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The study aimed at examining existing and well developed framework of academic performance Hong Kong which has its own unique education system and culture. The relationships between socioeconomic status, future time prospective, achievement goal, effort, academic performance, and the new concepts of parental involvement in employment were examined. Parental involvement was created to be an intermediate factor between socioeconomic status and future time prospective. 106 students in City University of Hong Kong had filled questionnaires containing the eight measures of different components in the framework. Result was, generally, consistent with the well-developed framework. Academic performance was significantly linked with future time prospective, parental involvement in employment, achievement goal and effort. For the socioeconomic status, the education background of parents was positively linked with the effort and academic achievement, and the parental income and family income were found to be positively related to student's future time prospective. However, different from the estimation, parental involvement in employment had no significant relationship with future time prospective, but significantly related with other variables. Further investigation was needed for investigation how those variables affect others.
Background and the rationales of the this research
Having an outstanding academic performance is always important for a student. In fact, the academic performance is not only positively related to students' performance in other levels of study, but also their performances and salaries in work (Kuncel, Crede, & Thomas, 2005). Even in university, it is no exception. Because of its importance, academics from the psychology and sociology have done numerous of researches in investigating the predictors of academic performances.
In this present research, it focused on studying how the sociological factors (student's socioeconomic status (SES) and parent involvement in employment affect the psychological factors (future time prospective, achievement goal and effort) which both proved as major factors influencing academic performance (e.g. Midgley et al., 1998, Simon et al., 2004 and Zimbardo and Boyd, 1999).
The conceptual framework of this present research was, mainly, based by Elliot (1997), Fenollar et al. (2007) and Phan (2009). However, the elements of SES and parental involvement would be further introduced into the framework. Parental involvement was introduced as a new element of study. For university students, they are experiencing a stage that close to employment, it is worthy to explore how parent's involvement, on top of the education aspect, affects students' academic performances. Even though the other part included in the framework had been examined in some foreign countries (e.g. Fenollar et al., 2007 and Phan, 2009), this framework had not yet be tested in Hong Kong. There is a need to test the framework in Hong Kong which has its unique learning culture and dissimilar education system.
Coleman et al. (1966) was the first formal research studying the relationship between socioeconomic status and the academic performances of students. It was found that students' socioeconomic status (SES) had huge influences for the academic performances of students. The better the SES students have, the greater their academic performances.
Because of the enlightenment of Coleman et al. (1966), numerous of sociologists tried to explore more in the relationship between SES and academic performances of students. Many of the finding shared the similar finding with Coleman et al (for example, Caro, 2009, Ginsburg and Bronstein, 1993, Lamdin, 1996, Liu and Lu, 2008, Silinskas et al., 2009). However, few of the literatures (such as, Lamdin, 1996) found no significant relationship between SES and academic performances of students.
Scholars had various ways to measure SES. Generally, aggregated SES and individual SES were the major methods measuring SES. Aggregated SES was determined by the financial situations of their schools or neighborhoods. For example, Brooks-Gunn, Denner, & klebanov (1995) used the proportions of students who were eligible to have free meal or reduced-price meals (Because only families that income level was lower than certain level can enjoy the lunch subside from the government in United State of America). It was found that the proportions of student receiving free/reduced-cost lunch were negatively related to the reading and mathematics performances of students. For the neighborhood's SES, it was measured by the proportions of residents that had not completed high-schools
Similar to the aggregated SES, there were also plenty of methods of measuring individual SES. However, parental income, parental education background and parental occupation were the major components (Sirin, 2005). Some scholars used only one single component to measure SES. For example, Silinskas et al. (2009) only used the occupations of parents in the study of Finland's students. The occupations were coded into five categories, which were, blue-collar, lower white-collar, higher white-collar, self-employed and not-at-work. Only the first three were used in the process of analysis. The Parental education background seems particularly solid among those three elements. Most of the finding, such as McEwan (2003), found a significant relationship between the parental education background and the education performances of students. It is interesting that maternal influences were proved to be more tremendous than the paternal influences. Indeed, students' mathematic performances was much more influenced by their parents' educational backgrounds than their Chinese language performances (Park and Hannum, 2002).
However, some of them used all three components in determined an individual's SES (e.g. Liu and Lu, 2008). Barring from the three prominent elements of SES, home resource was used in the studies of SES occasionally (Mcloyd, 1998). It was somehow caused by the difficulties of measuring it. The possessions, such as number of computers, number of studying rooms, as well as books were relatively tough to be measured and conceptualized.
