531	399
AS-3 Lack of Outreach Opportunities	Between groups	2.210	2	1.105	1.540	0.216
	Within groups	284.899	397	0.718
	Total	287.109	399
AS-4 Inadequate Learning Orientation	Between groups	2.265	2	1.132	1.577	0.208
	Within groups	285.066	397	0.718
	Total	287.331	399
AS-5 Lack of Interest	Between groups	0.646	2	0.323	0.451	0.637
	Within groups	284.259	397	0.716
	Total	284.905	399
AS-6 Problems of Interaction	Between groups	1.377	2	0.688	0.778	0.460
	Within groups	351.218	397	0.885
	Total	352.594	399
AS-7 Poor Time Management	Between groups	0.367	2	0.184	0.177	0.838
	Within groups	411.410	397	1.036
	Total	411.778	399

^***p < 0.001; ^**p < 0.01; ^*p < 0.05. [df: Degrees of freedom; F: F ratio; Sig: Significance].

Post-hoc Tukey was conducted to have clarity on the differences. The results are shown through Table 7. In case of AS-1: Examination Stressors, there was a significant difference between all 3 age groups i.e.<20 and = 20 age group and >20 and <20 age group.

Thus, the hypothesis H_1b: there is a significant difference in the academic stress with respect to the different age groups has been rejected.

Table 7

Tukey HSD results for academic stress factors and different age groups

Dependent variable	(I) Age	(J) Age	Mean difference (I-J)	Std. error	Sig.	95% Confidence interval
						Lower bound	Upper bound
AS-1: Examination Stressors	<20	=20	0.463^*	0.120	0.000^***	0.18	0.75
		>20	0.299^*	0.114	0.024^*	0.03	0.57
	=20	<20	–0.463^*	0.120	0.000^***	–0.75	–0.18
		>20	–0.164	0.097	0.212	–0.39	0.06
	>20	<20	–0.299^*	0.114	0.024^*	–0.57	–0.03
		=20	0.164	0.097	0.212	–0.06	0.39
AS-2: Inadequate Teaching Interaction	<20	=20	–0.058	0.112	0.863	–0.32	0.21
		>20	0.055	0.106	0.864	–0.20	0.31
	=20	<20	0.058	0.112	0.863	–0.21	0.32
		>20	0.113	0.091	0.429	–0.10	0.33
	>20	<20	–0.055	0.106	0.864	–0.31	0.20
		=20	–0.113	0.091	0.429	–0.33	0.10
AS-3: Lack of Outreach Opportunities	<20	=20	0.167	0.119	0.337	–0.11	0.45
		>20	0.193	0.113	0.201	–0.07	0.46
	=20	<20	–0.167	0.119	0.337	–0.45	0.11
		>20	0.026	0.096	0.961	–0.20	0.25
	>20	<20	–0.193	0.113	0.201	–0.46	0.07
		=20	–0.026	0.096	0.961	–0.25	0.20
AS-4: Inadequate Learning Orientation	<20	=20	0.200	0.119	0.211	–0.08	0.48
		>20	0.078	0.113	0.767	–0.19	0.34
	=20	<20	–0.200	0.119	0.211	–0.48	0.08
		>20	–0.122	0.096	0.412	–0.35	0.10
	>20	<20	–0.078	0.113	0.767	–0.34	0.19
		=20	0.122	0.096	0.412	–0.10	0.35
AS-5: Lack of Interest	<20	=20	0.057	0.118	0.881	–0.22	0.34
		>20	–0.034	0.112	0.950	–0.30	0.23
	=20	<20	–0.057	0.118	0.881	–0.34	0.22
		>20	–0.091	0.096	0.609	–0.32	0.13
	>20	<20	0.034	0.112	0.950	–0.23	0.30
		=20	0.091	0.096	0.609	–0.13	0.32
AS-6: Problems of Interaction	<20	=20	0.057	0.132	0.903	–0.25	0.37
		>20	0.146	0.125	0.474	–0.15	0.44
	=20	<20	–0.057	0.132	0.903	–0.37	0.25
		>20	0.089	0.107	0.681	–0.16	0.34
	>20	<20	–0.146	0.125	0.474	–0.44	0.15
		=20	–0.089	0.107	0.681	–0.34	0.16
AS-7: Poor Time Management	<20	=20	0.032	0.143	0.973	–0.30	0.37
		>20	0.076	0.135	0.840	–0.24	0.39
	=20	<20	–0.032	0.143	0.973	–0.37	0.30
		>20	0.044	0.115	0.922	–0.23	0.32
	>20	<20	–0.076	0.135	0.840	–0.39	0.24
		=20	–0.044	0.115	0.922	–0.32	0.23

