Use of learning styles in the selection of instructional strategies : Does pedagogy lead to practice?

Much has been written about the importance of learning styles in instructional design. Learning styles can be measured by the use of personality profiles such as the Myers-Briggs Type Indicator (MBTI). Learning styles can also be measured by Learning Style Inventories and defined by cognitive theory such as Gardner\u27s multiple intelligences. This literature review explores the different approaches to the study of learning styles and the practical use of learning style indicators as a tool for selecting instructional strategies. Many challenges exist in designing instruction to the personal level including costs, time, and instructor limits. Philosophical questions on the benefits of customization must also be considered. Research supports the need to have variety in instruction to better simulate real-world application. This literature review concludes instruction should be learner centered, but does not need to be personality centered

The use of tagging to support the authoring of personalisable learning content

This research project is interested in the area of personalised and adaptable learning and in particular within an e-learning context. Brusilovsky (1996) and Santally (2005) stress the importance of adaptive systems within e-learning. Karagiannikis and Sampson et al. (2004) argue that personalised learning systems can be defined by their capability to adapt automatically to the changing attitudes of the “learning experience” which can, in turn, be defined by the individual learner characteristics, for example the type of learning material. The project evolved to cover areas including personalised learning, e-learning environments, authoring tools, tagging, learning objects, learning theories and learning styles. The main focus at the start of the project was to provide a personalised and adaptable learning environment for students based on their learning style. During the research, this led to a specific interest about how an academic can create, tag and author learning objects to provide the capability of personalised adaptable e-learning for a learner. Research undertaken was designed to gain an understanding of personalised and adaptive learning techniques, e-learning tools and learning styles. Important findings of this research showed that e-learning platforms do not offer much in the way of a personalised learning experience for a learner. Additionally, the research showed that general adaptive systems and adaptive systems incorporating learning styles are not commonly used or available due to issues with flexibility, reuse and integration. The concept of tagging was investigated during the research and it was found that tagging is underused within e-learning, although the research shows that it could be a good ‘fit’ within e-learning. This therefore led to the decision to create a general purpose discriminatory tagging methodology to allow authors to tag learning objects for personalisation and reuse. The main focus for the evaluation of this tagging methodology was the authoring side of the tagging. It was found that other research projects have evaluated the personalisation of learning content based on a learner’s learning style (see Graf and Kinshuk (2007)). It was therefore felt that there was a sufficient body of existing evidence in this area whereas there was limited research available on the authoring side. The evaluation of the discriminatory tagging methodology demonstrated that the methodology could allow for any discrimination between learners to be used. The example demonstrated within this thesis includes discriminating according to a learner’s learning style and accessibility type. This type of platform independent flexible discriminatory methodology does not exist within current e-learning platforms or other e-learning systems. Therefore, the main contribution of this thesis is therefore a platform independent general-purpose discriminatory tagging methodology

Teacher Candidate Dispositions Identified by NCATE-Accredited Colleges of Education: How Professional Educators are Disposed Toward the Students, Curriculum, and Reasons They Teach

The education profession has a great deal of information on potential teachers\u27 knowledge and technical skills, but the study of affective attributes that are the human interface between teaching and student learning is still evolving. The central phenomenon exmined in this study is the affective and attitudinal attributes, or dispositions of teachers as defined by colleges of education. The researcher analyzed conceptual frameworks and affective attributes in Institutional Reports from colleges reviewed by the National Council on the Accreditation of Teacher Education (NCATE), whose standards require reporting on dispositions. The dispositional factors that these colleges surmise predict successful practice were coded and categorized, then compared with the prior literature regarding this phenomenon and student learning factor\u27s. Student learning factors were drawn from existing cognitive science research with potential parallels to the dispositions identified in the qualitative study. Dispositional codes were analyzed and categorized using a developmental model, resulting in four primary categories and nine subcategories: Cognitive Knowledge Thinking Skills Emotional/Values Personal Interpersonal Community Social Character Leadership Contextual Structure for Learning Philosophy Frequencies and rank orders of the specific dispositions identified are provided. Graphs comparing dispositional characteristics in the Institutional Report analysis to the Interstate New Teacher Support and Assessment Consortium (INTASC) Ten Core Principles are included within the discussion of findings. Subcategories of valued teacher dispositions were found to have marked similarity across the diverse colleges and universities. However, little consensus occurred in regard to the research literature-bases used by the colleges and almost no information regarding specific assessments was available at this level of analysis. Recommendations are included that encourage greater collaboration within the profession and across other professional domains to better articulate the research base and determine appropriate hierarchical measurement scales for evaluation. Recommendations for college of teacher education self-examination of dispositional research and assessments within the developmental model, with an emphasis on incorporation of cognitive science research are also provided. The self-examination includes probe questions for mapping where dispositions arc addressed in the program structure, validating the research base, and mapping evaluations across the program

