The impacts of self-efficacy on academic performance: An investigation of domestic and international undergraduate students in hospitality and tourism

Journal of Hospitality, Leisure, Sport & Tourism Education 20 (2017) 47–54

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Critical perspectives

The impacts of self-efficacy on academic performance: An investigation of domestic and international undergraduate students in hospitality and tourism

MARK

⁎

Huong T. Buia, , Kevin Kam Fung Sob, Anna Kwekc, John Rynned a

College of Asia Pacific Studies, Ritsumeikan Asia Pacific University, 1-1 Jumonjobaru, Beppu, Oita, Japan School of Hotel, Restaurant and Tourism Management, College of Hospitality, Retail and Sport Management, University of South Carolina, United States c Department of Tourism, Sport, and Hotel Management, Griffith University, Parkland Drive, QLD 4222, Australia d School of Criminology and Criminal Justice, Griffith University, Parkland Drive, QLD 4222, Australia b

A R T I C L E I N F O

ABSTRACT

Keywords: Self-efficacy Academic performance International students Asia

The substantial development of the tourism industry in Asia has resulted in growing international demand for tourism and hospitality higher education in Australia. Using a pre-and-post study design, the results indicate that after a semester of teaching and learning, the improvement in self-efficacy was only evidenced among high performing students. While self-efficacy was significant in predicting the performance of domestic students, this positive relationship was not found among international students. The results of this study bridge the knowledge gap identified in the literature and highlight a need for further understanding international students in English-based tourism and hospitality education.

1. Introduction The Asia Pacific region has a population of more than two billion people and is home to several important economies, such as Japan, China, and South Korea. At present, Asia has significantly more outbound tourists than any other emerging region (Cohen & Cohen, 2015). As a major employer on the continent, the tourism industry offers economic stability as well as a wide variety of jobs. However, as the industry continues to expand and develop, the lack of well-trained researchers and skilled industry managers is becoming a major concern. In particular, developing countries in Asia have a growing need for industry managers who meet international standards. Consequently, given their proximity to Asia, Western countries like Australia and New Zealand are facing an increase in the demand by Asian students for quality tourism and hospitality higher education (Hobson, 2008). East Asia has been the largest buyer of English-based courses (World Tourism Organisation, 2008). Young Asians’ desire to learn English-based courses entails the intersection of two major factors. One factor is the appeal of an association with the “imagined West,” believed to enable one to become more cosmopolitan and often representing high living standards and trendy lifestyles in contemporary Asia (Bui, Wilkins, & Lee, 2013; Kwek & Lee, 2013). The other factor is the relatively poor English education at home (Yoshino, 2002). Therefore, an increasing number of international students have enrolled in English-based institutions in the United Kingdom, the United States, and Australia. The rapid growth of international student enrolment in these English-speaking universities has generated the need to better understand cognitive factors that influence students’ learning behaviours. Arriving from Asian countries such Mainland China, South ⁎

Corresponding author. E-mail addresses: [email protected] (H.T. Bui), [email protected] (K.K.F. So), a.kwek@griffith.edu.au (A. Kwek), j.rynne@griffith.edu.au (J. Rynne).

http://dx.doi.org/10.1016/j.jhlste.2017.02.002 Received 30 March 2014; Received in revised form 19 January 2017; Accepted 24 February 2017 1473-8376/ © 2017 Elsevier Ltd. All rights reserved.

