Teaching and Learning Forum 2007 Home Page

Category: Professional practice
Teaching and Learning Forum 2007 [ Refereed papers ]
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

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 professor. 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. An individual's ability to rapidly assimilate such information is often the key to success. This preliminary learning style trial aimed to assess students' learning styles using the Felder-Silverman Learning Style Model, 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.


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:
  1. active or reflective;
  2. sensing or intuitive;
  3. visual or verbal;
  4. 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:

  1. synthesise and interpret presented data:
  2. frame questions and initiate discussion on technical issues;
  3. rapidly collate and digest the required background material;
  4. 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.

Student feedback

Towards the end of the semester, a Student Perceptions of Teaching (SPOT) survey was administered by the university. A total of 14 students participated in the survey. In addition to general questions about the instruction of the unit, two questions involving learning styles were included:
  1. Learning about my personal learning style has helped me in this unit;
  2. I feel that this unit catered to my learning style. Please comment.
The students indicated their agreement with the above statements by selecting from the following: strongly agree (SD) worth 5 points, agree (A = 4 points), neutral (N = 3 points), disagree (D = 2 points), strongly disagree (SD = 1 point), not applicable or don't know (NA = 0 points), and no response (NR = 0 points). Scores were aggregated to give an overall score with a maximum value of five using the following equation:

Equation

where n = the number of students, and the subscripts reflect the verbal responses described above. The SPOT scores were compiled by the Evaluation of Teaching Unit from UWA CATL and returned to the unit coordinator and tutor at the end of the semester. In addition to anonymous written feedback from Question B stated above, some students included comments with their ILS results earlier in the semester. All student responses in this study were voluntary and are presented anonymously in this paper.

Results and discussion

Learning style profiles

A total of 18 out of 23 students responded to the ILS questionnaire. This sample size was small and limits generalisations. However, the data can still be used to describe the preferences of the students in this unit, who were more inclined to be active, as indicated by a mean of -3 (Figure 1A), and visual learners, given a mean of -5.1 (Figure 1C). They tended to be well balanced in terms of the sensing/intuitive (mean of -1.2, Figure 1B) and sequential/global dimensions (mean of 0.6, Figure 1D). The data were fairly widely distributed with a standard deviation of 2.2 and 2.6 (Figure 1) with the exception of the visual/verbal dimension, where the scores were more tightly clustered at the visual end of the scale (standard deviation of 1.7, Figure 1C).

Figure 1
Figure 1: Student responses to the ILS online questionnaire for (A) the active/reflective, (B) the sensing/intuitive, (C) the visual/verbal, and (D) the sequential/global dimensions of the Felder-Silverman model, with means (mu), standard deviations (s), and n = 18 students
In order to better understand how well these data represent a typical sample of university students, these findings were compared with those of previous studies presented in the literature. The strengths of student preferences in this study (n=18) were compared to a sampled population (n=970) compiled from existing studies in Table 1 (Felder and Spurlin 2005). Based on reasoning suggested by Felder and Soloman (2006), in general, most of the students participating in this study had mild preferences, meaning that they were well balanced between the two dimensions of a learning style and were able to process information presented either way. However, the students exhibited unusually high preferences (moderate to strong) towards active learning. There were no verbally-oriented students in this study, which is considerably less than normal, and the number of moderately global learners was above average (Table 1).

Table 1: Strengths of preferences for the four learning style dimensions indicated by mild, moderate to strong (Mod-Str), and shown as percentages of students in this study (n=18) compared to other published results (n=970); data from other studies were compiled from studies A1, A2, A3, C, E, F in Felder ande Spurlin (2005)

Active vs ReflectiveSensing vs IntuitiveVisual vs VerbalSequential vs Global
Mod-Str ActMildMod-Str RefMod-Str SensMildMod-Str IntMod-Str VisMildMod-Str VerbMod-Str SeqMildMod-Str Glob
This study5044633501761390176122
Other studies256114404912474311286012

Student feedback

There did not appear to be any significant trend in response to Question A; the students were divided, with a mean of 3.0 (neutral) on whether learning about their learning style was beneficial within this unit (Figure 2). Regarding Question B, the mean student response (mean of 2.92, between neutral and disagree) was that the unit did not really cater to their learning style. Again, the students were divided, with a third of the class each agreeing, neutral, or disagreeing, and with two students not answering the question, perhaps due to confusion. Compared to the overall SPOT results for the unit, the responses to the two questions regarding learning styles had the two lowest mean scores.

Figure 2

Figure 2: Percent frequency of student responses to SPOTS survey questions, where SA = strongly agree, A = agree, N = neutral, D = disagree, SD = strongly disagree, and n = 14 students

Written feedback from the SPOT survey indicated that at least one student did not really understand what his/her learning style meant:

I did not really understand what my learning style meant - it was too mixed... but mostly, I don't know how to apply it.
Another student expressed a lack of motivation to attend university because he/she found that material delivered in the format of a lecture was not compatible with his/her learning style. One student expressed that no unit would be able to cater to a visual learning style.

