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Accounting Education: an international journal Vol. 18, No. 3, 233 253, June 2009 Understanding Students Choice of Academic Majors: A Longitudinal Analysis LIN MEI TAN and FAWZI LASWAD Massey University, New Zealand Received: July 2007 Revised: December 2007 Accepted: December 2007 ABSTRACT This study extends Tan and Laswad s 2006a study by surveying the same students at the beginning and end of their degree programme at a New Zealand university regarding their major choices, beliefs and attitudes towards majoring in or a non- discipline. Using the theory of planned behaviour, the objectives are to compare intentions with behaviour in relation to majoring in and other business disciplines and to examine changes in attitudes and beliefs between the beginning and end of university study. The results indicate many students choose majors that are consistent with their intentions at the beginning of their university study but some students also change their intentions and major in other areas. Some attitudes and beliefs change over time but the major choice tends to remain relatively stable. The results suggest that a higher proportion of students than other business students decide on their major prior to university study. This may suggest that promoting as a career may need to focus on pre-university students. KEY WORDS: behaviour Accounting major, education, career, theory of planned Introduction Over the past two decades, significant research in education has been devoted to understanding how and why students major in an or a non- discipline. Such research is pertinent particularly when the number and quality of students majoring in is declining (Ashworth, 1969; Adams et al., 1994; Karnes et al., 1997; Stice and Swain, 1997; Saemann and Crooker, 1999; Mauldin et al., 2000; Heaton, 1999; Fedoryshyn and Tyson, 2003) and when firms are facing difficulties in recruiting and retaining staff (Ahmed et al., 1997; Marshall, 2003). Correspondence Address: Ms Lin Mei Tan, School of Accountancy, Massey University, Palmerston North, Private Bag 11222, New Zealand. Email: l.m.tan@massey.ac.nz 0963-9284 Print/1468-4489 Online/09/030233 21 # 2009 Taylor & Francis DOI: 10.1080/09639280802009108
234 L. M. Tan and F. Laswad Prior research on students choice of major has identified a multitude of factors that could influence students major decisions. They include: availability of employment and earnings (Paolillo and Estes, 1982; Adams et al., 1994; AuYeung and Sands, 1997; Lowe and Simons, 1997), job satisfaction, aptitude, and interest in subject areas (Paolillo and Estes, 1982; Gul et al., 1989; AuYeung and Sands, 1997), and the influence of students teachers and parents (Paolillo and Estes, 1982; Cangelosi et al., 1985; Gul et al., 1989; Geiger and Ogilby, 2000). Studies that surveyed students perceptions were primarily conducted at specific points in time, such as in the first, second, third, or fourth year of undergraduate study, and focused on either students chosen major or their intention to major in a particular discipline. Apart from a few studies (such as by Cohen and Hanno, 1993; Allen, 2004; Tan and Laswad, 2006a), many prior studies lack a conceptual framework, making it difficult to generalise predictions or explain career choice decisions (Cohen and Hanno, 1993, p. 221). The theory of planned behaviour (Ajzen, 1988) is one conceptual framework that has been used to provide a better understanding of the factors that influence students choice of major. This theory has been used successfully in explaining intentions and behaviours in various decision-making situations such as exercising, purchasing goods, etc. Tan and Laswad (2006a) used this theory to examine first year students intentions to major in and other business disciplines. They found that students attitudes, subjective norms and perceptions of behavioural control influence their intention to major in or other business disciplines. However, they did not examine the relationship between intention and behaviour because students behaviour (i.e. ultimate major) could not be ascertained in their cross-sectional study, as the data was collected at the beginning of the introductory course. The studies conducted by Allen (2004) and Cohen and Hanno (1993) were also cross-sectional and used surrogate measures of intention that were not antecedents of choosing a major. They further assumed that students would not change their major intentions during the students academic career. We extend Tan and Laswad s (2006a) research by conducting a longitudinal study that allows us to (i) examine the students attitudes and beliefs with respect to intentions to major in a business discipline ( or non-) at the start of their first course in that is mandatory for all business students; and (ii) use this information to compare with their actual major choices three years later. Such a design not only allows us to test the theory of planned behaviour but also to understand whether there are changes in the students attitudes and beliefs about and non- disciplines over time as the students mature in terms of experience and knowledge. Students intentions may change because of changes in attitudes and beliefs, and the ultimate behaviour may therefore differ from their earlier intentions. The results of this study extend our understanding of students major choices and provide insights into ways to attract students or improve their attitudes and beliefs toward the study of as an academic discipline. This paper is organised as follows. The next section provides a review of the literature that examines the various influences on students choice of academic major. This is followed by an overview of the theory of planned behaviour, the research method, the data and the results. The final section discusses the conclusions and limitations of the study.