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Korea, and Hong Kong, these students have received a relatively poor English education at home and lack preparation for encountering the culture of Western countries. As a result, they face numerous challenges in coping not only with their new living environment but also with a culturally diverse learning environment (Barron, 2002; Kember, 2000; Niles, 1995; Ramsay, Barker, & Jones, 1999; Rynne, Kwek, & Bui, 2012). Adjusting to this new life can be difficult and stressful and can require these students to become more independent and self-regulated (Bryde & Milburn, 1990). With English as their second language, these students experience English language proficiency issues that have been widely identified as problematic, undermining their efforts to achieve better academic performance (Briguglio & Smith, 2012; Li, Chen, & Duanmu, 2010). Research suggests that possessing confidence in one's own ability strongly influences success in negotiating this transition and may lead to positive academic outcomes and performance (Chemers, Hu, & Garcia, 2001). As an emerging area of study, research on Asian students studying tourism and hospitality in Australia is still relatively limited in scope, with previous investigations focusing mainly on topics such as learning approaches (Biggs, 1996; Smith, Miller, & Crassini, 1998), the academic adjustment process (Ramsay et al., 1999), and common misconceptions about these students (Chalmers & Volet, 1997, 1992; Samuelowicz, 1987). More general research shows that students with high self-efficacy are better equipped to successfully complete their education (Bandura, Barbaranelli, Caprara, & Pastorelli, 2001; Lane & Lane, 2001). Conversely, students with low self-efficacy appear to face a higher likelihood of academic failure and tend to perceive learning tasks as more difficult and daunting than they actually are. Notably, Bandura (1997, 2006) argues that self-efficacy measures should be specific to the context where they are to be used and be able to reveal the factors required to deliver that performance. Given specific context and differences in the process of adjustment of Asian students in English-speaking education system, attention should be focused on the question of how do self-beliefs of international students (especially from Asia) influence their academic performance. In consideration of the large increase in international enrolments from Asia, this paper empirically examines how self-efficacy of international students in Australia affects their academic performance in comparison with domestic students. While previous studies in educational settings have investigated the effect of self-efficacy on academic achievement among primary, secondary, and tertiary students in general (Devonport & Lane, 2006; Lent, Brown, & Hackett, 1994; van Dinther, Dochy, & Segers, 2011; Zajacova, Lynch, & Espenshade, 2005), few studies have focused on first-year international undergraduate students in tourism and hospitality higher education degree programs, when adjustment to the new academic environment and outcome expectations are among the most difficult tasks to overcome (Chemers et al., 2001; Kwek, Bui, Rynne, & So, 2013; Lane, Hall, & Lane, 2002). Whilst students differ in the areas in which they cultivate their efficacy and in the levels to which they develop it (Bandura, 2006) over the course of tertiary education, contingence of self-efficacy to specific context warrants further investigation. The current study extends previous research regarding differences between domestic and international students in academic performance. A recent investigation predicted differences between domestic and Asian tourism and hospitality students in types or approaches to academic motivation (Rynne, Kwek, & Bui, 2012), but did not find the expected relationship between academic motivation and academic performance (i.e., when a student is highly motivated, he/she is expected to perform well academically). Another study provided important insights into the relationships between self-esteem, resilience, and academic performance of both domestic and international students in Australia, extending current knowledge of the role of these two important psychological factors in determining the academic performance of first-year tourism and hospitality students (Kwek et al., 2013). To better understand the unexpected outcomes of attempts to explain academic performance among first-year undergraduate students, this study utilised the Self-efficacy Towards Statistics Questionnaires (STSQ) developed by Lane et al. (2002). Bandura (2006), however, contends “there is no all-purpose measure of self-efficacy. The “one measure fits all” approach usually has limited explanatory and predictive value because most of the items in an all-purpose test may have little or no relevance to the domain of functioning” (p. 307). Therefore, beyond testing the STSQ in a new context of tertiary education in Australia, the current study also explores the scales in a research methods course that included both qualitative and quantitative analysis, a different task from original efficacy towards statistics of STSQ specified by Lane et al. (2002). The remainder of this paper is organized as follows. The next section reviews prior literature on the concept of self-efficacy and particularly its influence on academic performance. The subsequent section describes the research method adopted in this study. The ensuing two sections present the results and a discussion of the findings, and the final section offers concluding thoughts. 2. Literature review Self-efficacy is a significant variable in the thought-processing capability of individuals. Described as the “beliefs in one's capabilities to organize and execute the courses of action required to produce given attainments” (Bandura, 1997, p. 3), self-efficacy is a form of self-referent thinking with which people evaluate and regulate their own experiences, thoughts, and behaviour. In turn, this self-belief influences how people behave and make decisions, as well as the level of effort they expend on the task (Bandura, 1977; van Dinther et al., 2011; Zimmerman, Bandura, & Martinez-Pons, 1992). Self-efficacy affects people's choice of activities and behavioural settings (Bandura & Adams, 1977). Empirical tests have confirmed that different treatment approaches alter expectations of personal efficacy, and the more dependable the source of efficacy information, the greater the changes in self-efficacy (Bandura, Adams, & Beyer, 1977). Repeated observation of successful performances increased by a substantial amount the level (44%) and strength (38%) of self-efficacy, which in turn was accompanied by similar large increments in performance (35%) (Bandura, 1977). Self-efficacy proved to be a superior predictor of the amount of behavioural improvement. Self-efficacy is of particular importance in an academic setting. Academic self-efficacy has been defined as the “personal judgments of one's capabilities to organize and execute courses of action to attain designated types of educational performances” 48