Increasing International Student Integration in Ontario College Environments

This paper reviews the problem of how to increase international student engagement and integration in an Ontario College environment, with the ultimate goal of creating an environment and campus culture of mutual engagement. Research has shown that international students still do not report a high level of engagement at Ontario College campuses despite the fact most colleges have educated international students for many years. The dichotomy of international versus domestic student problematizes these issues from a myriad of perspectives. This Organizational Improvement Plan (OIP) proposes a multi-pronged solution involving the creation of an internationalization strategy, the development of academic and cultural engagement and identity workshops as pilot projects, the creation of a Professional Improvement Community, and the integration of embedded English as a Second Language classes into curriculum to achieve improved mutual integration among international and domestic students, faculty and administrators. The problem is viewed through an International Student Cultural Integration Framework, where adaptive and authentic leadership styles lead the change and implementation process. A Plan-do-study-act cycle (PDSA) describes the implementation process and how iterative cycles of change will move from pilot workshops to full-scale organizational implementation during the course of one academic year to long-term implementation plan over five years

Learning Styles, Multimedia Hybrid Versus Traditional Teaching, Course Satisfaction, and Learning Outcomes in Art Appreciation Courses

Dramatic changes in technology in the 1980s have had an impact on human lives, not only in the field of business, but also in the field of education. In recent years, more academic institutions have chosen to deliver curricula online, and instructors have used different educational technology tools to support students\u27 learning abilities. In fact, web-based educational approaches have been examined by numerous researchers, and as a practical issue in the educational field, web-based instruction can be cost-effective, flexible, and convenient. The purpose of this exploratory (comparative) and explanatory (correlational), prospective survey research design was to investigate the relationship among course delivery methods (multimedia hybrid versus traditional face-to-face), learning styles, course satisfaction, and learning outcomes (course grade and learning gains) in higher education art appreciation courses. This study was conducted in a private university in south Florida, with a sample of 71 participants. There were three classes that constituted the sample of students that were taught via multimedia hybrid (n=44) and two classes that formed a sample of students taught by traditional methods (n=29). Independent t-tests and Chi-Square tests showed no difference in student background characteristics and learning styles between the two groups; however, course satisfaction, course grade, and learning gains were significantly higher in the multimedia hybrid classes. Eta, Pearson r correlation, and hierarchical linear regression analyses were used to test the hypotheses, which were partially supported: (a) learning style and student characteristics explained 25.2% of the variation in course satisfaction for the traditional group versus 18.6% for the multimedia group; (b) learning style and student characteristics explained 16.7% of the variation in course grade for the multimedia group versus 15.3% for the traditional group; and (c) learning style and student characteristics explained 35.2% of the variation in learning gains for the traditional group versus 10.0% for the multimedia group. Reliability and construct validity were also examined. Findings suggest that use of instructional technology in teaching art related classes can enhance learning and course satisfaction. Recommendations for future research included construct validation of the Learning Style Inventory, and replication of this study in larger universities, with larger samples, and in different countries

An Examination of the Factors Underlying the Motivation and Learning Strategies of Generation 1.5 Korean American Students