^*The mean difference is significant at the 0.05 level. ^***p < 0.001; ^**p < 0.01; ^*p < 0.05 Sig: Significance.

ANOVA results in Table 8 reflect that there is a significant difference in perception of respondents in four of the seven factors influencing academic stress based on engineering streams have been considered for analysis. This is: AS-1: Examination stressors, AS-2: Inadequate teaching interaction, AS-4: Inadequate learning orientation, AS-6: Problems of interaction, but for other three factors i.e. AS-3: Lack of outreach opportunities, AS-5: Lack of interest and AS-7: Poor time management, the results didn’t reflect significant difference on academic stress with respect to engineering stream grouping. This shows for these three factors AS-3: Lack of outreach opportunities, AS-5: Lack of interest and AS-7: Poor time management, there is a similarity of perception of the respondents on the academic stress based on engineering streams grouping.

Table 8

ANOVA results for factors influencing academic stress based on engineering streams

		Sum of squares	df	Mean square	F	Sig.
AS-1: Examination Stressors	Between groups	19.869	3	6.623	9.269	0.000^***
	Within groups	282.942	396	0.714
	Total	302.811	399
AS-2: Inadequate Teaching Interaction	Between groups	8.069	3	2.690	4.304	0.005^**
	Within groups	247.462	396	0.625
	Total	255.531	399
AS-3: Lack of Outreach Opportunities	Between groups	2.321	3	0.774	1.076	0.359
	Within groups	284.789	396	0.719
	Total	287.109	399
AS-4: Inadequate Learning Orientation	Between groups	11.198	3	3.733	5.353	0.001^**
	Within groups	276.133	396	0.697
	Total	287.331	399
AS-5: Lack of Interest	Between groups	3.410	3	1.137	1.599	0.189
	Within groups	281.495	396	0.711
	Total	284.905	399
AS-6: Problems of Interaction	Between groups	9.157	3	3.052	3.519	0.015^*
	Within groups	343.438	396	0.867
	Total	352.594	399
AS-7: Poor Time Management	Between groups	6.927	3	2.309	2.259	0.081
	Within groups	404.850	396	1.022
	Total	411.778	399

^***p < 0.001; ^**p < 0.01; ^*p < 0.05. [df: Degrees of freedom; F: F ratio; Sig: Significance].

Post-hoc Tukey was conducted to have clarity on the differences. The results are shown through Table 9. In case of AS-1: Examination stressors, significant difference was found between civil and computer, civil and electronics and communication, civil and mechanical. In AS-2: Inadequate teaching interaction, the difference was significant between civil and electronics and communication, computer and electronics and communication In AS-4: Inadequate learning orientation, there was a significant difference between civil and electronics and communication, mechanical and electronics and communication. In AS-6: Problems of Interaction, significant difference was found between civil and computer. Thus, the hypothesis H_1c: there is a significant difference in the academic stress with respect to the different engineering stream groups has been partially accepted.

