674 resultados para Learning styles and preferences
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Thomas, L., Ratcliffe, M., Woodbury, J., and Jarman, E. 2002. Learning styles and performance in the introductory programming sequence. SIGCSE Bull. 34, 1 (Mar. 2002), 33-37.
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The purpose of this study was to investigate the relationship between learning styles and academic achievement in postsecondary education. It was the intent of the study to establish if there was a relationship between student learning style, teacher style, learner/teacher matching and/or mismatching, student gender and age, to the academic grades of students. This study was basically a replication of a study completed by Mary J. Thompson and Terrance P. O'Brien in 1991 on two campuses of a southeast community college in the United States. In the present study, 243 students and 18 teachers from two different campuses of a community college in the Province of Ontario participated in the research. All participants were administered the Gregorc Style Delineator and students identified by program, age and gender. Data were tested by two analysis of variance (ANOVA) models. In the first ANOVA model considered in this study, significant main effects were manifested in regard to the teaching style, age group and gender. With the exception of gender, these findings were very similiar to those of the original study. Duncan's multiple range test revealed that Concrete Sequential (CS) teachers assigned significantly lower grades than did teachers dominant in any of the other three learning styles. Post hoc testing revealed that students 25 years of age and older received significantly higher grades than did younger students. Female students also received significantly higher grades than did male students. In the second ANOVA model student/teacher learning style match/mismatch did emerge as a significant main effect. However, Duncan's multiple range test and Chi square analysis did not substantiate the relationship. Forty-eight references are cited.
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ACM Computing Classification System (1998): K.3.1, K.3.2.
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Purpose: This cross-sectional study was designed to determine whether the academic performance of optometry undergraduates is influenced by enrolment status, learning style or gender. Methods: Three hundred and sixty undergraduates in all 3 years of the optometry degree course at Aston University during 2008–2009 were asked for their informed consent to participate in this study. Enrolment status was known from admissions records. An Index of Learning Styles (http://www4.nscu.edu/unity/lockers/users/f/felder/public/Learning-Styles.html) determined learning style preference with respect to four different learning style axes; active-reflective, sensing-intuitive, visual-verbal and sequential-global. The influence of these factors on academic performance was investigated. Results: Two hundred and seventy students agreed to take part (75% of the cohort). 63% of the sample was female. There were 213 home non-graduates (entrants from the UK or European Union without a bachelor’s degree or higher), 14 home graduates (entrants from the UK or European Union with a bachelor’s degree or higher), 28 international non-graduates (entrants from outside the UK or European Union without a bachelor’s degree or higher) and 15 international graduates (entrants from outside the UK or European Union with a bachelor’s degree or higher). The majority of students were balanced learners (between 48% and 64% across four learning style axes). Any preferences were towards active, sensing, visual and sequential learning styles. Of the factors investigated in this study, learning styles were influenced by gender; females expressed a disproportionate preference for the reflective and visual learning styles. Academic performance was influenced by enrolment status; international graduates (95% confidence limits: 64–72%) outperformed all other student groups (home non graduates, 60–62%; international non graduates, 55–63%) apart from home graduates (57–69%). Conclusion: Our research has shown that the majority of optometry students have balanced learning styles and, from the factors studied, academic performance is only influenced by enrolment status. Although learning style questionnaires offer suggestions on how to improve learning efficacy, our findings indicate that current teaching methods do not need to be altered to suit varying learning style preferences as balanced learning styles can easily adapt to any teaching style (Learning Styles and Pedagogy in Post-16 Learning: A Systematic and Critical Review. London, UK: Learning and Skills Research Centre, 2004).
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Common Learning Management Systems (for example Moodle [1] and Blackboard [2]) are limited in the amount of personalisation that they can offer the learner. They are used widely and do offer a number of tools for instructors to enable them to create and manage courses, however, they do not allow for the learner to have a unique personalised learning experience. The e-Learning platform iLearn offers personalisation for the learner in a number of ways and one way is to offer the specific learning material to the learner based on the learner's learning style. Learning styles and how we learn is a vast research area. Brusilovsky and Millan [3] state that learning styles are typically defined as the way people prefer to learn. Examples of commonly used learning styles are Kolb Learning Styles Theory [4], Felder and Silverman Index of Learning Styles [5], VARK [6] and Honey and Mumford Index of Learning Styles [7] and many research projects (SMILE [8], INSPIRE [9], iWeaver [10] amonst others) attempt to incorporate these learning styles into adaptive e-Learning systems. This paper describes how learning styles are currently being used within the area of adaptive e-Learning. The paper then gives an overview of the iLearn project and also how iLearn is using the VARK learning style to enhance the platform's personalisation and adaptability for the learner. This research also describes the system's design and how the learning style is incorporated into the system design and semantic framework within the learner's profile.