Understanding Students Choice of Academic Majors 235 Literature Review Considerable literature has emerged which examines the timing of students career choices and the major influences on their choices. The following is a brief review of relevant studies. 1 Students vary as to when they make their academic major choices. Some students select their intended major prior to commencing university study (Karnes et al., 1997; Jackman and Hollingworth, 2005), while others make such decisions during or at the completion of their first or second year of tertiary education (Hermanson and Hermanson, 1995; Mauldin et al., 2000). Some students may even change their major in a later stage of their academic study when they realise that their intended major or chosen major does not suit them for various reasons. A number of factors influence students discipline choice. Prior studies suggest that students discipline choice is heavily influenced by earnings potential and job market conditions or opportunities (Paolillo and Estes, 1982; Gul et al., 1989; Inman et al., 1989; Adams et al., 1994; Felton et al., 1994; AuYeung and Sands, 1997; Lowe and Simons, 1997; Mauldin et al., 2000). For example, Ahmed et al. (1997) found that New Zealand students who intend to pursue a career in chartered accountancy place significantly greater importance on financial factors. Lowe and Simons (1997) findings in the USA also indicate that future earnings are the most important influence for, finance and management majors. Students experiences with uninteresting coursework and rote learning may also discourage the best students from pursuing an major (Imman et al., 1989). Students are more likely to choose an major when they consider interesting and enjoyable (Saeman and Crooker, 1999). Students performance in the introductory course is another possible factor that may influence their major choice, as students tend to perceive success in the introductory course as a signal that they have an aptitude for (Cohen and Hanno, 1993; Geiger and Ogilby, 2000). Poor performance, on the other hand, may be perceived by students as a signal that they may not have the required aptitude for and, therefore, should pursue a non- major. However, some studies (such as by Adams et al., 1994; Allen, 2004; Stice and Swain, 1997) suggest that course performance is not significantly related to high performing students decisions to major in. The intrinsic appeal of the job itself, such as job satisfaction, opportunity to be creative, autonomy, intellect, and a challenging and dynamic working environment, is another factor that may influence students academic major choice. A number of studies indicate that job satisfaction, for instance, is important in students discipline choice (Paolillo and Estes, 1982; Gul et al., 1989; AuYeung and Sands, 1997) but not as important as many other factors (Paolillo and Estes, 1982; Felton et al., 1994). Prior research suggests that college students choose specific majors that they perceive as being compatible with their particular personal styles (Gul, 1986; Wolk and Cates, 1994) or their own aptitude for the subject (Paolillo and Estes, 1982; Gul et al., 1989; AuYeung and Sands, 1997). Adams et al. (1994) and Mauldin et al. (2000) indicate that genuine interest in the subject is an important selection factor. Skills and background in mathematics were also identified as factors that could facilitate or hinder students decisions to major in (Cohen and Hanno, 1993). In making career choices, students may be further influenced by their instructors, parents, relatives, friends, or high school teachers. A secondary school career counsellor or adviser may shape students perceptions of and the profession (Marshall, 2003). However, empirical evidence shows mixed results. Some
236 L. M. Tan and F. Laswad studies suggest that teachers or instructors do not play a significant role in students choice of majors (see Cangelosi et al., 1985; Gul et al., 1989) whereas other studies (Paolillo and Estes, 1982; Hermanson and Hermanson, 1995; Geiger and Ogilby, 2000; Mauldin et al., 2000) suggest that individual instructors have a profound influence on students decisions to major in. Empirical evidence regarding the influence of referents, other than instructors, was also inconclusive. Cangelosi et al. (1985) found that friends do not influence most students toward or away from careers. Gul et al. (1989) note that parental influence is not a significant factor in students discipline choice decisions. Similarly, Paolillo and Estes (1982), Hermanson and Hermanson (1995), and Lowe and Simons (1997) indicate that friends, parents and high school teachers are less influential factors in students major choices. In contrast, Inman et al. (1989) and Mauldin et al. (2000) found that parents followed by instructors, have a strong influence on students choice of majors. One of the main deterrents to majoring in accountancy could be the poor public perception of the stereotypical accountant as dreary, cautious and boring number crunchers (Luscombe, 1988; Horowitz and Riley, 1990; Fisher and Murphy, 1995; Hermanson and Hermanson, 1995; Cohen and Hanno, 1993). Such pre-conceived ideas can result in college students self-selection into or out of certain majors. Accountants work is also perceived by students to be excessively time-consuming and unpleasant (Mauldin et al., 2000), or as being narrow, audit-focused and restricted to core (Marshall, 2003). The literature reviewed above indicates that a number of factors may influence students in choosing their academic majors. Moreover, students may regard some factors as more important than others and these factors may have a different impact in different cultures (AuYeung and Sands, 1997). The inconsistencies in results obtained from prior research make it difficult to draw generalisations about students choices of majors. A theoretical framework would provide a better understanding of the impact of various factors on students academic decisions. Theory of Planned Behaviour The theory of planned behaviour (TPB) developed by Ajzen (1988) is an extension of the theory of reasoned action (TRA) developed by Fishbein and Ajzen (1975). Both models consider attitudes, subjective norms, intentions and target behaviour. In summary, the TPB posits that people act in accordance with their intentions and perceptions of control over the behaviour, while intentions in turn are influenced by attitudes towards the behaviour, subjective norms, and perceptions of behavioural control (Ajzen, 2001, p. 43). The more favourable the attitude and subjective norm and the greater the perceived behavioural control are, the greater the likelihood the person s intention to perform the behaviour. Figure 1 depicts the three factors that determine intentions, which lead to behaviour. Individual attitudes toward the behaviour reflect the degree to which a person has a positive or negative perception of the behaviour. Attitudes about behaviour are determined by a person s beliefs about the consequences of performing that behaviour, and each belief is weighted by the subjective value of the outcome in question (Ajzen, 2001; Tan and Laswad, 2006a). Subjective norms, however, are linked to a person s perceptions of social pressure to perform or not perform the behaviour. It reflects a person s beliefs that other individuals or groups think he or she should perform the behaviour (i.e. normative beliefs). These normative beliefs, in combination with a person s motivation to comply with the different
