Elearning Report

8/3/2019 Elearning Report

1/87

The Seven E-learning

Barriers Facing Employees

By Penina Mungania

A Research Report

Funded by the Masie Center


2/87


3/87

3

Executive Summary

What distinguished providers with the most successful outcomes from others was the

use they made of the survey results, feedback from learners or the record of

complaints.

(Hawksley & Owen, 2002, p. 42)

As investment in human, time, and financial resources for e-learning continues to

rise, so should the interest in its effectiveness, quality, barriers faced, and best

practices. The purpose of this empirical study was to determine barriers experienced by

employee e-learners. Further, this study explored the nature of relationships among (1)

e-learning barriers; (2) employee demographics (age, gender, ethnicity, marital status,

organization type, and education); and (3) background factors such as experience with

e-learning and computers, job position, computer ownership, computer training, and e-

learning self-efficacy.

An anonymous validated Web-based survey was used to collect data, showing

the viability of Web-based surveys as a tool for promoting e-learning and organizationalresearch. The Barriers in E-learning and Self-Efficacy (BELSE) survey was used to

collect self-reported data, administered to a convenient sample of employee volunteers.

The instrument was comprised of (1) demographic questions; (2) the Barriers in E-

learning (BEL) scale, developed for the purpose of determining e-learning barriers; and

(3) E-learning Self-Efficacy (ELSE) scale, to measure Internet and computer self-

efficacy.

This exploratory study used quantitative methods for data collection and analysis

and some open-ended questions. Data were analyzed through descriptive and

inferential statistics. The participants were employees in seven organizations in the

United States and abroad. These organizations represent manufacturing, oil exploration

& manufacturing, IT consulting, wholesale distribution, public school district, and a

military division. A total of 875 employees who had taken e-learning courses delivered


4/87

4

100 percent online by their employers for the past two years participated voluntarily.

Their ability to participate in e-learning and in this study from remote locations, from the

Pacific Ocean to the Algerian desert, clearly demonstrates the ubiquity of e-learning.

The demographic makeup and background characteristics of the respondentswere explored to better understand the e-learning population. The figure below

highlights the employees characteristics.

Who are the E-learners?

Middle-aged audience (80% below 45)

Predominantly male (62%)

Married (69%)

European descent (49%)

Support staff (44%)

Hold a bachelors degree (37%)

Study in the office (56%)

Own a computer with Internet connectivity (88%)

Have been enrolled in less than ten online courses (80%)

Have participated in e-learning for the last three years (76%)

Prior e-learning experiences in another organization (34%)

Intermediate and advanced computer users (96%)

Have received computer software training (58%)

Overall positive e-learning experiences(87%)

Figure 1. Who are the E-learners?


5/87


6/87

6

The good news emerging from this study are the positive experiences and the

relatively few barriers reported. Barriers were rated relatively weak on all categories with

means ranging from 1.29 to 3.00 on a 5-point scale. But before and after every hill is a

valley! The hype accompanying e-learning and the assumption that it is smooth sailingfor e-learners is erroneous because there are significant modifications that need to be

made, ranging from content revisions to policy decisions.

Organizational differences and similarities

While similarities in the nature of barriers faced in the seven organizations exist,

there are statistically significant differences among these organizations. The type of

organization accounted for 5.5 percent of the variance in e-learning barriers. Employees

of the IT consulting company reported the most barriers on six of the seven categories

of barriers. The Oil exploration and manufacturing company employees perceived the

most situational barriers. While there are no significant differences between the two

government agencies and the two manufacturing companies, but significant differences

do exist among the three organizations in the service sector.

Predictors of e-learning barriers

Four key factors emerged as significant predictors of e-learning barriers, namely:(1) organization, (2) self-efficacy, (3) computer competence, and (4) computer training.

Computer competence and self-efficacy were negatively associated with barriers. Thus

if one reported high self-efficacy, this was associated with fewer the barriers. Those who

rated themselves as having no computer training and with low levels of computer skills

were more likely to say they encountered barriers.

Age, gender, ethnicity, marital status, level of education, prior experiences with

computers and e-learning, computer ownership, location of study, and job position are

not statistically significant predictors of barriers. The nature of these relationships is

summed up in the graphic below. The solid arrows indicate a direct relationship

between the variables while the dotted arrows show that these factors may affect ones

perception of barriers although the relationship is not statistically significant or direct.


7/87

7

The 4 Significant Predictorsof E-learning Barriers

(1)Organization type

(2)Self-efficacy

(3)Computer training

(4)Computer competence

The 7 E-learning Barriers

(1)Personal barriers

(2)Learning style barriers

(3)Instructional barriers

(4)Organizational barriers

(5)Situational barriers

(6)Content suitability barriers

(7)Technological barriers

Other Influential Variables

(1)Age

(2)Gender

(3)Ethnicity

(4)Marital Status

(5)Level of Education

(6)Job Position

(7)Computer Ownership

(8)Location of Study

(9)Prior experiences with e-learning

Figure 2. E-learning Barriers and Predictor Variables


8/87

8

Organizational Implications

Barrier reduction strategies have to be planned, continuous, and systemic

Continuous systemic changes must happen to improve the state of e-learning.Since organizations, individuals, and environments differ, so do the approaches to

reducing e-learning barriers. A variety of measures are essential encompassing,

personal, situational, technological, organizational, instructional, and content strategies.

