A Surface Approach to Learning Rewards First-year Engineering Students

Maria Svedin, Olle Bälter KTH Royal Institute of Technology

School of Computer Science and Communication School of Education and Communication in Engineering

Science Stockholm, Sweden

msvedi@kth.se

Max Scheja, Kerstin Pettersson Stockholm University Stockholm, Sweden

Abstract—In a study investigating first-year engineering students’ approaches to learning and studying, a surface approach to learning was shown to be the best predictor of academic achievement. A strategic approach to studying was found to be a negative factor. A questionnaire was distributed to first-year students aiming for Master of Science in Engineering in either Computer Science or Media Technology in the beginning and the end of their first year of study. In the first instance 150 students (69.5 %) answered the questionnaire and 87 (34.5 %) participated on both occasions.

Keywords—approaches to learning, engineering students

I. INTRODUCTION The aim of this study is to investigate how engineering

students’ approaches to learning and studying correlate with their study results. The aim is further specified in two research questions: How do first year engineering students’ approaches to learning and studying correlate with their study results? How do the changes in their approaches to learning and studying correlate with their study result? From a developmental and life long learning perspective, most teachers would like their students to achieve a deep learning approach while avoiding surface learning, but at least in engineering education, this is rarely evaluated. Since some research suggest that approaches are hard to change, it is essential that the educational context during the first year encourages and stimulates students to adopt a more deep/strategic approach to learning.

In following sections, concepts relevant to (engineering) students’ approaches to studying and learning are explored. Subsequently we present the study and our findings. We conclude by discussing these concepts and results, as well as how it may influence the students’ study approach.

II. BACKGROUND

A. Approaches to Learning and Studying The theory of approaches to learning derives from a

qualitative analysis of in depth interviews in which students described their learning behaviour and intentions when

studying a text. With focus on extracting meaning from a text but with different emphasis on outcome and process two distinct forms of dichotomies were identified: deep/surface and holistic/atomistic [1]. The deep/surface category has been the basis for the definition of deep and surface approach to learning. A deep approach to learning is characterized by the student’s will and intention to get an understanding of the study material in order to relate it to a larger context. A surface approach is characterized by a focus on mechanic repetition to memorize in order to automatically reproduce it. Subsequent research added a strategic approach to studying as a third and complementary category. Students with a strategic approach organize learning in an effective way to fulfil course requirements [2]. The students’ approaches are driven by their motivation and attitude; i.e. "by the extent they are able to adopt congenial approaches to studying" [3]. The approaches are not contradictory [4]; all students are believed to have streaks of them all that emerge based on the context and they are therefore not placed fully in a single approach.

The three approaches are said to depend on the content of the task set as well as the context in which the student carry out the task. Apart from these components, there seems to be an individual-bound component dependent both of the students’ conceptions of learning and of themselves as learners. [5] suggests that students’ approaches to studying are related to both of these. The results of studies trying to influence students towards more desirable approaches by implementing a student-centred learning environment are not univocal, which indicates that there are numerous of other factors that may influence the outcome [6].

B. Academic Achievement Previous research concludes that approaches to

studying have an impact on the outcome of learning in terms of understanding, where high achievement has been positively related to a deep and strategic approach and negatively related to a surface approach [7][4]. It is argued that this relationship typically is found among graduate students, whereas

2013 Learning and Teaching in Computing and Engineering

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DOI 10.1109/LaTiCE.2013.40

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2013 Learning and Teaching in Computing and Engineering

978-0-7695-4960-6/13 $26.00 © 2013 IEEE

DOI 10.1109/LaTiCE.2013.40

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undergraduate science students may be more inclined to adapt a combination between strategic and surface approach [8].

Studies among undergraduate psychology students and medical students have found that a deep approach did not predict academic achievement, but instead that a strategic approach is the best predictor of this [7][9]. These findings are attributed to the learning environment: in one study as a strictly fixed and defined curriculum and in another in reference to an overloaded curriculum. The pressure to achieve is also a possible explanation concerning the demand for high examination grades in these subject areas.

Adapting a deep approach to learning requires adequate preparation in the subject area; either having a poor background in the subject or the failure to use previous knowledge when learning will detract from using a deep approach [10].

