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Full Terms & Conditions of access and use can be found at http://www.tandfonline.com/action/journalInformation?journalCode=wttt20 Download by: [Dr Patrick Lee] Date: 20 July 2016, At: 14:53 Journal of Teaching in Travel & Tourism ISSN: 1531-3220 (Print) 1531-3239 (Online) Journal homepage: http://www.tandfonline.com/loi/wttt20 The relation among self-efficacy, learning approaches, and academic performance: an exploratory study Patrick C. Lee & Zhenxing Mao To cite this article: Patrick C. Lee & Zhenxing Mao (2016) The relation among self-efficacy, learning approaches, and academic performance: an exploratory study, Journal of Teaching in Travel & Tourism, 16:3, 178-194, DOI: 10.1080/15313220.2015.1136581 To link to this article: http://dx.doi.org/10.1080/15313220.2015.1136581 Published online: 10 Mar 2016. Submit your article to this journal Article views: 49 View related articles View Crossmark data

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Page 1: The relation among self-efficacy, learning approaches, and ...The relation among self-efficacy, learning approaches, and academic performance: an exploratory study Patrick C. Lee and

Full Terms & Conditions of access and use can be found athttp://www.tandfonline.com/action/journalInformation?journalCode=wttt20

Download by: [Dr Patrick Lee] Date: 20 July 2016, At: 14:53

Journal of Teaching in Travel & Tourism

ISSN: 1531-3220 (Print) 1531-3239 (Online) Journal homepage: http://www.tandfonline.com/loi/wttt20

The relation among self-efficacy, learningapproaches, and academic performance: anexploratory study

Patrick C. Lee & Zhenxing Mao

To cite this article: Patrick C. Lee & Zhenxing Mao (2016) The relation among self-efficacy,learning approaches, and academic performance: an exploratory study, Journal of Teaching inTravel & Tourism, 16:3, 178-194, DOI: 10.1080/15313220.2015.1136581

To link to this article: http://dx.doi.org/10.1080/15313220.2015.1136581

Published online: 10 Mar 2016.

Submit your article to this journal

Article views: 49

View related articles

View Crossmark data

Page 2: The relation among self-efficacy, learning approaches, and ...The relation among self-efficacy, learning approaches, and academic performance: an exploratory study Patrick C. Lee and

The relation among self-efficacy, learning approaches, andacademic performance: an exploratory studyPatrick C. Lee and Zhenxing Mao

The Collins College of Hospitality Management, California State Polytechnic University, Pomona, CA, USA

ABSTRACTSelf-efficacy influences students’ activities, effort and persistence,and it can help predict their motivation and academic perfor-mance. This study attempts to investigate the relationshipbetween self-efficacy, preferred learning methods, and academicperformance under different learning methods in a unique hospi-tality course setting. The results indicate that hospitality manage-ment students prefer a “learn by doing” approach instead ofcomputer-based learning and lecturing. This study concludesthat self-efficacy affects the academic performance in both lectur-ing and practical learning in hospitality education. However, stu-dents’ preference in terms of learning methods does not influencetheir academic performance. Emphasizing “learn by doing” in thehospitality higher education curriculum is recommended in addi-tion to recruiting faculty members with extensive industry experi-ence. Conversely, it is recommended that faculty find the means toincrease students’ self-efficacy when adopting different teachingapproaches.

ARTICLE HISTORYReceived 2 October 2015Accepted 16 December 2015

KEYWORDSSelf-efficacy; academicperformance; hospitalityeducation; learningapproaches

Introduction

Self-efficacy is defined as an individual’s belief in his or her ability to complete a task in aspecific situation, which affects the choice of activities, effort, and persistence of thatindividual (Bandura, 1977). Schunk (1995) stated that self-efficacy can help predictmotivation and performance. People prefer to avoid certain tasks if they have low self-efficacy and readily participate in such tasks if they believe they are capable (eventhough high self-efficacy may not guarantee competent performances if the requiredskills are lacking). Self-efficacy may be a factor that influences persistence. People whofeel successful have been found to work harder and persist longer when faced withdifficulty (Bandura, 1989). Outcome expectations are significant as people are motivatedto act if they believe there are positive outcomes. The perceived value of outcomesrefers to the extent to which individuals desire a certain outcome compared with otheralternatives. Given adequate skills, positive outcome expectations, and personally valuedoutcomes, self-efficacy is perceived to influence the choice and direction of humanbehavior (Bandura, 1989).