Understanding Students Choice of Academic Majors 237 Figure 1. Ajzen s (1988) theory of planned behaviour referents, determine the prevailing subjective norm regarding the behaviour (Ajzen, 2001; Tan and Laswad, 2006a). As many factors can interfere with an individual s control over an intended behaviour (Cohen and Hanno, 1993, p. 222), Ajzen s (1988) theory of planned behaviour refines the TRA by including the concept of behavioural control. Unlike attitude and subjective norms, this third factor, perceived behavioural control, is a non-motivational factor and represents the degree of control a person has over performance of the behaviour. To the extent that people are realistic in their judgements of behaviour difficulties, Ajzen posits that a measure of perceived behavioural control can act as a surrogate for actual control. The theory further assumes that perceived behavioural control has motivational implications for intentions. Those who believe that they have neither the means nor the opportunities to perform certain behaviour are unlikely to form strong behavioural intentions to engage in it, even if they hold favourable attitudes toward the behaviour and believe that important individuals would approve of their performing such behaviour (Ajzen, 1988, p. 134). The TPB, therefore, provides a suitable framework for examining the factors that influence students academic major decisions, and it has been used by Tan and Laswad (2006a), Allen (2004), and Cohen and Hanno (1993), in their studies of students academic major choices or intentions. Based on the TPB framework, this study extends Tan and Laswad (2006a) by comparing intentions with behaviour and examining whether specific personal, referents, and control factors influence students intentions and ultimate decisions to major or not to major in. Research Method Subjects Prior studies have used a cross-sectional design to examine students major decisions, either using /non- major students or graduates who have completed their career choice process (Cherry and Reckers, 1993; Cohen and Hanno, 1993; Ahmed et al., 1997). This study, however, provides a longitudinal examination of students attitudes, beliefs and major decisions. Data about attitudes, beliefs and major intentions were collected from business students in their first year at university when they enrolled in the introductory course, a compulsory course for the business degree. Data was also collected in the third year of study for the same students, when most students have confirmed their major choices. 2 Questionnaire The questionnaire contained items designed to assess the three major constructs in the TPB: attitudes, subjective norm and perceived behavioural control. These constructs were assessed by means of several direct questions, which were modelled on Cohen
238 L. M. Tan and F. Laswad and Hanno s (1993) questionnaire, with some minor modifications to reflect the New Zealand academic environment. Prior studies have identified these constructs as having significant effects on students choice of academic major or career (such as by Paolillo and Estes, 1982; Gul et al., 1989; Inman et al., 1989; Adams et al., 1994; Felton et al., 1994; AuYeung and Sands, 1997; Lowe and Simons, 1997; Mauldin et al., 2000). The questionnaire was divided into two parts. Part 1 of the questionnaire solicited information about their major. In the first year, students were asked about the discipline in which they intended to major. In the third year survey, students were asked their study major, the timing of their major choice and the reasons for changing their major if they did so. Part 2 of the questionnaire was further divided into Sections A, B and C. Section A sought the respondents attitudes (personal perceptions) to particular outcomes (see Table 1) and the likelihood of achieving those outcomes if they major in or non- disciplines. The steps involved: 1. evaluating 10 outcome statements on a five-point scale (1 ¼ extremely bad to 5 ¼ extremely good); 2. indicating the likelihood that each of the outcomes would occur if they choose as their major, using a five-point scale (1 ¼ very unlikely to 5 ¼ very likely); 3. indicating the likelihood that each of the outcomes would occur if they choose a non major, using a five-point scale (1 ¼ very unlikely to 5 ¼ very likely). Section B sought the respondents normative perceptions of the referents views of their choice of major and the degree of importance they placed on the referents views. Using a five-point scale (1 ¼ strongly disagree to 5 ¼ strongly agree), respondents were asked to indicate their agreement or disagreement with the statement that their parents/other relatives/friends/career counsellor (see Table 1) thought that they should or should not major in. To ascertain their motivation to comply with the above referents, respondents were further asked to indicate how important that person s opinion is to them using a five-point scale (1 ¼ very unimportant to 5 ¼ very important). Section C ascertained the respondents perceived behavioural control. Respondents were asked to indicate the extent of their agreement on a five-point scale (1 ¼ strongly disagree to 5 ¼ strongly agree) with each statement that relates to control beliefs (see Table 1). Research Design As the TPB requires measurement of students differential perceptions of the three constructs (personal, referents, and control) towards academic major choices, the differential score as used by Cohen and Hanno (1993) and Allen (2004) was adopted. For personal beliefs, respondents evaluations of each of the ten outcomes were first multiplied by the likelihood of the outcome occurring if was their chosen major. They were then summed (a) to provide a measure of the beliefs toward choosing as a major. The ten outcome evaluations were also multiplied by the likelihood of the outcome occurring if a non- major was chosen. The sum (b) of these ten outcomes provides a measure of the beliefs towards choosing a non- major. A differential score is obtained by deducting b from a. Since the theory predicts that positive scores are associated with choice of major, a positive differential score indicates that the student is more favourable towards the choice of as an academic major. Differential scores for perception of important people (referents) and control beliefs were computed in a similar manner.
