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Psychographic profile among potential first class public university undergraduates in Malaysia.

INTRODUCTION

In recent years, there is an increase in the expectations of stakeholders on the quality of graduates in Institutions of Higher Learning (IHE). Universities are expected to produce graduates that have the capacity to enhance their learning, potentially to higher levels of postgraduate studies. This is in line with the aspiration of Malaysia; to produce 60,000 doctorates by 2015 under the government effort known as Mybrain 15. Particularly, My brain '5 is one of the critical agendas of the National Higher Education Strategic Plan (Pelan Strategik Pengajian Tinggi Negara- PSPTN). Its main aim is to develop human resources that are highly knowledgeable as a catalyst to enhance research and innovation as well as to ensure that the development of knowledge based economy on innovation can be achieved successfully. Therefore, in order to achieve the development aims of the country, active educational plans which concentrate on improving education are required. A successful student at university is evidently influenced by other variables or a combination of variables consisting of academic and non-academic ones. Although significant research in this area has centered around specific variables that can be tied into academic success such as gender, age, achievement, academic ability, and financial status (Fuller, Manski, & Wise, 1982; Hossler, Braxton, & Coopersmith, 1989; Paulsen, 1990); a scarcity of researches exist relative to psychographic variables in academic environment. The following review explores and considers some of the major factors that may be pertinent to the development of psychographic variables model, including models and concepts from mainstream psychology, and the associated sub-disciplines of health, leisure, and physical activity.

Psychographics has been around for more than 30 years, but is still one of the least understood concepts in marketing research (Heath, 1995). Hence, in the context of marketing research, it seems that every scholar has his or her own definition of exactly what constitutes psychographics. Some define it simply as values or lifestyles while others have more elaborate definitions. According to Gunter and Furnham (1992) in their book Consumer profiles: An introduction to psychographics, psychographics seeks to describe the human characteristics of consumers that may have bearing on their response to products, packaging, advertising, and public relations efforts. Such variables may span a spectrum from self-concept and lifestyle to attitudes, interests and opinions, as well as perceptions of product attributes (Gunter &Furnham, 1992).In other words, psychographics consists of characteristics of individuals that describe them in terms of their psychological and behaviour makeup--how people occupy themselves (behaviour) and what psychological factors underlie that activity pattern. For example, a person's need to seek affiliation or peer group approval that makes him or her engage, say in going for theaters or playing golf. Theater going or playing golf, thus, becomes part of his or her psychographics. This psychographics, in turn, drives customer behaviour toward buying golf equipment or doing whatever is needed to implement that particular psychographic; it becomes motivational. Psychographic segmentation variables that come into play when we speak of psychographic segmentation are primarily psychological in nature.

The variables could be said to be part of the process of psychographic segmentation include interest, activities, opinion, behaviour pattern, hobbies, and lifestyle. Basically, psychographics have three components namely attitude, interest, and opinion (AIO). These components are also referred to as psychographics profile with the application of AIO to studying lifestyle based on quantitative measures. In other words, psychographic analysis is a technique that investigates how people live, what interest them, and what they like?-Also called lifestyle analysis or AIO because it relies on a number of statements about a person's activities, interest, and opinion. Therefore, psychographics profile is useful in understanding the AIO of potential 1st class students in UUM. In general, the psychographic researchers would like to analyze these three factors primarily in order to understand the psyche of the students. Then researchers can adopt a suitable coaching and mentoring strategy or they can alter an existing coaching and mentoring strategy. Woodside & Pitts (1976) and Abbey (1979) empirically tested the effectiveness of psychographics and found that lifestyle variables were important in classifying respondents and these variables communicate something that is real, meaningful, and relevant, beyond what demographic analysis could do.

