Creating an Instructional Design Supported by Knowledge ...



The Effectiveness of Knowledge Technologies in Accommodating Learning Styles

Bettie C. Hall

and

Joyce Pittman

Education and Knowledge Technologies Program

Department of Curriculum and Instruction

College of Education, Criminal Justice, and Human Services

University of Cincinnati

Cincinnati, OH 45221-0002

hallbe@email.uc.edu

Abstract: This paper presents the results of an investigation into the effectiveness of selected knowledge technologies in addressing various learning styles. The results of research studies over the past several years have offered empirical evidence of the effectiveness of knowledge technologies in accommodating a variety of learning disabilities (Roberts, 2004); however, few have focused specifically on learning styles. This investigation, which includes a survey of academic and sponsored research, provides evidence that selected knowledge technologies are effective in engaging students with different learning styles. Teachers, corporate trainers, and instructional designers can benefit by focusing on the use of only the most appropriate technology to address their particular student population's learning styles, which can result in considerable savings in cost and effort.

Introduction

This review of literature regards the specific issue of creating instructional design supported by knowledge technologies that accommodates various learning styles. The issue can be posed as the question: What knowledge technologies are proven effective in addressing the various learning styles of students? The purpose of the review is to determine from the literature the results of studies performed in recent years on this specific topic to determine what knowledge technologies have been used, what learning styles were examined, and what parameters were measured to indicate effectiveness. The findings from this review are summarized in a comparison table suitable for academicians and researchers, and for practicing professionals.

We are here concerned with the ability of instructional designers, educators, policy makers, and other educational stakeholders to make reasonable decisions about what technologies address which learning styles effectively. In this, we echo Rothenberger and Long (2004) in focusing on “how to optimize the capabilities of learners using these [emerging] technologies” (page 1).

The literature reviewed includes empirical research over the past 10 years (although some earlier works were included if they were deemed particularly relevant) from books, surveys, critical reviews, summaries, proceedings, and publications in refereed journals. Some information has also been drawn, although sparingly, from professional organization publications, as well as some online journals.

Assumptions

This review does not encompass the science of instructional design. While instructional design generally refers only to the planning and implementation of training and performance support, we recognize that it has broad impact on subsequent course development, delivery, management, and assessment. Therefore, as a research area, instructional design can draw from such diverse physical and social sciences as information systems, education, business management, and graphic design. It can also refer to the process, discipline, science, reality, system, technology, models, and development of instruction, as described by Berger & Kam (1996) and Ryder (20050, and would take us beyond the scope of this review. We limit our focus here to the knowledge technologies that may be used in instructional designs, or to support existing designs, but we recognize our audience still may include learners, instructors, software developers, information systems support personnel, and graphic artists, among others. We are also mindful that the use of knowledge technologies, like instructional design, is impacted by the constraints and capabilities of the technologies used to deliver, mediate, and/or manage the learning, as well as by those of the human, budgetary, scheduling and information resources available. Auerback (1999) described a number of methods and compared them to a list of training variables. She also defined common constraints as purpose, location, development and equipment costs, and best group size.

The terms knowledge technologies, adult learning styles, and effectiveness require operational definitions.

The Knowledge Technologies

Knowledge technologies can include concepts as diverse as artificial intelligence and document management, machine learning, and knowledge representation, so again, we focus on a narrow set of widely available technologies, such as hypermedia, defined by Rothenberger & Long (2004) as "the storage and retrieval of information in a nonsequential manner" (page 3), and have included mostly emergent technologies or digital media that have been used in distance learning and computer-aided mediation over the past 10 years. For simplicity, we have grouped technologies together in a taxonomy of “working use,” which may certainly be disputed and improved upon, but which serves our purposes here for understanding their impact on learning styles. We recognize here that we are ignoring a significant set of data supporting the print technologies, but including these would be beyond the scope of this study. The technologies we describe fall into three broad categories: multimedia, hypermedia, and the internet.

Hypermedia is an umbrella term for digital, linear or nonlinear, static or animated, linked information on the World Wide Web that can include text, audio, video, and graphics. Hypermedia is used here as the manifested format of such concepts as content mapping, topic mapping, semantic networks, intelligent agents, and expert locators (for a concise glossary of these terms, see ).