CONTACT Patrick C. Lee [email protected]

JOURNAL OF TEACHING IN TRAVEL & TOURISM, 2016VOL. 16, NO. 3, 178–194http://dx.doi.org/10.1080/15313220.2015.1136581

© 2016 Informa UK Limited, trading as Taylor & Francis Group

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The theory of self-efficacy is central to social cognitive theory. When an individualobserves others performing a task or behavior, as well as its consequence, he or sheadopts this experience as a reference, using it as a guide for subsequent behavior(Bandura, 1986). In short, social cognitive theory emphasizes the role of observationallearning with self-efficacy developing from external experiences (Bandura, 1989).According to social cognitive theory (Bandura, 1986), self-efficacy influences goalchoices, the amount of effort spent in achieving a goal, and the level of persistencewhen encountering difficulties. Bandura (1991) confirmed a link between social cogni-tive theory and motivations as well as personal attainments.

Alexander, Lynch, and Murray (2009) viewed hospitality education as a traditionalmodel of teaching. Described as kinesthetic learners, most hospitality managementmajors enjoy learning by doing (Yan & Cheung, 2012). Hsu and Wolfe (2003) foundthat hospitality management students favor an active experimentation style of learning.These students prefer active, sensorial, visual, and sequential learning styles comparedwith reflective, intuitive, verbal, and global learning styles (Lee & Kamp, 2005). Becausemillennial college students use technology at higher rates than other generations (Berk,2009; Junco & Mastrodicasa, 2007), computer-based learning (CBL) via the Internet is thecurrent trend in hospitality education. Hospitality educators prepare future hospitalityprofessionals by effectively and efficiently utilizing CBL in education (Chan & Choi, 2012).Lecturing represents the most common teaching approach in colleges/universities eventhough many researchers claim the method is ineffective (Lammers & Murphy, 2002).

In an academic setting, students’ beliefs in their self-efficacy with regard to learningare found to affect their perceived self-efficacy for academic achievement, which in turninfluences the academic goals they set for themselves and their final academic achieve-ment (Zimmerman, Bandura, & Martinez-Pons, 1992). Students with higher self-efficacyhave higher motivation to study and consequently achieve higher academic resultsaccording to social cognitive theory (Bandura, 1994; Pajaes, 1996). Students may havedifferent levels of self-efficacy and may perform differently according to various teachingmethods. For instance, generation Y students perceive CBL as the most preferablelearning method in an Asian academic setting (Chan & Choi, 2012). In contrast, hospi-tality management students may prefer to interact with professors in the classroom andlaboratory to receive hands-on experience (Stevens, Kitterlin, & Tanner, 2012).

Various studies have been conducted which examine self-efficacy in different disci-plines such as education and educational psychology. Becker and Gable (2009) exam-ined the relationship of self-efficacy with grade point average (GPA), attendance, andretention rate. Lent, Brown, and Hackett (1994) investigated self-efficacy and careerdevelopment. Academic motivation was reviewed in relation to self-efficacy (Pajaes,1996) while academic motivation and academic performance were used to examineself-efficacy (Schunk, 1991, 1995). Puzziferro (2008) investigated academic performanceand the effect of course satisfaction on self-efficacy. Bassi, Steca, Fave, and Caprara(2007) evaluated self-efficacy and the quality of learning experience while Chemers, Hu,and Garcia (2001), as well as Putwain, Sander, and Larkin (2013) looked at self-efficacy,academic performance, and students’ emotions such as feelings of stress and sense ofwell-being.

In hospitality education research, self-efficacy has been examined in relation tocomputer-based learning (Chan & Choi, 2012) and self-directed learning (Lema &

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Agrusa, 2007), internship job satisfaction (Song & Chathoth, 2010), career choices(Chuang, Goh, Stout, & Dellmann-Jenkin, 2007; Song & Chon, 2012), and academicperformance (Lane, Devonport, & Horrell, 2004; Lane, Devonport, Milton, & Williams,2003). Hospitality research on self-efficacy focuses mainly on human resources issues inthe hospitality industry such as career commitment (Niu, 2010), effect on feedback(Reynolds, 2006), recruitment and selection (Karatepe & Karadas, 2015), job satisfaction(Back, Lee, & Abbott, 2011; Jung & Yoon, 2015), motivation (Karatepe, 2015), innovation(Luoh, Tsaur, & Tang, 2014), creativity (Jaiswal & Dhar, 2015), and training (Kim, Erdem,Byun, & Jeong, 2011).