In the light of the results of previous research, this study was conceptualized to explore the relationship of various demographic factors such as gender with psychographic profiles of university students. Various research studies were conducted to examine whether psychographic profiles can be affected by demographic factors. These studies revealed significant relationship of psychographic profiles with some demographic factors. For instance, Sullivan (2001) examined demographic variables such as gender and age as they related to student success. Bandura & Locke (2003) studied the importance of self efficacy on student success. Regna (1984) investigated the relationship of an individual's perceived self-image to attitudes and motivations toward leisure participation. Altogether, 319 undergraduate college students were involved, selected through systematic random sampling. There was a significant relationship between perceived self-image, and the affective and cognitive components. However, there was no significant relationship between demographic variables and leisure attitudes. However, it is unfortunate that a gap exists in knowledge regarding the relationship between psychographic profiles and students' characteristics in research; therefore, the present study attempts to identify the relationship between psychographic profiles and demographic variable (gender) among potential first class students. The objectives of this quantitative study are to identify the psychographic profiles level among potential first class students and to compare the levels of each psychographic profile based on gender. In short, the objectives of the study are (1) to identify the level of psychographic profiles such as (achievement motivation, self efficacy, time management and leisure attitude) among first class students in University Utara Malaysia, and (2) to compare each psychographic profiles levels such as (achievement motivation, self efficacy, time management and leisure attitude) based on demographic variables such as (gender) among first class students in University Utara Malaysia.

MATERIALS AND METHOD

The population of this study was the listed potential first class undergraduate students in UUM. This group consisted of the students who obtained at least 3.50 of the CGPA within the duration of this study was conducted. Thus, they were referred to as potential first class students. Records from the Academic Affairs Department listed 3,939 potential first class students. The designed questionnaire was distributed to all students during the ceremony of the Dean's List Award; however only 424 students gave the feedbacks hence qualifying it as a convenience sample for analysis purposes. The psychographics attributes were developed by adapting some standard resources to measure achievement motivation (Helmreich and Spence, 1983, SE); time management (Macan, 1994); self efficacy (Schwarzer, 1992); and leisure attitude (Raghed and Beard, 1982).The measurement scale comprised of 41 items using five-point Likert-type scale with the responses ranging from strongly disagree (1) to strongly agree (5). The Cronbach's alpha for the psychographic scale in this study was .895.

The statistical tools chosen in this study were descriptive tools which were mainly for answering the identified objectives. Simple mean and variance were used to summarise the data. Several statistical techniques were applied in this study such as Descriptive analysis (averages and standard deviations); Independent sample t-test and analysis of variance were used to compare between the variables.

RESULTS AND DISCUSSION

The sample of the first class students as detailed in Table 1 consisted of 69 males (17.1%) and 355 females (82.9%). Most of them ranged between the ages of 21 to 23 years old, and this is an actual representation of the average age of undergraduate students in the UUM. In addition, half of them were Malays and almost 40.0% of the respondents were Chinese. Definitely, majority of the undergraduate students were single.

The level of psychographic characteristics among the first class students:

Such finding was investigated in this study where descriptive statistics were used to measure psychographic characteristics among the first class students as shown in Table 2.

A psychographic characteristic entails six dimensions which are: (1) task/work, (2) competitiveness, (3) mastery skills (4) self-efficacy, (5) time management, (6) leisure attitude. Descriptive statistics as tabulated in Table 2 showed that the first class students had the highest level on task dimension with a mean score of 4.162 and standard deviation of 0.556; whilst time management scored the lowest with a mean of 3.105 and standard deviation of 0.633. In short, the sample indicated that they moderately agreed with the psychographic characteristics which they possessed. Then, the psychographic level was computed from each dimension to identify psychographic level based on the following grouped of mean score:

1. Low, if the mean score is less than 2.44,

2. Moderate, if between 2.45 and 3.44, and

3. High, if the score is more than 3.45.

On the other hand, a summary of the level of psychographics among the potential first students is displayed in Table 3. It can be said that more than 90% of the students had either moderate or high psychographics level, which shows that such good performance student in education posses some good traits in psychographic characteristics in terms of tasks, competitiveness, self efficacy, time management, leisure attitude, and skill mastery.