Table 9

Tukey HSD results for academic stress factors and different engineering streams groups

Dependent variable	(I) Stream	(J) Stream	Mean difference (I-J)	Std. error	Sig.	95% Confidence interval
						Lower bound	Upper bound
AS-1: Examination Stressors	Civil	Computer	–0.343^*	0.120	0.022^*	–0.65	–0.03
		Electronics and Communication	–0.629^*	0.120	0.000^***	–0.94	–0.32
		Mechanical	–0.338^*	0.120	0.025^*	–0.65	–0.03
	Computer	Civil	0.343^*	0.120	0.022^*	0.03	0.65
		Electronics and Communication	–0.286	0.120	0.080	–0.59	0.02
		Mechanical	0.005	0.120	1.000	–0.30	0.31
	Electronics and Communication	Civil	0.629^*	0.120	0.000^***	0.32	0.94
		Computer	0.286	0.120	0.080	–0.02	0.59
		Mechanical	0.291	0.120	0.072	–0.02	0.60
	Mechanical	Civil	0.338^*	0.120	0.025^*	0.03	0.65
		Computer	–0.005	0.120	1.000	–0.31	0.30
		Electronics and Communication	–0.291	0.120	0.072	–0.60	0.02
AS-2: Inadequate Teaching Interaction	Civil	Computer	–0.010	0.112	1.000	–0.30	0.28
		Electronics and Communication	–0.336^*	0.112	0.015^*	–0.62	–0.05
		Mechanical	–0.216	0.112	0.216	–0.50	0.07
	Computer	Civil	0.010	0.112	1.000	–0.28	0.30
		Electronics and Communication	–0.326^*	0.112	0.020^*	–0.61	–0.04
		Mechanical	–0.206	0.112	0.255	–0.49	0.08
	Electronics and Communication	Civil	0.336^*	0.112	0.015^*	0.05	0.62
		Computer	0.326^*	0.112	0.020^*	0.04	0.61
		Mechanical	0.120	0.112	0.706	–0.17	0.41
	Mechanical	Civil	0.216	0.112	0.216	–0.07	0.50
		Computer	0.206	0.112	0.255	–0.08	0.49
		Electronics and Communication	–0.120	0.112	0.706	–0.41	0.17
AS-3: Lack of Outreach Opportunities	Civil	Computer	–0.092	0.120	0.867	–0.40	0.22
		Electronics and Communication	–0.163	0.120	0.528	–0.47	0.15
		Mechanical	–0.200	0.120	0.342	–0.51	0.11
	Computer	Civil	0.092	0.120	0.867	–0.22	0.40
		Electronics and Communication	–0.070	0.120	0.937	–0.38	0.24
		Mechanical	–0.107	0.120	0.807	–0.42	0.20
	Electronics and Communication	Civil	0.163	0.120	0.528	–0.15	0.47
		Computer	0.070	0.120	0.937	–0.24	0.38
		Mechanical	–0.037	0.120	0.989	–0.35	0.27
	Mechanical	Civil	0.200	0.120	0.342	–0.11	0.51
		Computer	0.107	0.120	0.807	–0.20	0.42
		Electronics and Communication	0.037	0.120	0.989	–0.27	0.35
AS-4: Inadequate Learning Orientation	Civil	Computer	–0.270	0.118	0.103	–0.57	0.03
		Electronics and Communication	–0.375^*	0.118	0.009^**	–0.68	–0.07
		Mechanical	0.007	0.118	1.000	–0.30	0.31
