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Editor's Note: This paper distills research on distance learning for students from a variety of cultures, age groups, learning styles, and backgrounds. It recognizes the role of assessment, instructional design, and interactivity to provide learning environments that support success. "Cultural orientations for heterogenous populations may be evidenced by conflicts in values, interpersonal interactions, communication patterns, time orientation and scheduling, rules of activity and engagement, cognitive processes, and processes of problem solving .  .  . Consideration of learner orientations can inform the designer of unique approaches to learning that may better support multiple cultures and facilitate successful completion of a course. The findings apply to learning in the workplace and to academic learning.

Web-based Learning Design: Planning for Diversity

Patricia McGee

Abstract. The increasingly prevalence of distance learning in the work and learning place requires attention to assumptions about Web-based learning environments and how they support a variety of learners. Fluent technological skills do not insure success in online learning. This paper examines issues of culture and learning orientation as they may relate to approaches to design.

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The distinction between workplace training and university learning is beginning to blur (Canter, 2000; Potashnik & Capper, 1998). Increasingly businesses are pressed to offer training at advanced levels in what may soon replace or supplant degrees offered at universities. The demand for just-in-time [1] rather than just-in-case [2] on the job training requires flexible scheduling and self-paced courses that meet the needs of individual learners (Fjortoft, 1995) at reasonable costs (Aldrich, 2001). The trend toward computer-based training (CBT) via multimedia and distance learning in the business world is mirrored in higher education (Pasquinelli, 1998). A study conducted by the National Center for Education Statistics (1999) indicates that almost half of all higher education institutions offer distance-learning courses. E-learning is an increasingly popular solution to training needs in military and corporate workplaces (Aldrich, 2001; NCES, 1999; Salopek, 1998) where learners do not want to take time off from work to complete a degree (Campbell, 2001; Rivera & Kostopolous, 2001) and are better supported by distributed education [3] (Ross & Powell, 1990) as industry and higher education realize the need for providing lifelong learning opportunities (Gartner Group, 2001). As this trends appears to be accelerating and distance learning technology rapidly evolves, the transfer of traditional training and development to a digital medium becomes a challenge in that assumptions about teaching and learning in a traditional classroom do not hold true in a virtual one. Anytime anywhere learning does not come without transformation on the part of the institution, the instructional designer, the instructor, and the student.

The proliferation of distance learning programs might suggest that transfer of content and instruction from a face-to-face to a virtual environment is a seamless process. Those who have designed, taken classes, or taught in both environments realize that this is not the case (Diaz & Cartnel, 1999). Whatever the motivations for offering online learning, student success is the desired outcome. However, attrition rates remain higher than in campus-based courses (Phipps & Merisotis, 1999;Kelman, 1997; Naidu, 1994; Garland, 1993), and tend to be higher for first-time distance learners (Morgan, 2000). In those cases where attrition rates are low, explanations are suspect because there is little evidence that success in a distance-learning course is nothing more than a matter of learner characteristics. Even for the experienced distance learner there is no guarantee that the context, interactions, or conceptualization of content will resemble previous experiences. Most distance learning programs attempt to provide services that support the distance learner. These include embedded study strategies (Morgan, Dingsdag, & Saenger, 1998), prior knowledge assessments (Portier & Wagemans, 1995), print and electronic resources for information retrieval and problem solving (Oliver, 1999), tutorials, and advising services (Wright, 1991). A common pre-course service is a self-assessment tool that either allows the student to measure his or her preparedness for taking a distance-learning course or serves as an anticipatory set [4] by intimating the nature of a distance-learning course. Such self-assessment tools are typically in the form of a 10-15 question survey in which the respondent answers ‘yes’ or ‘no’ to a series of learner behaviors attributes or competencies such as those identified by Rowntree (1995): computer skills, literacy/discussion skills, time management skills, and interactive skills. Some self-assessment tools include a sum score that indicates whether or not the learner will be successful in the course. These types of self-assessment instruments assume that the learner will (a) complete the survey, (b) reflect upon and honestly respond to the queries, and (c) take in consideration the analysis when determining to take a course.