Differences of the effect of Gender on the Psychographic Characteristics:

A series of MANOVA tests were conducted to analyse the differences in the variables measured among two gender groups, in which the details are listed in Table 4. In detail, for the achievement subscale, significant differences were found between gender groups (F=5.907, p-value =0.016). Specifically, female students have greater mean scores than male students. For the competitiveness subscale, non-significant differences were found between male and female students (F=0.916, p-value=0.339). Similar result was found for the mastery skills subscale (F=2.416; p-value = 0.121), self efficacy subscale (F=1.112; p-value = 0.292), and time management subscale (F=0.278; p-value = 0.599). However, significant differences were found between male and female students (F=5.049; p-value=0.025) in leisure attitude subscale.

Conclusion:

In the previous sections of this study psychographic and demographic variables were shown as essential factors identifying and reflecting students' success at the university. Psychographic profiles such as self efficacy, time management and motivation are important determinants of the student success at the university. Furthermore, gender is an important determinant of the student success at the university. The sample of the study consisted of 424 university students from one university in Kedah State. As a conclusion, this study reported the result of the descriptive profile of the respondents, presented the level of psychographic profiles such as self efficacy, time management and motivation and leisure attitude among university students in Malaysia. Therefore, outcomes of the study described some characteristics on the prospective students to assist in providing coaching and mentoring--by insuring students suited to their needs and desires for their study. Using those factors as a base, a researcher can determine how a particular group of students will respond to the intention of furthering their study. Hence, the current study was limited to students from one university and focused only on potential first class students. Therefore, studies conducted at other universities or with students studying in other universities could likely yield different results. In addition, more than 87.45% of the respondents of this study were female. The number of female students who participated in this study was more than male students, this is not surprising since more females are enrolled in Malaysian educational institutions compared to male and that females averagely perform better than males. Therefore, gender is an issue in all studies conducted in college population in Malaysia. This is definitely a very important area for any future research on Malaysian students. Another limitation of this study is the fact that quantitative data is taken through self-report measures; therefore, there is ample chance that participants chose answers which were not their true experience (Creswell, 1994).

From this study, it was found that our potential first class students are emotionally and psychologically prepared to undertake postgraduate studies in the future. With proper guidance, the prospective students are likely to succeed in their academic performance, and enhance psychological attributes at postgraduate level. As for recommendations for future research, this study recommends and proposes the following: Firstly, based on the limitation of the current study, ample opportunities are present for future research while using the same design and framework. Future researches should look into and study all public and private universities. Secondly, the study made effective use of quantitative methodology but recommends that future researches use qualitative methods to shed light on student's perception of the effective strategies at the university. Finally, the study recommends on enlightening the students and the workshop members of the educational sector on the importance of psychographic variables through the provision these skills in the curriculum and the facilitation of emotional intelligence training sessions.

ARTICLE INFO

Article History:

Received 14 November 2013

Received in revised form 24 December 2013

Accepted 28December 2013

Available online 18 January 2014

REFERENCE

Abbey, J., 1979. Does life style profiling work? Journal of Travel Research, 18(1): 8-14.

Bandura, A., E. Locke, 2003. Negative Self Efficacy and Goal Effects Revisited. Journal of Applied Psychology, 1: 87-99.

Creswell, J.W., 1994. Research design qualitative & quantitative approaches, London: SAGE Publications.

Fuller, W., C. Manski, D. Wise, 1982. New Evidence on the Economic Determinants of Postsecondary School Choice. Journal of Human Resource, 17: 477-498.

Gunter, B., A. Furnham, 1992. Consumer profiles : An introduction to psychographics, Consumer Research and Policy Series. New York.

Heath, Rebecca Piirto, 1995. "Psychographics: Q'est-cequec'est?" American Demographics: Marketing Tools, 74.

Helmreich, R.L., J.T. Spence, 1978. The Work and Family Orientation Questionnaire: An objective instrument to assess components of achievement motivation and attitudes toward family and career. Catalog of Selected Documents in Psychology, 8(2), (Document #1677).

