scholarly journals The implications of the research literature on learning styles for the design of instructional material

1999 ◽  
Vol 15 (3) ◽  
Author(s):  
Catherine McLoughlin
Keyword(s):  
Instructional Design ◽  
Individual Differences ◽  
Learning Styles ◽  
Learning Style ◽  
Adaptive Learning ◽  
Research Literature ◽  
Design Guidelines ◽  
Learning Cycle ◽  
Instructional Designers ◽  
Learning Material

<span>An enduring question for educational research is the effect of individual differences on the efficacy of learning. Aspects of individual differences that have been much explored relate to differences in learning styles, strategies and conceptions of learning. Such differences present a profound challenge for instructional designers, as research has shown that the quality of learning material is enhanced if the material is designed to take into account learners' individual learning styles (Rasmussen, 1998; Riding &amp; Grimley, 1999). In the context of the present research, learning style is taken to mean a consistent or habitual of mode of acquiring or imparting knowledge through study, experience or teaching (Beishuizen &amp; Stoutjesdijk, 1999). The purpose of this article is to propose ways in which individual differences can be accommodated when designing self-instructional learning materials in print for distance learners. It is advocated that instructional designers turn to research on learning styles to inform the design of adaptive learning material. Kolb's (1984) learning cycle and associated learning styles are described with a view to providing instructional design guidelines which accommodate (i) each stage of the learning cycle (ii) individual differences between learners in processing and presenting information. Examples of learning activities for each stage of the learning cycle are provided from a tertiary bridging course for adult learners. It is recommended that in designing for a diverse student body, the research literature on learning styles can provide insights that have the potential to improve instructional design.</span>

Intergenerational Learning Styles, Instructional Design Strategy, and Learning Efficacy

2020 ◽  
pp. 40-51
Author(s):  
Michael G. Strawser ◽  
Renee Kaufmann
Keyword(s):  
Instructional Design ◽  
Learning Styles ◽  
Learning Style ◽  
21St Century ◽  
Design Strategy ◽  
Instructional Designers ◽  
Intergenerational Learning ◽  
Educational Design ◽  
Broad Base ◽  
Learning Efficacy

Instructional designers must appeal to a variety of audience members both in terms of competency and preferred learning style. Though many factors may influence learning style, generational preferences may provide instructional designers a broad base of understanding undergirding strategic educational design choices. While it would be naive, and even inaccurate, to assume that Millennials constitute the only unique generational challenge for instructional designers, their sheer presence in organizations and their education expectations have changed the game—so to speak. Thus, in an attempt to clarify generational uniqueness, this chapter will explore general generational instructional trends while positioning instructional design as a necessary answer to 21st century learning efficacy challenges.

scholarly journals SCIENCE EDUCATION ADAPTIVE LEARNING SYSTEM AS A COMPUTER-BASED SCIENCE LEARNING WITH LEARNING STYLE VARIATIONS

2018 ◽  
Vol 17 (4) ◽  
pp. 711-727 ◽  
Author(s):  
Zulfiani Zulfiani ◽  
Iwan Permana Suwarna ◽  
Sujiyo Miranto
Keyword(s):  
Learning Styles ◽  
Learning Style ◽  
Adaptive Learning ◽  
Science Learning ◽  
Learning System ◽  
Learning Material ◽  
Learning Approaches ◽  
Slow Learners ◽  
Computer Based ◽  
Adaptive Learning System

Students with their different learning styles also have their own different learning approaches, and teachers cannot simultaneously facilitate them all. Teachers’ limitation in serving all students’ learning styles can be anticipated by the use of computer-based instructions. This research aims to develop ScEd-Adaptive Learning System (ScEd-ASL) as a computer-based science learning media by accommodating students’ learning style variations. The research method used is a mixed method at junior high schools in Tangerang Selatan. The final product of the research is a special learning media appropriate to students’ visual, aural, read/write and kinesthetic learning styles. The uniqueness of the media is its form of integrated science materials, accommodating fast and slow learners, and appropriate to their learning styles. ScEd-Adaptive Learning System as a developed computer-based science learning media was declared as good and valid by four media experts and five learning material experts. ScEd-ALS for kinesthetic style has a high effectivity to improve students learning mastery (100%), consecutively aural (63%), read/write (55%), and visual (20%). This media development can be continued with the Android version or iOS to make it more operationally practical. Keywords: adaptive learning system, science learning media, computer-based instruction, learning style.

