Hardiness in learning and study outcomes of business students

Hardiness in learning and study outcomes of business students NGUYEN DINH THO UEH International School of Business – ndtho@ueh.edu.vn Abstract Realizing the role that hardiness in lea

Hardiness in learning and study outcomes of

business students

NGUYEN DINH THO

UEH International School of Business – ndtho@ueh.edu.vn

Abstract

Realizing the role that hardiness in learning plays in the study outcomes of business students, this study investigates the impact of hardiness in learning of business students, overall as well

as its individual components, on their study outcomes, including quality of college life, quality of life, and learning performance The study also explores the degrees of necessity of the components of hardiness in learning (commitment, control and challenge) for the occurrence of study outcomes The results, based on a data set collected from a sample of 722 business students

in various universities in Ho Chi Minh City, reveal that overall hardiness in learning has a positive effect on study outcomes In terms of individual components, commitment, control and challenge have a positive impact on learning performance, however, control does not affect quality of college life and challenge has no effect on quality of life In addition, these components have different degrees of necessity for the occurrence of study outcomes These findings, generally, suggest that universities could enhance the outcomes of business students by offering programs that are able to cultivate students’ hardiness in learning However, attention should

be paid to the degree of necessity of each individual components, i.e., commitment, control and challenge, in order to achieve a desired level of study outcomes

business students

1 Background

Stress can generate psychological problems and can affect peoples’ effectiveness at working and studying To overcome challenges introduced by stress, people need to be psychologically hardy Hardiness is a concept used to describe people’s commitment, control, and challenge in their lives (Britt, Adler, & Barton, 2001; Fyhn, Fjell, & Johnsen, 2016; Kobasa, 1979; Maddi, 2002) Commitment refers to a “tendency to involve oneself in (rather than experience alienation from) whatever one is doing or encounters” Control is defined as a “tendency to feel and act as if one is influential (rather than helpless) in the face of the varied contingencies of

life” Challenge is described as a “belief that change rather than stability is normal in life and that the anticipation of changes are interesting incentives to growth rather than threats to security” (Kobasa, Maddi, & Kahn, 1982, 169)

Research shows that hardiness assists people in enhancing their health and performance when coping with stressful conditions (e.g., Maddi, 1999; Stoppelbein, McRae, & Greening, 2017) Highly hardy attitudes also help people to convert stressful events into common problems

to be solved (Bartone, Valdes, & Sandvik, 2016; Bartone, Eid, Johnsen, Laberg, & Snook, 2009; Maddi, 1999; Sezgin, 2009) or opportunities for growth and development (Kobasa & Puccetti, 1983), thus improving performance and quality of life (Alfred, Hammer, & Good, 2014; Bartone

et al., 2009; Johnsen, Espevik, Saus, Sanden, Olsen, & Hystad, 2017; Kelly, Matthews, & Bartone, 2014; Wiebe & McCallum, 1986) In education, a number of studies have also investigated the role of hardiness in students’ attitudes and behaviour For example, Abdollahi, Talib, Yaacob, and Ismail (2015) and Abdollahi, Talib, Carlbring, Harvey, Yaacob, & Ismail (2016) find that hardiness helps prevent stress and suicidal ideation among undergraduate students and moderates the relationships between problem-solving skills and perceived stress However, the role of hardiness in key study outcomes such as quality of college life and quality life and learning performance is still under-investigated

1.1 Quality of college life and quality of life

Quality of college life and quality of life are concepts that have received attention from researchers in the past several years (e.g., Arslan & Akkas, 2014; Cummins, 2010; Sirgy, Grzeskowiak, & Rahtz, 2007) Quality of life can be defined in terms of overall life satisfaction (e.g., Vaez et al., 2004) or it can focus on particular aspects of life And, quality of college life is defined as students’ satisfaction with their educational experience during the time they study and live at university (Sirgy et al., 2007) A number of studies explore the factors affecting quality

of college life and quality of life in the developed world For example, Vaez et al (2004) examine the relationship between health status and quality of college life and discover that the quality of college life for university students is lower than that of their working peers Research conducted

by Cha (2003) indicates that there is a positive relationship between quality of college life and personal factors such as optimism, self-esteem, etc Chow (2005) showed that socio-economic status, experience in learning, living conditions, and other factors have positive relationships with students’ well-being

