The effects of learning tendencies, learning approaches and learning habits on academic achievement: Evidence from Taiwanese college accounting students

This study examines student study behaviours via three major frameworks: Kolb's (1985) Experiential Learning model, Entwistle and Tate's (1994) Approach to Learning model, and Dunn and Dunn's (1993) Learning Style Model. Four learning tendencies (concrete learning, reflective observation, abstract conceptualisation, and active experimentation) were based on Kolb's model. Seven approaches to learning constructs were taken from Entwistle and Tate's Revised Approach to Learning Inventory: deep processing, shallow processing, operation learning, organised methods, strategic approach, motivation, and fear of failure. Learning habit variables were based on the four study factors used by Dunn and Dunn in their analyses of students learning styles: environmental factor, emotional factor, sociological factor and physiological factor. A self-reported survey which incorporates all these elements was administered to a total of 844 accounting major students across six colleges and universities in Taiwan.

Using self-reported class rank score as the academic achievement indicator (dependent variable) and the three sets of study behaviour variables as independent variables, a series of regression analyses were conducted. Regression models were first constructed separately for tendency, approach, and habit sets. For learning tendency variables, all but concrete experience was significantly positively related to achievement. For learning approach variables, deep/shallow processing, organised methods, motivation, and fear of failure were found to be significant. For learning habit variables, studying alone, comfortable study room, pleasant study mood were found to have favourable effect on achievement, whereas listening to music while studying tend to have a negative impact. Finally, all study behaviour variables were entered and a stepwise regression analysis was performed to assess the importance ranking of these variables in relation to their impact on achievement. The results of such analyses and their implications for future accounting education practices were discussed.

Introduction and motivation

In contrast to the widely cited learning tendency construct in accounting education literature, not so much research has been conducted in the areas of learning approaches and learning habits of accounting students. The learning approaches view of study behaviours is that students display differential propensities depending on how they perceive the surrounding learning environment. Learning approaches are also known in the general education literature as learning orientations, preferences, orchestrations, and processes (eg, Biggs, 1993; Entwistle and Waterson, 1988; Marton and Saljo, 1976a,1976b; Meyer et al., 1990; Richardson, 1990, 1994; Schmeck et al., 1977). Such a construct is usually task-oriented. An individual may display quite different learning approaches in differently perceived learning environments. In the paucity of research on learning approaches in accounting education, Lukas (1996) called on accounting educators for more research into this area.

Learning habits, on the other hand, is a construct which describes how an individual's learning habitually takes place environmentally, emotionally, sociologically, and physiologically. In the general education literature a substantial amount of research has focused on the ways teaching methods can cater for students' specific learning habits in order to produce favourable learning outcomes across a wide rage of disciplines (see Dunn et al, 1995 for a review). However, little has been done with the learning habits of accounting students.

In this paper, we endeavour to bring these three learning constructs together in one study for the purpose of obtaining a more integrated understanding about the study behaviours of college accounting students. Specifically, we seek to explore the association, if any, between these three learning constructs and their effects on the academic achievement of accounting students. Although this study was conducted in a Taiwanese higher education setting, our instrument should be readily applicable amongst accounting students in other countries. The following two specific research questions are addressed in this study:

Instrumentation and research method

In additional to the study behaviour variables, self-rated academic performance, perceived course benefit, and aptitude variables were also included in the background section of the questionnaire. Each was assessed with two items also on 1-6 Likert scale of agreement and the mean of these two items was taken as the indicator for that construct. The items addressing academic performance were: "In this course I am likely to get a satisfactory score" and "I have achieved satisfactory grades in most of the courses of the accounting program I've taken to date". The items addressing perceived course benefit were: "As far as knowledge acquisition is concerned, I have benefited much from this course" and "The instructor has been helpful to me in this course". The items addressing aptitude were: "Overall, I have a strong ability to learn the knowledge required by the accounting profession" and "I am suitable for a career in the accounting professions".

The questionnaire was administered to 844 students majored in accounting while they were taking one of the following courses: introductory accounting, intermediate accounting, advance acocunting, and auditing. The student sample was drawn from seven major colleges/universities in Taiwan (four public and three private). Of the 844 responses collected, 31 were returned as almost blank sheets and 58 cases were found to be with unusual response patterns as detected with at least one flag by our check item sets. We looked through all the flagged respondents and deleted 38 of them as appearing to lack of credibility. Twenty-eight of these records had consistent zigzag response patterns and the rest appeared like random responses. The other 20 cases were mostly detected with only one flag, and their responses appeared to be within tolerance, so we decided to keep them in the data and ended up with a total sample of 775 cases (241 males and 532 females, two with missing gender data) for our investigation purpose.