Therefore, we again zoom in on specific elements of hypermedia to provide more specificity.

• Asynchronous text, such as Email

• Synchronous text, such as instant messaging

• Groupware, such as Lotus Notes. These include multi-user dimension, object-oriented (MOOs).

• Search engines, such as Google

Independent publishing is another term that has come to include such varied technologies as blogs, personal web pages, online books, podcasting, RSS feeds, content management systems, peer-to-peer (P2P) file distribution, wikis, and wi-fi. We excluded ontologies such as WorldNet and OpenCyc as so recent as to not be widely known.

Multimedia refers to CD-ROM, computer- or web-based training (CBT/WBT), presentation software such as Powerpoint, and video games. It includes three dimensional vector or raster graphics tools, such as CAD/CAM used for virtual reality and simulations, and two dimensional vector or raster graphics tools, such as Visio or Flash.

Videoconferencing, including online classrooms.

We can use these technologies in a variety of ways to provide instruction and data visualization to learners, such as simulation, modeling, and demonstration, and use them in such various modes as streaming media or overheads, and deliver them using slide projectors or televisions, personal digital assistants (PDAs such as wireless telephones with video capabilities), over cable and wired or wireless networks. We can use them to provide heuristic software agents that monitor the user’s keyboard entries or mouse clicks and provide relevant information, and delivery various types of training, including experiential, web-based, and distance learning.

The Learning Styles

What is a learning style? The literature reveals a variety of answers. Grasha (1996) defines it as “personal qualities” (page 41). Rothenberger & Long (2004) define learning styles as “unique patterns of responses that learners develop with regard to various learning environments” (page 1). Felder (1996) defines learning styles as “characteristic strengths and preferences in the ways [learners] take in and process information” (page 18). Despite the variation on these themes, we agree with Tight (2002) that “learning, like breathing, is something everyone does all of the time…even if they do not realize that they are doing it” (page 23), and whether one takes the behavioralist, cognitivist, or constructivist points of view, there has been longstanding agreement that learners anatomically tend to be visual, auditory, or sensory/kinesthetic in their approach to that learning.

A number of schemas for discussing various adult learning styles were determined from a review of the literature, as follows:

1. Index of Learning Styles (ILS) (Felder & Silverman, 1996)

/This assessment classifies learning preferences as follows

1) Active/reflective

2) Sensing/intuitive

3) Visual/verbal

4) Sequential/global

This was developed by Fe3lder, R.M. and Soloman, B.A. at North Carolina State University, and is available at no cost to researchers and educators. Folder is with the Dept. of Chemical Engineering at NCSU. His studies have been in engineering education (Felder, 1996). Felder concluded that a learning styles model or inventory was “almost irrelevant” (Rothenbergh &U Long, 2004, page 1), and that “all of the models lead to more or less the same instructional approach.”

2. GRSLSS

The Grasha-Riechmann Student Learning Style Scales (GRSLSS)

The GRSLSS (Riechmann and Grasha, 1974) describes six polemic styles:

1) Independent – prefers self-paced instruction, and works alone

2) Dependent – views instructor and peers as sources of structure and guidance, and prefers authority to provide instructions

3) Competitive – wants to outperform their peers and recognition for accomplishments

4) Collaborative – prefers sharing and cooperation with instructor and peers, enjoys group work

5) Avoidant – prefers to not be involved in class activities, and is not interested in the course content

6) Participant – likes class activities and discussion, and is eager to learn course content.

The GRSLSS was designed for college-level distance education settings. It is a relevant scale since it addresses the social dynamic that serves as the main difference between the distance and traditional groups (e.g., relative absence of social interaction between instructor/student and student/student. Among its claims are that it helps faculty design courses and to develop sensitivity to students and learners, and it promotes a broad understanding of learning styles, which can prevent stereotyping and promote growth and development in those areas the student or learner is not the strongest.

3. Kolb Learning Styles Inventory

Kolb (1999) described four learning processes that comprise a learning cycle as concrete experience, reflective observation, active experimentation, and abstract conceptualization. From these, a learning styles inventory, a questionnaire, can be used to classify learners into four types: Type 1, concrete/reflective, Type 2, abstract/reflective, Type 3, abstract/active, and Type 4, concrete active.

