![]() |
||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
|
Julie Mills Mary Ayre David Hands Pam Carden
Abstract Individuals vary in the ways they prefer to receive, process and demonstrate their knowledge. Research suggests that mismatches between lecturers' expectations of the way students learn and students' own individual preferred learning styles lead to students' lack of motivation and interest, and may cause attrition. This paper describes how a teaching project at the University of South Australia aimed to achieve improvements in student satisfaction by redesigning approaches to teaching, learning and assessment of engineering courses to accommodate a range of learning styles.
Introduction The Learning Styles project at the University of South Australia commenced in 2001 with a teaching and learning grant awarded to two of the authors. Whilst much of the professional development work and data collection in the project was completed in the first two years, the major achievement of the project has been the embedding of "Learning about Learning Styles" within the engineering programs. The project encompassed the three Departments of Engineering: Advanced Manufacturing and Mechanical Engineering, Electrical and Information Engineering, and Geoscience, Minerals, and Civil Engineering. The project had a teaching and learning focus, rather than research, with the primary aim of improving student and staff knowledge of individual learning styles and through this to increase understanding and improve satisfaction with teaching and learning across the three Departments. Improvement focused on widening the range of teaching, learning and assessment strategies currently employed in recognition of the variety of learning styles present in classes of diverse students. This follows research findings that engineering students' motivation and success can be adversely affected if their learning styles, and the learning styles of the staff teaching them, are not taken into account (University of Western Australia, 1996; Felder, 1996). Research on learning styles suggests that in engineering courses, learning is optimised by the application of different learning styles to these courses. Yet most engineering lecturers assume not only that all students adopt (or should adopt) a uniform learning style, they expect the same learning style to be applied to all areas of engineering studies (Felder, 1993, 1996; Holt & Solomon, 1996). This project set out to encourage engineering faculty to challenge these assumptions. The project was developed with an 18-month implementation timeline and
had two main aims. Firstly, the project team planned to foster an understanding
of the variations in learning styles amongst students whilst presenting
them with methods for coping with differences between learning and teaching
styles. Secondly, the project aimed to raise awareness amongst teaching
faculty of the variations in learning styles of their students, of the
potential differences between their teaching methods and the learning
styles of the students, and strategies to overcome these differences.
The team was careful to point out that there was no expectation that differences
would be catered to on an individual basis. Rather, the expectation was
that faculty and students would be aware that differences exist, that
not all styles could be catered to all the time, but that all styles could
be catered to for some of the time.
Learning Styles The term 'learning styles' refers to the ways individuals and members of cultural groups prefer to receive, process and present information and ideas. Some people, for example, find it easier to understand a new concept by reading a textbook, whilst others prefer a pictorial explanation. Likewise, people may vary in how they most effectively demonstrate their understanding: graphically, verbally, or in writing. David Kolb (1984), one of the main classifiers of learning styles, identified the four basic learning styles as: convergent (good at problem solving, decision making, and the practical application of ideas); divergent (good imaginative ability and awareness of meaning and values); assimilative (good at inductive reasoning and creating theoretical models); accommodative (efficient in carrying out plans and like getting involved in new experiences). He found that engineers usually have a convergent learning style. There is some debate about the main influences on learning styles, with some authors (Felder, 1996; Kolb, 1984; Briggs-Myers, 1989) seeing the main influences as personality, life experiences, and the purpose of the learning. Others (Ballard & Clanchy, 1997) identify a particular set of life experiences: the expectations of teachers, as the dominant influence on learning styles. Whatever the causes of differences in learning styles, there is considerable evidence of disadvantage to students arising from a mismatch between lecturers' expectations of the way students learn, and students' own individual preferred learning styles. Research suggests that these mismatches in learning styles lead to lack of motivation and interest in students, affecting students' success, and causing attrition (University of Western Australia, 1996; Felder, 1996; Zywno & Waalen, 2001). Other authors (Anderson, 1991; Beyer, 1993; Harding, 1996) have looked at gender and cultural influences on learning styles, and at differences between the learning styles of mature-age and younger students. Knowledge of these gender and cultural differences are important both for equity reasons, and to support the academic welfare of international students. However, it is acknowledged that the whole field of learning styles is viewed as somewhat controversial. There are two reasons for this controversy: firstly, the danger of stereotyping - assuming that all women, or all international students, for example, will have the same learning styles. Secondly, the fear that learning methods that differ from those of the dominant majority may be viewed by some faculty (and some students) as less valid, or less effective than those favoured by the dominant group. Despite these reservations the evidence of improved student learning and satisfaction resulting from consideration of differences in learning styles was, in our view, sufficiently compelling to recommend this approach to improve teaching and learning. Learning Styles and Engineering Education