C. Disciplinary Differences Approaches to studying are dependent of the specific topic within a specific discipline and vary markedly across these [11], where arts students seem to be more inclined to adopt a deep approach and science students a surface approach. There have been several studies of whether the instrument is biased towards humanities or if the students are differentially oriented in the different departments [12][13], where the results have varied. [14] use Becher’s theoretical categorisation to explain the difference. The focus in the different disciplines affects the teaching style and students learning motives, students in hard applied disciplines strives to be able to develop and build (surface motive) rather than to reflect and critically evaluate the situation (deep motive) [14]. This finding is supported by [15] who found that the effect seems to be more due to the disciplinary teaching environment, where arts seems to adopt a teaching approach more keen on favouring a deep approach to studying in the students. The authors emphasises that the effect is significant, but not large.

D. First-year Engineering students As mentioned, a deep approach to learning is important from the perspective of learning in terms of understanding, as well as to build a solid ground of prerequisites for future learning opportunities. The approach to learning also has a strong impact on the students’ ability to life-long learning [16]. They suggest that one way to motivate students and improve their performance is to adapt the concept of course alignment within the program. What may contradict this is that students’ approaches may vary depending on their perception of the teaching and learning environment [17]. Another solution may be to use interdisciplinary collaborative assessment in order to conclude whether students have grasped the objectives and knowledge in the first-year engineering curriculum [18]. The measurement instrument was crafted to assess deeper levels of learning and created a feedback process, which led to improvements in the curriculum as well as to reduce the gap between student learning and teaching.

A study using The Study Process Questionnaire (R-SPQ_2F) developed by [17], distributed to 801 civil engineering students, concluded that civil engineering students are identifying as adopting a deep learning style rather than a more surface style [19]. The students were distributed approximately even on the first three years of the program, where the pattern was similar for each year.

III. METHOD

A. Questionnaire Approaches and Study Skills Inventory for Students

(ASSIST) is an evolved revision of the Approaches to Studying Inventory (ASI) developed in the late 1970’s [20]. In its short version, ASSIST is in an unembellished and manageable format, which makes it easily distributed and administered. It consists of 18 conceptually overlapping questions designed to allow the student to describe how they go about learning and studying. Responses are scored on a 1 – 5 scale, which forms three sub-scale score variables corresponding to the three study approaches. A high score in an approach means that the student exhibits the behaviour of it.

The questionnaire used in this particular study is a Swedish translation of the short version of ASSIST. It has passed through a cross-cultural validation process by people independent from the project to improve the translation and to ensure consistency in wording and meaning with the original version. During the development face validity was tested both from the researchers’ point of view and from the students’ perspective as respondents. The version of the Swedish translation of ASSIST used in this study has been revised to meet the requirement of internal reliability [21][22], and has been tested and supported in a Finnish translation [23].

B. Study Programs The present study sampled first-year students from

two programs; students aiming for Master of Science in Engineering in Computer Science (CS) or Media Technology (MT) in the beginning and the end of their first year of study. The programs were chosen by mainly two reasons: 1) to investigate how ASSIST as a questionnaire functions in this disciplinary setting and 2) because the programs are administered by the same department and have similarities and yet significant differences.

The main difference between the two programs is that the computer science program relies heavily on mathematics, while the media technology program is a broader education covering everything from printed to digital media. For a list of courses given during the first year in each program as well as the assessment methods for each course, see table I. Each course is defined by the European Credit Transfer and Accumulation System (ECTS) for credits, where in Sweden 1 ECTS credit corresponds to approximately 2/3 week of full time studies and one year of studies corresponds to 60 ECTS credits. Grades are given on a scale from A to F, where A is the highest grade and A to E is pass, where as F is

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fail. In the analysis they have been translated into numbers, so that A is 5 and F is 0.

TABLE I. COURSES AND ASSESSMENT METHOD

Program courses for each during the first year

Assessment method

ECTS creditsa Exam

Home exam

Exercise/ Laboration Seminar Other

MT

Introduction to Media Technology 7.5 3.5 4.0 Communication and infomation 7.5 3.0 3.0 1.5 Graphic Arts Technology 7.0 4.0 3.0 Programming for Interactive Media 8.0 8.0 Algebra and Geometry 7.5 7.5 Calculus in One Variable 7.5 7.5 Electrical Engineering 6.0 1.5 4.5

Waves (Physics) 6.0 3.0 3.0

CS

Introduction to Computer Science 16.0 11.5 4.5 Communication in Engineering Sciences 7.5 7.5 Mathematics, Basic Course 4.5 4.5

Linear Algebra 7.5 7.5 Calculus in One Variable 7.5 7.5 Calculus in Several Variable 7.5 7.5 Physics: Waves and Particles 7.5 5.0 2.5

a Apart from these courses, there is also a voluntary Introductory Course in Mathematics available as well as a Programme Integrating Course that runs during the first three years of studying.