1.2 Hardiness in learning and study outcomes of business students

The literature on education indicates that study at university is one of many causes of stress (e.g., Cole, Field, & Harris, 2004; Furr, Westefeld, McConnell, & Jenkins, 2001) When studying

at university, students not only have to focus on completing educational activities such as

readings, assignments, projects, and examinations, but they also have to manage personal matters such as finances, part time jobs, and social activities Hardiness in learning plays an important role in the learning process Students with high levels of hardiness in learning will spend their time and effort in studying They feel and act as if they are influential and welcome changes occurring during their lives at university During their university lives, students often experience stressful circumstances Students with high hardiness in learning will be able to control stress in their learning process This capability helps them transform the stress caused

by learning into more fun or enjoyable university lives, developing and maintaining their motivation to do what they need to do When students have capabilities to overcome the pressure

of learning in class, they will acknowledge the role of their professors and classmates in learning, leading to a high level of satisfaction with their learning at university, that is, their quality of college life is increased

During their years at university students are called upon to develop their cognitive and creative abilities; they develop knowledge and skills that will admit them to their chosen professions Given the high stakes involved, this experience can be very stressful The theory of hardiness (e.g., Maddi, 2002) posits that people who possess hardiness find stressful challenges

“developmentally provocative” and tend to respond to such challenges as opportunities They also enjoy higher levels of health and life satisfaction Applying this argument to business students, this study expects those who exhibit a higher level of hardiness in learning will enjoy

a high quality of college life, quality of life and learning performance In conclusion, hardiness plays an important role in the outcomes of individuals’ work and life such as mitigating stress, enhancing their quality of work and life as well as performance effectiveness However, the following questions have not been thoroughly answered and this study is undertaken with the aim of answering these two questions in a context of a transitioning economy, Vietnam Does hardiness in learning, conceptualized as a multidimensional construct (comprising commitment, control and challenge) enhance the study outcomes (including quality of college life, quality of life and learning performance) of business students?

What level of commitment, control and challenge should business students reach in order to achieve their desired level of quality of college life, quality of life and learning performance?

2 Method

2.1 Research context

The continuing economic transformation of the Vietnamese economy from a centrally-planned economy into a market-oriented economy and accession to the World Trade Organization have created several opportunities such as new markets for goods and services

exports, access to imported raw materials and technologies, and more opportunities for international business co-operation Together with opportunities, a more open market however leads to more challenges to Vietnamese firms They have to face with vigorous competition and the imposition of stricter business standards such as product quality and safety (Nguyen, Shultz,

& Westbrook, 2012) Among several challenges, lack of knowledge about business management

is perhaps one of the most pressing for Vietnamese firms Thus, providing qualified business graduates for the Vietnamese labor market a crucial role of Vietnamese universities Understanding the labor market’s need for competent graduates, Vietnamese universities are striving to improve the quality of their business education programs, putting more pressure on Vietnamese students because they are now have to complete more assignments and examinations and their performance standards are rising

Raising objective standards is important for improving educational outcomes, at the student side, however, the educational outcomes are reached when students’ outcomes, including students’ quality of college life, quality of life and learning performance, are enhanced For that reason, Vietnamese universities, with new performance standards, should comprehend what contributes to their students’ outcomes Consequently, Vietnamese is an appropriate country for the study of the role of hardiness in learning in quality of college life, quality of life and learning performance of business students

2.2 Procedure and sample

Research on the role of hardiness in learning in quality of college life, quality of life and learning performance focuses solely on the net effects using conventional statistical tools such

as multiple regression analysis or structural equation modelling (SEM) Such traditional statistical approaches however do not help researchers to discover the causal complexity of business phenomena (Ragin, 2008) The aim of this study was not only investigate the net effect

of hardiness in learning, overall and its individual components, but also the level of necessity of each component for students’ outcomes, comprising students’ quality of college life, quality of life and learning performance To reach this aim, this study first used SEM to test the net effect

of hardiness in learning, overall and its components, on quality of college life, quality of life and learning performance Then, the study, employing the necessary condition analysis (NCA; Dull, 2016a), investigates the levels of necessity of three components of hardiness in learning (i.e., commitment, control and challenge) for students’ quality of college life, quality of life, and learning performance