Understanding Students Choice of Academic Majors 239 Table 1. Factors (outcomes) used to examine students intentions to major in or other business disciplines Section A Personal Perception Career that deals with a lot of numbers Allows one to earn a high initial salary Broad exposure to business Allows one a chance to establish a private practice Career that is challenging Career with high future earnings and advancement potential Major that demands a heavy workload Career that provides a high social status Major that prepares one for a career with more job opportunities An academic major that is boring Section B Important Referents Parents Relative(s) Close friend(s) Career counsellor/adviser Section C Perceived Control Required workload Skills and background in mathematics Performance in course Job opportunities Interest in Less involvement in extracurricular activities A path analysis, which is an extension of the regression model, was used to test the TPB in predicting students choice of major as shown in Figure 1. The model is specified by the following path equations: Model 1: Major Choice ¼ a 0 þ b 1 Major Intention þ b 2 Control þ ] Model 2: Major Intention ¼ a 0 þ b 1 Personal þ b 2 Referents 1 þ b 3 Control 1 þ ] where: Major intention ¼ the self-reported intention to major in an or non- discipline at the beginning of first year, which assumes a value of 1 if the respondent intends to major in and 0 otherwise Major choice ¼ the major choice in an or non- discipline at the end of third year, which assumes a value of 1 if the respondent majors in and 0 otherwise Personal ¼ the differential personal perception of choosing an versus a non major at the beginning of first year Referents ¼ the differential perception of important referents about an and a non- major at the beginning of first year Control ¼ the perceived differential control over choosing an or a non major at the beginning of first year Data Collection The study was conducted in a large multi-campus New Zealand University with 1422 students enrolled in the introductory course. The first survey was conducted in
240 L. M. Tan and F. Laswad class at the beginning of the introductory course and 1009 students participated, giving a response rate of 71%. The second survey was conducted three years later when most students were in their third and final year of study. Since it would be difficult to conduct the survey in class for the same group of students, as they would be taking different courses depending on their majors, the questionnaire was posted to all students who participated in the first year study. Out of the 1009 questionnaires posted, 225 questionnaires were returned undelivered (either due to students changing address, dropping out of study without official notification, or graduating). 304 respondents returned completed questionnaires giving a usable response rate of 39%. Table 2 provides the respondents demographics. About 47% of the respondents were international students. Most respondents (87%) were between the ages of 18 and 25. There was also about an equal balance of female (54%) and male (46%) students. A comparison between the self reported major intentions in the first year and the actual behaviour in relation to major choice reveals that of the 68 students who intended to major in in the first year, only 37 students (54%) did major in. Alternatively, of the 236 students who had indicated their intention to major in non- disciplines, 24 (10%) chose to major in. Table 2 also shows when students decided on their majors. A high proportion of students selected their majors prior to commencing university study. In particular, Table 2. Demographic characteristics of respondents Accounting majors Non- majors Total n ¼ 61 n ¼ 243 n ¼ 304 Gender Female 41 123 164 Male 20 120 140 Nationality New Zealander 35 125 160 International students 26 118 144 Age groupings 18220 25 104 129 21225 18 117 135 26229 8 10 18 30239 9 9 18 40249 1 3 4 Intention to major In as indicated in first year In non- as indicated in first year 37 31 68 24 212 236 When major decided Before starting study at university 39 64 103 By end of semester of 5 33 38 year study By end of first year of study 12 123 135 By end of second year of study 3 19 22 Other times 2 4 6
Understanding Students Choice of Academic Majors 241 64% of majors reported that they have selected their major prior to university compared with only 26% for non- majors. This may be attributed to the visibility of an career in comparison with other business disciplines. Results The Models To test the prediction of the TPB, a path analysis was conducted. The Chi square statistic for goodness of fit is 41.275 with three degrees of freedom and a P value of 0.001. As shown in Figure 2, both students intention to major in a particular discipline and perceived behavioural control predicted students choice of major (Model 1). These two factors accounted for 32% of the variance in major choice. The coefficients (b ¼ Beta) for the independent variables, personal and referents, in Model 2 are positive and significantly different from zero (P, 0.001). However, the perceived control variable is not significant which is inconsistent with prior results. Thus, only two of the three factors made significant contributions to the prediction of intentions to major: personal factors (P, 0.01) and referents (P, 0.001). 3 The perceived behavioural control as suggested in the TPB literature requires one to be able to make a realistic judgment of a behaviour difficulty (Davies et al., 2002). Table 3 shows the correlation coefficients of the three constructs (the independent variables) in Model 2 for all respondents. All three constructs were significantly correlated with major intention (P, 0.01). Table 4 reports the overall mean response for the constructs in Model 2 for intention to major in and non- disciplines. The results show that, for each construct, the mean response for majors as predicted was higher than the mean response for non- majors and the difference was significant (P, 0.001). Figure 2. Theory of planned behaviour. Significant at the 5% level; Significant at the 1% level; Significant at the 0.1% level