Even though, the number of studies about SES and students had been done, only rare number of them tried to investigate how SES affect the academic performances of students. Lonigan (1994) proposed that the reason was that families with higher SES would have more motivations in participating education-related activities than the families with low SES. Caro (2009) studied the influences of SES toward the students in different age (from 7 to 15 years old). He conducted a longitudinal study in Canada to examine the academic achievement gap. It was found that the influences of the SES remain stable in the age group from 7-11 years old, however, the academic achievement gap widened dramatically after 11 years old.
Researches about parental involvement were mostly about the education. Parental involvement in education was defined as " parents interactions with schools and with their children to promote academic success" (Hill et al, 2004, p.1492). Some results were controversial about its effect on academic. For instance, Fan & Chen (2001) had found the parental involvement in education is significantly related with students' academic performance, however, Bronstein, Ginsberg & Herrera (2005) found no relationship between these two factors. Parental involvement in education was also identified as a way to alleviate the effect of students' family background and enhance students' potential (Dearing, Kreider, Simpkins & Weiss, 2006). Nonetheless, most of the previous studies only focused on middle schools' students and the education side of involvement. More could be done on explore the parental involvement on university students and the employment side of parental involvement.
Future time prospective
FTP refers to an individual's attitudes toward his or her expected future (Vazquez & Rapetti, 2006) and instrumentality is what most scholars used to measure FTP. To be simple, "instrumentality may be referred to as the perception that one's completion of a task or a proximal task goal may be instrumental to suture goal attainment (Phan, 2009, p.157). There were plenty of evidences proving that FTP was positively related to motivation in persisting in academic learning (Simon et al., 2004), academic achievement (Lenning, Burns and Conney, 1998 and Zimbardo and Boyd, 1999), interest in schoolwork (Andriessen et al., 2006) and time of doing homework (Shell and Husman, 2001).
Effort and achievement goal
Effort was a complicated concept to measure, as it is difficult to verify. Generally, it was referred to the amount of efforts utilized in the process of studying (Zimmerman and Risemberg, 1997). It was proved to be related to the academic performance and negatively related to class size (e.g. Fenollar et al. 2007 and Phan 2007, 2009).
Originally, there were only two elements in achievement goals, which is mastery goal and performance goal (Ames and Archer, 1988). However, in the recently, sociologist separated the performance goal into two categories, which were performance approach goals and performance avoidance goal and added work avoidance goal as into the elements of achievement goals. Students with different achievement goals had dissimilar goals toward learning. "Students adopting mastery goals are interested in acquiring new skills and improving their knowledge even in the face of obstacles, whereas those performances goals are usually interested in obtaining positive evaluations of ability and avoiding negative evaluation (Phan, 2007, p. 327-328). Students with performance approach would tend to striving favorable judgment of competence by their performance, whereas, students with performance avoidance would only want to avoid unfavorable judgment of competence (Phan, 2007). Barring from mastery and performance goal, work avoidance would be included in the achievement goal in this present study. Work avoidance was defined as 'the main concern to get work done with a minimum amount of effort' (Meece, Blumenfeld, & Hoyle, 1988, p. 515).
Both mastery goals and performances goal were found to be positively related with the efforts of students (Fenollar et al. 2007 and Phan, 2007, 2008). It might be caused by the students with performance goal would like to gain positive judgment and avoid negative judgment, hence they will pay more efforts in studying. However, work avoidance was negatively related to the efforts and academic performances of students.
According to (Ng, 2006), people with work avoidance goals only want to finish their work with minimum efforts and time. Contrary to the mastery and performance goal, it showed negative relationship with the efforts, and motivation in learning.
As the framework showed, this present study tried to explore the relationships between parental involvement in employment, socioeconomic status, Future time prospective, achievement goals, effort and academic performance. The framework was based by Phan (2007, 2009) which is based on the works of Elliot and his colleagues (1997). The framework had been adopted by many other scholars, such as Fenollar et al. (2007). Phan (2007, 2009) added the future time prospective (FTP) into the framework for further studies. In addition to the framework that had been already well-developed, SES and parental involvement in employment of students would be introduced for further investigation. The following is the hypothesis that was examined in this present study. Some of them were based from the previous find from various scholars.