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(Zimmerman, 1995, p. 203). Academic self-efficacy encourages and promotes academic achievement by increasing academic aspiration both directly and indirectly (Bandura, Barbaranelli, Caprara, & Pastorelli, 1996), and researchers have found evidence of a positive relationship between academic self-efficacy and academic achievement (Carini, Kuh, & Klein, 2006). For example, the results of a longitudinal study to examine the effects of academic self-efficacy on first-year university students’ academic performance indicated that academic self-efficacy was strongly related to performance, both directly to overall academic performance as well as indirectly through expectations and coping perceptions related to classroom performance, stress, health, and overall satisfaction in school (Chemers et al., 2001). Positive association between self-efficacy and perseverance are also evident in students high in self-efficacy. These students persist longer on a task than those who are low in self-efficacy (Bouffard-Bouchard, Parent, & Larivee, 1991). Additionally, students with low self-efficacy tend to use an avoidance coping strategy, such as delaying the start of a project, whereas students high in self-efficacy not only set attainable goals but also become resourceful in helping themselves achieve these goals (Lane, Devonport, Milton, & Williams, 2003). In measuring self-efficacy, researchers have argued that the tool used to measure such a particularized self-perception of competence should be highly consistent with the task being assessed (Pajares, 1996). Depending on the task, the efficacy assessment needs to be domain-specific where students are asked to provide judgments of confidence (Bandura, 2006). Questions in the assessment should therefore relate to the task at hand (Bandura, 1997; Pajares, 1996; Zimmerman, 2000), as collecting different dimensions and aspects of an individual can become fairly unrelated to the assessment of academic self-efficacy (Bong & Skaalvik, 2003). This approach will ensure that both particularized efficacy and achievement assessment directly correspond and as a result, prediction of behaviour is improved (Schunk, 1996; Schunk & Rice, 1991). Similarly, other results show that the most accurate predictions of self-efficacy occur when it is measured at a level specific to the prospective performance (Bong, 2001; Choi, 2005). To better predict self-efficacy, previous researchers developed a measure specific to a statistics and research methods course for sport students (Lane, Devonport, & Horrell, 2004; Lane et al., 2002; Lane, Hall, & Lane, 2004). While the self-efficacy towards statistics (STQS) was rigorously developed (Lane et al., 2002), it has yet been used with a cohort of students from various cultural backgrounds. Knowing how self-efficacy works in specific cultural context and domain functioning provide further guidelines for structuring experiences that enables students to realize desired personal changes. Therefore, the purpose of this research is to analyse students’ specific individual self-beliefs, such as those regarding academic self-efficacy, the research reported here improves the understanding of student outcomes in a focused area of tourism and hospitality higher education. The current research aims to achieve the following objectives: (1) To examine STSQ in a new context of tourism and hospitality tertiary education with a large cohort of international students; and (2) To explore the extent to which STSQ predicts student academic performance. 3. Method 3.1. Survey instrument The STSQ was developed expressly for use in a statistics and research methods course. The STSQ consists of 44 items divided into the six dimensions of general competency, using information technology, statistical theory, time management, motivated behaviour, and lecture behaviour (Lane et al., 2002). Further work (Lane, Hall et al., 2004) tested the measure of self-efficacy towards statistics on Level 1 students in sports and found it useful to predict performance. Since undergraduates of Australian hospitality and tourism tertiary education were also required to complete a research method course with considerable contents of statistics related knowledge, the author decided to adopt the STSQ with 44 items without prior interview to develop the measure. However, measure of academic performance was tailored to specific context of Australian first year tertiary curriculum. In detail, academic performance of the first year research course was measured by three assessment items. The first item was a qualitative assignment, which assessed students’ ability to code qualitative data collected from interviews and to write a report based on their interpretation of the data. In a similar approach, the second item, a quantitative assignment, required students to use basic descriptive and inferential statistical techniques to analyse data collected from survey questionnaires and to subsequently present a written report of their analysis results. The third item was the end-of-semester exam, which comprised both multiple choice and short answer questions. The three academic performance indicators were each assessed with the actual scores of the assessment item. To avoid subjectivity and bias, the tutors used uniform marking criteria as well as a meticulous grade-monitoring process, cross-checking the assignments with the highest, lowest, and middle range grades to ensure transparency and consistency in assessing students’ performance. 3.2. Data collection In this investigation, the study participants were first-year students enrolled in the second semester of a research methods course offered by the tourism and hospitality school of a large Australian university. Prior to participating, each student gave on-line informed consent. Students accessed the on-line survey through the university's computer-based course site. All 809 students enrolled in the course were invited to participate, and a total of 363 usable surveys resulted in a response rate of 45%. The survey of self-efficacy was administered in two class periods ten weeks apart. The Time 1 survey was conducted in the first two teaching weeks, after the course enrolment was finalized and major contents of the course to be taught has been explained to 49