An alternative to Kolb's system for identifying learning styles is the Myers-Briggs Type Personality Indicator (Briggs-Myers, 1989), which relates particular types of learning styles to personality types. This system categorises personality on four scales, giving rise to the identification of 16 personality 'types'. A study by Kramer-Koehler, Tooney and Beke (1995) used the Myers-Briggs test in two consecutive years to assess the learning styles of all first-year (about 200) engineering students at a New York university, and found that only 16% of the class had the 'typical' engineering personality profile of ISTJ (Introvert, Sensors, Thinkers, Judgers). On the basis of the class learning styles profile identified, a new core curriculum was designed which introduced engineering science and mathematical concepts only on a ''need to know" basis, and incorporated cooperative learning and the development of oral and written communication skills, at the expense of lecture-based teaching: first year retention rates improved by 50% as a result. Felder, Felder and Dietz (2002) conducted comparable research at another American university, and concluded that the restructuring of course instruction to allow for all learning types led to improved student outcomes. Richard Felder (1999) has devised a learning style model and inventory for use especially in the engineering and science disciplines. Combining the work of Knowles and Myers-Briggs, this instrument assesses students on four dimensions of preferences, using 44 questions each with answers (a) or (b) corresponding to one or other extreme of the dimension (eg. active or reflective). The four dimensions are
These dimensions are assessed as continuum where a learner may be located at any point on the axis between the two extremes. The scoring system ranges from 11a to 11b for each of the four dimensions, with only odd number results possible. For example, if a learner scores 1a or 3a on the active-reflective dimension it would indicate that they have a mild preference for active learning styles, whereas a score of 9b or 11b would indicate a strong preference for a reflective learning style. Scores of 5a or 7a would indicate a moderate preference for the active learning style. Overall the literature supports the notion that Engineering students have a diversity of learning styles but that few courses are structured to cater for this variety. Studies have shown, however, that once faculty awareness has been raised and the teaching adapted to accommodate all learning styles, student outcomes and attrition rate have responded positively.
The Felder instrument described previously, known as the 'Index of Learning Styles' (ILS) was originally developed in 1988 and has been widely used for a number of years in several universities. A summary of applications and an assessment of the reliability and validity of the instrument has recently been published (Felder and Spurlin, 2005), and concluded that the ILS is a suitable instrument for assessing learning styles, based on reliability and validity data. It was also concluded that the ILS has two major applications, firstly "to provide guidance to instructors on the diversity of learning styles within their classes and to help them design instruction that addresses the learning needs of all of their students" and secondly to "give individual students insights into their possible learning strengths and weaknesses" (Felder & Spurlin, 2005, p.110). These were exactly the purposes for which the ILS was employed within this project. The latest version of this instrument (Felder, 1999) was used to assess the learning styles of engineering faculty and students in this project. The team began by presenting as many students as possible with the self-assessment ILS questionnaire so that each individual student would be aware of their preferred learning style. Team members attended lectures for a variety of first and third year courses and gave students a comprehensive overview of what the findings may mean. Strategies for coping with difference were also handed out, and students were encouraged to retain their results for future reference. Concurrent with the approach to the students, the team held workshops and discussion sessions for faculty members to raise their awareness of the differences they may encounter amongst students in each class. To this end the collated results of the student questionnaires were returned to faculty members. Faculty were also asked to complete the ILS questionnaire themselves so they were aware of their own learning preferences. Discussions were held over ways and means of presenting coursework in a variety of ways that catered for all learning styles some of the time. In Semesters 1 and 2 in 2001 and Semester 1, 2002 most first year students and some second and third year students across the three departments had completed the learning styles assessment. This was also extended to a cohort of engineering students in Singapore and to students accessing the bridging program course 'Introductory Communication'. Student assessments were collated in course groups and the group analyses provided to faculty teaching these courses. Students retained a copy of their own assessment for future reference. A summary of the number, year level and department or course of the students tested in each semester is given in Table 1. It is possible that the results of about 10% of the nearly 700 students tested appear twice in that table. The first time the ILS questionnaire was administered to students, in Semester 1, 2001, it was distributed in orientation week to department first year cohorts who were present at the time, thus students were not within a particular course. The second time it was administered, in Semester 2, 2001, it was given to 7 course groups across years 1 to 3. Two of these groups were first year groups, therefore some first year students may have completed the questionnaire twice. Since all results were returned for processing anonymously, no individual student could be identified thereby making it impossible to eliminate this duplication from the results graphs. However, as the intention of the graphical results was to inform faculty about the general range of learning styles of students in their course or department, this was not considered to be a problem. For students who undertook the questionnaire more than once, this was considered by the project team to be a useful way of providing reinforcement of the importance of understanding personal learning styles to those students. At the same time that students and faculty were being introduced to the
