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Assessing Student Approaches to Learning: A Case of Business Students at the Faculty of Business Management, UiTM
Available online at www.sciencedirect.com
ScienceDirect Procedia - Social and Behavioral Sciences 90 (2013) 904 – 913
6th International Conference on University Learning and Teaching (InCULT 2012)
Assessing student approaches to learning: A case of business students at the Faculty of Business Management, UiTM Zahariah Mohd Zaina*, Irfah Najihah Basir Malanb, Fauziah Noordinc, Zaini Abdullahd abcd
Faculty of Business Management, Universiti Teknologi MARA, 40450, Selangor, Malaysia F
Abstract The main aim of the study is to investigate the approaches to learning, motives and strategies of the business students at the Faculty of Business Management, UiTM. The study is also to explore the impact of age, gender, academic programmes, working experience and CGPA on the learning approaches. All these variables are selected because they bring quality of the learning outcomes on a more realistic basis. Today, there is an increasing emphasis on quality of learning in higher education. The literature identifies the approaches to learning as a significant factor affecting the quality of student learning. It is necessary to look at approaches to learning practiced by students because students might rote learn and therefore not be engaged in meaningful learning. This involves students acquiring skills and strategies, which allow them to learn effectively throughout their lives and become lifelong learners. It is important for educators to understand student learning in order to achieve the desired high quality learning outcomes. A survey is conducted in this study and the sample of this study consists of the business students (N=477) enrolled at the Faculty of Business Management, UiTM Shah Alam. Data are obtained using the Biggs’ Study Process Questionnaire (SPQ) as a diagnostic tool for measuring students’ selff reported study processes in terms of six subscales (Surface Motives and Surface Strategies, Deep Motives and Deep strategies, and Achieving Motives and Achieving Strategies), three derived Scales (Surface Approaches, Deep Approaches and Achieving Approaches) and a composite derived Scale (Deep-Achieving Approaches). The key findings provide inputs to the current scenario on the learning process specifically for the Faculty of Business Management, UiTM and will act as a basis for improvement in learning approaches of students. © 2013 2012The TheAuthors. A Authors. Published by Elsevier © Published by Elsevier Ltd. Ltd. Selectionand/or and/or peer-review under responsibility of the of Faculty of Education, UniversityMARA, Technology MARA, Malaysia. Selection peer-review under responsibility of the Faculty Education, University Technology Malaysia. Keywords: students’ approaches to learning; SPQ; age; gender; academic programmes; working experience; CGPA
* Corresponding author. Tel.: 019-2601265 E-mail address: [email protected]
1877-0428 © 2013 The Authors. Published by Elsevier Ltd. Selection and/or peer-review under responsibility of the Faculty of Education, University Technology MARA, Malaysia. doi:10.1016/j.sbspro.2013.07.167
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1. Introduction One of the major areas investigated by researchers interested in describing and/or enhancing the quality of learning in university settings has been concerned with students’ approaches to studying and learning (Svennson, 1977), (Watkins, 1982), (Biggs, 1987), (Van Rossum and Schenk, 1984), (Ramsden, 1985), (Entwistle and Waterson, 1988), (Volet, 1988), (Jones, Caird and Putterill, 1989), (Regan and Regan, 1995) and (Zeegers, 1999). Analysis of investigations of knowledge that students already have corroborates the idea that there is a great potential or learning in human beings that remains undeveloped and that many educational practices dull instead of facilitate (Novak, 1985). Both instruction and evaluation strategies frequently applied in schools and universities justify and reward rote learning and often penalize meaningful learning (Novak, 1977a). When instruction centres on memorization of definitions, dates and problem-solving algorithms, and when evaluation requires verbatim answers or text-type problem solutions, meaningful learning with thoughtful reconstruction of knowledge can be a liability (Gonzales, 1997). According to (Novak, 1987), many students believe that memorizing school (or university) information is the only way to learn. Experience shows that educators often find themselves powerless to diminish rote learning and to increase meaningful learning. Novak (1987) also postulates that three important reasons explain the difficulty of this problem. First is the student may not be aware that there is an alternative to rote learning. Second, the concepts to be learned are presented in such an obscure way that learning by memorizing appears to be the only alternative. Lastly, evaluation of student learning often requires little more than verbatim recall of information or problem-solving algorithms. Based on these reasons, as suggested by Gonzales (1997) which imply knowing students’ ideas and taking them into account in the design of both curriculum and instruction is necessary, where meaningful learning by students can be enchanted. Only in this way can adequate conceptual change be promoted and, by sharing meanings, ideas of students can be brought closer to those of scientists. For most students who enter tertiary study, and especially for mature-age students whose most recent life experiences are not in an educational setting (in contrast to usual-age students), tertiary study presents a new learning environment in which students need to acquire or develop further a variety of strategies to successfully navigate through their courses. The development of appropriate strategies to successfully navigate through their courses. The development of appropriate strategies for studying and learning allows students to overcome problems, which would otherwise be disruptive to the learning process and affect learning outcomes. In turn, the development of appropriate strategies enhances the satisfaction that can be derived from gaining control over the learning situation (Cohen, 1993). However, not all students are able to choose the appropriate strategies to enable them to reap the academic and personal rewards. For example, some may lack the specific knowledge of the strategies that are available or may fail to transfer a previously learned routine or may have actually worked a negative routine into a bad habit (Garner, 1988). Furthermore, many students are not even consciously aware of their approaches which are often not appropriate either to their own intentions or to those of their teachers (Biggs, 1987a), let alone aware of the many subtle that need to occur as they consciously attempt to select strategies to cope with the oft-occurring competing lecturer and institutional demands (Beckwith, 1991). Although there is growing body of research on how students go about studying and learning, according to (Murray-Harvey and Keeves, 1994), this knowledge is undervalued. One of the reasons for this is that there is a perception that university students already know how to learn. Although in the early years of schooling much time is spent on the development of the process skills that are required to master the content of schoolwork, this time decreases proportionally as the student’s progress through their schooling. As a result, less time becomes allocated to instruction in the strategies and skills that facilitate the learning of content and more time becomes given to the content itself. This means that by the time students enter higher education it is often erroneously assumed that they have not only learned a body of knowledge but they have also learned how to learn (MurrayHarvey and Keeves, 1994). Students who are not equipped with the strategies and skills needed to meet the academic demands of their course and who have limited opportunities to confront such inadequacies are likely to have problems because they are “left guessing about lecturers’ expectations and develop coping rather than