H1: Socioeconomic status is positively related to parental involvement in employment
H2: Parental involvement in employment are positively related to future time prospective
H3: Future time prospective have influence on work performance goal (Phan, 2009)
H4: Both mastery goals, performance approach goal, performance avoidance goal are positively related to effort (Fenollar et al., 2007)
H5: Work avoidance is negatively related to effort (Fenollar et al., 2007)
H6: Effort is positively related to academic performance (Phan, 2009)
Only quantitative data would be collected as it can already provide sufficient information for analysis and the analysis of quantitative data is less complicated than qualitative data. Questionnaires used in this study would be composed by five parts, the scale of parental involvement in employment, achievement goal, study strategy and the future time prospective, as well as, some personal information. Participants' college, age, year, gender and CGPA results would be asked in the personal information. The CGPA results of this study could not be collected from the department of the respondents as the literature, since it is unlikely that the departments of City University would provide such sensitive information. Therefore, the CGPA results had to be obtained from the questionnaire, even though it is less accurate. Some respondents may lie about their CGPA results, respondents would be kept anonymous in order to make them feel more comfortable to provide their CGPA results.
Because of the limited time and resources, non-random sampling would be adopted. Questionnaires would be distributed in the Kowloon Tong campus of City University of Hong Kong in three different time shots, the morning, afternoon and evening within three days. The location of distributing questionnaires would be in the podium of the fourth floor since they are the only crowded areas allowing the questionnaire distribution. Interviews will leave after giving the questionnaires to the respondents collect the questionnaires 20 minutes later. While leaving the respondents may diminish the respond rate, it can give private spaces to the respondents to fill in the questionnaires. A small-scale pilot test was conducted before the data collection in order to test the questionnaires and sampling method. Only some trivial typing mistake was discovered in the design of questionnaire
150 questionnaires were distributed between 9th march, 2010 to 15th march, 2010. Totally, 106 questionnaires were, successfully, collected. The respondent rate is 61.67%. Respondents' ages range from 18 to 31. Most of them came from the age from between 20-24 and the mean was 22.35 (standard deviation = 2.07). The sample has an acceptable ratio in two genders. 56 respondents (53.3%) are male and 42 respondents (46.7%) are female. 26 respondents (25.7%) are year 1 students, 35 respondents (34.7%) are year 2 students and 40 respondents (39.6%) is year three students. No students from foundation year, year 4 and post-graduate is in the sample, it may somehow caused by their small number compared with other students. 66 respondents (62.3%) enter university through JUPAS and 40 respondents (37.7%) enter university through non-JUPAS. Most respondents came from college of business (36.20%), college of science and engineering (26.7%) and college of humanities and social science (22.9%).
The CGPA distribution was also fair. 62 students (58.49%) had CGPA between 2.5 and 3.5, 41 students (38.68%) had CGPA below 2.5, and 3 students (0.28%) had GPA above 3.5. Their mean CGPA was 2.71, with a standard deviation of 0.51.
The questionnaire composed with two pages and 41 questions. 7 scales were included in the first parts of questionnaire and some demographic data was asked in the second part. All of the scale of this research would be used 7-point Likert-type rating scale. The questionnaires required about 10-15 minutes to complete. It was kept as short as possible to rise the respondent rate and the inpatient of interviewees. In order to prevent the distortion of the scale during the process of translation, the questionnaires were written by English. There should be no problem for the understanding as the targeted population was university students who should be able to read English. Indeed, all words used in the questionnaires were kept as simple as possible.
Instead of aggregated SES, individual SES would be measured in this present study. Individual SES would be used because all interviewees would be come from City university of Hong Kong and its size is relatively small. It is impossible for comparing the aggregated school SES of different schools. The neighborhood SES is, indeed, complicated in the situation of Hong Kong.
Income, parental education backgrounds, as most literatures (such as Sirin, 2005), would be measured. Parental occupation would not be included in this present study as occupations were not representative enough as the situation in the foreign countries (such as Finland). It is complex to define the SES by the occupations in Hong Kong.
For the income, apart from parental incomes, family incomes and number of family members would also be asked. It is because it could give more accurate and comprehensive information of student's SES. An identical set of rankings of incomes would be given to interviewees in order to simplify the questionnaires. The lowest ranking was, 'less than HKD$6,000', and the highest ranking was 'more or equal to HKD$60,000'. The categories of family income were then transformed into ratio data using the median number of each category, e.g. 8,999.5 in '8,000 - 9,999'. The lowest and upper categories were transformed in the same range as their closet category, i.e. '<6,000' as '4,000 - 5,999' and 'â‰§60,000' as '60,000 - 79,999'. The incomes of family would be divided by the number of family members for calculating the household income per family member.