A sample of 722 business students in various universities in Ho Chi Minh City, the principal business centre of Vietnam, was surveyed to collect the data used to validate the measures and

to test the hypotheses The universities surveyed included University of Economics Ho Chi Minh City, Ho Chi Minh City University of Technology, Nong Lam University, Saigon University, Huflit

University, Banking University Ho Chi Minh City, Hoa Sen University, University of Finance – Marketing Face-to-face interviews was employed in this study The sample included 373 (51.7%) students in the first two years and 349 (48.3%) students in the second two years In

terms of gender, there were 479 (63.3%) female students and 343 (33.7%) male students

2.3 Measures

There was four constructs under investigation: Hardiness in learning, quality of college life, quality of life and learning performance Hardiness in learning was a multidimensional construct composed of three components: commitment, control, and challenge Each component of hardiness in learning was also measured by three items adopted from Bartone, Ursano, Wright, and Ingraham (1989) Note that this study examines hardiness in learning of business students, that is, in a specific context, not general hardiness The scale measuring hardiness therefore was modified to suit the research context

Quality of college life was measured by four items, borrowed from Sirgy et al (2007) These four items reflect students’ overall perception of their quality of college life when studying

at their universities Note that, quality of college life could be conceptualized as a multidimensional construct composed of various components such as students’ satisfaction with the faculty, facilities, student services, relationships with classmates, and extracurricular activities, this study focused on the overall measure of quality of college life (Nguyen et al., 2012; Sirgy et al., 2007) Quality of life was measured by four items borrowed from Peterson and Ekici (2007) Finally, learning performance was measured by four items reflecting students’ self assessment of their overall knowledge, skills and abilities obtained in their university This scale was based upon Young, Klemz, and Murphy (2003), and was modified and tested with Vietnamese business students by Nguyen and Nguyen (2010)

All items were measured by a five-point Likert scale anchored by 1: strongly disagree and 5: strongly agree The questionnaire was originally prepared in English and was translated into Vietnamese by an academic fluent in both languages Back-translation was conducted to ensure the meanings This procedure was undertaken because English is not well understood by all Vietnamese students Note that the items were randomly assign into the questionnaire with an aim of mitigating the agreement tendency bias Note also that the questionnaire were piloted by

a group of eight business students at the University of Economics Ho Chi Minh City to ensure the clarity of the item meaning

3 Results

3.1 Measure validation

Confirmatory factor analysis (CFA) was used to validate the measure The study first tested the scale measuring hardiness in learning (a second-order construct) and then, incorporated this scale into the measures of quality of college life, quality of life and learning performance (first-order constructs) to form the final measurement model (saturated model) The screening process showed that although the data exhibited slight deviations from normality, all univariate kurtoses and skewnesses were in the acceptable range of [-1, 1] The maximum likelihood estimation method therefore was used to estimate the parameters in the measurement and structural models (Muthen & Kaplan, 1985)

The CFA results indicate that the measurement model of hardiness in learning received

a good fit to the data: 2

[24] = 70.79 (p = 0.000), GFI = 0.979, CFI = 0.951, and RMSEA = 0.052

In addition, all factor loadings were sufficient and significant ( ≥ 0.50, p < 0.001) Next, the CFA results of one-factor model reveal that the one-factor model received a poorer fit compared

to the three-factor model: 2

[27] = 170.35 (p = 0.000), GFI = 0.947, CFI = 0.850, and RMSEA = 0.086 A Chi-square differential test also shows a significant difference between the two models leading to the choice of the three-factor model of hardiness: ∆2

[27-24] = 99.56 (p < 0.001); GFI

= 0.979; CFI = 0.951; and RMSEA = 0.052 The final measurement model also produced an acceptable fit to the data: 2

[178] = 419.71 (p = 0.000); GFI = 0.947; CFI = 0.942; and RMSEA = 0.043 The factor loadings of all items were also substantial and significant ( ≥ 0.50, p < 0.001) Finally, the correlation between any pair of constructs was smaller than the square root of the average variance extracted of each construct in the pair, supporting discriminant validity across constructs (Fornell & Larcker 1981)