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learning strategies for getting through the course” (Murray-Harvey and Keeves, 1991) . As well, students who have problems are often through of as being unable to master the content (Knapp, 1991) which is not necessarily the case. Many research findings point out that the approach to learning and study skills are significant factors affecting the quality of student learning. It is also known that quality of teaching-learning environment and assessment procedures affect student’s approaches to learning and ultimately quality of learning outcomes (Marton and Saljo, 1976), (Entwistle and Ramsden, 1983), (Ramsden, 1988), (Biggs, 1993), (Hounsell, 1997), (Enwistle, 2000a; 2000b), (Prosser and Trigwell, 2006), (Smith and Miller, 2005) and (Byrne, Flood and Willis, 2009). For more than three decades, researchers in education have attempted to understand learning from a phenomenographic perspective (Duff, 2004). Early research on student learning based on text reading experiments in the 1970s. The starting point is to find ways of describing some of the main differences in how students think about learning and carry out their studies. Students are asked to read an article and are interviewed to assess their level of understanding and to determine their process of learning. In these studies, (Marton and Saljo, 1976) identified two levels of processing of learning- deep and surface and this has been replicated and extended in many studies (Marton and Saljo, 1997), (Prosser and Trigwell, 1999), (Phan and Deo, 2007) and (Justicia, Pichardo, Cano and Fuente, 2008). Instead of “level of processing”, (Enwistle, Hanley and Hounsell, 1979) preferred to use the term “approach”, which is also accepted as the best descriptor for the qualitative differences in students’ responses to learning tasks (Marton and Saljo, 1997). Students adopting the deep approach to learning intend to understand the material, and they show active engagement and interest in their studies. They interact critically with the arguments and evidence by using prior knowledge and other resources. They also monitor the development of their own understanding (Enwistle, Mc Cune and Walker, 2000) . Learning is an internal process to them. In contrast, students who prefer the surface approach mainly tend to memorize the material without understanding. They intend to reproduce the learning material and use different forms of rote learning. Mainly, they are constrained by the specific learning task and do not go beyond it. In this approach, predominant motivation is fear of failure and concern with the completion of a course. Deep approach is more likely to result in a high level of understanding and effective learning whereas surface approach is likely to lead to a low level of understanding and ineffective learning (Entwistle and Ramsden, 1983). Interviews on everyday studying drew attention to the pervasive influence of assessment procedures on learning and studying. These suggested the need for additional category. Third approach to learning is called achieving / strategic approach. Students who are primarily concerned with achieving the highest possible grades prefer to use the achieving / strategic approach. These students use both deep and surface approaches as they see appropriate and have a competitive motivation. In this approach, the major intention is to achieve the highest grades possible by means of organized study methods and time-management (Entwistle and Ramsden, 1983). Achieving / strategic approach also involves monitoring one’s study effectiveness (Entwistle et al., 2000) and alertness to the assessment similar to metacognitive alertness and self-regulation (Entwistle, 2000b). After phenomenographic investigations, the second line of research has taken the form of designed inventories which measure these concepts and so allow relationships to be established in larger representative groups. The widely used inventory was the Approaches of Studying Inventory (ASI) and Study Process Questionnaire (SPQ). These are two best known questionnaires which investigate how students generally go about their learning. Both questionnaires are similar in that they are derived from students’ interview data and they both contain scales that attempt to discriminate between students who use either surface or deep approaches. In addition, both questionnaires also have an additional scale which describes a “competitive approach” that involves trying to gain the best results as efficiently as possible. In the Approaches of Studying Inventory (ASI) this is described as a “strategic” scale and in the Study Process Questionnaire (SPQ) as an “achieving” scale. Other than that, questionnaires in each of these three constructs are measured in relation to (i) intention and (ii) strategy. For this study, Study Process Questionnaire (SPQ) is employed. It is interesting to highlight this questionnaire at the product level in order to identify if teaching contexts differ. In an ideal system, it would be
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expected that students would operate at the highest level when engaging with learning activities. Different versions of Study Process Questionnaire (SPQ) have been used in studies for different purposes. Some of the recent studies are designed to investigate the reasons for poor performance at universities. Thus, these results can lead the educators to think how to increase quality of learning outcomes by promoting deep learning through teaching-learning process and assessment procedures (Entwistle et al., 2000) and (Byrne et al., 2009). Research to date on students learning approaches and study skills in education or in teacher training institutions is limited, yet students as teacher candidates must be prepared to facilitate their students how to learn effectively. The mere translation of educational practices without taking into account contextual differences is problematical and could result in undesired consequences. It is therefore crucial that educator candidates possess and use effective learning strategies in their pre-service education. If educator candidates used effective learning approaches and study skills in their own learning, they would provide their students with high quality learning approaches and study skills. For this reason, investigating the approaches to learning and study skills of business students at the Faculty of Business Management, UiTM is very important in order to see how well we educate our future educators and to enhance educator training programs as necessary. The learning approaches paradigm provides a framework within which educators can analyze the ways that students learn, and it also provides a means of examining the learning effects of cultural diversity in student backgrounds. Students have been identified as typically adopting different study approaches depending upon their background characteristics. These include age, gender, prior knowledge of subject matter and level of intrinsic interest, which are termed “Personal Variables”. Different study approaches have also related to what are termed “Situational Variables” namely the curriculum, teaching method, assessment and classroom climate. This study also seeks to examine the impact of age, gender, academic programmes, working experience and CGPA on the learning approaches of the business students at the Faculty of Business Management, UiTM. So, in this case, Study Process Questionnaire (SPQ) can play a role in the description and improvement of the teaching-learning process by contributing to an understanding of students’ approaches to learning on an individual or group basis and by providing a foundation upon which to measure the effects of other factors that impact on student learning. The purpose of this study is to determine the approaches to learning, motives and strategies of business students at the Faculty of Business Management, UiTM. For this purpose, answers to the following questions are sought: 1. 2.
What are the approaches to learning adopted by the business students at the Faculty of Business Management, UiTM? Does age, gender, academic programmes, working experience and CGPA have an impact on the learning approaches of business students at the Faculty of Business Management, UiTM?