However, very few studies have examined self-efficacy with learning methods andacademic performance in hospitality education. The objective of this study is to examinethe relationship between self-efficacy, preferred learning approaches, and academic per-formance using different teaching methods (i.e., computer based, hands-on/practical, andlecturing methods). This study is unique in that self-efficacy is examined in relation tostudents’ preferred learning approaches and their academic performance. In addition, thisresearch includes a quasi-experimental setting in which three different teaching methodsare used in the same course with the same instructor. Notably, the approach minimizes theeffects of the heterogeneity of individual respondents. This study provides a theoreticalcontribution on the importance of students’ self-efficacy in academic performance inhospitality education. The practical contribution of this study relates to course and curri-culum design and the influence of students’ self-efficacy by the instructors.

Literature review

Social cognitive theory maintains that certain elements of an individual’s knowledgeacquisition derive from observing the behavior of others. Self-efficacy, meanwhile, animportant aspect of social cognitive theory, is developed from external influences, self-perception and understanding the potential outcome of repeated behavior (Bandura,1977, 1988). Pajaes (1996) asserted that social cognitive theory can be used as a frame-work for instructors to improve student motivation, emotional well-being, and academicskills and performance.

Social cognitive theory

Social cognitive theory is a learning theory based on the idea that people learn byreferencing others. People learn by observing others, with the environment, behavior,and cognition as the key factors in influencing development in a reciprocal triadicrelation. Social cognitive theory affirms an important relation among self-efficacy, out-come expectations, and goals (Bandura, 1986). Bandura (1997) explained that environ-ment affects the behaviors of the students and, in turn, the students’ behavior affectstheir environment. The past behavior influences actions in the future. The researcherfurther explained that, when an individual observes a model performing a behavior withthe consequence, the individual remembers the sequence of events and uses thisinformation to guide his/her subsequent behavior (Bandura, 1997). In other words,individuals may choose to copy the behavior of the model if the outcome of thebehavior is rewarded.

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People often strive to achieve positive outcomes when outcome expectations andself-efficacy are related. However, self-efficacy and outcome expectations are occasion-ally confused in the literature. Bandura (1986) argued that the roles of self-efficacy andoutcome expectations are often differentially powerful, with self-efficacy acting as amore influential determinant of behavior. Lent et al. (1994) explained that self-efficacybeliefs concern an individual’s capabilities, i.e., “Can I do this?”, whereas outcomeexpectations involve the imagined consequences of performing particular behaviors,i.e., “If I do this, what will happen?” Bandura (1989) stated that whether self-efficacy andoutcome expectations uniquely affect behavior depends on the nature of a particularactivity. If the performance guarantees specific outcomes, self-efficacy is perceived to bethe predominant causal factor and a partial determinant of outcome expectations.However, if outcomes are only loosely connected to the quality of performance, out-come expectations may make an independent contribution to motivation and behavior.

Goal setting by students plays an important role in influencing their academicachievement. The higher the self-efficacy a student has, the higher the goals he/shewill set (Bandura, 1986; Locke & Latham, 1990). Self-efficacy influences not only students’academic goal setting but also their goal achievements; in addition, the combination ofself-efficacy and goals contributes to subsequent academic attainments (Zimmermanet al., 1992). Schunk (1984, 1989) and Lent, Brown, and Larkin (1984) indicated thatstudents with high academic self-efficacy display greater persistence, effort and interestin their academic learning and performance. Teachers play an important role in increas-ing students’ self-efficacy by providing feedback on their progress (Bandura & Cervone,1983; Schunk, 1986). However, this increase in efficacy can be temporary if the indivi-dual’s efforts have a negative outcome (Schunk, 1995).

Self-efficacy

Self-efficacy is defined as an individual’s belief in his or her ability to complete a task(Gist & Mitchell, 1992; Schunk, 1995). Wood and Bandura (1989) connected self-efficacywith motivation to meet situational demands. Self-efficacy can influence choices con-cerning activities, effort, and achievement. Individuals join activities with different self-efficacy levels obtained from their prior experience, personal qualities, and social net-works. As they complete their tasks, they know how well they are doing, which caninfluence their self-efficacy for continued learning (Schunk, 1995). Self-efficacy is viewedas a tool to anticipate outcomes and performance (Bandura, 1997). Schunk (1995)demonstrated that high self-efficacy does not generate effective performance if theindividual lacks knowledge and skills. Furthermore, self-efficacy is correlated withother self-beliefs, motivation, academic choices, changes, and achievement, althoughthe sizes and relations between these effects depend on how the individual’s self-efficacy and the tasks are operationalized and assessed (Pajaes, 1996). Zimmermanet al. (1992) confirmed that perceived self-efficacy impacts performance directly andindirectly by influencing the self-set goals, the level of goals set, the amount of effortindividuals have exerted, and the individual’s persistence when difficulties are encoun-tered (Bandura & Wood, 1989; Wood & Bandura, 1989).

