‘Intentional repetition’ and learning style: Increasing efficient and cohesive interaction in asynchronous online discussions

800x600 Normal 0 false false false EN-ID X-NONE X-NONE MicrosoftInternetExplorer4 /* Style Definitions */ table.MsoNormalTable {mso-style-name:Table Normal; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-parent:; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin:0cm; mso-pagination:widow-orphan; font-size:10.0pt; font-family:Times New Roman,serif;} The purpose of this study is to identify Kolb’s learning style of seventh-grade students. Learning style is a combination of the way how the student absorbs then processes the information. Kolb's learning style, developed by David Kolb, combines students' learning tendency and produces four learning styles; they are diverger, assimilator, converger, and accommodator. Learning style is one of the factors can cause misconceptions. A misconception is a difference between a student's conceptions and the expert. Usually, the concepts are difficult to correct. This misconception will affect a student's achievement and disturb in understanding and developing a student's knowledge. The method applied in this study was a survey method with describtive qualitative technique. The data were collected using Kolb's Learning Style Inventory (KLSI) 3.1 version . The subjects were 78 students in three schools with high, medium, and low grades The results indicated that from 78 students, there were 40 divergers (51%), 12 assimilators (15%), ten convergers (13%), and 16 accommodators (21%). Each kind of learning style affects a student's misconception. This research benefits in identifying misconceptions probably faced by students in certain subjects of science learning.

This study aimed to analyze the distribution of students' styles in learning Physics using the Kolb Learning Style Inventory (KLSI) in two different classes, namely XD and XG. The analysis results reveal that the Converger learning style is the most dominant, with 55.17% of students in XD and 73.53% in XG. The Converger learning style, characterized by a tendency for logical thinking and the ability to apply theory in practical contexts, is highly relevant in Physics education, which requires strong conceptual understanding and problem-solving applications. In addition, Converger, Accommodator, Diverger, and Assimilator learning styles were also identified, albeit in smaller numbers, with varying percentages across the XD and XG classes. This study reveals that the dominance of the Converger learning style in both classes suggests a strong alignment between current Physics teaching methods and the learning preferences of the majority of students. However, the presence of other learning styles underscores the importance of adopting diverse teaching strategies to ensure that all students, regardless of their learning style, are engaged and achieve optimal learning outcomes. This study also supports previous findings which proved that the Converger learning style is particularly effective in subjects that require analytical thinking and practical application, such as Physics. The implications of these findings advocate for developing more inclusive and adaptive teaching methods, integrating approaches that cater to all learning styles in the classroom.

The purpose of this research was to investigate the effects of formative assessment and learning style on student achievement in a Web‐based learning environment. A quasi‐experimental research design was used. Participants were 455 seventh grade students from 12 classes of six junior high schools. A Web‐based course, named BioCAL, combining three different formative assessment strategies was developed. The formative assessment strategies included Formative Assessment Module of the Web‐Based Assessment and Test Analysis system (FAM‐WATA) (with six Web‐based formative assessment strategies), Normal Module of Web‐Based Assessment and Test Analysis system (N‐WATA) (only with partial Web‐based formative assessment strategy) and Paper and Pencil Test (PPT) (without Web‐based formative assessment strategy). Subjects were tested using Kolb's Learning Style Inventory, and assigned randomly by class into three groups. Each group took Web‐based courses using one of the formative assessment strategies. Pre‐ and post‐achievement testing was carried out. A one‐way ANCOVA analysis showed that both learning style and formative assessment strategy are significant factors affecting student achievement in a Web‐based learning environment. However, there is no interaction between these two factors. A post hoc comparison showed that performances of the FAM‐WATA group are higher than the N‐WATA and PPT groups. Learners with a ‘Diverger’ learning style performed best followed by, ‘Assimilator’, ‘Accommodator’, and ‘Converger’, respectively. Finally, FAM‐WATA group students are satisfied with six strategies of the FAM‐WATA.