scholarly journals Improving Learner-Computer Interaction through Intelligent Learning Material Delivery Using Instructional Design Modeling

Entropy ◽  
2021 ◽  
Vol 23 (6) ◽  
pp. 668
Author(s):  
Christos Troussas ◽  
Akrivi Krouska ◽  
Cleo Sgouropoulou
Keyword(s):  
Instructional Design ◽  
Adaptive Learning ◽  
Educational Software ◽  
Learning Experience ◽  
Learning Material ◽  
Java Programming ◽  
Undergraduate University Students ◽  
Intelligent Tools ◽  
Content Based Filtering ◽  
Computer Interaction

This paper describes an innovative and sophisticated approach for improving learner-computer interaction in the tutoring of Java programming through the delivery of adequate learning material to learners. To achieve this, an instructional theory and intelligent techniques are combined, namely the Component Display Theory along with content-based filtering and multiple-criteria decision analysis, with the intention of providing personalized learning material and thus, improving student interaction. Until now, the majority of the research efforts mainly focus on adapting the presentation of learning material based on students’ characteristics. As such, there is free space for researching issues like delivering the appropriate type of learning material, in order to maintain the pedagogical affordance of the educational software. The blending of instructional design theories and sophisticated techniques can offer a more personalized and adaptive learning experience to learners of computer programming. The paper presents a fully operating intelligent educational software. It merges pedagogical and technological approaches for sophisticated learning material delivery to students. Moreover, it was used by undergraduate university students to learn Java programming for a semester during the COVID-19 lockdown. The findings of the evaluation showed that the presented way for delivering the Java learning material surpassed other approaches incorporating merely instructional models or intelligent tools, in terms of satisfaction and knowledge acquisition.

Knowledge Mining for Adaptive Multimedia Web-Based Educational Platform

2008 ◽  
pp. 205-257 ◽  
Author(s):  
Leyla Zhuhadar ◽  
Olfa Nasraoui ◽  
Robert Wyatt
Keyword(s):  
Learning Styles ◽  
Learning Style ◽  
Intelligent System ◽  
Learning Material ◽  
Online Information ◽  
Learning Sequence ◽  
Online Students ◽  
User Models ◽  
Web Based ◽  
The Web

This chapter introduces an Adaptive Web-Based Educational platform that maximizes the usefulness of the online information that online students retrieve from the Web. It shows in a data driven format that information has to be personalized and adapted to the needs of individual students; therefore, educational materials need to be tailored to fit these needs: learning styles, prior knowledge of individual students, and recommendations. This approach offers several techniques to present the learning material for different types of learners and for different learning styles. User models (user profiles) are created using a combination of clustering techniques and association rules mining. These models represent the learning technique, learning style, and learning sequence, which can help improve the learning experience on the Web site for new users. Furthermore, the user models can be used to create an intelligent system that provides recommendations for future online students whose profile matches one of the mined profiles that represents the discovered user models.