2. Methodology A survey is conducted in this study and the sample covers the area in UiTM, Shah Alam, Selangor. There are many students that come from various faculties. However, for the purpose of this study only focus on the business students (N=477) who enrolled at the Faculty of Business Management, UiTM, Shah Alam. A set of demographic variables are developed to seek answers to the research questions. A survey method is conducted in this study. Study Process Questionnaire (SPQ) is incorporated in this study. It is a self-report questionnaire that utilizes a Likert-scale format to measure the extent to which the students endorse different approaches to learning by identifying the Motives and Strategies that comprise these approaches. The questionnaire yield scores on three Motives (7 items each measuring Surface, Deep and Achieving Motives, respectively) and three associated Strategies for learning (7 items each measuring Surface, Deep and Achieving Strategies, respectively) and yield three derived Approaches scores that are obtained by summing respective Motives and Strategies scores (measuring Surface, Deep and Achieving Approaches respectively). The questionnaire also combines two of the Approaches scores to yield a Deep-Achieving Approach score. The questionnaire yield scores on 10 SPQ
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variables. The statistical methods used in this study are descriptive statistics (Mean for males and females), reliability (Cronbach’s alpha), correlation (males and females) and multiple regression analysis. 3. Discussion and Analysis 3.1. Descriptive statistics (Mean for males and females) The descriptive statistics table shows the mean for males and females according to the variables. Table 1 of descriptive statistics shows the mean for males (84) and females (393). The variables consists of age, working experience, CGPA, surface motives, surface strategies, deep motives, deep strategies, achievement motives, achievement strategies, surface approach, deep approach and achieving approach. 83.3% of males age are 18-21 years old while remaining are 22 years old and above. Besides that, 98.8% of males are having working experience while remaining is not. The lowest mean is surface strategies which is 2.38 while the highest mean is achievement motives which is 2.92. These suggest that average of 2.38 students is affected by surface strategies while average of 2.92 students are affected by achievement motives. Meanwhile, about 24.4% of females are age between 18 to 21 years old while remaining are 22 years old and above. For working experience, most of females on average don’t have working experience which account for 67.9%. The lowest mean is 2.58 which is CGPA while the highest mean is 4.30 which is achievement motive. These suggest that average of 2.58 of female students is affected by CGPA while average of 4.30 female students is affected by achievement motives. Based on these results, both males and females share the highest mean which is achievement motives. This indicates that majority of the students, on average mostly affected by achievement motives. Table 1. Descriptive statistics-Mean for males and females Variables Age Working experience CGPA Surface motives Surface strategies Deep motives Deep strategies Achievement motives Achievement strategies Surface approach Deep approach Achieving approach a Gender = Male (84) b Gender = Female (393)
Mean for males 18-21 years = 83.3% 22 years and above = 16.7% Yes = 98.8% No = 1.2% 2.69 2.53 2.38 2.76 2.63 2.92 2.41 2.46 2.69 2.67
Mean for females 18 – 21 years = 24.4% 22 years and above = 75.6% Yes = 32.1% No = 67.9% 2.58 4.09 3.79 4.06 3.89 4.30 3.83 3.94 3.98 4.06
3.2. Reliability (Cronbach’s alpha) Table 2 shows reliability test which is Cronbach’s alpha. Cronbach's alpha is a measure of internal consistency. It is a coefficient of reliability. A reliability coefficient of .70 or higher is considered “acceptable". The first variable which is surface motives contains seven items. It has a cronbach alpha of 0.970, suggesting that the items have relatively high internal consistency. Meanwhile, the alpha coefficient for the seven items in the surface strategies is 0.971; also supporting the items have relatively high internal reliability. The cronbach alpha
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for seven items in third variable which is deep motives is 0.973, and followed by seven items in deep strategies with an alpha coefficient of 0.969. These support that all items in the deep motives and deep strategies are closely related as a group. Meanwhile, the cronbach alpha for seven items in achievement motives, and seven items in achievement strategies are 0.968 and 0.977 respectively. On the other hand, 14 items in the variable of surface approach, 14 items in the deep approach and 14 items in the achieving approach has the same alpha coefficient which is 0.985. These mean that all the items in the respective variables have very high internal consistency and very closely related as a group. Table 2. Realibility test (Cronbach’s alpha) Variables (No.of items) Surface motives (7) Surface strategies (7) Deep motives (7) Deep strategies (7) Achievement motives (7) Achievement strategies (7) Surface approach (14) Deep approach (14) Achieving approach (14)
Cronbach’s alpha .970 .971 .973 .969 .968 .977 .985 .985 .985
3.3. Correlation (Males and females) Table 3 and Table 4 show the correlation among original variables according to males and females respectively. The original variables for the learning approaches are age, working experience, CGPA, surface motives, surface strategies, deep motives, deep strategies, achievement motives, achievement strategies, surface approach, deep approach and achieving approach. Correlations tell on how strong the relationships among the variables. Generally, a strong correlation is near to -1 or +1. Based on the Table 3 for Correlation (Males), the first until the third variable, the correlations are small, indicate that age, working experience and CGPA yields not much information about the data. Besides that, some of the correlations in the second variable which are surface strategies, achievement strategies, surface approach and achieving approach cannot be computed because at least one of the variables is constant. However, the remaining variables have uniformly large correlations. The strong correlation is surface approach. This suggests that surface approach gives more effects to males in their learning approaches. For the Table 4 for Correlations (Females), the first and second variables have uniformly large correlations among their variables. Meanwhile, the third variable has a small correlation, suggesting that CGPA yields not much information about the learning approaches. However, the remaining variables have large correlations and the most strongly correlated are surface approach and deep approach. This indicates that surface approach and deep approach gives more effects to females in their learning approaches. Hence, it can be conjectured that surface approach is the best predictor in learning approaches since it gives more effects to both males and females.
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Zahariah Mohd Zain et al. / Procedia - Social and Behavioral Sciences 90 (2013) 904 – 913 Table 3. Correlation (Males) Working Surface Surface Deep Deep Achmnt Achmnt expernc motive strategy motive strategy motive strategy Variables Age CGPA 1. Age 2. Working .245(*) expernc 3. CGPA -.202 -.164 4. Surface .231(*) .008 -.125 motive 5. Surface .198 .(a) -.060 .940(**) strategie 6. Deep .143 .057 -.115 .837(**) .788(**) motive 7. Deep .216(*) .204 -.128 .885(**) .890(**) .882(**) strategy 8.Achmnt .105 -.012 -.056 .924(**) .934(**) .821(**) .856(**) motive 9.Achmnt .074 .(a) -.085 .896(**) .854(**) .850(**) .905(**) .880(**) strategy 10.Surface .223(*) .(a) -.098 .988(**) .981(**) .828(**) .910(**) .943(**) .891(**) apprch 11. Deep .184 .132 -.125 .886(**) .860(**) .972(**) .968(**) .864(**) .901(**) apprch 12. Achieve .097 .(a) -.073 .940(**) .926(**) .861(**) .918(**) .974(**) .964(**) apprch * Correlation is significant at the 0.05 level (2-tailed), ** Correlation is significant at the 0.01 level (2-tailed) a. Cannot be computed because at least one of the variables is constant
Surface apprch
Deep apprch
Achieve apprch
.892(**) .948(**)
-
.914(**)
Table 4. Correlation (Females) Variables 1. Age 2. Working expernc 3. CGPA
Age .625(**)
Working expernc
CGPA
Surface motive
Surface strategy
Deep motive
Deep strategy
Achmnt motive
Achmnt strategy
Surface apprch
Deep apprch
Achieve apprch
-
-.091 -.133(**) 4. Surface .647(**) .739(**) motive .205(**) 5. Surface .635(**) .689(**) .955(**) strategy .209(**) 6. Deep .527(**) .642(**) .925(**) motive .258(**) 7. Deep .604(**) .700(**) .921(**) strategy .254(**) 8. Achmnt .604(**) .734(**) .975(**) motive .209(**) 9. Achmnt .552(**) .742(**) .887(**) strategy .247(**) 10.Surface .648(**) .722(**) .989(**) apprch .206(**) 11. Deep .572(**) .679(**) .934(**) apprch .257(**) 12. Achieving .593(**) .759(**) .956(**) .227(**) apprch ** Correlation is significant at the 0.01 level (2-tailed)