Above all policy and planning for e-learning must accompany any programmatic

changes in new and old programs.

Computer training is fundamental

Computer competency and training are significant predictors of barriers.

Strategies such as computer software training, modeling, and demonstrations are

essential. The level of education ranged from high school level to doctorates. However,

even with highly educated and experienced workers, computer and Internet skills fall

short. A lack of skills must be addressed through training.

Time for study and training

Multiple responsibilities lead to limited time for study and interruptions during

study. These situational barriers were the top three barriers. Training time has

traditionally been reserved and guarded, but the asynchronous nature of e-learning has

brought its own challenges. Unless employers and employees prioritize study time,

online learning efforts will continue to suffer.

Three Pillars of Successful E-learning

In sum, successful e-learning demands social, cognitive, and behavioral skills.

The three pillars that determine the success or failure of e-learning programs are the

interconnectedness among (1) person, (2) behavior, and (3) environment. These are the

three major areas that interventions should target.


9/87

9

1. E-learners cognitive skills: E-learners must have the prerequisite knowledge and

skills necessary to participate in e-learning. Computer competency through training,

and practice, and time management skills are essential.

2. Environment: Organizations must support e-learning by offering a supportive culture,incentives, models, resources, and fostering e-learning self-efficacy.

3. Belief and behavior: E-learners must have high e-learning self-efficacy and the

appropriate behavioral skills such as taking responsibility for learning.

Cognitive

Belief &Environment

Figure 3:Three pillars of successful e-learning

Everyone has responsibility for e-learning

The findings support the social cognitive theory that indicates a triadic

interchange between an individual, the environment, and behavior. In addition to

continued investment in e-learning, these stakeholders need to turn their attention to

fixing the challenges that accompany e-learning.

Although changes can be made to the organization, e-learning policy, design,

and technologies, individual employees must take responsibility for their own learning.


10/87

10

Frustrations are bound to occur regardless of other changes in the system if there is a

lack of skills, low self-efficacy, and lack of responsibility.

Organizational research and evaluation of e-learning is essentialResearch is about improving the current practice and knowledge. Learning from

evaluation and research results is a common factor in high performance distance

learning. Procedures for obtaining feedback and a process to incorporate that feedback

into future program planning are a critical success factor for distance learning

(Hawksley & Owen, 2002). Organizations need to pay attention to the end-users

experiences expressed in this report and not just vendors.

Continued critique of learning technology

Technology critics consistently argue for balanced review of any technology, but

the threats, challenges, and losses brought by technology are typically less discussed.

While focusing on barriers might be construed negatively, it is not intended to dissuade

organizations or individuals from using learning technologies. Rather, the purpose is to

raise the awareness of the nature of obstacles being faced by e-learners. Such

examination is critical considering the promises, expectations, heavy investments, and

exponential growth associated with e-learning.The barrier reduction strategies, recommendations, and conclusions drawn from

this study have the potential to improve the practice of e-learning in organizational

settings. This report includes areas of e-learning deserving further research. The results

have multi-dimensional and significance to various e-learning stakeholders including

prospective and current employee e-learners, instructors and facilitators, staff,

management, researchers, support staff, community members, software manufacturers,

and LMS vendors. Stakeholders must recognize that technology is only a tool for

teaching and learning that they are empowered to improve, customize or change it to

meet their needs.

Besides the threat of barriers, lie limitless opportunities and possibilities for

everyone involved in e-learning. As we embrace e-learning, the challenge is to learn

from our past successes, mistakes, and experiences!