We felt reasonably convinced about the statistical stability of our aggregate statistics due to the large sample size involved in our study. Research question one was answered by providing the summary statistics for all the study behaviour dimensions. Research question two was approached in two stages. The first stage involved setting up three multiple regression equations, one for each major study behaviour construct. For each equation, the relevant dimensions of each construct were the determinants of academic achievement. The magnitude of the R-square value for each equation was compared. The second stage involved a single regression equation in which those variables found to be significant in the first stage were entered in a stepwise fashion as determinants of academic achievement.

Results

For the learning tendency aspect, Taiwanese accounting students appear to display substantial concrete experience tendency, moderate reflective observation and abstract conceptualisation tendencies, and less in active experimentation tendency. In terms of learning approach aspect, Taiwanese accounting students tend to display moderate uses of deep processing and organised methods, show slightly more signs of surface processing, achievement motivation and fear of failure. More often than not, the most prominent features of Taiwanese accounting students' learning approach is described by operation learning and strategic approach. It is worth pointing out that both operation learning and strategic approach have been found to be associated with characteristics of a surface learning approach in a factor analysis of the original 15 ASI scales. The most mentioned learning habits are studying in quiet and alone, under bright light and cool temperature in a comfortable room, studying in pleasant mood, drinking beverages, and studying in evenings.

In regard to the association between study behaviour variables and academic achievement, all variables except concrete experience gave a significant positive effect on academic achievement (as indicated by positive regression coefficient estimates at p<0.001). Secondly, in relation to learning approaches, achievement motivation displayed the most significant positive result as a determinant of academic achievement (regression coefficient estimate=0.372, p<0.000). Organised methods also substantially affected the positive outcome of academic performance (regression coefficient estimate=0.154, p<0.000). Surface learning and fear of failure, however, showed negative effects on academic performance (regression coefficient estimates are -0.183 and -0.137 both at p<0.000 respectively). Only four learning habit variables gave statistical significance in their relations to academic performance at 0.05 level. Listening to music when studying showed a slight negative effect (b=-0.055, p<0.043), whereas studying in a comfortable room and in a pleasant mood showed slight positive effects (b=0.068 and 0.083 at p<0.029 and 0.049 respectively).

The second stage of the regression analyses was conducted by entering the eleven study behaviour variables as identified in the previous stage of analyses into a single regression scenario in a stepwise fashion. The Statistical Analysis System (SAS) provides three options for selecting variables in the PROC STEPWISE procedure: forward selection, backward selection, and stepwise selection (allow previously deleted variables to renter the selection process at a later stage). All three options yielded identical interpretations of our results using 0.10 as the significance level for entry into the model. Of the 11 study behaviour variables entered, seven were retained at the final step of selection. None of the variables relating to learning tendencies and learning habits met the criterion of selection into the final model. We also added certain product terms into the final model to test for the possible existence of interaction effects among our study behaviour variables. Only one of the interaction terms tested showed noticeable significance - fear * strategy. The major determinants of academic performance in order of descending importance are: aptitude, perceived benefit, organised study methods, and surface learning. The interaction term changed only the interpretation of the strategic approach effect. The interaction effect was further examined by collapsing it into low, medium, and high categories for fear of failure and strategic approach. The interaction appears to be of ordinal nature for both variables. The high use of a strategic approach for low fear of failure students showed the highest level of academic achievement.

Judging from the results of our regression analyses, it is concluded that the learning approaches aspect of study behaviours has the most impact on the academic outcome of learning. The adjusted R-square of learning approaches for predicting performance was 0.317, compared with 0.117 and 0.088 for learning tendencies and learning habits respectively. The effects of learning tendencies variables have been absorbed by the more powerful effect of learning approaches variables. Furthermore, when both learning tendencies and learning approaches are taken into account, the learning habits variables have been found to have no significant influence on academic achievement.

Conclusions and discussions

Of course, there is always a danger of treating learning approaches as if they are independent of learning environments. In fact, numerous researchers have suggested that learning environments do have a profound effect on study behaviours. Therefore, any attempt to modify students' learning approaches should also take into consideration students' perceptions of their learning environment. It may be argued that each course within the accounting program provides a unique learning environment. It is thus quite worthwhile to investigate how each course is perceived by the majority of students in that specific learning environment. A direction for further accounting education research might be the investigation of the match between students' perceptions of the learning environment and their manifest learning approaches. Both students and staff may benefit in a complementary manner, at an individual level, in the light of results from such contextual studies,

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