For the parental education backgrounds, similar to the incomes, an identical set of education level would be set. Interviewees would be asked the highest education that their parents completed. There would be totally six categories, which were "no regular educational experience", "completed primary schooling", "completed lower secondary schooling", "completed upper secondary schooling", completed tertiary education(non-degree), completed tertiary education (bachelor degree) and " completed master degree program or above".
Parental involvement in employment
Five questions about various aspects, such as opinion giving, information giving employment opportunities helps, composed the scale of parental involvement in employment. For example, "My parents provide me some opinions about my employment", "My parents provide me some information about my future employment" and
"My parents provide me some working opportunities"
Future Time Prospective
ZPTI would be used to measure the future time prospective scale, the same one as Phan (2007, 2009) used. It was originally developed by Zimbardo and Boyd (1999). There were 5 parts, which included, past-negative, past-positive, presenthedonistic, present-fatalistic as well as future, in ZPTI which had totally 56 questions. However, only the future scale of the future would be used, as the other parts were not related to this present study and shorten the length could reduced the inpatient of interviewees, and hence preventing them to fill in the questionnaires without heedful considerations.
Achievement goals and efforts
Mastery goals, performance-approach goals, and performance-avoidance goals would be measured by the scale developed Midgley et al. (1998). There would be six questions for each goal. Work avoidance would be measured by four items from Skaalvik (1997). Effort was measured by the scale developed by Elliot et al. (1999).
Academic performance of university student was measured by Grade Point Average (GPA) in many researches (Walpole, 2003) as it is simple and accurate. It is the prime official measure of students' academic performance in most tertiary educational institutions. Cumulative Grade Point Average (CGPA), which is the average of scores of GPA in all semesters finished, was used in this study. It provided a general understanding of the overall academic performance of respondents in all semesters. The CGPA range of this study was from 0 to 4.3.
The formula to calculate CGPA: [Total of (credit hours X score)] / Total credit hours
No significant relationship was found for the MANOVA testing of age and years and t-test for gender and entrance method with different scales and CGPA. However, significant finding was shown between college and parental involvement in employment (F=2.67, p<0.05), performance avoidance goal (F=3.14, p<0.05), effort (F=2.52, p<0.05) and CGPA (F=3.60, p<0.01).
Reliability of scales
The internal consistency reliability for all scales was acceptable. The Cronbach' s Alpha for parental involvement in employment was 0.89, Future time prospective was 0.83, Mastery goal was 0.91, Performance achievement goal was 0.89, Performance avoidance goal was 0.87, work avoidance was 0.86, and effort was 0.95.
The results of this present research were, generally consistent with the framework. Most of the hypothesized relationships were shown in the result, except for H2 and H5 which no significant relationship were shown. For H3, only work avoidance did not show significant relationship with future time prospective. In fact, work avoidance showed no significant relationships in the framework at all. The performance approach goal and effort (0.35) showed the strongest relationship among the framework. The second strongest was between performance avoidance goal and effort (0.31), and the third strongest relationship was between future time prospective and performance approach goal (0.28).
Parental involvement in employment and future time prospective
Contrary to the expectation, parental involvement in employment showed no significant relationship with future time prospective. However, both of them were significantly linked to other scale.
For the parental involvement in employment, it was found to be significantly linked with all achievement goal, effort and academic performance. It had a particularly strong relationship with performance avoidance goal (0.37). It is a very strong relationship in the research of social science. Apart from that, the relationship of it with mastery goal (0.29) and academic performance (0.26) were very strong as well.
For the future time prospective, it was found to be positively related with performance approach goal, performance avoidance goal and academic performance. Performance approach goal (0.30) showed the strongest relationship with it.
There were some interesting findings about the socioeconomic status. It was significantly influence the parental involvement in employment. Both education background of father, education background of mother, income of family, income of father and income of mother were positively related to the parental involvement in employment. Education background of father showed the strongest relationship with parental involvement in employment. Except income of father, all elements of socioeconomic status were significantly related to mastery goal and performance approach goal. No significant relationship was found between socioeconomic status and work avoidance.
However, it seemed that both the income and education side have different impact on other aspect of students. On one hand, only the three income elements were positively linked to the future time prospective and no such relationship were found in the education side. Yet, one the other hand, only the education background of parent showed significant relationship with work performance avoidance goal, effort as well as academic performance.
Except work avoidance, all elements of achievement are linked with effort. Yet, only mastery goal are significantly related with academic performance. All of the elements are significantly inter-related, and their relationships were very strong. The strongest relationship was between mastery goal and performance approach goal (0.51). The second strongest one was between performance approach goal and performance avoidance goal (0.51), and the third strongest one was performance approach goal and work avoidance (0.42).