242 L. M. Tan and F. Laswad Table 3. Correlations: Major intentions and constructs at first year Model 2: Major intention ¼ a 0 þ b 1 Personal þ b 2 Referents 1 þ b 3 Control 1 þ ] Differential perceived control Differential personal perceptions Differential perception of referents Major intentions 0.275 0.303 0.391 Differential perceived 0.281 0.375 control Differential personal perception 0.380 Significant at 0.1% level. Accounting Versus Non- Majors In this section, we examine each construct at the beginning of first year in greater depth. This provides further insights into the specific beliefs and attitudes that discriminate between students who indicated that they intended to major in, and students who indicated that they intended to major in other business disciplines. Table 5 presents the mean differential beliefs and the motivation to comply with referents for students who intended to major in and non- disciplines in their first year. Positive scores indicate normative beliefs that favour intentions to major in while negative scores indicate normative beliefs that favour a business area other than. With respect to the differential normative beliefs, Table 5 (columns 1 and 2) shows that students who intended to major in believed that each referent (parents, other relatives, friends, and career advisors and counsellors) thought that they should major in, while students who intended to major in non- disciplines believed that each referent thought that they should major in a non- discipline. The t-test results indicate significant differences between the two groups beliefs. This result is consistent with prior findings (Cohen and Hanno, 1993; Allen, 2004; Tan and Laswad, 2006a). Table 4. Mean (and standard error of the mean) response major intentions and construct at first year Intention Intention non-; Mean difference a Sum personal perceptions 15.000 20.1552 15.155 (2.893) (1.466) P ¼ 0 Sum perception of referents 7.5000 25.8904 13.390 (1.535) (0.879) P ¼ 0 Sum perceived control 20.0308 24.238 3.028 (0.535) (0.303) P ¼ 0 a Tests for differences in means are based on t-tests.
Understanding Students Choice of Academic Majors 243 Table 5. Mean differential perception of referents and motivations to comply at first year for students intending to major in versus non- Differential perceptions Motivation to comply Referents Intention Intention non- Intention Intention non- Parents 0.791 20.461 3.51 3.39 Other relatives 0.403 20.389 2.93 2.86 Friends 0.462 20.646 3.09 3.05 Career advisors and counsellors 0.296 20.452 3.31 3.24 Tests for differences in means are based on t-tests. Significance at the 0.1% level. 1 ¼ very unimportant to 5 ¼ very important. Table 5 (columns 3 and 4) shows the differences in motivation to comply with each referent. All four referents views were considered as being important to the students; parents views were ranked as most important followed by career advisors and friends. The t-test results indicate no significant differences between the two groups motivation to comply with referents. Table 6 presents the differential personal beliefs and outcome evaluations for first year students intending to major in or non-. A positive differential score indicates that choosing is more likely to lead to the specific outcome than choosing some other business major, while the opposite is true for a negative differential belief score. As shown in Table 6, there are some significant differences between students who intended to major in and students who intended to major in other business disciplines. Although students who intended to major in perceived a higher likelihood that would lead to such outcomes, both groups perceived that, as a major was more likely to lead to a career that deals with numbers and demands a heavy workload. This suggests that those who intended to major in non- disciplines have not chosen as their intended major because they perceived as too numbers-oriented and too demanding in terms of workload. Both groups perceived that their major would lead to a high initial salary and future earnings, provide them with a chance to establish a private practice, give broad exposure to business, and offer a challenging career and greater job opportunities. The t-tests indicate significant differences in the two groups perceptions. Interestingly, students who intended to major in non- believed significantly more than those who intended to major in that was likely to be a boring academic major. Such perceptions might have further discouraged them from choosing as their intended major. Overall, the differential outcome beliefs were similar to the results of Cohen and Hanno (1993), Allen (2004), and Tan and Laswad (2006a). In comparing the outcome evaluation scores (columns 3 and 4) in Table 6, students who intended to major in perceived a career in a field that deals with numbers, high initial salary, and entering a career that provides high social status as significantly (P, 0.001) more favourable than did non- majors. Students who intended to
244 L. M. Tan and F. Laswad Table 6. Mean differential personal beliefs and outcome evaluations at first year for students intending to major in versus non- Differential perceptions Outcome evaluations A career that deals with numbers Earning a high initial salary A field with broad exposure to business A career with a chance to establish a private practice A career that is challenging An academic major that is boring A career with high future earnings A major that demands a heavy workload A career that provides high social status A major that prepares for a career with greater job opportunities Intention Tests for differences in means are based on t-tests. Significant at the 5% level. Significant at the 1% level. Significant at the 0.1% level. 1 ¼ very unlikely to 5 ¼ very likely. Intention non- Intention Intention non- 0.877 0.710 3.68 3.27 0.333 20.015 4.49 4.21 0.208 20.284 3.94 4.93 0.468 0.067 3.99 3.96 0.375 20.239 3.98 4.02 20.020 0.892 2.03 2.07 0.458 20.000 4.42 4.33 0.333 0.215 3.09 2.96 0.145 20.132 3.94 3.70 0.291 20.436 4.51 4.41 major in non- viewed broad exposure to business more favourably than students who intended to major in (P, 0.05). In summary, nine of the ten outcomes (see Table 6, Columns 1 and 2) for majors are positive, indicating that these students believed that their intended majors were more likely to lead to the outcomes evaluated. In comparison, a business major other than was perceived as more likely to lead to six of the ten outcomes by those who intended to major in non- disciplines. For all ten outcomes, there were seven significant differences (P, 0.01) between the two groups personal beliefs. Table 7 presents the differential perceived control for those who intended to major in and non- in their first year. A positive differential score indicates that the factor would facilitate choosing as a major. A negative differential control belief score indicates that the factor facilitated choosing a business field other than. The results in Table 7 indicate that three out of the six differential control beliefs were perceived differently by the two groups.