11/87

11

Table of Contents

Executive summary .. 3

Table of Contents . 11

Background of the study... 13

Purpose 14

Significance of the study... 14

Conceptual and theoretical framework... 15

Research Design... 16

Research questions... 16

Instrument ... 17

Participants .. 19

Findings of the study. 19

E-learning Barriers .. 19

Organizational differences. 22

Who are the e-learners? .. 33

Recommendations. 50

Barrier reduction strategies .. 50

Using Web-based surveys .. 65

Recommendations for future research .. 66

Conclusion . 67

References 68

Appendices 72

Summary of barriers across all organizations 75

List of Figures

Figure 1 Who are the E-learners? ... 4

Figure 2 E-learning Barriers and Predictor Variables . 7

Figure 3 Three pillars of successful e-learning 9

Figure 4 Self-efficacy Theory .. 15

Figure 5 Variables under Study . 16


12/87

12

Figure 6 Responses over 4 Weeks 18

Figure 7 Employee Population and Sample Sizes 19

Figure 8 Responses by Organization .. 23

Figure 9 Significant Predictors of E-learning Barriers . 34

Figure 10 Responses by Age . 36

Figure 11 Responses by Gender .. 36

Figure 12 Responses by Ethnicity 36

Figure 13 Responses by Marital Status .. 37

Figure 14 Bar Graph Showing Level of Computer Competence . 37

Figure 15 Employees With or Without Computer Training 38

Figure 16 Responses by Level of Education .. 42

Figure 17 Responses by Work Position . 43

Figure 18 Responses by Location of Study 44

Figure 19 Owns Computer with Internet Connectivity . 44

Figure 20 E-learning Experience . 45

Figure 21 Prior E-learning outside Current Organization 46

Figure 22 Total Number of Online Courses Taken .. 46

Figure 23 Overall Rating of E-learning Experiences ... 47

Figure 24 Three pillars of successful e-learning 63

List of TablesTable 1 Growth of the E-learning Market in the US ... 13

Table 2 Types of Barriers ... 20

Table 3 Top and Least Common Barriers ... 21

Table 4 Other Perceived Barriers across All Organizations 23

Table 5 Organizational Differences on Personal Barriers 25

Table 6 Organizational Differences on Learning Style Barriers . 26

Table 7 Organizational Differences on Instructional Barriers . 27

Table 8 Organizational Differences on Organizational Barriers 27Table 9 Organizational Differences on Situational Barriers .28

Table 10 Organizational Differences on Content Suitability Barriers 29

Table 11 Organizational Differences on Technological Barriers 30

Table 12 Sector Differences in Barriers .31


13/87

13

Background of the Study

E-learning is a major trend and the most rapidly growing segment of the training

enterprise, with an increasing number of organizations adopting e-learning (Simmons,

2002; Taylor Nelson Sofres [TNS], 2001) as an alternative training delivery mode.

According to a survey by the American Society for Training and Development (ASTD)

and the Masie Center (2001), 52 percent of the courses were being offered either via an

Intranet or over the Internet, reflecting a trend towards increasing use of Web-based

training technology in organizations. E-learning trends the past five years and future

predictions show exponential increasing growth and investment as highlighted in the

table below.

Table 1 Growth of the E-learning Market in the US

Year Growth in US $ Source

1997 $197 million Moe, M. T., Bailey, K., & Lau, R. (1999) in Berge (2001)

2001 1.2 billion ASTD (June 2001)

2002 $5.5 billion Moe, M. T., Bailey, K., & Lau, R. (1999) in Berge (2001)

2003 $7 billion ASTD & NGA (June 2001)2005 $18 billion Lord (2002)

Continued investment in human, time, and financial resources for e-learning will

mostly likely continue but that is not enough. More attention in the effectiveness, quality,

barriers, and best practices of e-learning is fundamental.

There are several driving forces behind the growth of e-learning:

Technological advances such as computers, the Internet and the World Wide Web

To meet the changing demands of consumers and customers

Demand for life-long learning

To improve employees performance

Potential to cut costs, lower employee turnover, and raise profits

Potential to cut training costs


14/87

14

Potential to reach more trainees and sidelined populations

Potential to deliver just-in-time training

Access to expertise and resources irrespective of distance

Therefore the Web has been commended for bringing human capital at theforefront (Rossett, 2001) since people have become the key to success in todays highly

competitive global economy (Kreitner & Kinicki, 2002). Many organizations have

embraced e-learning but not all organizations have done so because there are

significant trade-offs involved (Nisar, 2002).

Purpose of the study

E-learning is a major change and a recent addition to instructional delivery

techniques that has brought with it unique issues that could impact e-learners

satisfaction (Schilke, 2001), learning (Garland, 1993), motivation to learn online

(Kramarae, 2001), involvement, and even completion (Giles, 1999). Thus the purpose of

the study was two fold:

1. To understand the nature of barriers encountered by employee e-learners

2. To determine the nature of relationships between barriers, demographics,

background characteristics, and self-efficacy.

Significance of the Study

The significance of this study has contributed to:

An understanding of employee e-learners in organizations

An understanding of factors that employees consider as barriers to starting,

continuing, and completing e-learning

A valid and reliable instrument for measuring e-learning barriers and self-efficacy

The theoretical and practical knowledge base of e-learning.


15/87

15

Conceptual and Theoretical Framework

Social Cognitive Theory

The examination of barriers was grounded on the social cognitive theory, which

indicates a triadic reciprocity between a person, the environment, and behavior

(Bandura, 1986). This interchange is illustrated below.

Person

SocialCognitive

Theory

Behavior Environment

Figure 4. Social Cognitive Theory

The dimension of self-efficacy was used in this study because self-efficacy

influences choices about which behaviors to undertake, the effort, and persistence

exerted in the face of obstacles to perform those behaviors (Campeau & Higgins, 1995).