Researches investigating in student's academic performance have been done in various aspects. This present study re-examined the theoretical framework between socioeconomic status, future time prospective, achievement goal, effort and academic performance of students. Although that framework had been examined by different scholars, the results were not consistent. The inconsistency might be due to the cultural differences between dissimilar regions. Therefore, this study tested the theoretical framework again in Hong Kong, and tried to investigate if the framework found by those previous studies could be applied in Hong Kong or not. Indeed, parental involvement in employment was introduced in the framework for being a mediating factor between socioeconomic status and future time prospective.
Most of the findings in this present study were consistent with the framework with Phan (2007, 2009). Future time prospective significantly influenced the Achievement goals (except work avoidance in this study), and the achievement goal significantly influenced the effort. There were three differences inconsistent with Phan (2007, 2009). First, different from Phan (2007, 2009), work avoidance showed no significantly with future time prospect and effort. Second, effort is positive related academic performance. The inconsistency might somehow caused by the tremendous culture differences between Fiji and Hong Kong.
Similar to the previous finding (e.g. Zimbardo et al., 1997), no significant difference was shown between different gender. There was not any significant difference between different age, number of family members, year of student and entrance method of university as well. However, students in different colleges showed differences in parental involvement in employment, performance avoidance goal, effort and CGPA. It might caused by the dissimilar learning environment, culture, entrance requirement (some colleges, such as school of law, required higher admitting requirement than other colleges), the workload and the difficulty of the courses in various colleges.
As the hypothesized framework, socioeconomic status significantly linked with the parental involvement in employment. The finding showed that Parents who were better educated and had higher incomes concerned more about the development of their children's career development. This research further found the socioeconomic status was positively related to the parental involvement in employment.
Other than that, it was found that education background and family income had dissimilar impacts toward students. The education background of parents had significant impact on students' effort and academic performances, but there is no impact at all for the income of family or parents. The find is similar to previous finding (such as, Liu and Lu, 2008). One of the explanations is that parents with higher socioeconomic status would have more motivations in participating education-related activities than the families with low SES in the previous research. Inconsistent with the previous finding (e.g. Ginsburg and Bronstein, 1993, Lamdin, 1996), no significant finding was discovered between the wealth of family and the academic performance of students. It might caused by the target population in this present study is university students. The financial benefits of students in high income family were not as prominent as the primary school and secondary schools. For example, most reference books could be found in the school library of university which had greater collection than the libraries in primary and secondary schools. Indeed, the syllabus in university was less reliant on the textbooks and examinations. More assessments were based on the assignments or daily performances, and most of the resources needed could be found in the internet. Both of these matters made the importance of family incomes had less influences toward the academic performances.
However, on the other hand, incomes of family and parents both significant influences the future time prospective, but the education background had no significant impacts on it. In the money-orientated culture of Hong Kong, it seemed the monetary side outweighed the education side, when students were considering their future. Students who came from wealthier families had better expectations then those came from less wealthy families. Yet, there was not solid prove for this explanation. Further investigation is needed for explain this finding.
Parental involvement in employment was the fresh concepts introduced in the framework. It was, originally, aimed at providing an intermediate element between future time prospective and socioeconomic status. However, it is out of expectation that there is no significant finding between future time prospective and parental involvement. Nonetheless, significant relationships were found between it and achievement goals, effort and academic performance. It showed that although the parental involvement in employment had no huge impact on future time prospective, it still influences the academic performances in another forms. Some elements might considered to be added in the framework in the future study in order to find out how did the parental involvement in employment affect the other elements in the existing framework if it is not significantly related to the future time prospective. Indeed, how the socioeconomic influences the future time prospective was also a topic that is worthwhile for further investigation.
In the line of previous finding, future time prospective kept affecting the effort of students significantly. Students with long-term envision toward their future spent more effort in their study for their future. Apart from that future time prospective, also, influenced the mastery goal, performance approach goal and performance avoidance goal. These finding could, somehow be explained by the socio-cultural context in Hong Kong which the academic success has enormous impacts on students' future career. Although the social mobility was claimed to be deteriorated in the recent year, the academic performance still a determining factor when students apply for a job after graduation. Therefore, students who had high future time prospective used concerned more about their academic performances because of its importance. They would strive for performing well in school, or at least preventing them from getting poor performance academically which may hinder them to find ideal job in the futures. It was reasonable that they will put extra effort in study compared with those with low future expectations.