Most distance-learning providers do not use self-assessment data to screen for course registration. Evidently it is assumed that through completing the survey the student will determine whether or not they will be successful and, if they do not meet the criteria for success, it is assumed they will not enroll in a course. Such an approach is grounded in the notion that only those with certain attributes will or should take distance-learning courses, a faulty assumption that is exclusive and discriminatory. More importantly, few contingencies or supports exist that can aid a potential distance learner in acquiring skills or knowledge necessary to succeed in an electronic learning environment. Without these supports novice distance learners may be at risk of failure (Dille & Mezack, 1991). Additionally, there is no evidence that accommodations for a range of abilities, skill levels, or learning styles are part of distance learning course design. It is a one-size fits all approach assuming that distance learners are a homogenous group. Yet the notion of distance learner as “static” rather than dynamic is increasingly questioned and believed to be invalid (Thompson, 1998; Holmberg, 1995).

Purpose

The purpose of this paper is to examine aspects of distance learning that are often overlooked in the design and development of Web-based learning environments as these relate to the learner. The ideas presented here draw from the following set of assumptions. First, there is no evidence that self-assessment tools are correlated with distance learning success. Second, although there may be specific characteristics that are correlated with success in distance learning, all learners should learn in environments that support their needs. Third, in order to learn, one must be actively engaged in the learner process. Fourth, there are key concepts that are relevant to all distance learners. It is the author’s premise that the more prepared and informed a learner is about the distance learning experience the more likely they are to complete a course and be more successful.

The narrowly defined attributes of the successful distance learner suggests that there is a need for mechanisms that will do more than identify the areas in which the potential learner needs to improve or change. As true of preparing to use tools and resources of any learning environment, users should be aware of the context of Web-based learning. In this way, when learners make practical decisions and choices requiring higher order thinking skills, meta-cognition, and self-analysis, they will be best supported for academic success.

A further consideration must be given to the increasingly similar nature of workplace and campus-initiated learning, particularly as distance learning becomes more commonplace in both contexts.

Although learner motivations vary between work-situated training and university learning, learner needs must be considered when designing instruction. The literature reviewed in this section includes several ways of looking at the college-age learner: learning differences, Web design and culture, and the Net generation.

Learner Differences

Models of distance learning indicate that the content to be delivered and the learning outcomes should in part determine the delivery medium. We know that some forms of distance learning are designed with limited peer-instructor or peer-interface interaction. Computer-based training (CBT) typically only provides multimedia and interface interaction. Limited forms of interaction, especially in CBT, may not support all learning needs. Instruction in general and distance learning in particular should start with an understanding of the population to be served (Granger & Benke, 1998). The trend in online learning design has been to develop a static interface that is developed by an instructional designer or a course instructor for a homogenous population. There is a growing body of evidence that indicates a need for course and interface design that addresses individual learner characteristics to provide a more learner-centered experience (Thompson, 1998).

Adaptive learning intends to address the needs of a wide range of learning needs across a variety of content areas (Jones, Greer, Mandicah, du Boulay, & Goodyear, 1992). Much development in adaptive learning has been for intelligent learning systems that are designed to transfer knowledge from the computer to the learner (du Boulay & Goodyear, 1992; McCalla, 1992). Increasingly there is a shift away from knowledge transmission to knowledge constructions (Derry, 1992; Jones, Greer, Mandicah, du Boulay, & Goodyear, 1992), and requiring support for cognitive processes (Woolf, 1992). In this approach, the computer guides the learner toward understanding, soliciting metacognitive reflection about what they know and understand. The system then can more authentically respond to the unique and individual needs of the learner (Laurillard, 1992).

Bruner (1960) believes that culture mediates a learner’s cognitive development as represented by three modes through which knowledge is acquired: enactive, iconic, and symbolic. In the enactive representation, an individual learns by doing and by recalling past events. Iconic representations are internally constructed through visualized and other sensory organizations. Symbolic representations are manifested through languages, both verbal and numerical. The learner’s social and cultural context, according to Bruner (1986, 1990), influences how, when, and what learning becomes knowledge. Cultural influences, however, are not necessarily conscious to the individual. Since an instructional designer’s knowledge of enactive, iconic, and symbolic representations may differ from that of the intended learner, Bruner recommends that all instruction begin with the learner’s experiences and contexts.