C. Respondents An invitation letter was sent via email to all of the

students who registered for one of the two programs in autumn 2011. The letter informed the students of the purpose of the study and about the volunteer participation. A few hours later another email was sent containing both a link to the web questionnaire and a link that registered the student as declining participation in the study. Students not selecting either of these options were sent a reminder one, two and three weeks later.

The same letters were sent to all students who were active in the end of the second semester in the spring of 2012.

D. Statistical Analysis The students’ scores for ASSIST were compared with

study results on courses and grades during the first year as recorded in the university’s database. The results were analysed through correlation analyses. Kendall’s rank correlation tau was used to measure the strength of association between academic achievement such as course grade and credits taken and approaches. Welch’s two sample t- test was used to analyse if group means differ, since the variance cannot be assumed to be equal.

For all of the statistical analysis a significance level of � = 0.05 is used. When correlations are used, the following is how to interpret the significance:

* : p<0.05, ** : p<0.01, *** : p<0.001

IV. RESULTS In the first instance 150 students (69.5 %) answered

the questionnaire and 87 (34.5 %) participated on both occasions. In the autumn sample 37 MT students participated, with a gender distribution of 45.9 % females and a mean age of 20.8 years old, with no significant differences between genders. 113 CS students participated, with a gender distribution of 14.2 % females and a mean age of 20.7. There were 22 MT students and 65 CS students who participated on both occasions, with a gender distribution of 54.5 % in MT and 13.8 % in CS and a mean age of 20.8 years old respective 20.5.

TABLE II. KENDALL’S TAU FOR APPROACH SCORE AND STUDENT ACHIEVEMENT AS IN GRADES AND ECTS TAKEN

Courses taken by CS students

Approach, autumn Deep Strategic Surface

Basic Course 0.10 -0.16 0.11 Calculus in One Variable 0.11 -0.28** 0.11

Calculus in Several Variable 0.09 -0.36*** 0.10

Linear Algebra 0.11 -0.24** -0.02

ECTS Credits 0.16 -0.28** 0.13

A. Approaches vs study result For CS students that participated in the first

questionnaire a negative correlation between strategic approach and credits was found, where students demonstrating a high score on strategy approach in the beginning of their studies perform worse (see table II). Students demonstrating a strategic approach also performed poorer in terms of grades in the Mathematics courses, with the basic course as an exception. The scores on deep and surface approach do not correlate with credits taken, but those in the 4th quartile of taken credits have significantly higher score on deep approach than those in the lowest quartile (p=0.038). For the MT students, no significant correlations or differences were found.

TABLE III. CHANGE IN APPROACH SCORE VS. ECTS CREDITS TAKEN

Mean change in approach, all

students

ECTS credits taken 60,

n=35 45 - 60, n=31

Less than 45, n=21

DEEP -0.3 +1.1 +0.2

STRATEGIC -1.1 -0.1 +3.2

SURFACE -0.3 -0.4 -3.7

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B. Change in approaches vs study result Among those who answered the survey on both

occasions, it is evident that students who take all of the required credits do not change their score on surface approach, whereas a lowered score is associated with taking fewer credits (table III). This connection is most evident among CS students (p=0.003) even though it is visible among MT students as well (p=0.02). Difference in strategic approach was not significant, with p >0.8.

TABLE IV. GRADES IN MATHEMATICS COURSE VS. CHANGE IN APPROACH.