For the achievement goal, as expectation, those four elements are closely inter-related. The co-relation between performance approach goal and performance avoidance goal was, especially, high. Their closed relationship was understandable as those four concepts were actually quite similar. In fact, some of the wordings in the scales were also quite similar as well.
It is unexpected that work avoidance had not showed any significant relationship with other elements in achievement goal and parental involvement in employment. Different from the previous finding (Phan, 2009), it had no significant relationship with effort. The other three elements show similar finding with Phan (2009). The mastery goal, performance approach goal and performance avoidance goal were linked to the effort. However, only mastery goal was linked to the academic performance. It is a meaningful finding as the finding showed that developing students interests in acquiring new skills and improving their knowledge even facing obstacles were more effective than making students interested in obtaining positive evaluations of ability and avoiding negative evaluation. Although both of them are able to enhance the effort of students in their academic study, only the mastery goal can effectively improve the student's academic performance. The assessment methods in university might be one of the main reasons. As mentioned before, apart from examination, assignment, presentation, individual paper or group paper as well as the performance in class were used to assess the academic performance of students in university. Those assignment required student a depth knowledge and they overcome some obstacles for getting high grades which students with mastery goal were good at.
It was worthwhile to consider this finding when schools consider some program to enhance their students' academic performance. Schools should force more on promoting the interests of students in studying. Indeed, schools might consider implementing so-call "foundation year" policy. It provides some fundamental course in various disciplines in students' first year in university. Students could, therefore, choose their major which they are interested in according their experience in the first year. It is better than forcing students to choose their major without any experience in their future major. It is much more to build up students' interests when they are studying in their favorite major.
There are some limitations in this present study.
First and most apparently, the sampling of this research is non-random. The sample was obtained in the school podium in three different time slot (morning, afternoon and evening). The time slot was set for preventing students to be excluded because of their time in going to schools. Yet, it still could not be ensured that every student had equal opportunities to be selected. Some students might be oversampled or undersampled, and there is no way to know if that happened. The representative and accuracy of this study was not as high as the random sampling.
Second, the target sample is limited in City University of Hong Kong. Although in the data collection, it tried to collect the data from various students. The cultural differences was neglected in this present studies. The current data was not representative enough for the whole university students in Hong Kong. Hence the result could not be generalized as the populations of university students in Hong Kong.
Third, only quantitative research method is used in this present research. Some concepts, such as the future prospective, are complicated and cannot be measured and elucidated by quantitative method entirely.
Fourth, the cross-sectional design only measured the variable in a restricted time-frame. The variable's effect might be delayed which cross-sectional design could not measured. A causal is tough to develop. The estimation power was, hence, restricted as well.
The framework of this present study was examined in different regions, such Fiji and Spain. However, each region's results were only similar, but not identical. Such framework can be further examined in other regions, in order to investigate whether the framework can be applied in other regions or not. It will be interesting to find out will and how the socio-cultural differences will affect the outcome.
Also, further investigation is needed to discover more detailed about the socioeconomic status and academic performance. Although the finding showed they were significantly linked, the process of how the socioeconomic status affect the academic performance still remind unclear. The reason of why education background and income of parents had dissimilar impacts in different elements in the framework is still unclear.
Apart from that, how the parental involvement in employment influenced the achievement goal, effort and academic performance was unknown as well. There was no significant relationship between it and future time prospective. Another new concepts and hypothesis should be considered in the framework for linking the parental involvement in employment and achievement goal.
Some kind of the socialization process may be the reasons behind the relationship between socioeconomic status and parental involvement in employment. But, it is not yet proved. There are still plenty of rooms for future investigation.
For the future study, if the resources and time is allowed, random sampling is preferred as it can effectively enhance the representative of the study. And, there is less chance has an over-sample or under-sample group of population. Indeed, the whole ten universities should be included in the target population. A population that represents the whole group of university students in Honk Kong could give more accurate and less-biased results. The cultural differences in ten universities could also be observed. A sample size that bigger than this presents study is also preferred, as it can reduce the sampling error in the data set. However a stratified-sampling might have to be consider, as some of universities, such as Lingnan University and Shue Yan University, had much lesser students than the other university. If a simple random sampling is used, there may be too few of the students being selected.
The present study will use cross-section and qualitative research method only. Some qualitative longitudinal measure methods can also be adopted. It may give a better understanding for how the different variables affect each other with time. Also, the qualitative method could be a supplement for investigations the process of how do them affect each others.