Self-efficacy affects performance when the perceptions of self-efficacy act as a beha-vioral predictor. Individuals who are labeled as self-diagnostic fear and avoid situations if

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their coping skills are exceeded. These individuals have low aspirations and weakcommitments to the goals pursued (Bandura, 1993). In contrast, people with high self-efficacy attempt to tackle difficult tasks rather than avoid them. Labeled as task-diag-nostic, these individuals set challenging goals, maintain a strong commitment to thesegoals, and overcome barriers. They believe that the level of difficulty is not the primaryreason that they cannot achieve the goals; instead, they believe that insufficient effort orlack of knowledge is the key (Bandura, 1993).

Self-efficacy has been shown to be positively and strongly related to persistence ineffort (Bandura, 1977). The stronger the belief an individual possesses, the greater andmore persistent are his/her efforts (Bandura, 1989). Before individuals make decisionsand act upon their choices, they tend to evaluate and integrate information regardingtheir own capabilities. With stronger perceived self-efficacy, higher goals can be reached,resulting in a firmer commitment (Bandura, 1992). Individuals who perceive themselvesto be highly effective provide sufficient effort that, if well executed, can producesuccessful outcomes. Those who perceive themselves to be less capable initially tendto halt their efforts and ultimately fail in the task, losing faith in their capabilities(Stajkovic & Luthans, 1998). On the other hand, Scouller (1998) suggested that students’preferences regarding different learning methods were associated with different extentof the academic performance.

In an academic setting, perceived self-efficacy motivates academic achievementdirectly and indirectly by influencing individual goals. In other words, self-efficacy andgoals contribute to academic attainments (Zimmerman, 1989). Self-efficacy, which hasbeen adopted to predict academic performance (Hackett & Lent, 1992; Multon, Brown, &Lent, 1991), is a powerful motivational construct to anticipate academic self-beliefs andperformance at different academic levels (Pajaes, 1996). It is also a useful tool forassessing academic motivation (Schunk, 1991) and career choices (Brown, Lent, &Larkin, 1989; Lent, Brown, & Larkin, 1986).

Self-efficacy is shown to be a predictor of academic motivation and performance.Song and Chathoth (2010) examined the self-efficacy of students (internship newco-mers) in a hospitality educational setting with regard to entry-level motivation to workin the industry and subsequent general job satisfaction. They recommended thatmanagers test newcomers’ general self-efficacy levels before socializing them. Self-efficacy was found to be strongly related to career decision while individual careerchoice goals were influenced by general self-efficacy, vocational interests, and person–job fit perception (Song & Chon, 2012). Chuang et al. (2007) examined whether career-decision self-efficacy (CDSE) was a strong predictor of career retention. Chuang (2010)found that the higher the level of CDSE the more likely students were to prefer not toembark on a career in the hospitality industry due to perceived barriers or negativeoutcomes. Apart from the taught modules, self-efficacy was found to be predictive ofthe academic performance of research methodology skills (Lane et al., 2004) as well asdissertation quality (Lane et al., 2003). Lane, Lane, and Cockerton (2003) also argued thatthere is a link between undergraduate performance and success at the postgraduatelevel.

Putwain et al. (2013) reported that academic self-efficacy can predict the academicperformance of psychology students while self-efficacy can predict learning-relatedemotions via academic performance. Self-efficacy may have an indirect effect on

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academic achievement and goals. Fenollar, Román, and Cuestas (2007) found that self-efficacy has a strong but indirect effect on the academic performance of business majorstudents while academic performance may be diminished by bigger class size. A studyacross 49 disciplines by Trigwell, Ashwin, and Milan (2013) revealed a relationshipbetween self-efficacy, academic motivation, academic achievement, and surface learn-ing. However, self-efficacy was not proven to be correlated with student academicperformance in all disciplines. Puzziferro (2008) concluded that time and study environ-ment are significantly related to academic performance but not self-efficacy to onlinetechnologies. Apart from the students themselves instructors have been found to playan important role in developing students’ self-efficacy. Studies have also shown thatincreasing self-efficacy results in better student academic performance. Hence, instruc-tors play an indirect role in influencing students’ GPA, attendance, and retention (Becker& Gable, 2009).