Two dimensions of self-efficacy were investigated and they are significant predictors of

barriers (1) Computer self-efficacy (CSE) and (2) Internet self-efficacy (ISE).

A Critique of Technology

Technology is a tool that is autonomous, neutral (neither good nor evil), and a

means to an end (Winner, 1977). E-learning is a technological tool for teaching and

learning that carries these characteristics. E-learning deserves a critical analysis of its

effects on society as recommended by Winner (1977), Postman (1993), Hamelink

(2000), Chidambaram and Zigurs (2001), Hatcher (2002), and Webster, (2002).

Online learning like any other technology is both a friend and an enemy, with

both good and bad effects. Practitioners and researchers continuously need to question

the intent and outcomes of technology on individuals, organizations and society.


16/87


17/87

17

Procedure

To protect human subjects, the study underwent a human studies committee

review and was approved before any data was collected. Confidentiality, anonymity,

and informed consent were maintained. Email pre-notifications were sent before the

study began and two reminders were sent out via email.

Instrument

A Web-based survey was used to collect data from volunteers. The survey was

anonymous and voluntary, measuring three constructs:

1. Demographic characteristics of e-learners

2. Barriers faced by employees engaged in e-learning3. E-learning self-efficacy

The items in the demographics section and Barriers in E-learning (BEL) scale

were developed based on distance learning literature and refined through a pilot study.

Items in the E-learning Self-Efficacy (ELSE) scale were a modification of the Eastin and

LaRose (2000) and Cassidy and Eachus (2002) instruments. The questions were all

based on a five-point Likert scale, with the scale ranging from strongly disagree (1) to

strongly agree (5). The combination of these two scales including demographics is

referred to as the Barriers in E-Learning and Self-Efficacy (BELSE) scale.

Response Rates

Pilot data was collected using a Web-based survey and the respondents were

given two weeks to respond. The pilot study was conducted in all the seven

organizations. Originally a total of 70 potential respondents were randomly chosen and

contacted in each of the seven organizations. There were 42 responses yielding a

response rate of 52.5 percent. It took each respondent an average of 14 minutes to

respond to the entire survey. Changes were made to the survey based on the feedback

from the pilot study and the comments from the subject matter experts.

Following the pilot study, the instrument was revised and sent to a convenient

sample of 4807 potential respondents in the seven participating organizations, who had


18/87

18

participated in online courses in the last two years. A Web-based survey was used over

a one-month period, leading to an 18% response rate. All responses were anonymous

thus contacting non-respondents was not an option.

The table below indicates the daily and weekly responses received and the effectof reminders when collecting data. Two reminders were sent at the end of the second

and third which. Notably, the first reminder led to an increase in responses from 150 to

310 showing the effectiveness of reminders when doing organizational surveys. The

figure below shows the fluctuation of responses during the data collection process

0

100

200

300

400

Week 1 week 2 week 3 week 4

Weeks

TotalResp

onses

Series1

Figure 6. Responses over 4 Weeks

Instruments Validity and Reliability of the Survey Scales

Seven subject matter experts reviewed the survey for validity. The reliability

analysis procedure provides information about the relationships between individual

items in the scale. The results indicated that both scales had very high reliability as

depicted below. The modifications of the survey resulted in a total of 15 questions under

the demographic, 42 items in the BEL scale and 24 items in the ELSE scale, resulting in

a total of 81 questions. The results indicate that the BELSE scale was highly reliable

and valid.

Survey Modifications

The researcher noted some revisions that could make the instrument better. For

example, future changes to the survey would include:


19/87

19

Asking about the location of the subjects in surveys dealing with international

populations, where geographic location becomes an important consideration. It

would be very informative to know how geographical location could be a barrier to

accessing content due to technology, language, or country restrictions exist. Ask whether one has completed the online course(s) or not needs to be added

In case studies, ask which particular course an employee was referring to for the

purpose of making changes to that course

Re-order some of the questions to avoid confusion because respondents seemed to

have a problem dealing with reverse questions.

Participants

These findings are a result of responses from employees in seven organizations

representing various industries and sectors as illustrated below. The figure below

indicates the population (N = total e-learners contacted) and sample sizes (n) of the

respondents.

IT ManufacturingN=867; n=125)

US Military(N=130; n=114)

Health Insurance(N=500;n=177)

IT Consulting(N=1600; n=131)

WholesaleDistribution

(N=1200; n=256)

Public SchoolDistrict

(N=500; n= 39)

Oil exploration &Manufacturing(N=10; n=8)

Total N=4807Sample size n=865

Figure 7. Employee Population and Sample Sizes in Seven Organizations


20/87

20

Findings

What are the Seven E-learning Barriers?

An increasing number of companies are adopting e-learning. But in their rush to takeadvantage of e-learnings benefits and promises, companies are finding that there are

significant barriers to adoption. (Simmons, 2002, p.19).