Comprehensive research into student learning has established that the effective use of learning strategies will enable students to take responsibility for their own learning, enhance their motivation in the learning process, and improve their academic success (Sternberg & Grigorenko, 2001). However, little research has investigated the learning strategies used by immigrant students and how these strategies relate to academic excellence. While survey instruments currently exist for assessing these constructs in the general population, the construct validity of theses scales has yet to be examined within immigrant populations. The subjects who participated in this study were randomly selected from the Korean American generation 1.5 students who were member of the Korean community churches located in Pittsburgh and Philadelphia. Students\u27 motivation and their use of language learning strategies were examined using two instruments: the Motivated Strategies for Learning Questionnaire (MSLQ) and the Strategy Inventory for Language Learning (SILL). Data were collected via 81 items from Motivated Strategies for Learning Questionnaire (MSLQ) and 50 items form the Strategy Inventory for Language Learning (SILL). An exploratory factor analysis was conducted in order to determine the factor structures for the self-regulated learning strategy and for the motivation question items. This study expands the continuum of ESL research by focusing on unexplored ESL population, Generation 1.5 immigrant students in higher education

A Novel Adaptation Model for E-Learning Recommender Systems Based on Student’s Learning Style

In recent years, a substantial increase has been witnessed in the use of online learning resources by learn- ers. However, owing to an information overload, many find it difficult to retrieve appropriate learning resources for meeting learning requirements. Most of the existing systems for e-learning make use of a “one-size-fits-all” approach, thus providing all learners with the same content. Whilst recommender systems have scored notable success in the e-commerce domain, they still suffer from drawbacks in terms of making the right recommendations for learning resources. This can be attributed to the differences among learners’ preferences such as varying learning styles, knowledge levels and sequential learning patterns. Hence, to identify the needs of an individual student, e-learning systems that can build profiles of student preferences are required. In addition, changing students’ preferences and multidimensional attributes of the course content are not fully considered simultaneously. It is by failing to review these issues that existing recommendation algorithms often give inaccurate recommendations. This thesis focuses on student learning styles, with the aim of dynamically tailoring the learning process and course content to meet individual needs. The proposed Ubiquitous LEARNing (ULEARN) system is an adaptive e-learning recommender system geared towards providing a personalised learning environ- ment, which ensures that course learning objects are in line with the learner’s adaptive profile. This thesis delivers four main contributions: First, an innovative algorithm which dynamically reduces the number of questions in the Felder-Silverman Learning Styles (FSLSM) questionnaire for the purpose of initialising student profiles has been proposed. The second contribution comprises examining the accuracy of various similarity metrics so as to select the most suitable similarity measurements for learning objects recommendation algorithm. The third contribution includes an Enhanced Collaboration Filtering (ECF) algorithm and an Enhanced Content-Based Filtering (ECBF) algorithm, which solves the issues of cold-start and data sparsity in- herent to the traditional Collaborative Filtering (CF) and the traditional Content-based Filtering (CBF), respectively. Moreover, these two new algorithms have been combined to create a new Enhanced Hybrid Filtering (EHF) algorithm that recommends highly accurate personalised learning objects on the basis of the stu- dents’ learning styles. The fourth contribution is a new algorithm that tracks patterns of student learning behaviours and dynam- ically adapts the student learning style accordingly. The ULEARN recommendation system was implemented with Visual Studio in C++ and Windows Pre- sentation Foundation (WPF) for the development of the Graphical User Interface (GUI). The experimental results revealed that the proposed algorithms have achieved significant improvements in student’s profile adaptation and learning objects recommendation in contrast with strong benchmark models. Further find- ings from experiments indicated that ULEARN can provide relevant learning object recommendations based on students’ learning styles with the overall students’ satisfaction at almost 90%. Furthermore, the results showed that the proposed system is capable of mitigating the problems data sparsity and cold-start, thereby improving the accuracy and reliability of recommendation of the learning object. All in all, the ULEARN system is competent enough to support educational institutions in recommending personalised course content, improving students’ performance as well as promoting student engagement.Arab academy for science technology & maritime transpor

When Failure Is Not an Option: Designing Competency-Based Pathways for Next Generation Learning

Proposes an online learning-assisted model in which students advance by demonstrating mastery of subjects based on clear, measurable objectives and meaningful assessments. Examines innovation drivers, challenges, and philanthropic opportunities