	Computer	Civil	0.270	0.118	0.103	–0.03	0.57
		Electronics and Communication	–0.105	0.118	0.811	–0.41	0.20
		Mechanical	0.277	0.118	0.089	–0.03	0.58
	Electronics and Communication	Civil	0.375^*	0.118	0.009	0.07	0.68
		Computer	0.105	0.118	0.811	–0.20	0.41
		Mechanical	0.382^*	0.118	0.007	0.08	0.69
	Mechanical	Civil	–0.007	0.118	1.000	–0.31	0.30
		Computer	–0.277	0.118	0.089	–0.58	0.03
		Electronics and Communication	–0.382^*	0.118	0.007	–0.69	–0.08
AS-5: Lack of Interest	Civil	Computer	–0.050	0.119	0.976	–0.36	0.26
		Electronics and Communication	–0.163	0.119	0.522	–0.47	0.14
		Mechanical	0.093	0.119	0.862	–0.21	0.40
	Computer	Civil	0.050	0.119	0.976	–0.26	0.36
		Electronics and Communication	–0.113	0.119	0.779	–0.42	0.19
		Mechanical	0.143	0.119	0.628	–0.16	0.45
	Electronics and Communication	Civil	0.163	0.119	0.522	–0.14	0.47
		Computer	0.113	0.119	0.779	–0.19	0.42
		Mechanical	0.256	0.119	0.140	–0.05	0.56
	Mechanical	Civil	–0.093	0.119	0.862	–0.40	0.21
		Computer	–0.143	0.119	0.628	–0.45	0.16
		Electronics and Communication	–0.256	0.119	0.140	–0.56	0.05
AS-6: Problems of Interaction	Civil	Computer	–0.380^*	0.132	0.021^*	–0.72	–0.04
		Electronics and Communication	–0.330	0.132	0.061	–0.67	0.01
		Mechanical	–0.145	0.132	0.689	–0.48	0.19
	Computer	Civil	0.380^*	0.132	0.021^*	0.04	0.72
		Electronics and Communication	0.050	0.132	0.981	–0.29	0.39
		Mechanical	0.235	0.132	0.282	–0.10	0.57
	Electronics and Communication	Civil	0.330	0.132	0.061	–0.01	0.67
		Computer	–0.050	0.132	0.981	–0.39	0.29
		Mechanical	0.185	0.132	0.497	–0.15	0.52
	Mechanical	Civil	0.145	0.132	0.689	–0.19	0.48
		Computer	–0.235	0.132	0.282	–0.57	0.10
		Electronics and Communication	–0.185	0.132	0.497	–0.52	0.15
AS-7: Poor Time Management	Civil	Computer	–0.050	0.143	0.985	–0.42	0.32
		Electronics and Communication	–0.340	0.143	0.083	–0.71	0.03
		Mechanical	–0.180	0.143	0.590	–0.55	0.19
	Computer	Civil	0.050	0.143	0.985	–0.32	0.42
		Electronics and Communication	–0.290	0.143	0.179	–0.66	0.08
		Mechanical	–0.130	0.143	0.800	–0.50	0.24
	Electronics and Communication	Civil	0.340	0.143	0.083	–0.03	0.71
		Computer	0.290	0.143	0.179	–0.08	0.66
		Mechanical	0.160	0.143	0.678	–0.21	0.53
	Mechanical	Civil	0.180	0.143	0.590	–0.19	0.55
		Computer	0.130	0.143	0.800	–0.24	0.50
		Electronics and Communication	–0.160	0.143	0.678	–0.53	0.21