In many learning environments, the designer of instruction enters into curriculum development with assumptions and beliefs that may be, consciously or unconsciously, at odds with the diversity of targeted learners. Such incompatibilities may sabotage attempts to adapt learning activities in that cultural predispositions may be overlooked. Although not an issue in a homogenous learning environment, cultural orientations for heterogeneous populations may be evidenced by conflicts in values, interpersonal interactions, communication patterns, time orientation and scheduling, rules of activity and engagement, cognitive processes, and processes of problem solving (Boggs, Watson-Gegeo, & McMillen, 1985; Kochman, 1981; Shade, 1981, 1989). Consideration of learner orientations can inform the designer of unique approaches to learning that may better support multiple cultures and facilitate successful completion of a course (Coggins, 1988).

Learner Orientations

There is much literature that clearly indicates that learning is best facilitated when individual needs of the learner are being met, but, as noted by Carrier and Jonassen (1988), there is a great deal of variance in how differences are described. The definitive common element among the learner characteristic literature is that working at one’s own pace supports a variety of needs. If instructional designers attempt to design computer-based training (CBT) to address specific learning they may be quickly overwhelmed and under-prepared to deal with the extent of differences addressed in learning psychology, as illustrated in Table 1.

Table 1

Learner Characteristics Typologies (Carrier & Jonassen, 1988, p. 205)

Carrier and Jonassen recommend identifying a general set of learner characteristics among a target population and then base the design on the most relevant characteristics for the intended learning objectives. For example, if the objective is learning a sequential procedural skill, presentation of steps in appropriate modes as indicated by cognitive style (visual, auditory, text) may be more relevant that providing a context that allows the learner to construct their own autonomously derived knowledge as indicated more specifically by motivation type. Consideration of learner orientations becomes critical in a Web-based learning environment in which the learner works autonomously and independently of others (Charp, 1994). Whether instructor led or computer-based, the learning environments must adapt to the unique needs of the individual learner.

Web Design and Culture

One common trait that all people share is culture. To illustrate the complexity and nature of creating adaptive learning for a generalized population, this paper focuses on the needs of the second fastest growing ethnic/racial group in the US, the Hispanic/Latino population which grew 40% from 1990 to 2000, increasing from 9.0 to 11.5 percent of the US population (US Census, 2000). This group is more likely than any other group to have limited access to technology outside of work or university resources. A recent report on Americans' access to technology tools finds that Anglos (50.3%) continue to be the most likely to use the Internet, followed by Asian American/Pacific Islanders (49.4%), African-Americans (29.3%), and Hispanics (23.7%) (Becht, Taglang, & Wilhelm,1999). Hence, there is less likelihood that Hispanic/Latinos come to the workplace or university with the technology skills and understandings, which would predict their success in distance learning.

Morgan (1994) recommends that a distance-learning course should provide connections among the learner’s prior experiences that relate to course content. This not only includes conceptual knowledge but also a consideration of the entering cultural beliefs and entry level skills which may shape and influences meaning and ability to connect prior learning and new learning.

The linguistically and culturally diverse population of the Hispanic/Latino culture is often at odds with the typically Westernized approach to university teaching and learning which focuses on knowledge transmission by an expert rather than the culturally preferred active knowledge construction. Therefore a Web-based course, design in the didactic, instructor-driven tradition may handicap some populations’ adaptation to the online learning experience.

The body of knowledge about cultural orientations is well substantiated. However, how cultural elements and characteristics are interpreted and manifested in Web environments is still unclear. Marcus and Gould (2001) analyzed international Web sites using Hofstede’s cross-cultural theory (1997) in an attempt to identify cultural aspects of user-interface. Hofstede identified five cultural dimensions which Marcus and Gould believe can serve as a guide to Web designers. As an initial attempt to consider the influences of Hispanic/Latino, index scores from the three cultures most closely identified with the Hispanic/Latino culture are summarized (see Table 2, Culture Indexes by Country). It is important to keep in mind that Hofstede’s rankings indicate that there is no universal consensus among cultural inclinations. Cultural influences in the US are even more multi-faceted. It is not possible to reflect the influence of American culture in the analysis that follows but it represents an attempt to consider design elements that more accurately reflect cultural traits as derived from cultural heritage.