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students. The Time 2 survey was conducted a week before the end of the semester, after all assignments had been completed. The two rounds of the survey allowed the researchers to examine changes in the level of self-efficacy before and after the students had undergone training. Students’ theoretical knowledge was developed and their skills were enhanced throughout the ten-week time space between surveys. 3.3. Data analysis Analysis involved three separate steps using SPSS 19. Specifically, the initial step entailed assessing the psychometric properties of the STSQ dimensions with exploratory factor analysis (EFA). The next step of analysis used regression analysis to access the relationship between STSQ and student academic performance. The final step required conducting a cluster analysis to place similar students into groups (Hair, Black, Babin, Anderson, & Tatham, 2005) based on their performance and subsequently comparing the degree of change in self-efficacy in Time 1 and Time 2 surveys across groups. 4. Results 4.1. Participant profile Of the 363 participants completing the survey, 150 (44%) were domestic students and 193 (56%) were international students. The majority of international students were from Asia, including China (70%), Korea (13%), Hong Kong, Taiwan, and Macau (9.5%), and Southeast Asia (5%). English was not the first language for a large proportion of Asian students. European and North American participants accounted for only 7% of the total international students. Altogether, 58% females and 34% males responded (29 cases that had missing data about gender were retained for further analysis as responses on the measurement scale were completed). The average age of the domestic group (mean=20.2) was slightly lower than that of the international group (mean=21.6). 4.2. Exploratory factor analysis (EFA) The original six-factor model of STSQ was developed from a qualitative study and only the internal consistency was assessed without a test on the factor structure of the scale (Lane et al., 2002). Therefore, the factor structure of the scale required assessment. EFA was conducted on 44 items using principal component analysis (PCA) with oblique rotation as the resultant factors were expected to be correlated. Factors were deemed acceptable if the eigenvalues were greater than one and the factor had at least three items loading highly on it, and in an effort to explore the factor structure without removing a considerable number of items, item factor loadings were deemed significant at 0.30 or greater with a sample size greater than 350 (Hair et al., 2005). EFA did not result in an extraction of six factors as indicated in the original study of Lane et al. (2002). However, transparency of the measurement scale was ensured since the scale has generic application after the removal of items that have been customized to the specific discipline. After removing 15 items with low factor or cross-loading into more than one factor, a five-factor model with 29 items were finalized to measure self-efficacy in the current research context with five dimensions: using information technology, motivated behaviour, time management, statistical theory, and lecture behaviour. Internal consistency of each dimension was deemed acceptable when the values of Cronbach's α of all scale dimensions were greater than 0.70. The solution of a five-factor model in this study did not support the original six-factor model by Lane et al. (2002) when the measure of “general competencies” was completely removed from the new factorial model. Majority of removed items were from the dimensions of statistical theory and motivated behaviour, suggesting that content validity of these three factors is problematic. Table 1 shows the results of the factor analysis for the Time 1 and Time 2 surveys. 4.3. Regression analysis of STSQ on academic performance Regression analysis was conducted to assess the relationship between self-efficacy and students’ academic performance. Three factors measuring time management, lecture behaviour and statistical theory were found to be significant predictors of academic performance and account for approximately 6.5% of the variance of the outcome variable (See Table 2). Dimensions measuring information technology and motivated behaviour did not significantly explain student academic performance, hence were removed from the regression model. Running regression analysis on sample of domestic students, authors found that only time management remained in the equation with R2=0.048. Performing the same analysis on international student sample, all dimensions of STQS failed to explain the variance of academic performance. 4.4. Measurement of self-efficacy across time and groups After assessing the reliability and validity of the measurement scales, the researchers computed composite variables for the five factors. A paired-sample t-test was then performed to compare the five composite scores before students took the research methods course (Time 1) and after having trained (Time 2). As Table 3 indicates, participants showed significant improvement in overall selfefficacy (t=2.83, p < 0.05). In addition, significant improvements also occurred in students’ ability to use information technology (t=2.03, p < 0.05), motivated behaviour (t=2.58, p < 0.05), time management (t=3.07, p < 0.05), and statistical theory (t=5.81, p < 0.05). However, lecture behaviour declined significantly (t=−2.72, p < 0.05), probably owing to a steadily increasing workload during 50