^*The mean difference is significant at the 0.05 level. ^***p < 0.001; ^**p < 0.01; ^*p < 0.05. Sig: Significance.

ANOVA results (Table 10) reflect that there is a significant difference in perception of respondents in three of the seven factors influencing academic stress based on university groups considered for analysis. This is: AS-2: Inadequate teaching interaction, AS-3: Lack of outreach opportunities and AS-5: Lack of interest but for other four factors i.e. AS-1: Examination stressors, AS-4: Inadequate learning orientation, AS-6: Problems of interaction and AS-7: Poor time management, the results didn’t reflect significant difference on academic stress with respect to universities. This shows there is a similarity of perception of the respondents on the academic stress based on university grouping. Thus, the hypothesis H_1d: there is a significant difference in the academic stress with respect to the different university groups have been partially accepted.

Table 10

ANOVA results for factors influencing academic stress based on nature of university

		Sum of squares	df	Mean square	F	Sig.
AS-1: Examination Stressors	Between groups	0.060	1	0.060	0.079	0.778
	Within groups	302.751	398	0.761
	Total	302.811	399
AS-2: Inadequate Teaching Interaction	Between groups	3.648	1	3.648	5.764	0.017^*
	Within groups	251.883	398	0.633
	Total	255.531	399
AS-3: Lack of Outreach Opportunities	Between groups	4.306	1	4.306	6.059	0.014^*
	Within groups	282.804	398	0.711
	Total	287.109	399
AS-4: Inadequate Learning Orientation	Between groups	2.139	1	2.139	2.985	0.085
	Within groups	285.192	398	0.717
	Total	287.331	399
AS-5: Lack of Interest	Between groups	3.608	1	3.608	5.105	0.024^*
	Within groups	281.297	398	0.707
	Total	284.905	399
AS-6: Problems of Interaction	Between groups	0.856	1	0.856	0.968	0.326
	Within groups	351.739	398	0.884
	Total	352.594	399
AS-7: Poor Time Management	Between groups	1.323	1	1.323	1.282	0.258
	Within groups	410.455	398	1.031
	Total	411.778	399

^***p < 0.001; ^**p < 0.01; ^*p < 0.05. [df: Degrees of freedom; F: F ratio; Sig: Significance].

7 Discussion

The researchers have investigated the effects of academic stress and students’ Mental Health management. [20 –22]. Also the research was done on Stress monitoring through non-invasive instrumental analysis [23 –25]. This study indicates that there is a significant difference in the factors influencing Academic stress based on different streams of engineering. Also there is a significant difference in case of the factors of Academic Stress based on the nature of university. It consisted of 34 items on Academic Stress describing the stress information from their institution/personal life as well as from the other various sources. There were 34 questions on Academic Stress. Academic Stress was compared based on gender, age, engineering streams and nature of university. The results of factor analysis as shown through Table 4 which highlights that based on factor analysis seven factors emerged. These seven factors explained 51.126 % of variation.

ANOVA results through Table 5 reflect that there is a significant difference in perception of respondents in one of the seven factors influencing academic stress based on gender groups (male and female) considered for analysis to reject hypothesis H_1a .

ANOVA results through Table 6 and 7 showed that there is a significant difference in the academic stress with respect to the different age groups to reject hypothesis H_1b

ANOVA results through Table 8 and 9 reflect that there is a significant difference in perception of respondents in four of the seven factors influencing academic stress based on engineering streams considered for analysis. Thus, the hypothesis H_1c: there is a significant difference in the academic stress with respect to the different engineering stream groups has been partially accepted.

ANOVA results (Table 10) reflect that there is a significant difference in perception of respondents in three of the seven factors influencing academic stress based on nature of university groups considered for analysis. Thus, the hypothesis H_1d: there is a significant difference in the academic stress with respect to the nature of university groups have been partially accepted.

8 Summary

This is a detailed Indian study done via a questionnaire study about what determines academic success among engineering students from two different universities. Four hypotheses were examined with results highlighting engineering streams and the nature of the universities most affecting the students.

9 Limitations of the study

Like any research study, the present study also has some limitations. In addition to theoretical analysis, physiological parameters like breathing rate, pulse rate could also be included for analysis. It is time to think intensely about managing and controlling students’ stress as it is leading to depression and tackling it, is an urgent concern.

10 Significance of the study

It is time to think intensely about managing and controlling academic stress as it is deep-rooted malaise and tackling it, is the immediate concern. As engineering students have to work in industries, so for better quality of life free from stress and improved employability skills, such innovative activities should be developed to ascertain the sustainable academic’s abilities of students. To control the outcome of stress properly, there are certain precautions and methods that should be taken that will boost productivity. This may boost the efficiency of students and assist in dealing with the critical issue of suicides and many other crimes, thus contributing to healthy social system.