The first research question addressed the barriers that employees engaged in

e-learning face. To answer this question, a survey made up of 42 items (see

appendix 1) was constructed to determine what barriers employees faced when they

engage in e-learning. This scale is referred to as the Barriers in E-learning (BEL)

Scale. The mean (average rating) for each of the items are presented in appendix 1.

An interplay of forces interfere with participation of adults in educational and

training activities (Sheets, 1992) as employees involved in e-learning face several

types of barriers. These barriers fall under seven categories as illustrated below.

Table 2 Types of Barriers

Factor Name of factor Mean

Factor 1 Personal barriers 1.54

Factor 2 Learning Style 2.01

Factor 3 Instructional barriers 1.96

Factor 4 Organizational barriers 1.84

Factor 5 Situational barriers 2.81

Factor 6 Content suitability barriers 2.31

Factor 7 Technological barriers 2.05

Situational barriers relate to the an employees environment and lifescircumstances and are the most prevalent barriers (mean=2.81). These barriers have to

do with lack of time for study, time management problems, over commitment to multiple

roles and responsibilities, interruptions during study. These items were also ranked as

the top three barriers.


21/87

21

Table 3: Top and Least Common Barriers

Top three barriers The three least common barriers

1. Over commitment to multiple roles

and responsibilities (mean=3.10)

2. Interruptions at work, home or

wherever one studies (mean=2.88)

3. Lack of time to study (mean=2.99)

1. Problems with language (reading

level) used in course materials

(mean=1.43)

2. Lack of confidence in my ability to

participate in e-learning (mean=1.52)

3. My resistance to change (1.53)

The good news emerging from this study is that overall, employees seem to

experience very few barriers since the highest rating was 3.10 on a 5-point scale.

However, this finding is somewhat challenged by the findings from the comments on

barriers that followed. Employees documented other barriers that they experienced in

the process of taking Web-based courses. The table below is a synthesis of perceived

barriers in all organizations. Their comments support and elaborate the findings

emerging from the closed-ended questions, providing a richer and in-depth view of the

kinds of barriers they are faced with when they engage in e-learning.

E-learning barriers are heterogeneous encompassing personal, organizational,

content, situational, instructional, and technological barriers. Many similarities and

differences do exist among these organizations. A comparative analysis among what

other researchers have found with regard to barriers in distance learning reveals more

similarities than differences.

Statistically, the prevalence and degree of barriers is significant. However, the

open-ended responses indicate some similarities across the seven organizations.These barriers are captured in more detail in appendix 3.


22/87

22

Table 4. Other Perceived Barriers across all Organizations

Barrier Categories Characteristics

Personal Barriers Time management problems

Adult prideLanguage problem

Attitude towards e-learning

Learning style or preferences

Situational Barriers Time for study

Interruption during study

Organizational Barriers Cultural problems concerning credibility of e-learning

Lack of time for study

Interpersonal barriers

Limited online course availability

Registration system problems

Lack of awareness of available online courses

Lack of credit or certification after completion

Failure to involve employees in planning or decision making

Technological barriers Learning Management Systems (LMS) quality

Connectivity problems

Lack of training

Navigation problems

Limitations of technical support

Loss of data and inability to save or transfer data

Content-Suitability

Barriers

Learner expectations of the course

Course relevance

Content not audience-specific

Poor content quality and limited rigor

Poorly constructed assessments


23/87

23

Instructional Barriers Lack of progress reports and feedback

Limited learner engagement

Poor instructional design

Limited reference materialsAccess and navigation problems

Limited use of multimedia

Unclear or inconsistent instructions

Inability to save work

Information overload

Lack of instructor presence/interaction

Poor coordination

E-learning Barriers and Differences among Organizations

Human beings are different and so do the organizations they work for. Not only is

the demographic make up for each organization different but so are the policies,

technologies, mission, and processes. An analysis was done to determine whether

barriers perceived differ based on the type of organization as depicted below.

Organization

Military

ITConsulting

Wholesale

Health

PSDO

ilITM

anufacturing

Count

300

200

100

0

114

131

256

177

39

125

Figure 8. Responses by Organization


24/87

24

The results indicate significant differencesamong organizations on perceived

barriers. Below is a discussion of the similarities and the differences among these

organizations.

1. IT Manufacturing Company. E-learning barriers perceived by employees in thisorganization are significantly differentfrom the other organizations other than with

the Oil Company, which is also a manufacturing company.

2. Oil Exploration and Manufacturing Company. E-learning barriers perceived by

employees in this organization are not significantly differentfrom any of the other

organizations. However, it should be noted that the sample size was very small.

3. Public School District. E-learning barriers perceived by employees in this

organization are significantly differentfrom the IT manufacturing and the IT

consulting company.

4. Heath Insurance Company. E-learning barriers perceived by employees in this

organization are significantly differentfrom IT Manufacturing, wholesale, IT

Consulting, and the military.