Understanding Students Choice of Academic Majors 245 Table 7. Mean perceived differential control at first year Intention Intention non- Workload in /non courses Skills and background in mathematics Performing well in / non- courses Availability of opportunities in /non- fields Interest in /non subjects Less involvement in extracurricular activities if an /non- major is chosen Tests for differences in means are based on t-tests. Significance at the 0.1% level. 1 ¼ strongly disagree to 5 ¼ strongly agree. 0 20.302 0.257 21.136 0.121 20.425 0.015 20.630 20.121 20.269 20.272 20.275 Skills and background in mathematics and performing well in courses appeared to be significant factors in facilitating the intention to major in. However, those who intended to major in non- felt more strongly than those who intended to major in that skills in mathematics would hinder their choice of as their major. Performing well in course(s) appeared to hinder their intention to major in, whereas performing well in a non course appeared to facilitate their intended major. Their perceptions of the availability of opportunities in their intended major also appeared to influence their intentions. These results are generally consistent with the findings of Cohen and Hanno (1993) and Allen (2004). Changes in Students Perceptions Students develop their attitudes and beliefs through experience. Accordingly, their attitudes and beliefs may change over time as experience may validate, reinforce or modify their beliefs and attitudes. As shown in Table 2, 37 of the 68 students who intended to major in have majored in by the third year and 24 of the 226 students who intended to major in non- have majored in by the third year. A Chi-square test indicates a significant difference (P ¼ 0.001) between intention to major and actual major choice. This suggests that attitudes and beliefs about study majors may have changed during the period from when the intentions were expressed at the beginning of university study and when the major choice was confirmed. To examine changes in attitudes and beliefs, the respondents were divided into two main groups the No change group and the Change group. The No change group comprises two sub-groups: those who intended to major in and have actually majored in
246 L. M. Tan and F. Laswad (Group 1), and those who intended to major in non- and actually majored in non- (Group 2). The Change group comprises two sub-groups: those who intended to major in but majored in non- (Group 3), and those who intended to major in non- but majored in (Group 4). Table 8(a) presents the mean differential perception of referents for the four groups. There were no significant differences in Group 1 s perceptions of referents between first and third year. For Group 2, there were significant changes in perceptions of their relatives and friends views. In the third year as compared to the first year, this group had stronger beliefs that their relatives and friends thought they should major in non. There was also a significant difference in Group 3 s perceptions of referents in the first and third year. In the third year, this group perceived that their referents thought they should major in non-. This is in sharp contrast to their perceptions in the first year when they perceived that their parents, friends and career advisors thought they should major in. Perhaps they had reassessed their perceptions after the views of their referents had changed. Group 4 s perception of referents is interesting. There is a significant difference in perceptions that relate to the parents and the relatives views in the first year. In the first year, even though they perceived that their parents and relatives thought they should major in, their intention was to major in non-. In the third year, they had stronger beliefs that their parents and relatives thought that they should major in and they ultimately did major in. This finding suggests that these students might have been influenced by their parents and relatives in their decisions to change majors. 4 Table 8(b) presents the results for the four different groups motivations to comply with referents. The paired samples t-test showed no significant differences in views from first year to third year for all groups except for Group 4. This group perceived their relatives views as being less important when they were in the third year as compared to when they were in their first year. Generally, the results indicate that the four groups perceptions of referents remained relatively stable. Table 9 shows the four groups results for differential personal beliefs in the first year and third year. There were no significant differences in beliefs for Groups 1, 3 and 4 between the first year and third year. Significant changes were found for Group 2 s perceptions. This group appeared to have higher beliefs in the third year than in the first year that dealt a lot with numbers but had lower beliefs that a non- career is more challenging and that an major is boring. The perceptions of Group 2 also changed with regard to a high initial salary. In their third year as compared with their first year, this group had higher perceptions that an major has the potential to earn a high initial salary. However, this group did not change their intended major to even though some of their beliefs had changed. Table 10 shows the results for outcome evaluations for the four groups. Group 1, 3 and 4 s views did not change over the years. Group 2 s evaluation of a field with broad exposure to business changed significantly. They had stronger beliefs in the third year that their non- major would provide them with a broad exposure to business, as compared to their belief in first year. Table 11 provides a comparison between control factors for the four groups. For Groups 1 and 3, there were no changes in the perceptions of control factors. Group 2 s views have changed with regard to performing well in and the availability of job opportunities. This group s perception of availability of opportunities in was more positive from the first to the final year of study. The results further show improvement in their perception that performance in non- study would facilitate selection of non- as a major. The significant change in Group 4 s views is interesting.