4. Myers-Briggs Type Indicator

Myers-Briggs TI (MBTI)

1) Extraverts

2) Sensors

3) Thinkers

4) Judgers

These 4 can be combined to form 16 learning styles. It is based on Carl Jung’s theory of Psychological Type.

5. Hermann Brain Dominance Instrument

The Hermann Brain Dominance Instrument (HBDI)

1) Quadrant A – left brain, cerebral;

2) Quadrant B – left brain, limbic; sequential

3) Quadrant C – right brain, limbic; emotional, kiinesthetic

4) Quadrant D – right brain, cerebral; visual, holistic, innovative

Hoerner (1998) uses Kalsbeek’s (1989) definition of learning styles as “a person’s preferred approach of information processing, idea formation, and decision making. He reminds us that when “portions of the instruction become mediated, an entirely new set of problems related to instructional efficacy is introduced. It is no longer just a question of learning styles, but also the sophistication of the instructional design used to create the mediated instruction, the effectiveness of the mechanism used to deliver the instruction, and wehterh or not a student has a preference for, or an interst in, the particular instructional technology being used.” (page 5).

Others also agree that using a computer can have beneficial effects on the learns. As Kozma (1994) stgates, “learners…benefited from the use of computers because the capaqbiolities of this medium were employed to provide representations and perform or model operations that were salient to the task and that the learners had difficulty providing for themselves.” (page 13)

In addition to these, the Illinois Online Network (2003) describes four "common" learning styles:

1) Visual/Verbal – prefer reading information, and prefer tools such as Blackboard, and Powerpoint

2) Visual/Nonverbal – prefer using graphics or diagrams to represent information, and learn best through graphical tools such as images, charts, tables, and graphs.

3) Auditory/Verbal – prefer to listen to information, and learn best through group participation, collaborative activities, streaming audio, computer conferencing, and online chat

4) Tactile/Kinesthetic – prefer physical, hands-on experience, and learn best through three-dimensional simulations, and online presentations and discussions of projects, field work, and activities.

The Measures of Effectiveness

This study examined a mixture of qualitative and quantitative elements, and sought empirical studies, surveys, and reviews using trustworthy methodologies and that validated their findings using objective criteria. The most relevant studies included comparisons, surveys, and factor analyses that included standard, statistical validation of the data obtained or derived.

Discussion

A review of the literature provided mixed results. Like other recent researchers (see for example Beyth-Marom, Saporta, and Caspi, 2005), the authors found an abundance of empirical studies comparing traditional classroom and online instructional delivery, but relatively little that focus on specific instructional technologies and their effectiveness on learning styles. Of the studies that do provide that focus, there is a general lack of consensus regarding what learning style model and which knowledge technologies used in their studies. This lack of agreement obfusticates what seemed like a simple question of which tools can be effectively used with which styles to achieve desired outcomes that can be objectively measured, tested, and validated.

As an exampole of this complexity, we review here a few of these studies. Benson, Haney, Ore, Persell, Schulte, Steele, and and Winfield (2002) decry the lack of systematic evidence of how computer-mediated instruction affects student learning in sociology (page 142). However, they agree that “digital technologies may have profound effects on the dprocesses of teaching and learning.” (page 142), and describe those as follows: computer mediated interaction, may break down social barriers, facilitate substantive discussion, promote peer review of writing, and can be used to permit students with various learning styles to process course information visually or audibly. Previous studies have established that student performance in learning material using instructional technologies is affected by their preferred learning styles (see Benson, et al. 2002). They quote studies that provide evidence that visual learners are positively affected by computer-assisted technologies, and that students who are abstract, independent thinkers also perform well in classes that use such technologies. (page 148).