Learning Styles Project, the project team began building a website to
provide more comprehensive knowledge of the project and of learning styles
in general. The website was designed as a device for dissemination of
information and ideas for use by both faculty and students. As well as
giving basic information on learning styles and the ILS questionnaire,
the site outlines strategies for teaching and learning incorporating the
variety of learning styles amongst students. An annotated reference section
and a discussion board are also featured with the intention that it will
remain an ongoing and evolving outcome of the project. http://www.unisanet.unisa.edu.au/lsproject/learning_styles_home_page.htm
Table 1 - Learning Styles assessment involvement 2001 & 2002
Improving Faculty and Student Understanding of Learning Styles Since the aim of the project was to raise awareness of the diversity of learning styles amongst both faculty and students, dissemination of information was tackled at two levels. For faculty it was important that they realised the variation of learning styles that existed amongst students in their courses and tried to work towards catering for all types in their teaching. For students it was necessary that they knew and understood their own preferred learning style, but it was also important to give them information on how they might work around differences between their learning style and the teaching they received. Faculty Faculty who had opted into the project met together informally, and the discussion generated at these meetings contributed to an informed approach in broadening teaching and assessment methods. At a meeting early on in the project, for example, the implications of the learning styles profiles shown in Figure 1 were discussed, in particular, students' marked preference for visual learning styles. Students In the first week of semester 2, 2001 a total of 365 students across the three Departments of AME, GMC, and EIE and across undergraduate year levels 1 to 3 were assessed. Members of the project team again spoke to the students giving them an outline of the learning styles and how students could use the knowledge of their individual styles to help with their learning. Following assessment, individual group profile and total student results were circulated to faculty, and course coordinators provided feedback to students. The data collected from engineering students in both semesters 1 and
2 of 2001 (i.e. excluding the Introductory Communication cohort) has been
aggregated to construct the learning style student profiles shown below
(Figure 1). Comparative graphs of student and faculty (21 responses) results
were also made (Figure 2). The vertical axis in each graph represents
the % of students (and staff in Figure 2) from the total number assessed
(478 students and 21 staff) who scored that value on the learning styles
continuum for each dimension. The horizontal axis represents the student
or staff members' scores on the Felder scoring system explained previously.
In the above graphs, a score of 1-3 indicates a mild preference for one or the other (a or b) dimension but shows an essentially well-balanced approach to learning. A score of 5-7 indicates a moderate preference for one dimension of the scale and shows that a student will learn more easily in a teaching environment that favours that dimension. A score of 9-11 indicates a strong preference for one dimension of the scale and implies that a student may have real difficulty learning in an environment that does not support that preference. The most notable characteristic of the student learning styles profiles (Figure 1) is the strong skew towards visual, as opposed to verbal, learning styles. The other learning styles are fairly evenly spread across the range, though no students at all were assessed as strongly sequential learners and there is a stronger tendency towards sensory rather than intuitive learning. The extension of the questionnaire to a cohort of engineering students in Singapore was undertaken to explore any cultural differences or similarities in learning styles compared with the results from South Australian students. The team found little difference between the two campuses. Whilst some allowance needs to be made for the different sample sizes in drawing conclusions from Figure 2 (478 students, 21 faculty), these graphs demonstrate the variation of styles amongst all participants, but specifically the similarities and differences between faculty and students. There were relatively few differences between faculty and students in the sensory/intuitive, visual/verbal and sequential/global dimensions. There were marked differences, however, in the active/reflective dimension, showing a clear preference for active learning amongst students but with strong preferences for reflective learning by faculty. Finally, at the start of semester 1, 2002, information about learning styles was again passed on to students from courses in first and third years. 147 students were assessed and results were circulated to faculty who reported back to the students. These results showed no marked differences with those obtained in 2001. Learning styles assessments have continued for all first year students since 2002, but the data has not been collected, rather the purpose has been for student development.