.925(**)
-
.950(**)
.954(**)
-
.948(**)
.930(**)
.926(**)
-
.908(**)
.897(**)
.936(**)
.890(**)
-
.988(**)
.935(**)
.946(**)
.972(**)
.906(**)
-
.949(**)
.989(**)
.988(**)
.939(**)
.927(**)
.952(**)
-
.954(**)
.939(**)
.958(**)
.970(**)
.974(**)
.966(**)
.960(**)
-
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3.4 Multiple regression analysis The result of the multiple regression analysis is displayed in Table 5. The result indicates that most of the relationships are in predicted positive direction and the estimate for the major variables are significant. However, there is also estimation between dependent variables and independent variables which is considered insignificant. For instance, such as surface strategies and academic programs, deep motives and academic programs, deep strategies and academic programs, achieving strategies and academic programs. Thus, only these variables are not supported. The coefficients of multiple determinations (R²) for each variable are also quite high. In this study, multicollinearity is not shown for all the variables investigated. Meanwhile, the variance inflation factor (VIF) is below 10 for all the independent variables. For diagnostic purpose, the Durbin-Watson value falls within the acceptable range. It implies there is no autocorrelation problem. Table 5. Multiple regression analysis results Dependent variables Surface motives
Surface strategies
Deep motives
Deep strategies
Achieving motives
Achieving strategies
Surface approach
Explanatory variables
Unstandardised coefficients
R-square
Gender Age Working experience CGPA Academic programs
.922*** .414*** .644*** -.108** .041***
.771***
Gender Age Working experience CGPA Academic programs
.774*** .408*** .591*** -.117** .015
.741***
Gender Age Working experience CGPA Academic programs
.809*** .224*** .538*** -.161*** .011
.697***
Gender Age Working experience CGPA Academic programs
.712*** .284*** .556*** -.146*** .001
.74.5***
Gender Age Working experience CGPA Academic programs
.845*** .260*** .604*** -.089* .029**
.739***
Gender Age Working experience CGPA Academic programs
.785*** .151** .750*** -.160*** -.016
.758***
Gender Age Working experience CGPA Academic programs
838*** .412*** .619*** -.112** .028**
.766***
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Deep approach
Achieving approach
Gender Age Working experience CGPA Academic programs
.761*** .254*** .545*** -.151*** .007
Gender Age Working experience CGPA Academic programs
.804*** .207*** .679*** -.123*** .006
.731***
.766***
*p ≤ .05; **p ≤ .01; ***p ≤ .001
4. Conclusion This study investigates the approaches to learning, motives and strategies of business students at the Faculty of Business Management, UiTM. For this purpose, there are 9 approaches to which are surface motives, surface strategies, deep motives, deep strategies, achievement motives, achievement strategies, surface approach, deep approach and achieving approach. From the figure of correlations, the results show that surface approach gives more impact to the learning approaches since it has the highest correlation which is 0.994 with 0.01 level of significant. Besides that, this study also examines the impact of age, gender, academic programmes, working experience and CGPA on the learning approaches of the business students at the Faculty of Business Management, UiTM. Based on the multiple regression analysis, it can be conjectured that gender has more impact on the learning approaches since it has the highest coefficients among explanatory variables for all dependent variables. Moreover, it is also significant with all the dependent variables (p≤0.01). Study Process Questionnaire (SPQ) has indicated robust reliability and constructs validity in some of the measures. An effort should be put into curriculum design, and especially with teaching and assessment methods, so that a constructive and desirable learning context is created to facilitate a positive study orchestration. References Beckwith, J.B. (1991). Approaches to learning, their context and relationship to assessment performance. Higher Education, 22, 17-30. Biggs, J.B. (1987). Study process questionnaire manual. Australian Council for Educational Research, Melbourne. Biggs, J.B. (1987a). Student approaches to learning and studying. Hawthorn, Victoria: Australian Council for Education Research. Biggs, J.B. (1993). What do inventories of students’ learning processes really measure? A theoretical review and clarification. British Journal of Educational Psychology, 63 (1), 3-19. Byrne, M., Flood, B., & Willis, P. (2009). An inter institutional exploration of the learning approaches of students studying accounting. International Journal of Teaching and Learning in Higher Education, 20 (2), 155-167. Cohen, M.L. (1993). Listening to students’ voices: What university students tell us about how they learn. Paper presented at the Annual Meeting of the American Education Research Association, Atlanta. Duơ, A. (2004). The role of cognitive learning styles in accounting education. Journal of Accounting Education, 22, 29–52. Entwistle, N.J., Hanley, M., & Hounsell, D. (1979). Identifying distinctive approaches to studying. Higher Education, 8, 365-380. Entwistle, N.J. & Ramsden, P. (1983). Understanding student learning. Croom Helm, London. Entwistle, N.J. & Waterson, S. (1988). Approaches to study and levels of processing in university students. British Journal of Educational Psychology, 58, 258-265. Entwistle, N.J., Mc Cune, V., & Walker, P. (2000). Conceptions, styles and approaches within higher education: Analytic abstractions and everyday experience. In R.J. Sternberg, & L.F. Zhang (Eds.), Perspectives on cognitive, learning, and thinking styles. New Jersey: Lawrence Erlbaum.
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Enwistle, N.J. (2000a). Approaches to studying and levels of understanding: The influences of teaching and assessment. In J.C. Smart (Eds.), (pp. 156-218). New York: Agathon Press. Entwistle, N. J. (2000b). Promoting deep learning through teaching and assessment: Conceptual frameworks and educational contexts. Paper presented at TLRP Conference, Leicester, November 2000. Garner, R. (1988). Verbal-report data on cognitive and metacognitive strategies. In C.E.Weinstein, E.T. Goetz, & P.A. Alexander (Eds.), Learning and study strategies: Issues in assessment, instruction and evaluation (pp. 63-76). New York: Academic Press. Gonzales, F.M. (1997). Evidence of rote learning of science by Spanish university students. ProQuest Education Journals, 97 (8). Jones, J., Caird, K., & Putterill, M. (1989). First year university commerce students’ views of their learning environment. Research and development in Higher Education, 10, 86-97. Justicia, F., Pichardo, M.C., Cano, F.B.G., & Fuente, J. (2008).The revised two-factor study process questionnaire (R-SPQ-2F): Exploratory and confirmatory factor analyses at item level. European Journal of Psychology of Education, XXIII (3), 355-372. Knapp, M. (1991). Teaching for meaning in high poverty classrooms. New York: Teachers College Press. Marton, F. & Saljo, R. (1976). On qualitative differences in learning – 1 outcome and process. British Journal of Educational Psychology, 46, 4-11. Marton, F. & Saljo, R. (1997). Approaches to learning. In F. Marton, D. Hounsell, & N. Entwistle (Eds.), The experience of learning. Edinburgh: Scottish Academic Press. Murray-Harvey, R. & Keeves, K.P. (1991). Children thinking provides food for thought. Campus, 1 (7), 16. Murray-Harvey, R. & Keeves, K.P. (1994). Students learning processes and progress in higher education. Paper presented at the Annual Meeting of the American Educational Research Association, New Orleans. Novak, J. D. (1977a). A theory of education. Ithaca. New York: Cornell University Press. Novak, J.D. (1985). 