Educational programs based on social cognitive theory have proven to be effective inincreasing students’ self-efficacy (van Dinther, Dochy, & Segers, 2011). Enactive mastery,vicarious experiences, and verbal persuasion have been suggested by instructors toenhance students’ self-efficacy and strengthen their academic abilities (Margolis &McCabe, 2006). Instructors may implement different instructional strategies to improvestudents’ self-efficacy (Siegle & McCoach, 2007) such as outlining lesson objectives,underscoring accomplishments, offering feedback and encouragement, and providingstudent models. The literature suggests that increased interaction in class by instructorsincreases the potential for students’ achievements. It is also suggested that instructorself-efficacy may influence students’ self-efficacy and academic achievements (Ross,1992).

Learning approaches

Lecturing, which is a fact of academic life, is the commonly adopted teaching method incolleges and universities (Lammers & Murphy, 2002; McKeachie, 1994); because of itspracticality, it will remain so. Dorman (2001) stated that the classroom learning environ-ment is strongly associated with academic self-efficacy. Such a strong influence ofinvolvement on self-efficacy suggested that instructors who provide opportunities forstudents to participate in peer and class discussions are likely to elevate their students’confidence levels (Velayutham & Aldridge, 2013). Highly active students who utilize theiranalytical and metacognitive skills to manage this type of learning environment canachieve better learning outcomes (Chemers et al., 2001; Knight & Wood, 2005).Considerable evidence has reported that lecturing is an ineffective pedagogical toolfor promoting conceptual understanding (Alexander, McDaniel, Baldwin, & Money, 2002;Knight & Wood, 2005). However, lecturing can be more conducive and effective tolearning if the fundamental properties of humans as learners are identified(deWinstanley & Bjork, 2002).

Computer-based learning (CBL) has developed methods to track different levels oflearning progress (Oh, 2003). CBL encourages learners to raise questions and sharedifferent ideas in online discussion forums (Dongsong & Lina, 2003). The check-in andcheck-out practice in Second Life (Davis, 1989) and hotel guestroom design in a virtualenvironment (Chan & Choi, 2012) represent examples of CBL in hospitality education.

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Compeau and Higgins (1995) defined computer self-efficacy as “an individual judgmentof one’s capability to use a computer,” which is important to individuals because theirattitudes towards computers influence both the frequency of usage and their intensitywhen utilizing computer programs. Increased performance in computer learning isrelated to higher self-efficacy (Harrison, Kelly, & Hochwarter, 1997). Chan and Choi(2012) indicated that the design of CBL programs can enhance the perception ofstudents towards computer self-efficacy. Chu (2010) noted that learners with higherInternet self-efficacy can gain more knowledge and perform better using CBL.

Tribe (2002) stated that the goal of hospitality education is to prepare students to fillthe industry’s entry-level positions, whereas Ford and LeBruto (1995) emphasized theimportance of hospitality graduates who are able to “roll up their sleeves” within acurriculum based on practical learning. Ladkin (2000) referred to practical learning inhospitality education and identified the traditional focus of hospitality programs asfocusing on the development of “technical operational skills and competencies.”Students who engage with actual management decision-making, actual guests andappropriate levels of pressure can be more adequately prepared for the industry andcan more effectively reflect on working in operational areas (Alexander et al., 2009).Tims, Bakker, and Derks (2014) found positive associations between self-efficacy andproactive job-crafting behaviors. The researchers stated that efficacious employees weremore likely to proactively search for opportunities to learn new things. Another studyshowed that trainees who entered their job with a predisposition for challengingsituations and hard work were more likely to exhibit increased self-efficacy duringtraining. Based on this finding, trainers should implement more techniques that increasethe trainee’s self-efficacy and skill acquisition during the beginning of the training period(Colquitt, LePine, & Noe, 2000).

Following the review of the literature and the purpose of the study, the followinghypotheses are made:

H1. Academic performance is associated with the preferences of learning methods whenlearning self-efficacy is controlled.

H2. Academic performance is affected by learning self-efficacy and the preferences oflearning methods when other variables such as gender and transfer status are controlled.