The lecturers who opted into the project were requested to demonstrate how they would ensure their teaching methods would accommodate all learning styles, and to develop new resources if necessary. As was to be expected, each lecturer tackled this requirement in a different way. An example of one of the approaches utilised follows. Engineering Materials Lectures illustrated with photographs, sketches and graphs, cater for both visual and verbal learners. They are designed in a logical progression of facts and concepts, and thus also cater for sequential learners. Tutorials are mainly problem-solving exercises, which should be attempted before the session, either in groups or individually, catering for active or reflective learning styles. When appropriate, group work is also permitted in the tutorial itself. Demonstrations and videos assist those with visual and sensing learning styles. Case study sessions require group work, catering for active
learning styles. Within the group, students are also expected to perform
individual tasks, which is where reflective learning is required. Groups
in which all learning styles are represented will be those which work
most effectively. The sensing and sequential learners will contribute
their logical thinking and apply the established procedures to the problems
while the intuitive and global learners will more readily solve complications
and look at the overall problem.
Evaluations At the end of semester 2, 2001, and the end of semester 1, 2002, a learning styles specific evaluation was administered to several courses involved in the project in which students were asked to evaluate their own understanding of learning styles and how teaching relates to them. The main purpose of these evaluations was to determine whether the Learning Styles project had been effective in raising awareness amongst students about learning styles and whether students felt that teaching in the course addressed their preferred learning styles. Results were forwarded to respective faculty members responsible for teaching those courses. Findings from Evaluations 2002 Overall, findings from the evaluations suggest that:
Mainstreaming of Learning Styles Understanding One of the final challenges facing the project team was that of ensuring that the progress made in the engineering departments during the project, regarding student and teacher awareness of learning styles, was not lost as soon as the funded project was completed. The concept of "mainstreaming" the project approaches into the ongoing teaching and learning practices of the departments was adopted to address this, through both faculty and students. Mainstreaming via Faculty The project team also requested that Heads of Departments direct faculty to include a section on Learning Styles in each course handbook. This would encourage faculty to constantly rethink their teaching practices in line with divergent learning styles. The web site will be a valuable tool in this process. Mainstreaming via Students
Conclusion There is considerable evidence from previous studies to show that faculty assumptions about "typical" learning styles of engineering students are inaccurate and that a wide range of learning styles will actually exist within any engineering class. This has been reinforced again by the results of the current project. It is therefore important to raise the awareness of faculty responsible for engineering education about the likely effects on student achievement if teaching and assessment practices do not accommodate this range. This paper discusses a project that focused on awareness raising, and education about learning styles, for both faculty and students in a variety of engineering disciplines at the University of South Australia. The primary requirements for improved teaching and learning in this area are improved knowledge and understanding of learning styles, and reflection on practice, followed by any necessary modifications to practice in the light of this knowledge. The project initiated a process for faculty and students to achieve this, but also highlighted the necessity for mainstreaming this process if the improvements to teaching and learning are to continue. The Learning Styles Project web site is an important resource to support mainstreaming. Another strongly recommended strategy to achieve mainstreaming is to include learning styles information in course handbooks along with the web site URL, giving students, as well as faculty, continuing access to information on all aspects of learning styles.
References Anderson, M. (1991) Learning styles of the graduate career
change woman engineer: then and now. Proceedings of GASAT 6th International
Conference, University of Melbourne, Victoria, Australia, |