The Use of Learning Styles as a Guide for Project Group Formation and Methods of Assessment

Since the introduction of a new degree programme in Product Design and Development (PDD) in 2004 a study of student learning style preferences has been undertaken to profile the first year intake on the three different degree programmes within the School of Mechanical and Aerospace Engineering at Queen’s University Belfast. A broadening of the range of acceptable subjects for entry and the acceptance of students without ALevel mathematics onto the PDD programme suggested that these students might prefer to study in a manner different to previous “generations” of engineering undergraduates. As well as identifying characteristic differences between disciplines the study provided information which is used across the degree programmes to enhance student learning and improve students’ self awareness of learning style preferences and strategies. With the objective of improving the range of student skills and abilities, required of professionally competent engineers, individual learning style preferences have been used in the formation of project groups. The profiling of learning styles within student cohorts has also provided information that has been used to adjust the methods of assessment and target areas where students require most development in order to achieve a more balanced learning style combination. The paper also discusses the experience of forming groups with both balanced and unbalanced learning style preferences, student reflections on their experiences of working in such groups and measured changes in student learning style preferences as a result of the changes in teaching and assessment methods. Context The Product Design & Development (PDD) degree at Queen’s University Belfast aims to produce BEng and MEng graduates professionally competent in all phases of new product development from conception through design, implementation and operation. Working as part of the conceive, design, implement, operate (CDIO) Initiative (www.cdio.org) the School of Mechanical and Aerospace Engineering has undergone a process of reforming its existing engineering degree programmes which now include more group based projects and more active and interactive learning. In the case of the PDD degree a new programme has been built with CDIO standards at the core. The first MEng cohort from this degree will graduate in 2008 Introduction The four stages of the experiential learning cycle defined by Kolb (1983) (Figure 1) led him to propose that students have a dominant phase in which they prefer to learn. He subsequently developed a Learning Style Inventory to identify how these preferences might vary across a group of students. Knowing how students prefer to learn, Kolb’s objective was to individualise instruction to produce students competent in all four of these learning styles, who would be balanced and integrated learners. Others such as Felder and Silverman (1988) have identified positive benefits gained from planning learning opportunities to take account of the broad ranges of learning styles found among engineering undergraduates. Figure 1: The four stages of the Kolb Experiential Learning Cycle Kolb’s and other methods of measuring learning style preferences have become popular and are widely used but there is limited commonality between the competing methods. In a study of thirteen different models (Coffield et al, 2004) found fault with many, including the most popular, and little evidence of benefit directly attributable to adoption of such methods and exaggerated claims from many practitioners. They did, however, acknowledge that where the examination of learning styles of both student and lecturer had been carried out there was clear evidence that the educational experience overall had been improved. They concluded that the development of a “lexicon of learning” facilitated productive discussion between teachers and students and that this selfawareness and metacognition enabled students to improve how they learnt. Preferring to work in one mode does not mean that the student is necessarily better when working this way. It is a level of preference not competence which is being measured. It is also important to emphasise that these modes are not predetermined or innate and that development of proficiency in the different modes can be acquired. A CDIO structured degree programme (Crawley et al, 2007) seeks to produce students who are professionally competent in all phases of the development of a product or system and necessarily needs to provide opportunities for this development to take place. It was proposed that profiling of student cohorts by measuring learning style preferences could be used to identify areas needing most development so that both curriculum and assessment could be planned to provide sufficient opportunity for this to take place. From Stage 1 the PDD students undertake a number of group Design Build Test (DBT) projects. The intention here is to mimic professional practice where product design and development is carried out in heterogeneous groups. These group projects also facilitate the acquisition of personal and interpersonal skills such as team working, project management and leadership which are much prized by employers but which have not traditionally been part of the disciplinary knowledge taught in purely engineering science modules. Set in the CDIO context of conceiving, designing, implementing and operating a product the group needs to perform well in all phases of the project to meet all the intended learning outcomes. Halstead & Martin (2002) and others have found that students allocated to groups on the basis of learning style preference can perform at a higher level than those placed randomly or allowed to self select their project group. To assist in the objective of maximising performance and development the learning outcomes and assessment methods are constructively aligned (Biggs, 1999) and tasks best suited to each of the preferences are present among the assessed elements. Honey and Mumford (1986) contend that the most effective problem solvers are good all rounders who can adapt to a range of environments. The DBT projects facilitate an engaged and motivated student to take control of their own learning. Each student has the opportunity to work on tasks at which they are most comfortable and to improve their abilities in other less preferred areas to become more rounded learners. Characteristic Profiles of Degree Programme Cohorts The study conducted first set out to measure the learning style preferences of the student cohort. An ongoing process of measuring the learning style preferences of students in all three degree programmes offered by the School of Mechanical and Aerospace Engineering when they first enrol in stage 1 is followed up by subsequent retests of the same students in later years of their degree to measure any changes in preference which have occurred. The Learning Combination Inventory (LCI) tool used was devised by Johnston & Dainton (1997) at the Rowan University, New Jersey. The LCI has twenty eight Likert scale (5 point), forced answer, tick box questions which are well matched to the learning objectives of the group based DBT projects and takes 10 to 15 minutes to complete. The questions focus on identifying preference in specific circumstances; for example “I would rather draw or build a model than read or write about a subject”. The questions relating to the different learning styles are not obvious to the student as they are irregularly mixed throughout the questionnaire and the students are not given prior information about the definitions of the different styles. Totals are calculated using a separate guide sheet which the students do not see beforehand. Preference between four learning styles; Precise, Sequential, Technical & Confluent processor, can be identified by four integer totals between 7 and 35. Table 1: Interpretation of Learning Combination Inventory Totals LCI Total Interpretation 7 17 'I avoid this action tendency wherever possible. This is not really me' 18 25 'I use this as needed' 26 35 'I strongly favour this action tendency. This is typically me' A precise processor prefers to gather, process and use data and to demonstrate their understanding through the writing of answers and factual reports. A sequential processor prefers clear and explicit instructions. They need to be organised and to have the time necessary to complete tasks to their satisfaction. A technical processor is much less comfortable with writing, preferring hands on practical experiences and problem solving tasks. A confluent processor is creative and imaginative and enjoys finding and making the widest connections between ideas. It should also be noted that the tool used focuses strongly on how a student prefers to carry out tasks and that there can be a distinct difference between how individuals choose to give and receive information. Carrizosa and Sheppard (2000) for instance found that engineering design students much preferred to receive visual information but rarely used this medium when working within their groups. This study concentrates on how the groups operated and not on how information has been provided or presented to the students. The study has proved consistent over three years and shows that there are significantly large numbers of students dominated by a preference for practical, hands-on learning. Many have avoidance tendencies for learning that requires precise data collection, manipulation and presentation. There is a significant minority of students most comfortable when working to a detailed plan and others who feel out of their comfort zone when required to generate original ideas or concepts. Among the three degree programmes characteristic cohort profiles can be identified. This is consistent with the notion proposed by Kolb (2000) that individuals choose careers congruent with their learning style preferences. The Aerospace and Me