Methodology

All students who were in the undergraduate program in hospitality management werethe target population of this study. Since the topic concerns preferred learningapproaches, the target respondents had to undergo three teaching approaches (i.e.,computer-based learning, practical learning and lecturing) in one subject with the sameinstructor in one quarter or semester in order to be constant in the learning environ-ments and external factors.

A survey questionnaire and grade book were used to collect data from the studysample, which consisted of senior hospitality management students at a university onthe west coast of the United States. The survey was completed by three separate groups

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of students who took the lodging management seminar course in three academicquarters from Fall 2014 to Spring 2015. This lodging management seminar was a four-unit course that consisted of two lectures and one laboratory every week in a 10-weekquarter. This seminar was a compulsory course for hospitality management studentswho selected the hotel track. Three different teaching approaches (i.e., lectures in aseminar room, computer-based learning of a property management system, and hands-on practice in a lodging property) were included in this course. The total sample size was90 students (29 students in Fall 2014, 32 students in Winter 2015 and 29 students inSpring 2015). The reason for selecting this lodging management seminar course wasbecause students experienced three learning methods in a 10-week quarter. A newgroup of students took the course each quarter with the exact same teaching instruc-tions, methods, materials and instructor. In other words, the learning environmentsremained constant.

The questionnaire had two sections, which were developed and adopted fromSchwarzer (1992, 1993) (Appendix A). In Part A, there were 10 questions regardingself-efficacy in learning (SEL). A four-point Likert scale, which was adopted bySchwarzer (1992, 1993), was used for each question (1 = not at all true, 2 = hardlytrue, 3 = moderately true, and 4 = exactly true); therefore, the scores ranged from 10to 40. Questions regarding SEL by Schwarzer (1992, 1993) were used by Becker andGable (2009). Part B asked students about their preference for each learningapproach, i.e., computer-based learning, hands-on practical learning and face-to-facelecturing. They were asked to rank three learning approaches in order of preference.In addition, certain student information, such as gender and transfer status, were onthe questionnaire. The grade book recorded the scores of each participant whoexperienced all three teaching approaches, and the full score of each approach was100. Examination and projects were adopted as the assessment methods of thesethree approaches. The questionnaires were distributed to the students in the firstclass in Week One, which was voluntary based, whereas all the scores were collectedand recorded at the end of the quarter.

Several statistical techniques were employed to examine the relationship betweenlearning self-efficacy, preferred learning methods, and academic performance (grade)under the three different teaching approaches. First, bivariate correlation was used toreveal the relationship between the learning self-efficacy score and the grades of thethree different learning methods. Second, MANCOVA was utilized to assess whether thestudents’ preferred learning mode had relations with their academic performance, i.e.,the test scores, providing a potential covariate of learning self-efficacy. Third, threeseparate regression analyses were used to examine whether learning self-efficacy andthe degree of the students’ preference with respect to the specific learning mode had aneffect on the grades of the three types of learning methods while the other variablessuch as gender and transfer status were controlled.

Findings

Table 1 describes information regarding student gender, transfer status, and learningmethod preference. As shown, the students were predominantly female, with moretransfers than first-time freshmen, and favored practical learning instruction.

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Table 2 reports information on the test scores under different learning methods and thetotal score of individual learning self-efficacy, collected from the student’s gradebook andthe self-efficacy in learning survey, respectively. It appears that, as referred to in Table 2,students had the highest performance in the practical learning test, followed by thecomputer-based learning test and lecturing test. In addition, the Pearson correlation coeffi-cients among all test scores and total self-efficacy score were calculated. Although there wasno relation between self-efficacy and the computer-based learning score, self-efficacy wasstatistically significantly correlated with both the lecturing and practical learning scores.

Multivariate analysis of covariance (MANCOVA) was conducted to examine the differ-ence of learning method preference on test scores under different learning methods(i.e., lecturing, practical learning, and computer-based learning) while controlling theeffect of learning self-efficacy. Table 3 presents the results. No significant main effect wasfound (λ = 0.920, F (6,168) = 1.189, p < 0.05, ηp

2 = 0.041), although the covariate (learningself-efficacy) was statistically significantly related to the combined test scores of face-to-face, hands-on, and computer-based tests. No test score was significantly associatedwith the preference of learning methods when the effect of learning self-efficacy wasfactored out. Therefore, H1, Academic performance is associated with the preferences oflearning methods when learning self-efficacy is controlled, was not supported.