Beacham, Elliott, Alty, & Al-Sharrah (2002) studied whether different media combinations affected learner’s understanding of computer-based learning materials, and whether their learning styles affecting that understanding for various media combinations. Using three categories of combinations, text and graphics, text only, and sound and graphics, they concluded that understanding was enhanced with the sound and graphics (diagrams) combination regardless of the learner’s preferred learning style. Their dual coding theoretical perspective was thus supported by these findings, but perhaps the most intriguing idea is their tentative conclusion is that the media combination is just as important as learning style. In their words “if the combination of media is inapproapriate, it does not matter which learning style a student adopts” (page 7).

Auerbach (1999) described matching group needs to training methods, as opposed to individual needs, by comparing a list of training variables to a list of available training methods. She reminds of pragmatic constraints on intentions, such as purpose, location, development cost, equipment cost, and best group size for using the knowledge technologies. She also describes the methods widely available to educators, such as print, multimedia, formal presentations, information discussion groups, classroom training, experiential learning, CBT, WBT, and distance learning.

Mueller (2001) compared learning styles with Gardner’s concept of multiple intelligences. While Gardner himself cautions against the use of the intelligences as “learning styles,” Mueller offers instructional designs that involve the following: 1) assessing the learning styles through educated guesses, 2) choosing activities that appeal to the majority of the learners or structuring activities so that different appeals are linked; and 3) Letting the group decide.

Hoerner, Jr. (1998) investigated the importance of matching an instructional technology to learner’s preferred styles using the MBTI. His investigation examined the effecxtivness of three instructional technologies: illustrated text, interactive CD-ROM, and non-interactive, linear videotape. His empirical study concluded that, while the choice of instructional materials appropriate to students’ learning styles is significant and that there is clear evidence tht CD-ROMs and videotapes both accommodate introvert and extrovert, sensing and intuitive (IS and EN) learning styles, the evidence did not show a clear indication of which of the latest instructional methodologies—CD-ROM, and videotape—was more effective with any of the learning styles (page 16). Knowledge of how learning styles can impact how they learn from mediated methodologies is critical as we continue to invest in knowledge technologies. In Hoerner’s view, people’s learning styles won’t change in the future, but the technologies we use to address those styles certainly will (page 17).

The results of one of the most recent studies (Beyth-Marom, et al. 2005) do support the need to provide individualized teaching and learning opportunities to students because of their diverse learning styles, as some prefer autonomy and control over synchronous interaction, and others prefer just the opposite (page 259). Their study of a a turotiral delivered synchronously via satellite, and asynchronously via video-cassette provided evidence for their conclusion that the needs of both can be met by synchronously providing instruction, then posting a recording of that synchronous event on a swb site that accommodates learners who asynchronous learning, and tying the two groups together through online discussion groups.

Instructional Design Strategies Incorporating Knowledge Technologies

In this discussion, we distinguish between communication technologies and knowledge technologies used in instructional design. Some designs separate these in to synchronous (happening in the same time frame) and asynchronous, e.g., email, in which events occur in sequential time frames). The instructional design strategies that can incorporate the knowledge technologies that include learning contracts, discussions, lecture, self-directed learning, mentoring, small group work, collaborative projects, case studies, forums, focus groups, listservs, form posts, message boards, and chats.

Results

The results provide guidance to instructional designers in creating effective online courses to meet the needs of students with various learning styles, to determine whether the criteria used to determine online course effectiveness are adequate or whether other criteria should be developed.

Hoerner’s (1998) hypothesis asks, Do students with different learning styles have any preference for learning technical information delivered by one of the technologies studied? His study entailed two additional hypotheses, one based on gender, and the other based on there being a “significant relationship” between MBTI quadrants and sensory preferences, classroom preferences, and choice of instructional methodology (page 11). His results show IS preferred CD-ROM, IN liked both CD-ROM and text, EN liked both hands-on and CD-ROM, and ES preferred videotape. The introverted intuitives scored the highest in preferring an instructional condition. CD-ROM provided a variety of learning styles with the information in an appealing format. The Introverted Sensors liked CD-ROM and hands-on experiences. Extroverted sensors preferred videotapes, while Extroverted Intuitives preferred hands-on experience, CDROM, self-instruction and small group work. There was a positive relationships between MBTI quadrant learning styles and instructional methodology preferences.