5. Wholesale Company. E-learning barriers perceived by employees in this

organization are significantly differentfrom IT manufacturing, health insurance, and

IT consulting. This indicates differences even among organizations in the service

sector.6. IT Consulting Company. E-learning barriers perceived by employees in this

organization are significantly differentfrom those perceived by employees in the

Public School District, IT Manufacturing, Health, and Wholesale.

7. Military. E-learning barriers perceived by employees in this organization are

significantly differentfrom those perceived by employees in the IT Manufacturing

and health insurance companies.

There are no significant differences between the public school district, which are

also government-supported institutions.

Organizational Differences on Personal/Dispositional Barriers

The IT consulting companyhad the highest mean (1.73), indicating that the

employees perceived more personal barriers, while the oil exploration and


25/87

25

manufacturing company had the least barriers. Overall, personal barriers in e-learning in

these organizations are few (mean = 1.54 on a 5-point scale).

There were significant organizational differencesin terms of personal barriers.

The organizations that had significant differences are:1. IT Manufacturing and IT Consulting

2. Health Insurance and Wholesale

3. Health Insurance and IT consulting

4. Health Insurance and Military

Based on these results, the Health Insurance Company seems to be significantly

different from others on this factor. Note that there were no significant differences

involving the Oil Exploration and Manufacturing Company and the Public school district

on this factor. However, these two had small sample sizes.

Table 5. Organizational Differences on Personal Barriers

Type of Barrier Organization Mean N

1. Personal 1. IT Manufacturing 1.48 125

2. Oil E & M 1.29 8

3. Public School District 1.40 39

4. Health Insurance 1.34 1775. Wholesale 1.59 256

6. IT Consulting 1.73 128

7. Military 1.64 114

Total 1.54 847

Organizational Differences on Learning Style Barriers


employees perceived more learning style barriers. Overall, learning style barriers in e-

learning in these organizations are few (mean = 2.00) as illustrated below.

There were significant organizational differences among:

IT Consulting company and Public school district

IT consulting company and Health Insurance


26/87

26

Table 6. Organizational Differences on Learning Style Barriers


2. Learning Style 1. IT Manufacturing 2.00 125

2. Oil E & M 1.75 8


4. Health Insurance 1.78 177

5. Wholesale 2.02 256



Total 2.00 847

Organizational Differences on Instructional Barriers


employees perceived more instructional barriers. Overall, employees in these

organizations perceived few barriers (mean = 1.96 on a 5-point scale).

There were significant organizational differences among:

IT Manufacturing and Healthcare

Health Insurance and Military IT Consulting was significantly different from all the sixorganizations

Table 7. Organizational Differences on Instructional Barriers


3. Instructional 1. IT Manufacturing 2.11 125

2. Oil Expl. & Manufacturing 1.44 8

3. Public school district 1.74 39





Total 1.96 847


27/87

27

Organizational Differences on Organizational Barriers

The IT consulting company(mean = 1.99) and the wholesale company

(mean=1.98) had the highest means, indicating that the employees perceived more

organizational barriers. Overall, employees in these organizations perceived feworganizational barriers (mean = 1.84 on a 5-point scale). Under organizational barriers,

there were more similarities than differences across organizations as illustrated below.

There were significant differences in these organizations:

IT Manufacturing and Wholesale

Health Insurance and Wholesale

Health Insurance and IT consulting

Table 8. Organizational Differences on Organizational Barriers


4. Organizational 1. IT Manufacturing 1.72 125

2. Oil E & M 1.55 8




6. IT Consulting 1.99 1287. Military 1.85 114

Total 1.84 847

Organizational Differences on Situational Barriers

The Oil Exploration and Manufacturing Companyhad the highest mean (3.00),

indicating that the employees perceived more situational barriers. Compared to other e-

learning barriers, situational barriers seem to be the most prevalent yielding the highest

mean of 2.81.

Under situational barriers, there were more similarities than differences across

organizations evident among:

Health Insurance and IT Manufacturing

Health Insurance and IT Consulting


28/87


29/87

29

Total 2.31 847

Organizational Differences on Technological Barriers

Similar to the types of barriers discussed above, the post hoc test revealed that

the IT consulting companyhad the highest mean (2.38), thus its employees seem to

experience more technological barriers. Overall, technological barriers were weak

(mean=2.05 on a 5-point Likert scale). Significant differences exist between:

IT Manufacturing and Wholesale

IT Manufacturing and IT Consulting

Health Insurance and Wholesale

Health Insurance and IT consulting Health Insurance and Military

Table 11. Organizational Differences on Technological Barriers


7. Technological 1. IT Manufacturing 1.82 125

2. Oil E & M 1.92 8






Total 2.05 847

Based on these results, the respondents in the seven organizations surveyed

perceived relatively weak e-learning barriers on all categories with means ranging from

1.29 to 3.00.