The Learning Style-Based Adaptive Learning System Architecture

2015 ◽  
Vol 5 (2) ◽  
pp. 1-10 ◽  
Author(s):  
Chyun-Chyi Chen ◽  
Po-Sheng Chiu ◽  
Yueh-Min Huang
Keyword(s):  
Learning Styles ◽  
Learning Style ◽  
Adaptive Learning ◽  
System Architecture ◽  
Learning System ◽  
Learning Materials ◽  
Learning Path ◽  
Different Types ◽  
Learning System Architecture ◽  
Adaptive Learning System

In the current study of learning process that show learners will take a different way and use different types of learning resources in order to learning better. Any many researchers also agree that learning materials must be able to meet the various learning styles of learners. Therefore, let learners can effective to improve their learning, for different learning styles of learners should be given different types of learning materials. In this paper the authors propose a learner's learning style-based adaptive learning system architecture that is designed to help learners advance their on-line learning along an adaptive learning path. The investigation emphasizes the relationship of learning content to the learning style of each participant in adaptive learning. An adaptive learning rule was developed to identify how learners of different learning styles may associate those contents which have the higher probability of being useful to form an optimal learning path. In this adaptive learning system architecture, it will according to different learning styles given different types of learning materials and will according to learner's profile to adjust learner's learning style for providing suitable learning materials.

The Factor Structure and Validity of the Learning Styles Profiler (LSP)

2008 ◽  
Vol 24 (2) ◽  
pp. 117-123 ◽  
Author(s):  
Peter J. O’Connor ◽  
Chris J. Jackson
Keyword(s):  
Individual Differences ◽  
Learning Styles ◽  
Job Performance ◽  
Learning Style ◽  
Factor Structure ◽  
Predictive Validity ◽  
Approach And Avoidance

The Learning Styles Profiler (LSP; Jackson, 2002 ) is a modern measure of individual differences in learning style. The LSP is based on a neuropsychological model of learning, modeled on principles of approach and avoidance, and argues for the division of personality into temperament and character. There has been little research into the psychometric structure and predictive validity of this instrument. In Study 1, the factor structure of the LSP is examined, and in Study 2 the criterion-related validity of the LSP is assessed. Results support the proposed factor structure of the LSP and show that 3 of the 4 LSP scales are significant predictors of Job Performance.

scholarly journals Blended Learning Strategies of Telegram-Assisted Learning Towards Student Mathematics Learning Results Reviewed from Learning Style

2020 ◽  
Vol 4 (2) ◽  
pp. 133
Author(s):  
Kadek Suryati ◽  
I Gede Adnyana
Keyword(s):  
Learning Styles ◽  
Blended Learning ◽  
Learning Outcomes ◽  
Learning Strategies ◽  
Learning Style ◽  
Learning Strategy ◽  
Mathematics Learning ◽  
Sampling Technique ◽  
Learning Material ◽  
Online Application

The research aims to describe the influence of telegram-assisted blended learning strategies on mathematics learning outcomes in terms of learning styles. This research is a quasi-experimental research using 2x3 factorial design. The respondents taken is the second semester students majoring in informatics engineering at the STMIK STIKOM Indonesia campus. The sampling procedure in this study was a random sampling technique that was started by carrying out the equivalency test of 4 classes taken using the one-way ANOVA test. After that randomly selected, two classes as an experimental class and two classes as a control class. To get instruments that have validity before use, questionnaires and tests are first tested and validated by experts who are experts in their fields. Normality and homogeneity tests are needed as a prerequisite before analyzing the data. The method used to analyze data is two-way ANOVA. The results showed that (1) student mathematics learning outcomes taught with telegram-assisted blended learning strategies were better than conventional mathematics learning outcomes of students taught, (2) the effect of telegraph-assisted blended learning strategies on student mathematics learning outcomes in learning styles. Based on the results of the research that has been carried out, it is recommended that further researchers or educators be able to develop a blended learning strategy as a way to convey learning material so that they can pay more attention to the learning styles of each student and can develop telegrams with more attractive features so that the telegram becomes one of online application for learning media.

scholarly journals Adaptive Online Module Prototype for Learning Unified Modelling Language (UML)

2016 ◽  
Vol 6 (6) ◽  
pp. 2931 ◽  
Author(s):  
Arief Hidayat ◽  
Victor Gayuh Utomo
Keyword(s):  
Online Learning ◽  
Learning Styles ◽  
Learning Style ◽  
Verbal Learning ◽  
Unified Modeling Language ◽  
Software Systems ◽  
Learning Material ◽  
Online Module ◽  
Industry Standard ◽  
Online Learning Resources