Table 2

Cultural Indexes by Country

The five cultural dimensions identified by Hofstede and analyzed in Web design by Marcus and Gould (2000) are Power Distance, Collectivist/Individualist, Masculine/Feminine, Uncertainty Avoidance, and Time Orientation. Although the countries depicted in Table 1 vary in their cultural predispositions, we can assume that of the three, Mexico is the country of origin for the greatest population of Hispanic/Latino in the US. Therefore, in the summary below, Marcus and Gould’s Web design recommendations come from Mexico indexes.

Power Distance (PD). “The extent to which less powerful members expect and accept unequal power distribution within a culture” (Marcus & Gould, 2001, p. 5). Cultures with high PD have more centralized power structures, disparate salary rewards, acceptance of inequities, and centralized authority. Low PD cultures have less hierarchical difference in authority, more equitable salaries, and equity is desirable. Interface implications for a high PD country such as Mexico include: structured and expert information presentation, strong use of cultural values and corresponding symbols, emphasis on leader and expert rather than user, focus on security and restricted access, and information access determined by social role.

Collectivism vs. Individualism. This index refers to the degree to which an individual relates to society or values their own achievement and status In general members of collectivist cultures are more intrinsically motivated. (see Table 3)

Table 3

Collectivist and Individualistic Indexes

Implications for Web design for collectivist societies include: minimal emphasis on individual achievement, success manifested in terms of socio-political ideals, nationalistic slogans and gross generalizations, authority and experience respected and valued, relationships are determinant of moral actions, and personal information is kept private.

Masculinity vs. Femininity (MAS). Hofstede generalizes about gender roles in societies, acknowledging that roles may vary in cultures that have similar MAS indicators. In general, feminine cultures tend to allow cross-gender behaviors while masculine cultures are more likely to maintain strictly defined gender roles. Traditional masculine cultures value wealth, challenge, promotion, and recognition of achievements. Feminine cultures value good relations with co-workers, pleasant and congenial home and workplace, and job security. Marcus and Gould suggest the following interface implications for high feminine cultures: interchangeable roles, cooperation and collaboration, and aesthetic expression of values.

Uncertainty Avoidance (UA). “Cultures vary in their avoidance of uncertainty, creating different rituals and having different values regarding formality, punctuality, legal-religious requirements, and tolerance for ambiguity” (Marcus & Gould, 2000, p. 20). High UA cultures: tend to have higher rates of suicide, accidents, additive disorders and prisoners; are more tactical than strategic in business, expecting long-term commitments from employees; have a more expressive populace that have expectations of structure and predictable rules and norms; see teachers are seen as experts and authorities to be respected; and, see what is out of the norm as deviant and unacceptable. Cultures with low UA: have higher intakes of caffeine and more psychosis; business cultures are more informal and strategic; appear easy-going although the general population is not overly emotive; accept that teachers may not know all the answers and learning is more open-ended; and see out of the normal phenomenon as a curiosity. Marcus and Gould suggest that Web design for high UA should consist of: simple, straight forward design with minimal choices and concise information, intimation of consequences of actions before user makes decisions, clear and unambiguous navigation, “mental models and help systems that help users from becoming lost” (p. 20), and consistent and repetitive visual cues.

Long versus Short-Term Time Orientation (LTO). Hofstede found that countries with long-term Time Orientation believe that stability requires hierarchical relations, view the family as the model for all organizations with elders and males having most authority, believe that virtuosity does not result in equitable treatment, and see that virtuosity means working hard to improve oneself, at least in the workplace. Short-term Time Orientation cultures: emphasize the individual and equitable relationships, personal fulfillment through self-actualization. Although there is not data available for Mexico for this index, there is evidence that the orientation is long-term (Hall, 1989).

Although Marcus and Gould’s analysis is limited in its scope, it does reveals inherently different ways of looking at the world as reflected in culturally situated Web sites. Such perspectives may operate at subconscious levels in the instructional designers as they create learning experiences for Web-based learning environments. Consideration of these unapparent preferences may reduce cognitive load and stress for the learner, thereby contributing to a positive course outcome.