No change groups Table 8. Mean scores for referents Change groups Group 1 Group 2 Group 3 Group 4 Intention and major in Intention and major in non Intention in but major in non- Intention in non but major in (a) Mean differential perception of referents for different groups Parents 1.057 0.600 20.539 20.748 0.567 20.200 0.348 1.000 Other relatives 0.486 0.286 20.426 20.738 0.300 20.233 0.000 0.609 Friends 0.486 0.486 20.426 20.931 0.300 20.600 20.304 0.348 Career advisors etc. 0.382 0.529 20.512 20.622 0.222 20.482 0.087 0.217 (b) Mean motivation to comply for different groups Parents 3.56 3.58 3.33 3.32 3.47 3.67 3.83 3.67 Other relatives 3.03 2.81 2.80 2.70 2.80 3.07 3.33 2.83 Friends 3.19 3.00 3.02 2.95 3.00 3.10 3.33 3.00 Career advisors etc. 3.33 3.14 3.21 3.17 3.24 3.24 3.58 3.21 Tests for differences in means are based on t-tests. Significant at the 5% level. Significant at the 1% level. Significant at the 0.1% level. Understanding Students Choice of Academic Majors 247
248 L. M. Tan and F. Laswad Table 9. Mean differential personal beliefs for different groups No change groups Change groups Group 1 Group 2 Group 3 Group 4 Intention and major in Intention and major in non Intention in but major in non Intention in non but major in A career that deals with numbers 1.000 0.923 0.750 1.006 0.809 0.857 0.571 0.762 Earning a high initial salary 0.423 0.346 20.698 0.273 0.250 0.450 0.381 0.524 A field with broad exposure to business 0.200 0 20.333 20.351 0.250 20.250 0 0.053 A career with a chance to establish a private practice 0.480 0.240 0.071 0.126 0.450 0.100 0.050 0.400 A career that is challenging 0.615 0.385 20.272 20.029 0.050 20.050 0.167 0.222 An academic major that is boring 20.154 20.269 1.024 0.641 0.150 0.300 0.316 20.316 A career with high future earnings 0.640 0.560 20.071 0.082 0.200 0.250 0.579 0.632 A major that demands a heavy workload 0.462 0.462 0.247 3.193 0.150 0.450 0.158 0.421 A career that provides 0.192 0.231 20.222 20.035 0.050 0.200 0.526 0.421 high social status A major that prepares for a career with greater job opportunities 0.423 0.615 20.503 20.322 0.150 0.100 0.526 0.211 Tests for differences in means are based on t-tests. Significant at the 5% level. Significant at the 1% level. They appeared to have developed some interest in between their first and third year of study. Summary and Conclusions This study extends the literature that uses Ajzen s (1988) theory of planned behaviour in examining the factors that impact on students intentions and their eventual decision to major in or a non- discipline. A sample of business students enrolled in an introductory course participated in the study. A follow up survey was conducted at the end of their third year of university study. The results show that major intentions and perceived behavioural control were determinants of
Understanding Students Choice of Academic Majors 249 Table 10. Mean differential outcome evaluations for different groups No change groups Change groups Group 1 Group 2 Group 3 Group 4 Intention and major in Intention and major in non Intention in but major in non Intention in non but major in A career that deals with numbers Earning a high initial salary A field with broad exposure to business A career with a chance to establish a private practice A career that is challenging An academic major that is boring A career with high future earning A major that demands a heavy workload A career that provides high social status A major that prepares for a career with greater job opportunities Tests for differences in means are based on t-tests. Significant at the 5% level. 3.78 3.70 3.23 3.25 3.55 3.23 3.63 3.79 4.46 4.32 4.19 4.10 4.55 4.19 4.46 4.54 3.94 3.83 3.90 4.06 3.97 3.87 4.27 4.23 3.94 3.86 3.93 3.99 4.03 3.93 4.17 4.04 3.94 3.88 3.99 4.04 4.00 3.93 4.30 4.35 1.94 2.03 2.07 1.96 2.13 2.23 1.95 1.91 4.41 4.43 4.32 4.35 4.43 4.23 4.61 4.70 3.00 2.91 2.92 2.88 3.18 3.04 3.26 3.00 3.82 3.85 3.72 3.62 4.06 3.94 3.64 4.09 4.62 4.57 4.39 4.32 4.40 4.33 4.61 4.48 major choices and two factors (personal and referents) were determinants of students major intentions. Further analysis of these factors revealed that the students academic major intentions (whether or non-) were influenced by the perceptions of important referents, particularly their parents. Students outcome evaluations showed that market-related factors (high initial salary and future earnings, and greater job opportunities) were perceived favourably by all students. This result is similar to the findings of prior studies in other countries. As indicated in Tan and Laswad s (2006a) study, students, regardless of the country from which they originate, consider these factors in making decisions about their major intentions. Comparison of differential personal perceptions of the two groups revealed that those who intend to major in generally hold positive attitudes towards the