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Table 1 EFA for self-efficacy scale (Time 1 and Time 2).

Using information technology (IT) Use statistical packages Use spreadsheets, graphs Use computers package Use computer to calculate Use basic Windows software Motivated behaviour (MB) Work alone and not rely solely on lectures Know what you are doing is right Work with a logical progress Motivate yourself to read extra research Make decisions and persevere Speak up and ask if unsure about something Think logically Time management (TM) Get work done by set deadlines Organize your time Get all work completed Work in your own time Place your information in a well placed order and plan Collect research efficiently Get required information from textbook and journals Statistical theory (ST) Deal with statistical theory Select the important results Work with numbers Come to grips with what the numbers actually mean Understand what data shows Collect the right type of data Collect data accurately Lecture behaviour (LB) Remain alert for two hours Remain focused on lecture content Turn up to lectures

Factor loading

Eigenvalue

% of variance

Cronbach's α

Mean

T1

T2

T1

T2

T1

T2

T1

T2

T1

T2

T1

T2

10.965

11.940

38%

41%

0.91

0.92

3.43

3.52

0.85

0.77

0.830 0.903 0.922 0.810 0.752

0.946 0.922 0.912 0.860 0.729 2.487

2.597

9%

9%

0.84

0.87

3.30

3.38

0.60

0.62

0.852 0.587 0.454 0.339 0.554 0.665 0.647

0.998 0.926 0.774 0.734 0.664 0.659 0.498 1.778

1.444

6%

5%

0.83

0.84

3.42

3.97

0.62

0.71

0.589 0.697 0.459 0.396 0.727 0.817 0.587

0.963 0.872 0.846 0.649 0.566 0.540 0.457 1.432

1.309

5%

5%

0.89

0.88

3.18

3.33

0.61

0.59

0.788 0.498 0.576 0.686 0.517 0.582 0.486

0.925 0.846 0.761 0.706 0.639 0.509 0.479 1.089

1.011

4%

5%

0.71

0.76

3.26

3.15

0.77

0.77

0.742 0.817 0.739

0.895 0.846 0.776

SD

the 12 weeks of the course, leading to a decline in lecture attendance. Furthermore, to classify student performance for the second research question, the researchers conducted a cluster analysis on the three academic performance indicators. A two-cluster solution was ultimately accepted as best differentiating the student sample according to performance. The first group comprised 216 students (59.5%) with relatively low scores for all three assessment items and therefore was designated as the “low performer” group, with 136 (65%) being the international students. The other group was labelled as the ‘high performer’ group, as the students of this cluster consistently achieved higher scores in their assessment items. Of the total 147 high performing students, only 57 participants (42%) were international students. While the proportion of domestic students was distributed evenly between the high and low performer groups (72 and 78 students respectively), a greater proportion of the international students belonged to the low performer group (136 students, or 70%). Comparing the two clusters to their average scores on the two assignments and the exam shows that on all three assessment items, the scores of the high performer group were significantly higher than those of the low performer group. T-test further revealed that international and domestic students differed in their academic performance. Significant differences (p < 0.05) were found for all three assessment items, with domestic students scoring higher on assignment 1 (qualitative skills) and the exam (short-answer and multiple-choice) and international students performing better on assignment 2 (quantitative skills). In other words, domestic

Table 2 Regression analysis of impacts self-efficacy on academic performance. Variable

B

Beta

t

Sig.