Comments about the ILS as a tool to assess personal learning styles were generally positive. Students felt that their learning profiles were fairly accurate, although they expressed some ambiguity in their choice of answers:

I believe they are fairly accurate, but of course, not all the questions were easy to answer.

Many of the questions I would answer both.

One student pointed out that his/her learning style changed depending on subject matter. For more abstract disciplines such as arts, he/she felt that a visual/global/intuitive learning style, was more appropriate, while adopting a more sensory/sequential approach to maths:
I think my answers are dependent on the type of knowledge I am learning... if I was answering this for an arts unit I feel my results might be slightly different.
The results illustrated that the students did not appear to benefit from learning about learning styles. Given the positive feedback that the ILS is fairly accurate as a tool to asses learning styles, the question is why was this not the case for this project? This part of the study attempts to ascertain an idea of the strengths and weaknesses of teaching methods used in the unit in terms of each learning style dimension.

With respect to the general unit structure, reading material chosen by the speaker was available online for students prior to each seminar. After each seminar, the PowerPoint presentations were also uploaded so that students could review the material for the final examination. Both of these actions allowed more time for reflective learners to absorb material than the 45 minute seminar provided to them. However reflective learners did not get enough time to reflect on seminars beforehand because the material was not uploaded until afterwards. A short quiz was administered on the reading at the beginning of each seminar. The quiz and ensuing discussion actively engaged the students thereby giving active learners a chance to become more involved. In terms of the seminars themselves, the speakers used PowerPoint presentations. It is thought that such multimedia presentations benefit visual and sensing learners (Felder and Silverman 1988) through the use of graphics and by providing real world examples. Sensing learners also had an advantage because the material presented tended to be more concrete than abstract, although this may have caused difficulties for intuitive learners. Sequential learners may have become frustrated because each topic was comparatively unrelated to the previous week. In a similar manner, global learners may have struggled with this due to the lack of a big picture.

Tutorials provided an opportunity to discuss study questions based on the seminar held the previous day. However, the timetable for this unit was constraining, so that, again reflective learners did not have a great deal of time to reflect on the material. Learner-centred practice was introduced to the tutorials to provide an opportunity for active learners to become engaged and to facilitate a better learning community. The idea of a learning community is one where both program facilitators and participants are considered as resources and are responsible for the learning that takes place within the group, but that ultimately, participants are responsible for their own learning (CATL 2006). By introducing small group discussion to the class, students were encouraged to interact amongst themselves. This facilitated both active and visual learning, as each group was required to explain their answers using illustrations to the whole class. This seemed to work well; not only did all of the students get involved in small group conversation, but most of the class participated in the ensuing discussion. The students seemed to enjoy learning this way, and the SPOT scores indicated that they felt the teaching was well suited to small groups and that useful class discussion was simulated in tutorials (means of 4.07 and 3.79, agree). The tutorial was also where global and intuitive learners had the opportunity to make connections and gain a better understanding of the big picture. However, these kinds of learners probably struggled in tutorials for the same reasons as above; the concepts presented were rarely abstract, and the topics were somewhat unrelated each week. Preferring order, sequential learners may also have had difficulty with the tutor's creative teaching style because it is a reflection of her own global learning style. This is a common mistake among teachers (Felder 1993).

The question remains whether our teaching methods facilitated or inhibited learning for these students with moderate to strong preferences towards active, visual and global learning styles. According to Felder and Silverman (1988), mismatches of learner/teaching styles can lead to poor performance and frustration among students, and in some cases can result in students withdrawing from a unit. Rather than modifying teaching methods to accommodate student learning styles, the best strategy to avoid such issues is to adopt a balanced approach to teaching and to periodically address both sides of each learning style dimension (Felder and Spurlin 2005; Felder 1993).

Conclusions

The Index of Learning Styles shows significant promise as a tool to improve student experiences at university. Integrating the ILS into teaching methods may help to avoid issues of student frustration and lack of motivation, and ultimately may help to prepare students for successful careers in science, engineering and research. This preliminary learning style trial indicates, however, that several key points must be addressed if the ILS is to be successfully integrated into university teaching methods.

This study emphasises that the lecturer must think carefully about weekly timetables and activities throughout the semester. One of the problems we encountered was that students with certain learning styles may not have had enough time to digest material. Additionally, it is important to discuss learning styles and studying strategies early in the semester, so that the students have a clear understanding of their own learning preferences and are aware of available study techniques to adopt based on individual profiles. An early discussion of learning styles would also assist students and teachers alike to identify when a mismatch of learning and teaching styles exists, so that steps can be taken early on to facilitate a better learning environment throughout the semester.