11 Implications of the study

Academic stress can severally hinder academic performance as well as adjustment in life in several ways. The suggested research will help to reduce stress, improve efficiency and productivity of the engineering students. This attempt may help in plunging stress that emerges from drug addiction, smoking and drinking. Their physical and mental health will improve. This study can be extended to students of other colleges and public enterprises. The study will also be extremely useful for students of Medical and para-medical sciences. The suggested techniques can be adopted as for managing stress in all educational institutions.

Conflict of interest

None to report.

Footnotes

Appendix

Table A1

Stress scale: This scale consists of 75 items describing the stress in your institution/college/personal life from the various sources. The level of stress you feel for each item can be indicated by marking a tick mark (√)

S. no.	Kindly rate the following factors causing stress from 1–5 in the order of priority with 1 being least and 5 as highest	1	2	3	4	5
	Academic Stress Questions (1–34)
1.	Lack of interest in some subjects	1	2	3	4	5
2.	Lack of concentration during study hours	1	2	3	4	5
3.	Difficulty in memorizing and retention of lectures	1	2	3	4	5
4.	Overload of assignments	1	2	3	4	5
5.	Callous attitude of teachers	1	2	3	4	5
6.	Personal hesitation to ask questions in class	1	2	3	4	5
7.	Inadequate query handling by teacher	1	2	3	4	5
8.	Inadequate space/room for studying at home	1	2	3	4	5
9.	Lack of confidence in the class	1	2	3	4	5
10.	Lack of opportunity to meet teachers	1	2	3	4	5
11.	Slow in getting along with the curriculum	1	2	3	4	5
12.	Unable to complete the assignment in time	1	2	3	4	5
13.	Monotonous teaching style by the teacher	1	2	3	4	5
14.	Lack of case studies to support teaching and learning	1	2	3	4	5
15.	Lack of interactive sessions in class	1	2	3	4	5
16.	Exam papers are tough	1	2	3	4	5
17.	Examination syllabus is too heavy in some subjects	1	2	3	4	5
18.	Worrying about the examinations	1	2	3	4	5
19.	Concern about results after examinations	1	2	3	4	5
20.	Tendency to ‘day-dream’ when trying to study	1	2	3	4	5
21.	Study periods are often too short for me to get ‘warmed up’ and concentrated	1	2	3	4	5
22.	Missing important points while taking notes in class	1	2	3	4	5
23.	Too tired, sleepy and listless to study efficiently	1	2	3	4	5
24	Enjoyment of loafing (spending time ideally), ‘bull- seasons’ (amusing and illogical use of words) interferes with my study	1	2	3	4	5
25.	Dislike of certain courses and teachers interferes with getting good results	1	2	3	4	5
26.	Unable to discuss academic failures with parents	1	2	3	4	5
27.	Not able to grasp the subject matter	1	2	3	4	5
28.	Inadequate subject knowledge of the teachers	1	2	3	4	5
29.	Inadequate lab space	1	2	3	4	5
30.	Inadequate library facilities	1	2	3	4	5
31.	Less placement opportunity provided by the institute	1	2	3	4	5
32.	Fear of appearing in the placement activities	1	2	3	4	5
33.	Fear of failure in job selection interviews	1	2	3	4	5
34.	Unfavorable location of placement	1	2	3	4	5

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Determinants of academic stress amongst engineering students

Abstract

BACKGROUND:

OBJECTIVE:

METHODS:

RESULTS:

CONCLUSIONS:

Keywords

1 Introduction

2 Stress

2.1 Causes of stress

2.2 Academic stress

2.3 Personal stress

2.4 Financial stress

3 Population and sampling

4.1 Reliability and validity

Table 3 Reliability statistics S. no. Items Factor name Cronbach alpha 1. 34 Academic stress 0.913

6 Results

8 Summary

9 Limitations of the study

10 Significance of the study

11 Implications of the study

Conflict of interest

Footnotes

Appendix

References

Table 3
Reliability statistics

S. no. Items Factor name Cronbach alpha

1. 34 Academic stress 0.913