Cultural Learning Style

Another area of research that can inform the design of Web-based learning environments is that of learning styles. Consideration of learning preferences speaks to the issue of adapting instruction to the learner, a commonplace event in traditional instruction. Adaptive learning in Web-based environments is more challenging because the mediating technology controls and limits the type and amount of information known about a learner and the speed with which interaction occurs. Also, integrating learner choice and path [5] requires more development time and energy. However, an adaptive approach may result in lower attrition rates and higher levels of success. Although the concept of learning preference is used to define a wide range of typologies and theories, most theories fall into one of the following groups: learning preference, learning strategy, learning style, cognitive strategy, or cognitive style (McLoughlin, 1999).

It is important to note that within a culture, individuals have different styles so using one approach, however culturally relevant it may be, is not necessarily appropriate or effective for an entire group. One solution to the challenge of diversity is to provide multiple paths that learners may take, each of which is designed to support a specific learning preference. The content should remain consistent across the site but the interface through which the learner interacts can be designed to complement learning preference.

The research on learning preference by culture in Web-based learning environments is limited but does reflect some of the tenets suggested by Hofstede and Marcus and Gould. Sanchez (1996) examined US adult Hispanic learning styles and subsequent implications for Web-based learning. She examined motivation maintenance level, task engagement level, and cognitive processing level of 240 adult learners. She found that Hispanic learners preferred evaluative feedback, active participation, collaboration, and concrete and practical material. Learners tended: to retain facts well, use elaborative processing, have a positive attitude about learning, exhibit self-discipline and diligence, attend closely to tasks at hand, use “imagery, verbal elaboration, comprehension monitoring and reasoning” (p.58), identify the main idea, apply effective test-taking strategies and reflect on accuracy of information. The Hispanic learners preferred active experimentation and tended to use judgment (thinking of feeling) when interacting with others. Herz and Merz (1998) found that face-to-face simulation supports Kolb’s concept of active experimentation, a learning preference identified by Sanchez and Gunawardena (1998). Sanchez and Gunawardena (1998) make the following recommendations for distance learning for Hispanic adults, cautioning that they are not intended to perpetuate stereotypes or disallow for factors that might vary cultural traits but rather as a strategy to consider different options in course design:

• Provide a variety of instructional strategies that can be supported through a variety of media, allowing students to chose among activities that have one objective.
• Provide consistent, clear, and frequent feedback in a variety of formats.
• Provide opportunities for collaboration.
• Encourage and provide opportunities for reflection.
• Design curriculum that engages learners in making connections among theory and practice using higher order thinking.

The nature of distance learning as it is now conceptualized may not be supportive of collectivist cultures. Anakwe, Kessler, and Christensen (1999) found motives and communication patterns of learners from individualist cultures were supported in a distance learning environment more so than learners from a collectivist culture. The key areas that were not conducive to the collectivist learning were the very characteristics of distance learning that are touted as the greatest benefits: learner’s self-reliance and independence. The authors believe that this may reflect a cultural predisposition toward technology. When used as a medium to work alone and compete against others it may appeal to individualistic learners but when technology is used to communicate and collaborate it may appeal more to collectivist learners.

A generalized cultural learning orientation in a Web-based learning environment can help the learner draw upon what they know and are familiar with as they are assisted in transferring their skills and knowledge acquired in traditional learning environments to online learning. Some types of CBT may be better suited to cultural orientations than other. For example, a simulation-game can support much of the Hispanic/Latino style preferences in that it can be highly interactive, can engage the learner at higher levels of reasoning, and can adapt to the learner’s entry level of skill.

Net Generation

Another consideration for adaptive learning is the age of the target population. There is a growing body of evidence that suggests that design needs and preferences may vary among age groups. The Net generation [6] has grown up with a variety of electronic media that are unique and which research suggests has influenced their perspectives and preferences (Tapscott, 1999). This generation::

• Has grown up with digital entertainment
• Has access to digital resources outside of schools
• Accepts diversity
• Is curious
• Is assertive and self-reliant
• Is strongly independent
• Tends to be emotionally & intellectually open
• Is inclusive
• Is freely expressive
• Tends to be innovative
• Is investigative

Most of the Net Generation has had access to computers and the Internet at home (Grunwald, 2000). This is not true of many minority groups, including the Hispanic/Latino population (NTIA, 1999). It is not clear that one population has a advantage over another when confronted with digital learning environments, however, it can be safely assumed that familiarity with technology reduces the cognitive load when the learner engages in CBT training or learning.