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The object of this study is to identify the learning styles (LS) used by the students of the subject of physiology of the exercise of the program of Physiotherapy, with the purpose of establishing a direct relationship later on between the learning styles and the possible pedagogic strategies that but they favor the compression of the physiology of the exercise 48 subject of second and third year of career they were interviewed through the instrument standardized compound number (CHAEA). This study carried out an analysis descriptive and of typical deviation of the data. They were differences statistically significant in the styles of active and reflexive learning, in front of the Theoretical and pragmatic styles what puts in evidence the necessity to generate pedagogic strategies inside the subject that this chord with the tendency of the active and reflexive learning of the students.
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This paper closely examines factors affecting students’ progression in their engineering programs through fieldwork conducted at three Australian universities. To extract clues on how specific teaching methods can be used to maximize learning, the investigation considered factors such as understanding how students take in, process and present information. A number of focus groups were conducted with students and the data gathered was combined with survey results of students’ and academics’ learning styles. The paper reports on the process followed, and provides some analysis of the gathered data, as part of an Australian Learning and Teaching Council, ALTC, Associate Fellowship program.
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Accounting education is critical and any improvements in tertiary education of accounting students should result in better prepared graduates entering the profession. This study evaluates accounting students’ learning styles and the interaction of learning styles and teaching methodologies during degree programmes. Nine classes of accounting students (648 students) spread across four years and two degree programmes were evaluated. Students self-evaluated their learning style, pre-instruction. They were then subject to two separate teaching techniques (one active and one passive) in each course. Learning styles were then re-assessed and teaching techniques evaluated. Accounting students displayed a preference for passive learning, even those far advanced in their degrees. Furthermore, when learning styles matched teaching methods used, usefulness was assessed as high but when learning styles and teaching methods differed, usefulness deteriorated. Overall, the teaching methods were deemed more effective by active rather than passive learners. The implications are significant. To maximise educational benefit for the accounting profession, student learning styles should be assessed before designing appropriate teaching methodologies. This has resource implications which would have to be considered.
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This work shows the use of adaptation techniques involved in an e-learning system that considers students' learning styles and students' knowledge states. The mentioned e-learning system is built on a multiagent framework designed to examine opportunities to improve the teaching and to motivate the students to learn what they want in a user-friendly and assisted environment
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Many studies have widely accepted the assumption that learning processes can be promoted when teaching styles and learning styles are well matched. In this study, the synergy between learning styles, learning patterns, and gender as a selected demographic feature and learners’ performance were quantitatively investigated in a blended learning setting. This environment adopts a traditional teaching approach of ‘one-sizefits-all’ without considering individual user’s preferences and attitudes. Hence, evidence can be provided about the value of taking such factors into account in Adaptive Educational Hypermedia Systems (AEHSs). Felder and Soloman’s Index of Learning Styles (ILS) was used to identify the learning styles of 59 undergraduate students at the University of Babylon. Five hypotheses were investigated in the experiment. Our findings show that there is no statistical significance in some of the assessed factors. However, processing dimension, the total number of hits on course website and gender indicated a statistical significance on learners’ performance. This finding needs more investigation in order to identify the effective factors on students’ achievement to be considered in Adaptive Educational Hypermedia Systems (AEHSs).
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The majority of current first year university students belong to Generation Y. Consequently, research suggests that, in order to more effectively engage them, their particular learning preferences should be acknowledged in the organisation of their learning environments and in the support provided. These preferences are reflected in the Torts Student Peer Mentor Program, which, as part of the undergraduate law degree at the Queensland University of Technology, utilises active learning, structured sessions and teamwork to supplement student understanding of the substantive law of Torts with the development of life-long skills. This article outlines the Program, and its relevance to the learning styles and experiences of Generation Y first year law students transitioning to university, in order to investigate student perceptions of its effectiveness – both generally and, more specifically, in terms of the Program’s capacity to assist students to develop academic and work-related skills.
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Objectives This paper reports on the preferred learning styles of Registered Nurses practicing in acute care environments and relationships between gender, age, post-graduate experience and the identified preferred learning styles. Methods A prospective cohort study design was used. Participants completed a demographic questionnaire and the Felder-Silverman Index of Learning Styles (ILS) questionnaire to determine preferred learning styles. Results Most of the Registered Nurse participants were balanced across the Active-Reflective (n = 77, 54%), and Sequential-Global (n = 96, 68%) scales. Across the other scales, sensing (n = 97, 68%) and visual (n = 76, 53%) were the most common preferred learning style. There were only a small proportion who had a preferred learning style of reflective (n = 21, 15%), intuitive (n = 5, 4%), verbal (n = 11, 8%) or global learning (n = 15, 11%). Results indicated that gender, age and years since undergraduate education were not related to the identified preferred learning styles. Conclusions The identification of Registered Nurses’ learning style provides information that nurse educators and others can use to make informed choices about modification, development and strengthening of professional hospital-based educational programs. The use of the Index of Learning Styles questionnaire and its ability to identify ‘balanced’ learning style preferences may potentially yield additional preferred learning style information for other health-related disciplines.