Learning Styles and Administering Inventories
Learning Style Inventories
Myers-Briggs Personality Test
Free on-line adapted Myers-Briggs personality style test.
The Keirsey Temperament - Different Drums, Different Drummers
Determine your personality portrait. David Keirsey website offers the Keirsey Temperament Sorter I/II and Keirsey Temperament Theory from his books, Please Understand Me or Please Understand Me II.
Howard Gardner's Multiple Intelligences Inventory - SCROLL DOWN to just below the cartoon
Determine your learning strengths. Learn about multiple intelligences and take an MI Inventory test. Hosted by University of Vermont, Course PSS 162.
Learning Styles Survey for College
Or....take this interactive survey. Provided by Catherine Jester, Learning Disability Specialist, Diablo Valley College.
The Vark Inventory
No. It's not aadvark. It's visual, aural, reading, kinesthetic!
Classic Intelligence Quotient
Did you always want to know what the mystery was with all this IQ stuff? Here's your chance to find out.
Emotional Intelligence
EQ (Emotional Quotient) may be a bigger predictor of success than IQ.
Jung Typology Test
Where are you on the judging,sensing,thinking and intuitive scale?
Learning Style Mechanics, courtesy of The University of Western Australia
An Application of Learning and Teaching Styles:
A Case Study of Science and Engineering Seminars
Eloise J. Brown
School of Plant Biology and School of Environmental Systems Engineering
Jo Pluske
Faculty of Natural and Agricultural Sciences
The University of Western Australia
Introduction
The ability of students to take in material taught at a university level is a function of both their own personal learning style and the teaching style of the lecturer (Felder and Silverman 1988). Student learning styles vary among individuals, and it is important that teaching methods support a wide variety of learning styles in order to facilitate the best education possible. According to the Felder-Silverman learning style model, there are four dimensions of learning styles (Felder and Silverman 1988). The model originally included a fifth dimension that has been eliminated (Felder and Spurlin 2005), and one of the dimensions has since been renamed (Felder and Henriques 1995). The current Felder-Silverman model (Felder and Spurlin 2005) categorises a student as a learner who is:
- active or reflective;
- sensing or intuitive;
- visual or verbal;
- sequential or global.
Felder and Spurlin (2005) provide a description of these four dimensions and how they relate to other learning style models. They suggest that active learners prefer to be actively involved through discussion or the application of a concept compared to reflective learners, who are apt to think it through first (Felder and Soloman 2006). The active/reflective dimension is also found in the Kolb learning style model (McCarthy 1987; Kolb 1984), and is related to the distinction between extroverts and introverts by the Myers-Briggs Type Indicator (MBTI) (Lawrence 1994).
Alternatively, sensing learners tend to be detail-oriented, patient, practical, and are good at memorisation, whereas intuitive learners are more inclined to be innovative, work faster and prefer to avoid repetition. As noted by Felder and Spurlin (2005), this dimension is also recognised within the MBTI (Lawrence 1994) and is similar to the idea of concrete versus abstract from the Kolb model (Kolb 1984). Visual learners learn better through the use of visual aids, while verbal learners benefit more from written and verbal explanations (Felder and Spurlin 2005). This dimension was developed from cognitive studies of information processing (Felder and Henriques 1995; Crowder and Wagner 1992; Martin 1978). The literature suggests that most people tend to be visual learners and this notion places students at a disadvantage in a typical university setting where material is presented largely in the format of lectures and reading material (Felder 1993; Barbe and Milone 1981).
According to Felder and Spurlin (2005), sequential learners prefer linear thinking processes. This contrasts with global learners, who take a more holistic approach, learning in large jumps, and who are able to quickly find creative solutions to complex problems once they have grasped the big picture (Felder and Soloman 2006). In previous studies, the distinction between sequential and global learners has also been referred to as left versus right-brain dominant (Felder and Spurlin 2005; Torrance and Rockenstein 1998; Herrmann 1990; McCarthy 1987).