Least Common Barriers: Personal barriers (mean=1.54)

Most common barriers: Situational barriers (mean=2.81)

Personal barriers are the least common while

situational barriers are the most prevalent!


30/87

30

Overall, employees of the IT consulting company (Organization 6) perceived

more barriers in all categories other than situational barriers where the Oil Exploration

and Manufacturing company (organization 2) perceived the most barriers (mean=3.00).

On all categories of barriers, the IT Consulting Company significantly differed from other

organizations. On almost all factors other than under instructional and instructor

barriers, the Oil Exploration and Manufacturing company did not significantly differ from

the other organizations. Caution should be exercised when interpreting the results of

this organization due to the small sample size (n=8).

Sector Differences

Since there were organizational differences, the organizations were combined

into three sectors to find out whether there were differences by sector. Several

organizational typologies exist (Hall, 1987), for example, non-profit versus profit, or by

societal sector such as educational, medical, and health, among others. The

categorization to three sectors:

Manufacturing sector

Service sector

Government sector

Hall (1987) quote below is important to note when interpreting these findings.

There is a basic difficulty in classifying anything: A classification that worksmarvelously in one situation might be disastrous in another types oforganizations in terms of their functions in society will vary as much withineach type as between types. Thus, some schools, hospitals, banks, and steelcompanies, may have more in common because of their routine character.Toassume that you are holding constant the major variable by comparing severalschools or several steel mills is unwarranted until one looks at the technologies

employed.(Hall, 1987, p.46-47).


31/87

31

Table 12. Sector Differences in Barriers

Manufacturing sector Government organizations Service sector

No significant differenceson all barrier categories

between

IT Manufacturing

company

Oil Exploration and

Manufacturing company

No significant differenceson all categories between the

Public school district

Military

Significant differenceson all categories of

barriers among

Health insurance

Wholesale

IT consulting

Relationship between Organization and E-learning Barriers

The type of organization can be used to predict e-learning barriers. There was a

significant relationshipamong barriers and type of organization, age, gender, and level

of education.

The significant differences among the seven organizations indicate that there are

organizational factors in play that affect e-learners perceptions. Organizational culture,

resources such as computer labs, time off to study during working hours, quality,

technologies, content, and support structures differ within and across organizations.

The seven organizations differed in their type of e-learning technologies such as

learning management systems (LMS). Resource availability and allocations for e-

learning differ and this could have implications for e-learning. Four out of seven were

international Fortune 500 organizations. Organizational differences could impact their

offerings as well as their ability and effectiveness in dealing with challenges facing e-

learners.


32/87

32

Who are the E-learners?

A Look at Employee Demographics

Demographic changes are a major force affecting the workforce. Globalization,

technology and migration have changed the traditional make-up of learners. The

findings confirm that e-learning has opened doors to a very diverse population.

Studies differ on the effect of demographics on distance learners perceptions

with recent studies by Litchfield, Oakland, and Anderson (2002) and Feldhaus (1999)

arguing that demographics do not have a significant impact on e-learner perceptions, as

confirmed by this study.

To determine the relationship between barriers and demographics, various

predictor variables shown on the figure below were examined. Significant relationships

emerged between e-learning barriers and four variables illustrated in figure 9 below.

Key predictors of E-learning Barriers

(1) Organization

(2) Self-efficacy

(3) Computer training(4) Computer competence or skills

The other demographic and background characteristics were not significant

predictors of e-learning barriers. Each of these variables is explored in more depth

below as well as the nature of these relationships.


33/87

33

Figure 9. Significant predictors of e-learning barriers

Age

The results indicate that the majority of employees participating in the study were

between 32 and 38 years old (31%). Thus the major participants of e-learning are a

relatively young audience with approximately 80% are below 45 years of age. The

graph below depicts the age representation.

There are inconsistent findings on the effect of age on DL experiences. Thisstudy found that the relationship between an employee e-learners age and perceived

barriers was not significant. The findings of this study confirm Giles (1999) and

Feldhaus (1999) findings that age does not make any difference in ones DL

experiences. However, the results contradict Fjortofts (1995) study that found age to be

a significant predictor of persistence in DL. Although age was not a statistically

Self-Efficacy

ComputerTraining

ComputerCompe-tence

Predictors Organiza-tion


34/87

34

significant predictor of e-learning barriers, it has a significant relationship with

organization, gender, and marital status.

Age in Years

Over

53

46-

52

39-

45

32-

38

25-

31

18-

24

Count

300

200

100

0

67

97

201

268

194

32

Figure 10:Responses by Age

Gender

The majority of employees who participated in the study were male (62%)

compared to 36 percent females as illustrated below. The results show that gender is

not a significant predictor of e-learning barriers confirming what other studies such as

Feldhaus (1999), Giles (1999), and a review of literature by Sheets (1992) found.

However, Kramarae (2001) have found women face more barriers whenever they learn

online.