This study examines the learning styles of students in social work classes at Norfolk State University. Knowledge of learning styles can enhance the ability of faculty to build on student experiences and construct new learning opportunities. Kolb's Learning Style Inventory was administered to identify each student's dominate learning style. The theoretical underpinning is experiential learning, which supports the concept that learning styles are developed through experiences. The results indicated that diverging and accommodating learning styles occurred most often. Students with these styles learn best in classes where activities include lectures, role playing exercises, discussions, opportunities to practice skills, and reflection.

On the Relationship among Iranian ESP Learners’ Learning Strategy use, Learning Styles and their English LanguageAchievement

The effects of adopting the innovative dynamic product design method on the performance of students of different learning styles

SUMMARYMethods of optimizing students' learning have been a major concern of educators over time. If occupational therapy educators know the students' learning styles at the onset of their training, teaching can be designed to enhance students' optimal learning throughout their education. This study determined learning styles of 201 junior students (age range = 18–57, mean age = 30.9), enrolled in an urban occupational therapy program from 1990 to 1999. Kolb's Learning Style Inventory, a 12-item questionnaire, was administered to the students in the spring of their junior years. Their learning styles were determined using Kolb's criteria. Results yielded: variations in students' preferred learning styles in each class from year to year; higher percentage of convergers (mean = 35%), fewer divergers (mean = 18%). Overall, students were mostly convergers (mean = 35%) and assimilators (mean = 25%). Applications of the findings to teaching students are discussed.

Improving Education under Work-Hour Restrictions: Comparing Learning and Teaching Preferences of Faculty, Residents, and Students

The study described looks at the effects of learning style profile of teams on the quality of materials developed in a collaborative learning process. The study was carried out on collaborative teams of four or five university students, formed through learner preferences. Learning styles of the teams were determined using Kolb's Learning Styles Inventory. The learning style profiles of each team were found to vary, and each team had at least two students with different learning styles. At the end of the process, each team produced a printed material-developing manual. Evaluation was carried out by experts via analysis of the materials from the viewpoint of content adequacy, scientific accuracy, organization and originality, the specifications of which are also provided in the study. Statistical analyses indicated some significant differences between the teams regarding the product quality. Implications for practice in terms of team formation and possible effects on performance are given.

Relationships between critical thinking dispositions and learning styles.

The paper presents a module for studying of learning styles integrated in Moodle. The module is based on the Kolb's Learning Styles Inventory, Felder-Silverman Learning Styles Model, Gardner's Multiple Intelligence Inventory, Reid model. Also some results of pilot study with the module are performed.

The Impact of Learning Style Preferences on Foreign Language Achievement: A Case Study of Iranian EFL Students

The purpose of this article is to examine students’ views on the blended learning method and its use in relation to the students’ individual learning style. The study was conducted with 31 senior students. Web based media together with face to face classroom settings were used in the blended learning framework. A scale of Students’ Views on Blended Learning and its implementation, Kolb’s Learning Style Inventory, Pre-Information Form and open ended questions were used to gather data. The majority of the students’ fell into assimilators, accommodators and convergers learning styles. Results revealed that students’ views on blended learning method and its use are quite positive.

This research compares the learning preferences, locus of control and self assessment of 477 students to that of their instructors using the Kolb's Learning Style Inventory, Gregorc Style Delineator, and Rotter's Internal-External Locus of Control instruments in an effort to determine if an individual student's success is affected by match/mismatch of student and instructor learning preferences and attitude.

The Learning Style Inventory (LSI) is a commonly employed measure of learning styles based on Kolb’s Experiential Learning Model. Nevertheless, the psychometric soundness of LSI scores has historically been critiqued. The present article extends this critique by conducting a reliability generalization study across studies and versions of the test. Results indicated that internal consistency and test-retest reliabilities for LSI scores fluctuate considerably and contribute to deleterious cumulative measurement error. Reliability variation was predictable by test version and several study features.