Time management Statistical theory Lecture behaviour Constant R2=0.065

3.973 −3.950 1.709

0.247 −0.245 0.132

3.698 −3.661 2.186

0.000 0.000 0.029

Adjusted R2=0.057

F=8.261

Sig. 0.000

Dependent variable: academic performance. Independent variable excluded: Using information technology, motivated behaviour.

51

p < 0.05

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Table 3 Paired-sample t-test for self-efficacy of Time 1 and Time2 (overall sample N=363). Efficacy scale

Mean value

Using information technology Motivated behaviour Time management Statistical theory Lecture behaviour Overall

SD

t-test

Time 1

Time 2

Time 1

Time 2

t-value

df

Sig.

3.43 3.30 3.42 3.18 3.26 3.31

3.52 3.38 3.51 3.33 3.15 3.38

0.85 0.60 0.61 0.62 0.77 0.54

0.77 0.62 0.71 0.59 0.77 0.53

2.03 2.58 3.07 5.81 −2.72 2.83

363 363 363 363 363 363

0.043 0.010 0.002 0.000 0.007 0.005

p < 0.05.

students performed better on the assessments requiring strong language skills, whereas international students performed better on the assessment involving numerical and statistical skills. The researchers conducted further ANOVAs across the two groups resulting from the cluster analysis on the overall level of selfefficacy in Time 1 and Time 2. The results presented in Table 4 indicate that prior to the training, overall self-efficacy (F=1.21, p > 0.05) was not statistically different between the low and high performer groups. After the training, the high performer group had a significantly higher self-efficacy score (F=7.50, p < 0.05). To assess the change in self-efficacy in the two groups, the researchers conducted a paired-sample t-test, and the results show that for low performers, the level of self-efficacy is not statistically different between Time 1 and Time 2 (t=0.91, p > 0.05). However, for the high performer group, a significant increase in self-efficacy was evident (t=3.75, p < 0.05).

5. Discussion The research has accomplished the objectives to explore STQS in relation to student academic performance. The self-efficacy model established in this study consists of five factors after removals of 15 items from the original model by Lane et al. (2002). In particular, the measure of competency of statistical theory with 16 items in the original model (Lane, Hall et al., 2004) has been finalised by a scale of 7 items in the current study. Furthermore, measure of “general competencies” has proven to be irrelevant to Australian sample, therefore, was removed from further analysis. The five-factor model established in the current study does not centre on self-efficacy in statistics, but embraces a broader range of task-specific efficacy in which time management is the most important variable to predict academic performance in addition to statistic theory and lecture behaviour. While Lane et al. (2002) developed assessment of students’ self-efficacy using qualitative methods to understand their perception, weakness in psychometrics is inherent, which justified our modification of the scales using a quantitative approach. The five-factor model emerged from our study has tailored the STQS to a new context with different task requirement. The findings reflect that each context of tertiary education is likely to produce its own factor structure is consistent with Bandura's (1997, 2006) argument that self-efficacy measures should be context specific. Further, the findings of this study have demonstrated a need to improve the predictive power of self-efficacy on academic performance. Previous researchers have suggested adopting social cognitive theory, which recommends measuring self-efficacy at a task-specific level (Bandura, 1997; Choi, 2005). While the self-efficacy scale used in this study measured statistical and quantitative analytical skills, it was not designed to measure other academic skills such as writing and semantic interpretation. Therefore, a need exists to adjust the scale to better measure the tasks involved in this course is warranted. The findings of this study indicate that a student's level of self-efficacy varies with the student's performance. Cluster analysis divided the entire cohort into two groups without regard for nationality. While Time 1 survey showed the level of self-efficacy to be similar among the students in the two groups, the Time 2 survey revealed improvement in the level of self-efficacy only among high performers. This significant increase of self-efficacy may indicate that high performers engaged more with the course. The more students study or engage with a course, the more they tend to learn the material and become more adept with it (Carini et al., 2006). Consequently, this finding highlights the issue of engagement among low performers, as student engagement is positively linked to Table 4 ANOVA and t-test of self-efficacy for low and high performer groups. Group

Efficacy (Time 1)

SD

Efficacy (Time 2)

SD

t-value

df

Sig.