250 L. M. Tan and F. Laswad Table 11. Mean perceived differential control No change groups Change groups Group 1 Group 2 Group 3 Group 4 Intention and major in Intention and major in non Intention in but major in non- Intention in non- but major in Workload in /non courses Skills and background in maths Performing well in /non courses Availability of opportunities in /non fields Interest in / non- subjects Less involvement in extracurricular activities if an /non major is chosen Significant at the 5% level. Significant at the 1% level. Tests for differences in means are based on t-tests. 20.194 0.194 20.304 20.299 20.393 20.071 0.091 20.273 0.139 0.194 20.403 20.367 0.071 20.250 20.409 20.909 0.083 0.639 20.691 20.485 20.037 20.333 0.091 0.046 0.139 0.694 20.371 20.142 20.214 0.107 0.318 0.864 0.639 0.472 21.222 21.323 20.286 20.714 20.682 0.273 20.056 20.389 20.299 20.239 20.214 0 20.227 20.318 profession and the study of. It appeared that those who intended to major in were not deterred by the heavy workload, as the higher workload would perhaps be compensated for by other benefits, such as higher initial salary and the potential to establish a private practice in the future. These results suggest that the profession is attracting students who are favourably disposed to the traditional characteristics of the profession. In contrast, those who intended to major in non- might have been discouraged from pursuing an major due to their perception of as demanding a heavy workload and dealing a lot with numbers. This suggests that there are opportunities for promoting study to influence non- students beliefs about the profession and the study of. Taking into account the beliefs held by respondents who intend to major in disciplines other than and the importance of referents, the profession should perhaps promote
Understanding Students Choice of Academic Majors 251 the positive aspects of an career, not only to pre-university students but also to the public. This strategy would enhance the public profile of members of the profession. The results further indicate that there were significant differences in the control perception between students who intend to major in and those who intend to major in non- disciplines. Mathematical skills, academic performance, and employment opportunities appeared to be the control perceptions that distinguished between those who intend to major in and non-. The comparison of beliefs and attitudes between students in the first and third year of study indicates some changes of perceptions for three out of the four sub-groups. There were no significant changes in beliefs and attitudes of those who intended to major in and actually majored in. This group appeared to have chosen their career path at an early stage and was determined to continue with it. Although there were some significant changes in beliefs and attitudes exhibited by the second group (i.e. those who intended to major in non- and majored in accordance with their intention), the changes were merely in the form of stronger or weaker beliefs; in most cases there were no changes in the directions of their beliefs and attitudes except for their perception on earning a high initial salary. Perhaps this explained why they followed through with their intended non- major. The results for the change groups are interesting. Those who intended to major in but ultimately majored in a non- major had changed perceptions of their referents views (parents, friend, and career advisors). Either this group had modified their perceptions of the views of their referents, or their referents themselves had changed. For example, they may have had different friends between the first and last year of study. Apart from this, their other beliefs and attitudes did not change significantly over the three years. For those who intended to major in non- but ultimately majored in, their perception of was also significantly changed. This finding suggests that the profession and the academics have the potential to influence students perceptions of during their studies at university. Overall, there were very few changes in students personal attitudes and perceived control between their first and third years of study. This suggests that attitudes developed early in university are generally stable and tend to last, further suggesting that attempts to influence these attitudes should be made early. Generating students interest in a subject area during their first year is also an important determinant as it has an impact on change of major. Stimulating students interest in starting from their first year of study may perhaps sway them to consider as their major. Lastly, there are limitations to making generalisations of our results to the population as this study was conducted on one particular multi-campus university. Our longitudinal study permits measurement of differences in beliefs and attitudes from one period to another, but it has the disadvantage of some participant attrition. This may bias the results and affect their generalisability. Notes 1 This literature was extensively reviewed by Tan and Laswad (2006a). 2 Introductory is usually taken by students in their first year of study. For those who intend to major in, the intermediate and advanced courses are taken in their second and third year of study respectively. 3 Testing whether gender is an explanatory variable in models 1 and 2 indicates that gender is not a significant variable in both models. 4 We did not explore the potential effects of students grades in the introductory course on the change in majors as we have adopted the TPB as the conceptual framework for examining the factors