Educators and instructional designers should take heed of these characteristics that may not be reflected in traditional development processes. When designing instruction for this generation within a technology-based environment the following factors must be considered: gender differences in the use and application of technology, the preponderance of digital play as opposed to the work ethic of older generations, the influence of global information and relationships, and the decreased reliance on a teacher for guided learning. Clearly, the attributes of this generation suggest a need for self-directed learning within an environment that allows exploration and problem solving.

Research indicates that simulation and games can support higher order thinking and problem solving (Hamel & Bishop, unpublished). Although here is little current research that indicates members of the Net generation have better cognitive skills that their counterparts from other generations, their tendency toward autonomy and independence suggests that these learners may be better problem solvers who can analyze, synthesize, and evaluate effectively (Grunwald, 2000;Tapscott, 1999; McKenzie, 1998; Bloom, 1956).

As distance learning appears to be on the brink of becoming a preferred mode of learning in the workplace, the generation that will be most effected is the one now entering the workforce or completing an undergraduate education. The autonomous and independent nature of Web-based learning necessitates problem solving and higher order thinking for the learner who primarily interacts with a computer rather than receiving individual feedback from an instructor. Simulation-games are by definition dependent upon higher order thinking and require the player to make independent judgments and thus provide a remarkably well suited environment for a novice distance learner to test the waters of Web-based learning.

Conclusions and Recommendations

Globalization and the increasing prevalence of the Internet in homes, workplace, and public institutions require that instructional designers and educators look beyond generalized approaches to learning and focus on multiple paths for acquiring knowledge. Although many distance learning programs currently survey potential students about their probably success, there are few systems that provide training to insure success. Shifts from broadcasting to narrow-casting and from large group learning to individualized learning indicate that in order to meet the growing demands of just-in-time and just-in-need learning, Web-based learning must be flexible and adaptable to the learner, not just the content. The design and development of Web-based learning environments should include:

Analysis of target population(s) preferences in Web design, interaction as well as entry technical and communication level skills. This is essential to the instructional designer who may enter into the design process with an unconscious predilection for certain interface designs and pedagogical approaches that limit breadth of enactive, iconic, and symbolic representations (Bruner, 1960).

Review of content by subject matter and culture experts for design integrity and cultural relevancy. As the work and learning place is gradually subsumed by what we now call the Net generation, considerations described here may become superfluous. Until then, it is the responsibility of trainers, educators, and instructional designers to make conscious and informed decisions about how the unique needs of a learner can be best supported in Web-based learning environments.

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End Notes

[1] Acquiring skills or knowledge as it is required.

[2] Learning or training that is not necessarily required but may be used in the future.

[3] On demand episodic learning in which the learner determines what they need to learn and who can offer the most appropriate education or training (Campbell, 2001).

[4] Relates prior experiences to new learning.

[5] Adaptive learning recommends that learners are given choices or directed to the most appropriate level of learning. One course might be designed to accommodate a learner who has no experience with content or some experience. Entry knowledge would determine the path the learner follows.

[6] Anyone born after 1979 who has grown up with access to and experience with electronic toys, communication tools, and Internet resources (Tapscott, 1999; McKenzie, 1998).

About the Author:

Patricia McGee, Ph.D. is assistant professor in the Department of Interdisciplinary Studies and Curriculum and Instruction at the University of Texas at San Antonio. She has studied and taught about a variety of topics and issues related to technology and learning.

Dr. McGee has been involved with distance learning programs since 1986 when she taught for and then managed staff development programming for TI-IN Network. Her varied research interests include inservice teacher learning with and about technology; preservice understanding of technology; and Web-based learning and culture. Currently she is project director for a USDOE "Preparing Tomorrow’s Teachers to Use Technology" grant. Dr McGee can be reached at pmcgee@utsa.edu or 210 458-7288.