Low performer High performer Mean square F Sig

3.29 3.35 0.34 1.21 0.27

0.55 0.51

3.32 3.47 2.14 7.50 0.01

0.53 0.55

0.91 3.75

215 146

0.36 0.00

p < 0.05.

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academic performance. While the overall findings of this study indicate a significant relationship between self-efficacy and academic performance among the domestic student sample, they fail to explain the effect of self-efficacy on academic performance of international students. Although our findings on the Australian domestic student sample are consistent with previous studies (Bong, 2001; Choi, 2005), the samples used in those studies were homogenous, whereas the sample used in this study is relatively diverse. Thus, the results imply that cultural factors might explain the divergence of the outcomes. As this study demonstrates, despite the training provided, academic outcomes of students with low self-efficacy do not improve over time. As a majority of students in this category are international students from Asia (70%), educators should focus their attention on the needs and requirements of this group of students. As the tourism and hospitality industry is an important economic sector in developing Asia, skilled workers with critical thinking and problem solving abilities are thus increasingly essential. Therefore, relating the classroom training to problems of the industry in Asia might be a strategy for strengthening student engagement with the course. Previous research has identified a number of challenges international students face when studying overseas, including issues such as living away from home, adjusting to changes in a different learning environment, and cultural shock. Moreover, students find material such as research methods hard to learn (Lane et al., 2002, Lane, Devonport et al., 2004; Lane, Hall et al., 2004). Difficulties in adapting their approach to learning and the academic adjustment from high school to university may lead first-year students to judge learning tasks to be more difficult than they actually are. International students from Asia might find the subject of research methods overwhelming partly because of a shortage of skills, such as critical thinking or applied statistics, which they have not developed in their home high-school education. A range of discipline-specific bridging courses, such as basic statistics, use of statistical software, and basic theoretical background, should be designed to bring the level of skills and knowledge of international students closer to that of domestic students. The nature of self-efficacy in a research methods course comprises technical skills and knowledge, such as using information technology and statistical theory, in addition to personal skills in time management and students’ motivated behaviour for learning and for lecture. While the improvement in technical skills might be accomplished by a hands-on approach in teaching, the development of students’ soft skills and motivation could evolve from the way students’ achievement is recognized and encouraged. Therefore, the design of the assessments might have to accommodate both perspectives. 6. Conclusion With the growth and development of tourism in Asia, universities in Australia that offer tourism and hospitality undergraduate programs can continue to expect high numbers of international enrolments from these markets. Industry managers with research skills and the ability to analyse tourism information are crucial to the expansion of the tourism and hospitality in developing countries. For this reason, higher education institutions need to continue to improve the internationalization of their curriculum and teaching strategies to cater to this special cohort of students. The results of this study raise genuine issues of concern. In particular, the findings suggest that in the research methods course, significantly more international students fall into the low performer category and fewer into the high performer category. Further investigation can clarify the academic challenges international students face in comparison to domestic students. Limitations of this study offer several opportunities for future research. As the findings are confined to first-year undergraduates in one university and in one particular course, future research might expand the scope and scale of the research to assess the selfefficacy of different cohorts of students in a wider range of courses. In addition, although this research investigated the effects of selfefficacy on academic performance using a repeat survey design, the time between the two surveys may have been too short to analyse the academic performance of students. Furthermore, domestic and international students may not have started the course with a similar background, and these differences could have affected the study's results. In addition, the scale of self-efficacy was developed in a Western context. Therefore, validation of the scale in a new cultural context may be an opportunity for future study. A major limitation of the study was that the authors did not conduct a qualitative analysis of task-specific domain for self-efficacy measures. Hence, further investigation can test the impact of self-efficacy on academic performance using mixed methods or an experimental design method. Despite its limitations, this study contributes by highlighting the importance of the tourism industry in Asia, major challenges confronting international students and their studies —and the need to equip industry managers with research skills. References Bandura, A. (1977). Self-efficacy: toward a unifying theory of behavioral change. 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