'Metalearning and metaknowledges strategiest to help students learn how to learn, in West. In A.L. Pines (Eds.), Cognitive structure and conceptual change (pp. 189-209). Orlando: Academic Press. Novak, J.D. (1987). Human constructivism: A unification of psychological and epistemological phenomena in meaning making. Proceedings of the Second International Misconceptions and Educational Strategies in Science and Mathematics Conference, June 1987. Ithaca, New York: Department of Education, Cornell University. Phan, H.P. & Deo, B. (2007). The revised learning process questionnaire: A validation of Western model of students’ study approaches to the South Pacific context using confirmatory factor analysis. British Journal of Educational Psychology, 77, 719-739. Prosser, M. & Trigwell, K. (1999). Understanding learning and teaching: The experience in higher education. Buckingham, England: SRHE and Open University Press. Prosser, M. & Trigwell, K. (2006). Confirmatory factor analysis of the approaches to teaching inventory. British Journal of Educational Psychology, 76, 405-419. Ramsden, P. (1985). Student learning research: Retrospect and prospect. Higher Education Research and Development, 4, 51-69. Ramsden, P. (1988). Context and strategy: Situational influences on learning. In R.R. Schmeck (Eds.), Learning strategies and learning styles (pp. 159-184). New York: Plenum Press. Regan, L. & Regan, J. (1995). Relationships between first-year university students’ sources on Biggs’ Study Process Questionnaire and students’ gender, age, faculty-of-enrolment and first-semester grade-point-average. Paper presented at 25th Annual Conference of the Australian Teacher Education association Inc., Sydney, 5-8 July1995. Smith, S.N. & Miller, R.J. (2005). Learning approaches: Examination type, discipline of study and gender. Educational Psychology, 25 (1), 43-53. Svennson, I. (1977). Learning processes and strategies: Are three perspectives better than one?. British Journal of Educational Psychology, 47, 233-243. Van Rossum, E.J. & Schenk, S.M. (1984). The relationship between learning conception, study strategy and learning outcome. British Journal of Educational Psychology, 54, 73-83. Volet, S.E. (1988). Modeling and coaching of relevant metacognitive strategies for enhancing university students’ learning. Learning and Instruction, 1, 319-336. Watkins, D. (1982). Academic achievement and the congruence of study motivation and strategy. British Journal of Educational Psychology, 52, 260-263. Zeegers, P. (1999). Student learning in science: A longitudital study using the Biggs SPQ. HERDSA Annual International Conference, Melbourne, 12-15 July 1999.
ScienceDirect Procedia - Social and Behavioral Sciences 90 (2013) 904 – 913
6th International Conference on University Learning and Teaching (InCULT 2012)
Assessing student approaches to learning: A case of business students at the Faculty of Business Management, UiTM Zahariah Mohd Zaina*, Irfah Najihah Basir Malanb, Fauziah Noordinc, Zaini Abdullahd abcd
Faculty of Business Management, Universiti Teknologi MARA, 40450, Selangor, Malaysia F
Abstract The main aim of the study is to investigate the approaches to learning, motives and strategies of the business students at the Faculty of Business Management, UiTM. The study is also to explore the impact of age, gender, academic programmes, working experience and CGPA on the learning approaches. All these variables are selected because they bring quality of the learning outcomes on a more realistic basis. Today, there is an increasing emphasis on quality of learning in higher education. The literature identifies the approaches to learning as a significant factor affecting the quality of student learning. It is necessary to look at approaches to learning practiced by students because students might rote learn and therefore not be engaged in meaningful learning. This involves students acquiring skills and strategies, which allow them to learn effectively throughout their lives and become lifelong learners. It is important for educators to understand student learning in order to achieve the desired high quality learning outcomes. A survey is conducted in this study and the sample of this study consists of the business students (N=477) enrolled at the Faculty of Business Management, UiTM Shah Alam. Data are obtained using the Biggs’ Study Process Questionnaire (SPQ) as a diagnostic tool for measuring students’ selff reported study processes in terms of six subscales (Surface Motives and Surface Strategies, Deep Motives and Deep strategies, and Achieving Motives and Achieving Strategies), three derived Scales (Surface Approaches, Deep Approaches and Achieving Approaches) and a composite derived Scale (Deep-Achieving Approaches). The key findings provide inputs to the current scenario on the learning process specifically for the Faculty of Business Management, UiTM and will act as a basis for improvement in learning approaches of students. © 2013 2012The TheAuthors. A Authors. Published by Elsevier © Published by Elsevier Ltd. Ltd. Selectionand/or and/or peer-review under responsibility of the of Faculty of Education, UniversityMARA, Technology MARA, Malaysia. Selection peer-review under responsibility of the Faculty Education, University Technology Malaysia. Keywords: students’ approaches to learning; SPQ; age; gender; academic programmes; working experience; CGPA
* Corresponding author. Tel.: 019-2601265 E-mail address: [email protected]
1877-0428 © 2013 The Authors. Published by Elsevier Ltd. Selection and/or peer-review under responsibility of the Faculty of Education, University Technology MARA, Malaysia. doi:10.1016/j.sbspro.2013.07.167
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1. Introduction One of the major areas investigated by researchers interested in describing and/or enhancing the quality of learning in university settings has been concerned with students’ approaches to studying and learning (Svennson, 1977), (Watkins, 1982), (Biggs, 1987), (Van Rossum and Schenk, 1984), (Ramsden, 1985), (Entwistle and Waterson, 1988), (Volet, 1988), (Jones, Caird and Putterill, 1989), (Regan and Regan, 1995) and (Zeegers, 1999). Analysis of investigations of knowledge that students already have corroborates the idea that there is a great potential or learning in human beings that remains undeveloped and that many educational practices dull instead of facilitate (Novak, 1985). Both instruction and evaluation strategies frequently applied in schools and universities justify and reward rote learning and often penalize meaningful learning (Novak, 1977a). When instruction centres on memorization of definitions, dates and problem-solving algorithms, and when evaluation requires verbatim answers or text-type problem solutions, meaningful learning with thoughtful reconstruction of knowledge can be a liability (Gonzales, 1997). According to (Novak, 1987), many students believe that memorizing school (or university) information is the only way to learn. Experience shows that educators often find themselves powerless to diminish rote learning and to increase meaningful learning. Novak (1987) also postulates that three important reasons explain the difficulty of this problem. First is the student may not be aware that there is an alternative to rote learning. Second, the concepts to be learned are presented in such an obscure way that learning by memorizing appears to be the only alternative. Lastly, evaluation of student learning often requires little more than verbatim recall of information or problem-solving algorithms. Based on these reasons, as suggested by Gonzales (1997) which imply knowing students’ ideas and taking them into account in the design of both curriculum and instruction is necessary, where meaningful learning by students can be enchanted. Only in this way can adequate conceptual change be promoted and, by sharing meanings, ideas of students can be brought closer to those of scientists. For most students who enter tertiary study, and especially for mature-age students whose most recent life experiences are not in an educational setting (in contrast to usual-age students), tertiary study presents a new learning environment in which students need to acquire or develop further a variety of strategies to successfully navigate through their courses. The development of appropriate strategies to successfully navigate through their courses. The development of appropriate strategies for studying and learning allows students to overcome problems, which would otherwise be disruptive to the learning process and affect learning outcomes. In turn, the development of appropriate strategies enhances the satisfaction that can be derived from gaining control over the learning situation (Cohen, 1993). However, not all students are able to choose the appropriate strategies to enable them to reap the academic and personal rewards. For example, some may lack the specific knowledge of the strategies that are available or may fail to transfer a previously learned routine or may have actually worked a negative routine into a bad habit (Garner, 1988). Furthermore, many students are not even consciously aware of their approaches which are often not appropriate either to their own intentions or to those of their teachers (Biggs, 1987a), let alone aware of the many subtle that need to occur as they consciously attempt to select strategies to cope with the oft-occurring competing lecturer and institutional demands (Beckwith, 1991). Although there is growing body of research on how students go about studying and learning, according to (Murray-Harvey and Keeves, 1994), this knowledge is undervalued. One of the reasons for this is that there is a perception that university students already know how to learn. Although in the early years of schooling much time is spent on the development of the process skills that are required to master the content of schoolwork, this time decreases proportionally as the student’s progress through their schooling. As a result, less time becomes allocated to instruction in the strategies and skills that facilitate the learning of content and more time becomes given to the content itself. This means that by the time students enter higher education it is often erroneously assumed that they have not only learned a body of knowledge but they have also learned how to learn (MurrayHarvey and Keeves, 1994). Students who are not equipped with the strategies and skills needed to meet the academic demands of their course and who have limited opportunities to confront such inadequacies are likely to have problems because they are “left guessing about lecturers’ expectations and develop coping rather than