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Ragheb, M.G. and J.G. Beard, 1982. Measuring leisure attitude. Journal of Leisure Research, 14(2): 155-167.

Schwarzer, R. (Ed.), 1992. Self-efficacy: Thought Control of Action. Washington, DC: Hemisphere.

Sullivan, P., 2001. Gender Differences and the Online Classroom: Male and Female College Students Evaluate Their Experiences. Community College Journal of Research & Practice, 25: 805-819.

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(1) Noor Azniza Ishak, (2) Lim Khong Chiu, (3) Fauziah Abdul Rahim, (4) NorIdayu Mahat, (5) Nor Laily Hashim, (6) Ariffin Abdul Mutalib, (7) Malek, T. Jdaitawi

(1) School of Social Development, Universiti Utara Malaysia, 06010 Sintok, Kedah, Malaysia.

(2) School of Government and International Studies, Universiti Utara Malaysia, 06010 Sintok, Kedah, Malaysia.

(3) School of Education and Modern Languages, Universiti Utara Malaysia, 06010 Sintok, Kedah, Malaysia.

(4) School of Quantitative Science, Universiti Utara Malaysia, 06010 Sintok, Kedah, Malaysia.

(5) School of Computing, Universiti Utara Malaysia, 06010 Sintok, Kedah, Malaysia.

(6) School of Computing, Universiti Utara Malaysia, 06010 Sintok, Kedah, Malaysia.

(7) School of Social Development, Universiti Utara Malaysia, 06010 Sintok, Kedah, Malaysia .

Corresponding Author:

Noor Azniza, Ishak, School of Social Development, Universiti Utara Malaysia, 06010 Sintok, Kedah, Malaysia

E-mail: noorazniza@uum.edu.my
Table 1: Profile of sample.

Demographic      Class          Frequency   Percent (%)

Gender           Male           69          12.55
                 Female         355         87.45
Age (year)       18-90          56          13.90
                 21-23          300         74.30
                 24-26          46          11.40
                 More than 27   2           0.50
Ethnic           Malay          210         52.00
                 Chinese        161         39.90
                 Indian         25          6.20
                 Others         8           2.00
Marital status   Single         397         98.30
                 Married        7           1.70

Table 2: Descriptive Statistics of Psychographic Characteristics.

Psychographic      Mean    Std.        Skewness
characteristics            Deviation   Statistic   Std. Error

Task/work          4.162   0.556       -0.881      0.121
Competitiveness    3.652   0.614       -0.087      0.121
Self Efficacy      3.692   0.617       0.346       0.121
Time Management    3.105   0.633       0.391       0.121
Leisure Attitude   4.156   0.658       -0.797      0.121
Skill Mastery      3.322   0.450       0.234       0.121

Psychographic      Kurtosis
characteristics    Statistic   Std. Error

Task/work          2.083       0.242
Competitiveness    -0.083      0.242
Self Efficacy      1.383       0.242
Time Management    0.402       0.242
Leisure Attitude   0.953       0.242
Skill Mastery      0.289       0.242

Table 3: Level of Psychographic among the Students.

Psychographic level   Frequency   Percent

Low                   3           0.7
Moderate              100         24.8
High                  301         74.5
Total                 404         100.0

Table 4: Result of MANOVA for Gender Factor.

Source   Variable           Mean Square   F       Sig

Gender   Achievement        1.804         5.907   0.016
         Competitiveness    0.346         0.916   0.339
         Mastery Skills     0.486         2.416   0.121
         Self Efficacy      0.423         1.112   0.292
         Time Management    0.111         0.278   0.599
         Leisure Attitude   2.167         5.049   0.025
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Article Details
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Author:Ishak, Noor Azniza; Chiu, Lim Khong; Rahim, Fauziah Abdul; Mahat, NorIdayu; Hashim, Nor Laily; Mutal
Publication:Advances in Natural and Applied Sciences
Article Type:Report
Geographic Code:9MALA
Date:Aug 1, 2013
Words:2854
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