Mean change in approach, all students

Grade, Calculus in One Variable

A, B C, D, E F n 39 27 21

DEEP change -0.8 +0.9 +0.8from/to 16.5 / 15.7 15.7 / 16.6 15.7 / 16.5

STRATEGIC change -0.6 -0.5 +3.0

from/to 13.0 / 12.4 15.7 / 15.2 17.4 / 20.4

SURFACE change 0.0 -0.4 -4.1

from/to 21.8 / 21.8 20.8 / 20.4 21.2 / 17.1 Results of individual courses do not correlate with

scores of approaches, with the exception of Mathematics. High grades in Mathematics courses correlate strongly negatively with a strategic approach and positively with a surface approach. The two programs had one mathematics course that was the same, Calculus in One Variable, (table IV). For both programs, a higher grade associated with a decreased score in deep approach as well as a small change in surface approach.

TABLE V. GRADES IN MATHEMATICS VS. CHANGE IN CS STUDENTS’ APPROACHES

DEEP STRATEGIC SURFACE

<-1 0 ± 1 > 1 <-1 0 ± 1 > 1 <-1 0 ± 1 > 1 n 24 18 23 20 23 22 29 22 14

Mean difference -3.5 0.0 3.4 -3.8 0.1 2.5 -4.6 0.0 4.3Linear Algebra 2.8 2.5 2.3 3.1 3.0 1.5 2.0 2.6 3.5

Calculus in One Variable 3.0 2.4 2.0 2.5 3.0 1.9 2.1 2.4 3.5Calculus in Several Variable 2.1 1.3 1.2 1.5 2.2 1.0 1.1 1.9 1.9

Mean ECTS credits taken 52.3 46.4 49.2 52.4 53.9 42.5 45.4 51.0 56.0

For the CS students, grades in Mathematics also

correlate positively with a reduction in strategic score and negatively with a reduction in surface approach (table V). Grades in the course Linear Algebra is the most prominent, it

correlates negatively with change in strategic score during the school year (-0.31**), whereas it correlates positively with a change in surface approach (0.30**). A change in surface approach also correlates positively with grades in Calculus in One Variable (0.24*) and total amount of ECTS credits taken (0.25**)

For these students, a high score on surface approach seems to be the best predictor of academic achievement.

V. DISCUSSION The results indicate that a high score on surface approach along with not changing it during the first year of study is the best predictor of academic achievement.

The results in the present study are in contrast to previous studies on, among others, undergraduate psychology students and medical students where a strategic approach was found to be the best predictor. Undergraduate students in science have been found, particularly during their first year, to be more inclined to adapt a combination between strategic and surface approach, whereas in this study a strategic approach was found to be a negative predictor.

Is this a problem, and what kind of arrangements should in that case be taken to deal with it? Since the courses in Mathematics are those who indicate the above given pattern the most, the focus should be on how they differ from the others during the first year curriculum. A big difference with the mathematics courses compared to the others is that they are dependent on one exam for the whole grade and for the ECTS credits given; while the exams in the other courses are divided into different blocks such as home exams, exercises and seminars (table I).

Design features that encourage a deep approach are those who promote a constructive dialogue as well as interactive learning activities, and hence enhance the students’ understanding of the content [15]. It is of value that there is a congruence and coherence in the curriculum and that the teaching is based upon an inner logic of the subject and its pedagogy. When constructing the curriculum, it is of importance to get the courses integrated within the program, so that the students understand why they are studying it. It might be a good idea to have program exams as a complement to course exams, which assess interdisciplinary [18]. For the students to be able to adapt a deep/strategic approach in their future studies as well as a ground for lifelong learning, it is crucial that they have an adequate prerequisite knowledge and conceptual understanding of the subject. This could prove to be problematic for the students in the long run, since a surface approach is more linked to short-time knowledge, whereas a deep/strategic approach is more positively linked to high academic achievement and a more active engagement and interest in the subject [7][8].

VI. CONCLUSION A possible interpretation of this result is that the courses in mathematics discourage a strategic approach to learning and

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that students demonstrating a high score in surface approach are likely to take more credits as well as receive higher credits.

VII. FUTURE WORK This investigation will continue. In the study year 12/13 some changes have occurred in the program design, where courses have been moved or changed. The questionnaire has been sent out to the first-year engineering students in the same programs as in the study above. In future studies we will be able to evaluate if these changes had any effects in the way that the students develop their approach to learning in their first year of studying engineering, and by this come closer to defining program design effects in this discipline.

VIII. ACKNOWLEDGMENTNTS We would like to thank the reviewers for taking time to give feedback and clear comments, which made this article more clear and easy to follow as well as it opened a discussion about possible future studies.

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