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learning strategies for getting through the course” (Murray-Harvey and Keeves, 1991) . As well, students who have problems are often through of as being unable to master the content (Knapp, 1991) which is not necessarily the case. Many research findings point out that the approach to learning and study skills are significant factors affecting the quality of student learning. It is also known that quality of teaching-learning environment and assessment procedures affect student’s approaches to learning and ultimately quality of learning outcomes (Marton and Saljo, 1976), (Entwistle and Ramsden, 1983), (Ramsden, 1988), (Biggs, 1993), (Hounsell, 1997), (Enwistle, 2000a; 2000b), (Prosser and Trigwell, 2006), (Smith and Miller, 2005) and (Byrne, Flood and Willis, 2009). For more than three decades, researchers in education have attempted to understand learning from a phenomenographic perspective (Duff, 2004). Early research on student learning based on text reading experiments in the 1970s. The starting point is to find ways of describing some of the main differences in how students think about learning and carry out their studies. Students are asked to read an article and are interviewed to assess their level of understanding and to determine their process of learning. In these studies, (Marton and Saljo, 1976) identified two levels of processing of learning- deep and surface and this has been replicated and extended in many studies (Marton and Saljo, 1997), (Prosser and Trigwell, 1999), (Phan and Deo, 2007) and (Justicia, Pichardo, Cano and Fuente, 2008). Instead of “level of processing”, (Enwistle, Hanley and Hounsell, 1979) preferred to use the term “approach”, which is also accepted as the best descriptor for the qualitative differences in students’ responses to learning tasks (Marton and Saljo, 1997). Students adopting the deep approach to learning intend to understand the material, and they show active engagement and interest in their studies. They interact critically with the arguments and evidence by using prior knowledge and other resources. They also monitor the development of their own understanding (Enwistle, Mc Cune and Walker, 2000) . Learning is an internal process to them. In contrast, students who prefer the surface approach mainly tend to memorize the material without understanding. They intend to reproduce the learning material and use different forms of rote learning. Mainly, they are constrained by the specific learning task and do not go beyond it. In this approach, predominant motivation is fear of failure and concern with the completion of a course. Deep approach is more likely to result in a high level of understanding and effective learning whereas surface approach is likely to lead to a low level of understanding and ineffective learning (Entwistle and Ramsden, 1983). Interviews on everyday studying drew attention to the pervasive influence of assessment procedures on learning and studying. These suggested the need for additional category. Third approach to learning is called achieving / strategic approach. Students who are primarily concerned with achieving the highest possible grades prefer to use the achieving / strategic approach. These students use both deep and surface approaches as they see appropriate and have a competitive motivation. In this approach, the major intention is to achieve the highest grades possible by means of organized study methods and time-management (Entwistle and Ramsden, 1983). Achieving / strategic approach also involves monitoring one’s study effectiveness (Entwistle et al., 2000) and alertness to the assessment similar to metacognitive alertness and self-regulation (Entwistle, 2000b). After phenomenographic investigations, the second line of research has taken the form of designed inventories which measure these concepts and so allow relationships to be established in larger representative groups. The widely used inventory was the Approaches of Studying Inventory (ASI) and Study Process Questionnaire (SPQ). These are two best known questionnaires which investigate how students generally go about their learning. Both questionnaires are similar in that they are derived from students’ interview data and they both contain scales that attempt to discriminate between students who use either surface or deep approaches. In addition, both questionnaires also have an additional scale which describes a “competitive approach” that involves trying to gain the best results as efficiently as possible. In the Approaches of Studying Inventory (ASI) this is described as a “strategic” scale and in the Study Process Questionnaire (SPQ) as an “achieving” scale. Other than that, questionnaires in each of these three constructs are measured in relation to (i) intention and (ii) strategy. For this study, Study Process Questionnaire (SPQ) is employed. It is interesting to highlight this questionnaire at the product level in order to identify if teaching contexts differ. In an ideal system, it would be
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expected that students would operate at the highest level when engaging with learning activities. Different versions of Study Process Questionnaire (SPQ) have been used in studies for different purposes. Some of the recent studies are designed to investigate the reasons for poor performance at universities. Thus, these results can lead the educators to think how to increase quality of learning outcomes by promoting deep learning through teaching-learning process and assessment procedures (Entwistle et al., 2000) and (Byrne et al., 2009). Research to date on students learning approaches and study skills in education or in teacher training institutions is limited, yet students as teacher candidates must be prepared to facilitate their students how to learn effectively. The mere translation of educational practices without taking into account contextual differences is problematical and could result in undesired consequences. It is therefore crucial that educator candidates possess and use effective learning strategies in their pre-service education. If educator candidates used effective learning approaches and study skills in their own learning, they would provide their students with high quality learning approaches and study skills. For this reason, investigating the approaches to learning and study skills of business students at the Faculty of Business Management, UiTM is very important in order to see how well we educate our future educators and to enhance educator training programs as necessary. The learning approaches paradigm provides a framework within which educators can analyze the ways that students learn, and it also provides a means of examining the learning effects of cultural diversity in student backgrounds. Students have been identified as typically adopting different study approaches depending upon their background characteristics. These include age, gender, prior knowledge of subject matter and level of intrinsic interest, which are termed “Personal Variables”. Different study approaches have also related to what are termed “Situational Variables” namely the curriculum, teaching method, assessment and classroom climate. This study also seeks to examine the impact of age, gender, academic programmes, working experience and CGPA on the learning approaches of the business students at the Faculty of Business Management, UiTM. So, in this case, Study Process Questionnaire (SPQ) can play a role in the description and improvement of the teaching-learning process by contributing to an understanding of students’ approaches to learning on an individual or group basis and by providing a foundation upon which to measure the effects of other factors that impact on student learning. The purpose of this study is to determine the approaches to learning, motives and strategies of business students at the Faculty of Business Management, UiTM. For this purpose, answers to the following questions are sought: 1. 2.