Table 1. Student profile information.Student Frequency (n) Percentage (%)

Gender:Male 28 31.1Female 62 68.9Transfer status:First-time freshmen 35 38.9Transfer student 55 61.1Learning method preference (first choice):Lecturing instruction 27 30.0Practical learning instruction 57 63.3Computer-based learning instruction 6 6.7

Table 2. Test scores, self-efficacy and correlation table.Variable Mean SD 1 2 3

1. Lecturing test score 70.80 9.7402. Practical learning test score 89.69 9.018 0.1833. Computer-based learning test score 83.74 16.536 −0.067 0.261*4. Self-efficacy score 34.41 4.025 0.412** 0.269* 0.041

Notes: **p < 0.01; *p < 0.05.

Table 3. Results of MANCOVA.Effect Value F Hypo. df Error df Sig. Partial eta squared

Self-efficacy (covariate) Pillai’s Trace 0.208 70.374** 3 84 0.000 0.208Wilks’ Lambda 0.792 70.374** 3 84 0.000 0.208Hotelling’s Trace 0.263 70.374** 3 84 0.000 0.208Roy’s Largest Root 0.263 70.374** 3 84 0.000 0.208

Preference Pillai’s Trace 0.081 10.191 6 170 0.313 0.040Wilks’ Lambda 0.920 10.189 6 168 0.314 0.041Hotelling’s Trace 0.086 10.187 6 166 0.316 0.041Roy’s Largest Root 0.073 20.065 3 85 0.111 0.068

Note: **p < 0.01.

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Table 4 presents the summarized results of three regression analyses. Each test scoreunder a different learning method was separately regressed against student gender (indummy coding), transfer status (in dummy coding), learning method preference (indummy coding) and learning self-efficacy. Self-efficacy did not statistically significantlyimpact on the computer-based learning test score but did impact on lecturing andpractical learning test scores. The results also echoed the findings from Table 3 thatpreferred learning methods appeared to have no significant difference regarding stu-dents’ test scores. Therefore, H2, Academic performance is affected by learning self-efficacy, and the preferences of learning methods when other factors such as genderand transfer status are controlled, was partially supported for both face-to-face andhands-on learning methods.

Discussion

Practical learning is a preferred learning approach, from the opinions of hospitalitymanagement students. Lecturing is their second priority, and CBL is the least preferablelearning approach. These findings confirm the fact that students in the hospitalitymanagement programs are kinesthetic learners (Stevens et al., 2012). Yan and Cheung(2012) found the importance of experiential learning in the hotel schools for preparingstudents with practical skills while the authors also emphasized the recognition fromhospitality educators on the adoption of experiential learning. Hospitality managementstudents prefer active and sensing learning styles (Su, 2012) and they favor activeexperimentation (Hsu & Wolfe, 2003). They have a preference for active learning versusreflective learning (Green & Sammons, 2014). However, this preference is different fromwhat Moskal, Dziuban, Upchurch, Hartman, and Truman (2006) as well as Oh and Reeves(2013) discovered, which was that generation Y students perceive CBL as the mostpreferable learning method.

Although there is no relation between self-efficacy and CBL scores, self-efficacystatistically significantly affected both lecturing and practical learning scores. This find-ing readdresses the issue that self-efficacy of technology was not correlated withstudent academic performance (Puzziferro, 2008). On the other hand, students whopossess higher self-efficacy in lecturing and practical learning can perform better andachieve higher academic performance. This also reaffirms the social cognitive theoryregarding the relation among self-efficacy, outcome expectations, and goals (Bandura,1986). Therefore, self-efficacy influences the students’ academic performance relative tolecturing (Dorman, 2001) and practical learning (Tims et al., 2014). This supports the

Table 4. Regression results (n = 90).Face-to-face test score B (S.E.) Hands-on test score B (S.E.) Computer test score B (S.E.)

Gender 3.636 (1.987) −2.218 (1.990) 6.553 (3.843)Transfer status −4.522* (1.918) −0.792 (1.921) 2.733 (3.709)Face-to-face dummy 2.799 (3.893) −7.338 (3.898) 2.397 (7.527)Hands-on dummy 2.627 (3.744) −4.207 (3.749) 4.675 (7.239)Self-efficacy 0.918** (0.229) 0.636** (0.229) 0.064 (0.443)Adj-R2 0.218 0.086 −0.014F(5,84) 5.976** 2.667* 0.759

Note: **p < 0.01; *p < 0.05.