Evaluating student learning styles as a tool to better address student needs is an approach that has been successfully implemented at many universities across a wide range of disciplines. In a case study of collaborative learning in a web-based computer science course, Alfonseca et al. (2006) found that learning styles were a key feature for successful group formation. In particular, the active/reflective and sensing/intuitive dimensions affected the quality of the resulting work, and collaborative learning was improved by incorporating new grouping rules into the software to group students by learning style (Alfonseca et al. 2006). Another study that focused on the role of educational software in chemical engineering demonstrated the effectiveness of multimedia programs in addressing the learning styles typically neglected by traditional teaching methods (Montgomery 1995), namely the active, sensing, visual and global dimensions (Montgomery 1995; Felder and Silverman 1988).
In a study of international business management, cultural conditioning was reflected in student learning styles, with marked differences present (De Vita 2001). Other factors that were found to influence learning styles in a study of biomedical engineering students included cohorts (freshman, sophomore, etc.) and gender, with a significant portion of female students preferring active and sensing learning (Dee et al. 2002). These studies emphasise the need to adopt a multi-style teaching approach to engage all of the students while increasing their comfort levels in their less favoured learning style dimensions (De Vita 2001; Felder 1993).
Although previous research has found that in some instances, learning/teaching style mismatches may help students to learn in different ways (De Vita 2001, Entwistle 1988), students with stronger preferences are less adept at learning in these situations (Felder and Spurlin 2005). A study of matching/mismatching styles in a computer-based learning environment found significant differences in student performance, with superior performance in matched compared to mismatched conditions (Ford and Chen 2001). Significant effects were also found in this study for gender, with male students more affected by matching (Ford and Chen 2001). Similarly, an investigation of the effect of varying the design and delivery of interactive multimedia on the learning and attitudes of students majoring in elementary education found that students scored significantly higher when learning style matched instruction (Carlson 1991). A study of student attrition from engineering at one university reported a clear link between learning style and attrition, with a high percentage of global learners (70%, n=10) leaving the program during their first semester (Dee and Livesay 2004). This research demonstrates that an evaluation of teaching and learning styles can be beneficial and can facilitate student learning.
The reality of many fields today, particularly in science and engineering, is that the dissemination of information at a professional level is often in the format of a seminar. Speakers at international conferences and departmental seminars tend to follow somewhat prescribed formats where there is less flexibility to cater to individual student needs compared to within a university lecture. The purpose of this preliminary study was to determine how students responded to scientific seminars and whether they felt that having an understanding of their personal learning style was beneficial. In addition, the study investigated whether a mismatch of learning/teaching styles had an effect on learning.
This preliminary trial was integrated within a fourth-year environmental engineering unit at the University of Western Australia (UWA), consisting of a series of scientific seminars on topics ranging from physical and biological oceanography to biogeochemical processes in aquatic environments. The learning outcomes for the unit specified that students would gain an improved ability to rapidly synthesise and interpret multi-disciplinary and technical data. Within this context, this study aimed to assess students' learning styles using the Felder-Silverman Learning Style Model (Felder and Spurlin 2005, Felder and Silverman 1988), to use student responses to evaluate teaching methods, and to identify future research needs within science and engineering seminar-style units. Although limited in its scope to one unit at a single university, this preliminary trial can be used in a wider context as an example of how learning styles and strategies can be implemented into a real learning environment with genuine time and resource constraints.
Framework for the study
The unit was structured with a weekly seminar followed by a tutorial where students discussed the material presented to them. Each seminar was given by a different invited speaker. The students were at Level 4 and hence were able to effectively engage in this project. They were encouraged to ask questions during the seminars and in the ensuing discussions. Weekly reading material consisting of two scientific papers was posted on the unit website at least one week prior to each seminar. Study questions were developed shortly after each seminar and were posted on the unit website for discussion the following day in tutorial. The first author of this paper was the tutor for this unit. As part of a Postgraduate Teaching Internship through the Centre for the Advancement of Teaching and Learning (CATL) at UWA, her responsibilities for this unit included administering half of the seminars and tutorials. Due to scheduling constraints, most of her teaching took place during the second half of the semester, with the exception of the very first tutorial.