3.2 Common method bias

This study used a cross-sectional data set collected from a single respondent (i.e., business students) which may raise the possibility of common method biases (Podsakoff, MacKenzie, Lee,

& Podsakoff, 2003) Note that, in the design phase, the items measuring the constructs in the model were randomly assigned to the questionnaire with an aim of lessening such biases In this analysis phase, two statistical procedures were undertaken to assess this possibility First, a CFA Harman’s single factor model test was employed The CFA one-factor model received a very poor fit to data [2

(184) = 1511.88 (p = 0.000), GFI = 0.800, CFI = 0.684, and RMSEA = 0.100], compared to the trait factor model [2

[178] = 419.71 (p = 0.000); GFI = 0.947; CFI = 0.942; and RMSEA = 0.043] Next, an unmeasured latent variable that was allowed to load on each item into the trait model was investigated The results indicate that the size and statistical significance

of the loadings were almost identical to those reported in the measurement model In addition, all loadings of the items on the unmeasured latent variable were not significant The results indicate that the common method variance, if existed, was not a pervasive problem in this study

3.3 Structural model: Testing the net effect of hardiness in learning on

quality college life, quality of life and learning performance

The SEM results show that the proposed model produced an acceptable fit to the data:

2[196] = 445.12 (p = 0.000); GFI = 0.946; CFI = 0.941; and, RMSEA = 0.042 Table 1 presents the estimates of the structural paths proposed in the model A closer examination of the structural paths reveals that hardiness in learning had a significant impact on quality of college life (p < 0.001; R2 = 30.8%), quality of life (p < 0.001; R2 = 9.2%) and learning performance (p < 0.001; R2 = 31.6%) Note that the gender of students served as a control variable and the results show that student gender did not explain the variances of quality of college life, quality

of life and learning performance

Table 1

Effects of hardiness in learning on quality college life, quality of life and learning

performance

Hardiness in learning  Quality of college life 0.70 0.086 0.56 8.10 0.000 Hardiness in learning  Quality of life 0.41 0.079 0.30 5.21 0.000 Hardiness in learning  Learning performance 0.82 0.100 0.56 8.22 0.000 Control

variable

Student gender  Quality of college life 0.00 0.047 0.00 -0.04 0.97 Student gender  Quality of life 0.00 0.057 0.00 -0.07 0.95 Student gender  Learning performance -0.11 0.056 -0.07 -1.87 0.062

Note B: unstandardized estimate; SE: standard error; β: standardized estimate; CR: critical ratio; p:

p-value

When examining the impact of each component of hardiness in learning separately, the SEM results show that the proposed model received a poorer fit compared to the model in which hardiness in learning was a second-order construct, but it was acceptable: 2[176] = 673.17 (p

= 0.000); GFI = 0.918; CFI = 0.882; and, RMSEA = 0.063 Table 2 presents the estimates of the structural paths proposed in the model A closer examination of the structural paths reveals that commitment and challenge had positive effects on quality of college life (p < 0.001 and p < 0.01, respectively) but control did not (p = 0.653) These components explained 31.0 percent of the variance of quality of college life In terms of quality of life, the results show that commitment and control had positive impacts on quality of life (p < 0.01 and p < 0.001, respectively; R2 = 7.8%), but challenge did not (p = 0.095) Finally, all three components of hardiness

(commitment, control and challenge) in learning underlie the learning performance of business students (p < 0.001, p < 0.05, and p < 0.001, respectively; R2 = 25.4%)

Table 2

Effects of components of hardiness in learning on quality college life, quality of life and learning performance

Commitment  Quality of college life 0.64 0.077 0.54 8.39 0.000 Control  Quality of college life 0.03 0.057 0.02 0.45 0.653 Challenge  Quality of college life 0.13 0.049 0.13 2.61 0.009 Commitment  Quality of life 0.21 0.068 0.16 3.00 0.003