What are the approaches to learning adopted by the business students at the Faculty of Business Management, UiTM? Does age, gender, academic programmes, working experience and CGPA have an impact on the learning approaches of business students at the Faculty of Business Management, UiTM?
2. Methodology A survey is conducted in this study and the sample covers the area in UiTM, Shah Alam, Selangor. There are many students that come from various faculties. However, for the purpose of this study only focus on the business students (N=477) who enrolled at the Faculty of Business Management, UiTM, Shah Alam. A set of demographic variables are developed to seek answers to the research questions. A survey method is conducted in this study. Study Process Questionnaire (SPQ) is incorporated in this study. It is a self-report questionnaire that utilizes a Likert-scale format to measure the extent to which the students endorse different approaches to learning by identifying the Motives and Strategies that comprise these approaches. The questionnaire yield scores on three Motives (7 items each measuring Surface, Deep and Achieving Motives, respectively) and three associated Strategies for learning (7 items each measuring Surface, Deep and Achieving Strategies, respectively) and yield three derived Approaches scores that are obtained by summing respective Motives and Strategies scores (measuring Surface, Deep and Achieving Approaches respectively). The questionnaire also combines two of the Approaches scores to yield a Deep-Achieving Approach score. The questionnaire yield scores on 10 SPQ
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variables. The statistical methods used in this study are descriptive statistics (Mean for males and females), reliability (Cronbach’s alpha), correlation (males and females) and multiple regression analysis. 3. Discussion and Analysis 3.1. Descriptive statistics (Mean for males and females) The descriptive statistics table shows the mean for males and females according to the variables. Table 1 of descriptive statistics shows the mean for males (84) and females (393). The variables consists of age, working experience, CGPA, surface motives, surface strategies, deep motives, deep strategies, achievement motives, achievement strategies, surface approach, deep approach and achieving approach. 83.3% of males age are 18-21 years old while remaining are 22 years old and above. Besides that, 98.8% of males are having working experience while remaining is not. The lowest mean is surface strategies which is 2.38 while the highest mean is achievement motives which is 2.92. These suggest that average of 2.38 students is affected by surface strategies while average of 2.92 students are affected by achievement motives. Meanwhile, about 24.4% of females are age between 18 to 21 years old while remaining are 22 years old and above. For working experience, most of females on average don’t have working experience which account for 67.9%. The lowest mean is 2.58 which is CGPA while the highest mean is 4.30 which is achievement motive. These suggest that average of 2.58 of female students is affected by CGPA while average of 4.30 female students is affected by achievement motives. Based on these results, both males and females share the highest mean which is achievement motives. This indicates that majority of the students, on average mostly affected by achievement motives. Table 1. Descriptive statistics-Mean for males and females Variables Age Working experience CGPA Surface motives Surface strategies Deep motives Deep strategies Achievement motives Achievement strategies Surface approach Deep approach Achieving approach a Gender = Male (84) b Gender = Female (393)
Mean for males 18-21 years = 83.3% 22 years and above = 16.7% Yes = 98.8% No = 1.2% 2.69 2.53 2.38 2.76 2.63 2.92 2.41 2.46 2.69 2.67
Mean for females 18 – 21 years = 24.4% 22 years and above = 75.6% Yes = 32.1% No = 67.9% 2.58 4.09 3.79 4.06 3.89 4.30 3.83 3.94 3.98 4.06
3.2. Reliability (Cronbach’s alpha) Table 2 shows reliability test which is Cronbach’s alpha. Cronbach's alpha is a measure of internal consistency. It is a coefficient of reliability. A reliability coefficient of .70 or higher is considered “acceptable". The first variable which is surface motives contains seven items. It has a cronbach alpha of 0.970, suggesting that the items have relatively high internal consistency. Meanwhile, the alpha coefficient for the seven items in the surface strategies is 0.971; also supporting the items have relatively high internal reliability. The cronbach alpha
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for seven items in third variable which is deep motives is 0.973, and followed by seven items in deep strategies with an alpha coefficient of 0.969. These support that all items in the deep motives and deep strategies are closely related as a group. Meanwhile, the cronbach alpha for seven items in achievement motives, and seven items in achievement strategies are 0.968 and 0.977 respectively. On the other hand, 14 items in the variable of surface approach, 14 items in the deep approach and 14 items in the achieving approach has the same alpha coefficient which is 0.985. These mean that all the items in the respective variables have very high internal consistency and very closely related as a group. Table 2. Realibility test (Cronbach’s alpha) Variables (No.of items) Surface motives (7) Surface strategies (7) Deep motives (7) Deep strategies (7) Achievement motives (7) Achievement strategies (7) Surface approach (14) Deep approach (14) Achieving approach (14)
Cronbach’s alpha .970 .971 .973 .969 .968 .977 .985 .985 .985
3.3. Correlation (Males and females) Table 3 and Table 4 show the correlation among original variables according to males and females respectively. The original variables for the learning approaches are age, working experience, CGPA, surface motives, surface strategies, deep motives, deep strategies, achievement motives, achievement strategies, surface approach, deep approach and achieving approach. Correlations tell on how strong the relationships among the variables. Generally, a strong correlation is near to -1 or +1. Based on the Table 3 for Correlation (Males), the first until the third variable, the correlations are small, indicate that age, working experience and CGPA yields not much information about the data. Besides that, some of the correlations in the second variable which are surface strategies, achievement strategies, surface approach and achieving approach cannot be computed because at least one of the variables is constant. However, the remaining variables have uniformly large correlations. The strong correlation is surface approach. This suggests that surface approach gives more effects to males in their learning approaches. For the Table 4 for Correlations (Females), the first and second variables have uniformly large correlations among their variables. Meanwhile, the third variable has a small correlation, suggesting that CGPA yields not much information about the learning approaches. However, the remaining variables have large correlations and the most strongly correlated are surface approach and deep approach. This indicates that surface approach and deep approach gives more effects to females in their learning approaches. Hence, it can be conjectured that surface approach is the best predictor in learning approaches since it gives more effects to both males and females.