Further work

This study was a preliminary attempt to determine if certain learning styles could be applicable for teaching and learning in a Level 4 unit at UWA. Due the small class size, the data set collected from surveying the class was very small. To make significant deductions about the benefits of implementing different learning styles, it would therefore be useful to further develop this type of study and apply it to a larger class or classes. The best strategy to cater for all learning styles is to adopt a balanced approach to teaching and to periodically address both sides of each learning style dimension (Felder and Spurlin 2005; Felder 1993). However, this may be impractical for seminar style units such as this one, where different speakers present varied topics each week. Perhaps the emphasis in such units should instead be placed on early assessment and discussion of learning styles so that students are aware of individual strengths and weaknesses, and can develop study strategies to improve their ability to rapidly assimilate information from a wide variety of fields. Involving the students in a discussion of the unit structure could also be helpful if students are aware that the design of class activities is informed by research on learning styles. Practical issues associated with timing of activities should also be thought through well in advance of any future research taking place. By incorporating learning styles into more units at UWA, future research can begin to understand not only trends in student learning, but also some of the causes of student frustration, and how better to cope with mismatches of learning/teaching style that can potentially lead to student attrition. Such research will serve only to benefit the student experience at university.

Acknowledgments

We are grateful to the students, for this study would not have been possible without them. We wish to thank Carolyn Oldham and Euan Harvey for their support and for helpful comments on the manuscript, Allan Goody and Tama Leaver for assistance with University research project procedures and for providing an expert introduction to this field, Ben and Barbara for many insightful conversations, Kevin for his encouragement, Anya Waite for providing the opportunity, and Tim Colmer for the inspiration.

References

Alfonseca, E., R.M. Carro, E. Martin, A. Ortigossa, P. Paredes. (2006). The impact of learning styles on student grouping for collaborative learning: A case study. User Modeling and User-Adapted Interaction, 16(3-4), 377-401.

Barbe, W.B. and M.N. Milone. (1981). What we know about modality strengths. Educational Leadership, February 1981, 378-380.

Carlson, H.L. (1991). Learning style and program design in interactive multimedia. Educational Technology Research and Development, 39(3),41-48.

CATL. (2006). Foundations of University Teaching and Learning Program Outline. University of Western Australia, Centre for the Advancement of Teaching and Learning, Postgraduate Teaching Internship Scheme.

Crowder, R.G. and R.K. Wagner. (1992). The Psychology of Reading. 2nd Edition. Oxford University Press. Chapter 9.

Dee, K.C., G.A. Livesay. (2004). First-year students who leave engineering: learning styles and self-reported perceptions. Annual Conference and Exposition: Engineering Education Reaches New Heights, 20-23 June 2004, Salt Lake City, Utah, USA.

Dee, K. E.A. Nauman, G.A. Livesay, J, Rice. (2002). Research report: learning styles of biomedical engineering students. Annals of Biomedical Engineering, 3, 1100-1106.

De Vita, G. (2001). Learning styles, culture and inclusive instruction in the multicultural classroom: A business and management perspective. Innovations in Education and Teaching International, 38(2), 165-174.

Entwistle, N.J. (1988). Styles of Learning and Teaching. David Fulton. London, England.

Felder, R.M. (1993). Reaching the second tier: Learning and teaching styles iin college science education. Journal of College Science Teaching, 23(5), 286-290.

Felder, R.M. and E.R. Henriques. (1995). Learning and teaching styles in foreign and second language education. Foreign Language Annals, 28(1), 21-31.

Felder, R.M. and J. Spurlin. (2005). Applications, reliability and validity of the Index of Learning Styles. International Journal of Engineering Education, 21(1), 103-112.

Felder, R.M. and L.K. Silverman. (1988). Learning and teaching styles in engineering education. Engineering Education, 78(7), 674-681 with author's preface - June 2002. http://www.ncsu.edu/felder-public/Papers/LS-1988.pdf, accessed 20 October 2006.

Felder, R.M. and B.A. Soloman. (2006). Index of Learning Styles, http://www.ncsu.edu/felder-public/ILSpage.html, accessed 20 October 2006.

Ford, N., S.Y. Chen. (2001). Matching/mismatching revisited: an empirical study of learning and teaching styles. British Journal of Educational Technology, 32(1), 5-22.

Kolb, D. (1984). Experiential learning: Experience as the source of learning and development. Prentice Hall.

Lawrence, G. (1994). People Types and Tiger Stripes. 3rd Edition. Centre for Applications of Psychological Type.

Litzinger, T.A., S.H. Lee, J.C. Wise, and R.M. Felder. (2005). A study of the reliability and validity of the Felder-Soloman Index of Learning Styles. Proceedings of the 2005 ASEE Annual Conference, American Society for Engineering Education, June 2005.

Martin, M. (1978). Speech recoding in silent reading. Memory and Cognition, 6, 108-114.

McCarthy, B. (1987). The 4MAT system: Teaching to learning styles with right/left mode techniques. EXCEL. Inc.

Montgomery, S.M. (1995). Addressing diverse learning styles through the use of multimedia. Proceedings of the Frontiers in Education Conference, 3a2.13-3a2.21, November 11-14, 1995 Atlanta, Georgia, USA.

Zywno, M. (2003). A contribution to validation of score meaning for Felder-Soloman's Index of Learning Styles. Proceedings of the 2003 ASEE Annual Conference, American Society for Engineering Education, June 2003.

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.


[ Refereed papers ] [ Contents - All Presentations ] [ Home Page ]
This URL: http://lsn.curtin.edu.au/tlf/tlf2007/refereed/brown.html
Created 14 Jan 2007. Last revision: 20 Jan 2007.