Dede (2005) describes a neomillennial learning style that includes fluency in multiple media, communal learning, and learning based on students being able to find, filter, and synthesize multiple sources of information, rather than relying on a single source of knowledge (page 1). The learner’s ability to communicate with others across physical and cultural boundaries using avatars and virtual artifacts can lead to “mediated immersion” (page 3), which transcends previous types of asynchronous communication capabilities. For example, the “time sink” experienced by participants in massively-mutliplayer online role-playing games (MMORPGs) is a phenomenon that, although it may have impact on various learning styles, is not treated in this review.

|Knowledge Technology |Examples of Digital or Software Tool |Examples of Hardware and Communication |Learning Style |

| | |Media | |

|Groupware |Lotus Notes, Chat rooms, Message |PC, PDA, Laptop; |Visual/Verbal |

| |boards, Listservs |Internet, Local Area Network, | |

| | |Client-Server | |

|Internet |Distance learning, virtual |PC, PDA, Laptop, Wireless, Cable, |Visual/Verbal |

| |classrooms, database-driven web |Telecommunications; |Visual, Nonverbal |

| |sites, forms |Internet, World Wide Web, Wide Area | |

| | |Network | |

|Hypermedia |Blogs, Wikis, Vlogs, Content maps, |PC, PDA, Laptop, Wireless, Cable, |Visual/Verbal |

| |Smart agents, Advance organizers, |Telecommunications, Internet, World |Visual/Nonverbal |

| |P2P, RSS feeds, Podcasts |Wide Web, Wide Area Network |Auditory/Verbal |

|Multimedia |Interactive CD-ROM, |Diskette, CD-ROM, Video or audio tapes;|Visual/Verbal |

| |Videoconferencing, Streaming media |Video recording, Audio recording, |Visual/Nonverbal |

| |(video and/or audio, Desktop |Streaming media (live or archived) |Auditory/Verbal |

| |publishing, text | |Tactile/Kinesthetic |

Table 1. Knowledge technologies associated with various learning styles

Recommendations for Additional Research

This study reviewed theoretical and other literature to determine what criteria has been used to determine the online instructional strategies that are the most effective in accommodating different learning styles. We then used a qualitative scoring mechanism in a Likert-like table to determine whether that criteria is adequate, or whether additional criteria should be established to measure effectiveness.

Through a search of library resources, databases, and online resources, a set of relevant articles, web sites, and books were identified and critically examined to determine whether it was relevant, unbiased and valid. The literature included theory-based, qualitative and quantitative research material. The scope of the review included refereed journals, published books, government documents, and other scholarly publications in the fields of education and training, particularly in curriculum and instruction, but also included computer science, engineering, psychology, and sociology, among others. To make sure the literature was wide enough to ensure the majority of relevant material, yet narrow enough to exclude irrelevant material, the citation index, ERIC database, and JSTOR was used, and prominent researchers and dominant theories were identified. The information derived from selected literature was synthesized and reported in this summary of what is, and what is not, known about evaluating the effectiveness of online instructional strategies in meeting the needs of students with various learning styles.

The focus of this review has been limited to adults, defined here as students and people over 18 years of age. Adults can demonstrate a higher need than children for critical thinking and reflection, which might thus affecting the correlation between effective learning and the technology used. Whether these findings might hold true for children is an area that would need additional investigation before applying the results to that population.

Areas of controversy have been identified as (Thornburg, 2005) time, cost versus value, difficulty measuring results, quality of learning content, perceived difficulties using the system, the infrastructure, and internal resistance.

Further research is needed to answer questions around methodologies used, particularly in validating whether the use of emergent knowledge technologies enhance learning by addressing specific learning styles in an objective, quantifiable manner such as through standardized test scores when compared to learners who do not use those emergent knowledge technologies.

Despite the lack of objective research on this specific topic, sufficient evidence exists that people do vary in their preferred manner of acquiring, retaining, and using information, and teaching styles do not always match these preferences. As Felder (1996) states, “If professors teach exclusively in a manner that favors their students’ less preferred learning style modes, the students’ discomfort level may be great enough to interfere with their learning. On the other hand, if professors teach exclusively to their students’ preferred modes, the students may not develop the mental dexterity they need to reach their potential for achievement in school and as professionals.” (page 18).

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