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findings that self-efficacy can help predict and impact academic performance (Bandura,1994, 1997; Schunk, 1995). However, the preference of learning methods appeared tohave no significant difference in terms of the students’ test scores when the impact ofself-efficacy was considered.

Conclusions and implications

This research provides additional evidence that students’ preferences of learning meth-ods do not appear to influence their academic performance. Hospitality managementstudents continue to prefer “learn by doing” as their learning approach and, althoughthey are generation Y, CBL is not their preferred approach. This study finds that students’preference of learning methods does not influence their academic performance.However, in hospitality education, self-efficacy does affect the academic performance,specifically in lecturing and practical learning. According to social cognitive theory (Lentet al., 1994), self-efficacy can be used as a predictor and a motivator of hospitalitystudents. In this study, it has emphasized the importance of self-efficacy on the aca-demic performance of both lecturing and practical learning.

A couple of practical implications for hospitality education can be derived from thisstudy. On one hand, significantly emphasizing “learn by doing” in the curriculum isrecommended. Although Chan and Choi (2012) suggested utilizing CBL to preparefuture hospitality leaders, because of students’ preference and natural “hospitality,”sufficient opportunity for practical learning within the college (Ladkin, 2000) and colla-boration with industry partners for internships and/or hands-on experience should bethe top priority. On the other hand, recruiting faculty members with extensive experi-ence in the hospitality industry and learning in well-established training facilities such astraining restaurants and hotels can help hospitality management students learn andperform better (Alexander et al., 2009).

In addition, faculty plays an important role in increasing students’ self-efficacy,particularly in lecturing and practical learning. Providing feedback and participating inpeer and class discussions can help increase self-efficacy (Velayutham & Aldridge,2013). Margolis and McCabe (2006) recommended that enactive mastery, vicariousexperiences and verbal persuasion be adopted by the instructors in the class tostrengthen the self-efficacy of the students. On the other hand, instructors canchange their instructional strategies to improve students’ self-efficacy (Siegle &McCoach, 2007). Faculty also must establish methods to explore the self-efficacy ofstudents in different learning methods to design the courses and to improve stu-dents’ learning outcomes in hospitality education. For example, faculty can adopt aquestionnaire concerning general self-efficacy or self-efficacy on a specific learningapproach to examine students’ self-efficacy. It would be beneficial to conduct thissurvey on the first day of the class to examine the self-efficacy of students in differentlearning methods.

There are several limitations associated with this research. The comparativelysmall sample size, i.e., 90 students from one university, involved in this survey isthe first limitation. Including more students from more courses and from moreuniversities to ensure that the results are more representative, generalizable andreliable is suggested. Second, the demographic of the students is homogeneous.

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Exploring the differences in race, age, ethnicity as well as hotel industry experienceis recommended for other control variables. In addition, the learning self-efficacyquestionnaire may not work well using computer-based instructions. A new self-efficacy questionnaire based on computer-based instructions (or online learning)should be developed in the future. In addition, there is a lot of research in the areaof learning styles of the students, which has not been investigated with therespondents in this study. The learning styles of the students may affect theirself-efficacy, academic motivation and academic performance. This is an interestingaspect to be explored in the future. Finally, the classroom environment created bythe instructors (van Dinther et al., 2011) and even some personal factors of theinstructors such as the passion for teaching and the preference of teaching meth-ods can affect the self-efficacy of the students, which again can be explored infuture.

Disclosure statement

No potential conflict of interest was reported by the authors.

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Appendix

Appendix A. Questions on self-efficacy in learning

Please indicate the amount of your agreement with the following ten statements.

Not At AllTrue(1)

HardlyTrue(2)

ModeratelyTrue(3)

ExactlyTrue(4)

1. I am certain I can manage the problems in my life so I canfocus on my studies.

* * * *

2. I am certain I can obtain financial aid to pay tuition. * * * *3. I am certain I can find the time to do all my homework. * * * *4. I am certain my family and friends want me to succeed incollege.

* * * *

5. I am certain I can control the stress in my life so I can do well inschool.

* * * *

6. I will choose school over work if schedules conflict. * * * *7. I will always find a way to get to class. * * * *8. I am positive I can earn enough money to keep attending. * * * *9. I know I will get a good position when I graduate if I do well. * * * *10. I will take care of my health so I can achieve better grades. * * * *

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