Given that each seminar was delivered by a different guest speaker on the subject of their own research, there was little the unit coordinator or tutor could do to change the content or structure of individual seminars based on student learning style needs. In addition, the timetable was fixed. As a consequence, this study focuses on evaluating student learning and teaching styles subject to the material available and under the prescribed circumstances. For example, the lecture notes were not available to be posted online until after the seminar, and this meant that some students, such as reflective learners, may not have been catered for as well as they might have been. Likewise, the less than 24 hour period between seminars and tutorials represents somewhat of a time constraint for certain groups of learners.
Nevertheless, the unit learning outcomes were specified in advance and suggested that students would gain an improved ability to:
- synthesise and interpret presented data:
- frame questions and initiate discussion on technical issues;
- rapidly collate and digest the required background material;
- gain an appreciation of the multi-disciplinary nature of environmental issues.
The idea was that, faced with complex and often new topics delivered by the seminars, students would have to adapt their learning strategies in order to best assimilate information from a wide variety of fields. Ultimately students were expected to synthesise the scientific papers, the seminar, the tutorial discussion and their own independent reading into a formal report. Today, this style of information dissemination is common in professional scientific, engineering and research environments, and an individual's ability to rapidly assimilate such information is often the key to success. The question is whether we can gain insights from learning styles models on how better to prepare students for a future in such fields.
Methods
Learning style profiles
A web-based tool known as the Index of Learning Styles (ILS) is a self-scoring questionnaire based on the Felder-Silverman learning style model and developed by Felder and Soloman (2006) from North Carolina State University, USA, which can be used to assess learning style preferences on the four dimensions. The ILS consists of 44 questions with two answers to choose from, for example: "When I am learning a new subject, I prefer to (a) stay focused on that subject, learning as much about it as I can; (b) try to make connections between that subject and related subjects" (Felder and Soloman 2006). The ILS has been translated into several other languages and has been online in its current format since 1996, with the website receiving over 500,000 hits per year (Felder and Soloman 2006). Several reliability and validity studies of the ILS indicate that it is an appropriate psychometric tool for evaluating learning styles of engineering students (Felder and Spurlin 2005; Zywno 2003; Litzinger et al. 2005). Scores on a scale of (±1 to 3 indicate mild preferences, (±5 to 7 indicate moderate preferences and (±9 to 11 indicate a strong preference towards a particular learning style dimension (Felder and Soloman 2006).
At the beginning of the semester, the 23 students in the class were given an information sheet on learning styles with suggestions for different study strategies to adopt based on personal learning styles (Felder and Soloman 2006). They were asked to determine their own learning style profile using the ILS and email the results to the tutor. Their results were compiled and presented to the class with a description of the four dimensions. Due to scheduling constraints, this was not actually discussed until late in the semester.
Authors: Eloise Brown is a PhD candidate for Marine Science, who is co-enrolled at the School of Plant Biology in the Faculty of Natural and Agricultural Sciences and the School of Environmental Systems Engineering in the Faculty of Engineering, Computing and Mathematics. In 2006 she participated in the UWA Postgraduate Teaching Internship. Postal address: School of Plant Biology (M090), The University of Western Australia, 35 Stirling Hwy, Crawley, Western Australia, 6009. Email: brown@sese.uwa.edu.au
Jo Pluske is a lecturer in the School of Agricultural and Resource Economics and was the Faculty of Natural and Agricultural Sciences' CATLyst (liaison between the Centre for the Advancement of Teaching and Learning and the Faculty) at the University of Western Australia.
Please cite as: Brown, E. J. and Pluske, J. (2007). An application of learning and teaching styles: A case study of science and engineering seminars. In Student Engagement. Proceedings of the 16th Annual Teaching Learning Forum, 30-31 January 2007. Perth: The University of Western Australia. http://lsn.curtin.edu.au/tlf/tlf2007/refereed/brown.html
Copyright 2007 Eloise J. Brown and Jo Pluske. The authors assign to the TL Forum and not for profit educational institutions a non-exclusive licence to reproduce this article for personal use or for institutional teaching and learning purposes, in any format (including website mirrors), provided that the article is used and cited in accordance with the usual academic conventions.
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