Every student has their own learning style. Some students may prefer to read the learning material while some other students may prefer to discuss with their colleagues to help them understanding the information more effectively. One of the learning materials is Unified Modeling Language or UML. UML is an industry standard language to specify, visualize, construct, and document the artifacts of software systems. Today, many UML online learning sites are designed to give added information to students other than face-to-face interaction in the classroom. However, most of UML materials provided by the online learning resources are limited to text-based material which is suitable only for students with verbal learning styles. This research aims to identify and analyze the needs before developing a prototype of an adaptive online module. The research is also driven by the need to develop a prototype of adaptive online module that is based on the student's learning style categories in order to help students understand UML better. The result of this research is a prototype of adaptive online module which will identify students' learning styles and lead the students to learning environment that suits their learning style.

scholarly journals A Survey for Need Assessment to Classify Learning Styles of Students Studying in Master Degree Programs at Universities

2018 ◽  
Vol 34 (2) ◽  
Author(s):  
Zafar Iqbal ◽  
Zill E Huma ◽  
Sana Nasir
Keyword(s):  
Individual Differences ◽  
Public Sector ◽  
Learning Styles ◽  
Survey Research ◽  
Learning Style ◽  
Mass Communication ◽  
Teaching Style ◽  
Degree Programs ◽  
Public And Private ◽  
Public And Private Sector

Students’ learning is highly subjective owing to their individual differences, environment and background which decide their learning styles. The purpose of this study was to explore learning styles of university students owing to generic role in their learning. There is need to assess whether students of different universities with different backgrounds but with same discipline prefer same or different learning styles. Four general universities were selected; two from each, public sector and privatesector.314 students were involved in the study from selected universities. A questionnaire was developed in the light of literature to explore learning styles of students mainly based on Grasha Reichmann Learning Style Survey (1974). Survey research design was used to collect data. The number of students against every learning style was calculated through statistical distribution. To infer the significance of results, t-test and ANOVA were applied. The findings showed that learning styles were closely linked gender wise. Further, there was no vast difference in learning styles of the students in respect of public and private sector universities. Subject based results are generally aligned but there are variations in couple of subjects like mass communication. The study concludes that students use variety of learning styles in different situations. If teacher used teaching style compatible to preferred students learning style then they would take more interest in the lesson and learn better.

scholarly journals Exploring the Use of Self-Regulation Strategies in Programming with Regard to Learning Styles

2018 ◽  
Vol 2 (2) ◽  
pp. 14-28
Author(s):  
Ãœnal ÇAKIROÄžLU ◽  
Betül ER ◽  
Nursel UÄžUR ◽  
Esra AYDOÄžDU
Keyword(s):  
Learning Styles ◽  
Learning Style ◽  
Time Management ◽  
Self Regulation ◽  
Instructional Designers ◽  
Learning Style Inventory ◽  
Self Regulated Learning ◽  
Regulation Strategies ◽  
Context Of Learning ◽  
Almost All

This study attempts to understand the relationship between learning styles of and self-regulated learning of pre-service computer teachers in a programming course. Students’ strategies for self-regulation with regard to their learning styles were assessed on the basis of qualitative data in terms of programming course. The Turkish version of Felder Soloman learning style inventory was used to identify the students’ learning styles. The results suggest that the characteristics of learning styles are somewhat related to self-regulation strategies. Time management was identified as a leading self-regulation strategy among learning styles, while shortcomings regarding target setting and self-efficacy strategies were prominent with almost all learning styles. Characteristics of other self-regulation strategies do not directly match with expected behaviors of learning styles in the context of learning programming. It is hoped that the study may shed light for instructors and instructional designers to design more appropriate settings for teaching programming taking learning styles in to consideration. 

Sign in / Sign up

Export Citation Format

Share Document