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Zahariah Mohd Zain et al. / Procedia - Social and Behavioral Sciences 90 (2013) 904 – 913 Table 3. Correlation (Males) Working Surface Surface Deep Deep Achmnt Achmnt expernc motive strategy motive strategy motive strategy Variables Age CGPA 1. Age 2. Working .245(*) expernc 3. CGPA -.202 -.164 4. Surface .231(*) .008 -.125 motive 5. Surface .198 .(a) -.060 .940(**) strategie 6. Deep .143 .057 -.115 .837(**) .788(**) motive 7. Deep .216(*) .204 -.128 .885(**) .890(**) .882(**) strategy 8.Achmnt .105 -.012 -.056 .924(**) .934(**) .821(**) .856(**) motive 9.Achmnt .074 .(a) -.085 .896(**) .854(**) .850(**) .905(**) .880(**) strategy 10.Surface .223(*) .(a) -.098 .988(**) .981(**) .828(**) .910(**) .943(**) .891(**) apprch 11. Deep .184 .132 -.125 .886(**) .860(**) .972(**) .968(**) .864(**) .901(**) apprch 12. Achieve .097 .(a) -.073 .940(**) .926(**) .861(**) .918(**) .974(**) .964(**) apprch * Correlation is significant at the 0.05 level (2-tailed), ** Correlation is significant at the 0.01 level (2-tailed) a. Cannot be computed because at least one of the variables is constant
Surface apprch
Deep apprch
Achieve apprch
.892(**) .948(**)
-
.914(**)
Table 4. Correlation (Females) Variables 1. Age 2. Working expernc 3. CGPA
Age .625(**)
Working expernc
CGPA
Surface motive
Surface strategy
Deep motive
Deep strategy
Achmnt motive
Achmnt strategy
Surface apprch
Deep apprch
Achieve apprch
-
-.091 -.133(**) 4. Surface .647(**) .739(**) motive .205(**) 5. Surface .635(**) .689(**) .955(**) strategy .209(**) 6. Deep .527(**) .642(**) .925(**) motive .258(**) 7. Deep .604(**) .700(**) .921(**) strategy .254(**) 8. Achmnt .604(**) .734(**) .975(**) motive .209(**) 9. Achmnt .552(**) .742(**) .887(**) strategy .247(**) 10.Surface .648(**) .722(**) .989(**) apprch .206(**) 11. Deep .572(**) .679(**) .934(**) apprch .257(**) 12. Achieving .593(**) .759(**) .956(**) .227(**) apprch ** Correlation is significant at the 0.01 level (2-tailed)
.925(**)
-
.950(**)
.954(**)
-
.948(**)
.930(**)
.926(**)
-
.908(**)
.897(**)
.936(**)
.890(**)
-
.988(**)
.935(**)
.946(**)
.972(**)
.906(**)
-
.949(**)
.989(**)
.988(**)
.939(**)
.927(**)
.952(**)
-
.954(**)
.939(**)
.958(**)
.970(**)
.974(**)
.966(**)
.960(**)
-
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3.4 Multiple regression analysis The result of the multiple regression analysis is displayed in Table 5. The result indicates that most of the relationships are in predicted positive direction and the estimate for the major variables are significant. However, there is also estimation between dependent variables and independent variables which is considered insignificant. For instance, such as surface strategies and academic programs, deep motives and academic programs, deep strategies and academic programs, achieving strategies and academic programs. Thus, only these variables are not supported. The coefficients of multiple determinations (R²) for each variable are also quite high. In this study, multicollinearity is not shown for all the variables investigated. Meanwhile, the variance inflation factor (VIF) is below 10 for all the independent variables. For diagnostic purpose, the Durbin-Watson value falls within the acceptable range. It implies there is no autocorrelation problem. Table 5. Multiple regression analysis results Dependent variables Surface motives
Surface strategies
Deep motives
Deep strategies
Achieving motives
Achieving strategies
Surface approach
Explanatory variables
Unstandardised coefficients
R-square
Gender Age Working experience CGPA Academic programs
.922*** .414*** .644*** -.108** .041***
.771***
Gender Age Working experience CGPA Academic programs
.774*** .408*** .591*** -.117** .015
.741***
Gender Age Working experience CGPA Academic programs
.809*** .224*** .538*** -.161*** .011
.697***
Gender Age Working experience CGPA Academic programs
.712*** .284*** .556*** -.146*** .001
.74.5***
Gender Age Working experience CGPA Academic programs
.845*** .260*** .604*** -.089* .029**
.739***
Gender Age Working experience CGPA Academic programs
.785*** .151** .750*** -.160*** -.016
.758***
Gender Age Working experience CGPA Academic programs
838*** .412*** .619*** -.112** .028**
.766***
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Deep approach
Achieving approach
Gender Age Working experience CGPA Academic programs
.761*** .254*** .545*** -.151*** .007
Gender Age Working experience CGPA Academic programs
.804*** .207*** .679*** -.123*** .006
.731***
.766***
*p ≤ .05; **p ≤ .01; ***p ≤ .001
4. Conclusion This study investigates the approaches to learning, motives and strategies of business students at the Faculty of Business Management, UiTM. For this purpose, there are 9 approaches to which are surface motives, surface strategies, deep motives, deep strategies, achievement motives, achievement strategies, surface approach, deep approach and achieving approach. From the figure of correlations, the results show that surface approach gives more impact to the learning approaches since it has the highest correlation which is 0.994 with 0.01 level of significant. Besides that, this study also examines the impact of age, gender, academic programmes, working experience and CGPA on the learning approaches of the business students at the Faculty of Business Management, UiTM. Based on the multiple regression analysis, it can be conjectured that gender has more impact on the learning approaches since it has the highest coefficients among explanatory variables for all dependent variables. Moreover, it is also significant with all the dependent variables (p≤0.01). Study Process Questionnaire (SPQ) has indicated robust reliability and constructs validity in some of the measures. An effort should be put into curriculum design, and especially with teaching and assessment methods, so that a constructive and desirable learning context is created to facilitate a positive study orchestration. References Beckwith, J.B. (1991). Approaches to learning, their context and relationship to assessment performance. Higher Education, 22, 17-30. Biggs, J.B. (1987). Study process questionnaire manual. Australian Council for Educational Research, Melbourne. Biggs, J.B. (1987a). Student approaches to learning and studying. Hawthorn, Victoria: Australian Council for Education Research. Biggs, J.B. (1993). What do inventories of students’ learning processes really measure? A theoretical review and clarification. British Journal of Educational Psychology, 63 (1), 3-19. Byrne, M., Flood, B., & Willis, P. (2009). An inter institutional exploration of the learning approaches of students studying accounting. International Journal of Teaching and Learning in Higher Education, 20 (2), 155-167. Cohen, M.L. (1993). Listening to students’ voices: What university students tell us about how they learn. Paper presented at the Annual Meeting of the American Education Research Association, Atlanta. Duơ, A. (2004). The role of cognitive learning styles in accounting education. Journal of Accounting Education, 22, 29–52. Entwistle, N.J., Hanley, M., & Hounsell, D. (1979). Identifying distinctive approaches to studying. Higher Education, 8, 365-380. Entwistle, N.J. & Ramsden, P. (1983). Understanding student learning. Croom Helm, London. Entwistle, N.J. & Waterson, S. (1988). Approaches to study and levels of processing in university students. British Journal of Educational Psychology, 58, 258-265. Entwistle, N.J., Mc Cune, V., & Walker, P. (2000). Conceptions, styles and approaches within higher education: Analytic abstractions and everyday experience. In R.J. Sternberg, & L.F. Zhang (Eds.), Perspectives on cognitive, learning, and thinking styles. New Jersey: Lawrence Erlbaum.
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