Challenge  Quality of life 0.10 0.059 0.09 1.67 0.095 Commitment  Learning performance 0.50 0.076 0.37 6.57 0.000 Control  Learning performance 0.16 0.071 0.12 2.20 0.028 Challenge  Learning performance 0.37 0.068 0.33 5.43 0.000

Note B: unstandardized estimate; SE: standard error; β: standardized estimate; CR: critical ratio; p:

p-value

3.4 NCA results: Exploring the degree of necessity of commitment, control

and challenge for quality college life, quality of life and learning performance

SEM was used to investigate the net effects of hardiness in learning (overall as well as its components) on quality college life, quality of life and learning performance To discover the levels of necessity of these conditions, this study utilized NCA This is an analysis method that assists researchers in identifying the degree of a necessary (but not sufficient) condition for an outcome In order to examine the level of necessary conditions, NCA determines the ceiling line, the line that separates the area with observations from the area without observations (Dul, 2016a) Two common techniques used for determining the ceiling line are the ceiling envelopment technique (a piecewise linear line) with free disposal hull (CE-FDH) and the ceiling regression (a straight line) with free disposal hull (CR-FDH) because they are more flexible techniques The NCA results produced by the NCA package (Dul, 2016b) included the CE-FDH and CR-FDH ceiling lines and bottleneck tables

The ceiling lines and bottlenecks, produced by the NCA package, showing the degrees of necessity of commitment, control and challenge for quality of college life are presented in Figure

1 and Table 3, respectively In Table 3, the degrees of all necessary conditions (commitment, control and challenge) were determined through their bottlenecks, expressed as percentage of

the range of observed values (0% = lowest value, 100% = highest value; Dul, 2016b) On closer examination of the bottleneck results one can see these conditions (commitment, control and challenge) exhibited different levels of necessity However, the effect size of two conditions (commitment and challenge) were small (< 0.1) in both techniques (CE-FDH and CR-FDH) Only one condition (control) plays a necessary condition for the outcome (quality of college life) For example, at the level of 20 percent of quality of college life, it is necessary that control should at least be 16.7.0% At this level of quality of college life, commitment and challenge were not necessary conditions Only when quality of college life was at the 60-percent level, all three conditions (commitment, control and challenge) were necessary conditions (CE-FDH: commitment = 16.7%, control = 25.0%, and challenge = 8.3%; CR-FDH: commitment = 3.3%, control = 15.0%, and challenge = 2.4%; Table 3)

Similarly, Figure 2 and Figure 3 are the ceiling lines presenting the degrees of necessity of commitment, control and challenge for quality of life and learning performance, respectively Table 4 and Table 5 are the bottlenecks showing the degrees of necessity of commitment, control and challenge for quality of life and learning performance, respectively As in the case of quality

of college life, control received the strongest effect size (dCE-FDH = 0.255; Table 4) in serving as a necessity condition for the occurrence of quality of life Commitment, however, was a necessary condition for the occurrence of learning performance that received the strongest effect size (d CE-FDH = 0.229; Table 5)

Figure 1 Ceiling lines of necessary conditions for quality of college life

Note: QCL: Quality of college life; Lower solid line: OLS regression line; Upper solid line: CR-FDH ceiling line; Dashed line: CE-FDH ceiling line

Challenge

OLS CE-FDH CR-FDH

NCA Plot : Challenge - QCL

Control

OLS CE-FDH CR-FDH

NCA Plot : Control - QCL

Commitment

OLS

CE-FDH

CR-FDH

NCA Plot : Commitment - QCL

Table 3

Bottleneck table: Required minimum levels of commitment, control and challenge for different desired levels of quality of college life (%)

Quality of

college life

Commitment Control Challege Commitment Control Challege

Note: CE-FDH: ceiling envelopment-free disposal hull; CR-FDH: ceiling regression-free disposal hull; d:

effect size; NN: not necessary; NA: not available

Figure 2 Ceiling lines of necessary conditions for quality of life

Note: QoL: Quality of life; Lower solid line: OLS regression line; Upper solid line: CR-FDH ceiling line;

Dashed line: CE-FDH ceiling line

Control

OLS CE-FDH CR-FDH

NCA Plot : Control - QoL

Commitment

OLS

CE-FDH

CR-FDH

NCA Plot : Commitment - QoL