Gender

MaleFemaleCount

600

500

400

300

200

542

314

Figure 11. Responses by Gender


35/87

35

Ethnicity

The results indicate ethnic diversity in the e-learning population surveyed. The

surveyed employees are located around the globe representing African, Asian,European, Latino, Pacific Islands, and Native-American ethnicities as illustrated below.

The majority of employees participating in the study were of European descent (49

percent).

Studies differ on their findings on the significance of ethnicity in e-learning. Some

studies have found that race made no difference in white males and females ability to

learn (Feldhaus, 1999) and ethnicity was not a significant predictor of persistence or

dropout in college computer-conferenced courses (Giles, 1999). However, Feldhaus

(1999) study revealed that race was a barrier to minorities learning process. Charner

and Fraser (1986) noted that the reasons for non-participation in adult education are

related to race among other factors. These findings conflict with the results of this study.

Although ethnicity is not related to barriers, it has a significant relationship with

ones education level.

Ethnicity

Pacific-Islander

OtherNative-Am

erican

IndianLatino

European

AsianAfrican

Count

500

400

300

200

100

0

195

516143

423

2840

Figure 12. Responses by Ethnicity


36/87

36

Marital Status

The results indicate that the majority of employees participating in the study were

married (68.7 percent) and the rest were single (29.4 percent) as illustrated below.Marital status did not emerge as significant predictor of e-learning barriers, confirming

what other studies have found out (Sheets, 1992). Although marital status was not a

significant predictor of barriers, it is significantly correlated with gender and age.

Marital Status

SingleMarriedCount

700

600

500

400

300

200

254

594

Figure 13:Responses by Marital Status

Other Background Variables

Considering the continued trend of the use of e-learning around the world and

globalization, e-learner demographics has various implications for e-learning as other

researchers have noted. Knowledge of learner characteristics could be used for

prediction of learners persistence or attrition (Giles, 1999); information on the kinds of

learners being served (Franklin, Yoakam & Warren, 1996) and aids in program planning

and policy formulation (Sheets, 1992).

Sheets (1992) noted that it is possible that less than 10 percent of the variance

regarding the prediction of persistence in distance learning is accounted for by


37/87

37

demographic variables. Actually, the findings of this study supported this notion

because only 5.5% accounted for by demographics. It is no wonder that Sheets (1992)

recommended that future studies should focus on other personal and situational factors

that go beyond gender, age, and educational background. Therefore, besides looking atdemographics, it is important to consider other factors that come into play in e-learning.

The nature of relationships between perceived barrier and other predictor variables is

examined below.

Computer Skills

Most employees rated themselves as average and/or expert computer users

(95.5%) with only a handful rating themselves as novices (only 4.3%) as illustratedbelow. Computer competency is a significant predictor of e-learning barriers. Most of the

respondents rated themselves as being experts (41 percent) or average of average

computer competence (54.3 percent) and this helps to explain why they experienced

few barriers. However, regardless of their skills, technological barriers were common in

their comments.

Computer Competence

NoviceExpertAverage

ount

500

400

300

200

100

0 37

356

470

Figure 14. Level of Computer Competence


38/87

38

Computer Training

The influence of computer training was determined by asking employees whether

they have had either face-to-face or online computer software training to improve their

computer skills. A majority of the respondents (58%) have received training while others

have had no training at all (41%) as depicted below. Computer training emerged as a

significant predictor of e-learning barriers.

The need for computer competency and training is clearly evident throughout

including the comments from the open-ended question. Several quotes such as the one

below attest to the numerous technological barriers encountered by employees, pointing

out technological challenges regardless of experience. I have worked with computers

for the past 11 years and I'm having problems moving around (the) site. I can't imagine

what people with little experience are having. Computer and Internet competency is a

must for e-learners and training should be provided whenever these skills are lacking.

Computer Software Training

YesNo

COUNT

600

500

400

300

499

357

Figure 15:Employees With or Without Computer Training

Computer and Internet competency is amust for e-learners. Training should be

provided whenever these skills are lacking.


39/87

39

Self-Efficacy

Perceived self-efficacy is defined as peoples judgments of their capabilities toorganize and execute courses of action required to attain designated types of

performances(Bandura, 1986, p. 391)

Self-efficacy emerged as a significant predictor of barriers. Self-efficacy

is not concerned with the skills one has but with judgments of what one can do with

whatever skills one possesses (Bandura, 1986). The employees had high levels of

self-efficacy, measured on a 5-point Likert scale (see appendix 2).

The relationship between the ELSE and BEL is negative, indicating that the

fewer the barriers an employee perceived, the higher his/her e-learning self-efficacyis and vice versa. It is no wonder that barriers were rated low. This confirms the

findings of Collins (1982) cited in Bandura (1986) who found that highly self-

efficacious students were usually quicker to discard faulty strategies and to display

more positive attitudes towards a subject.

Implications

The significant relationship between barriers and self-efficacy is critical for e-

learning because self-efficacy influences:

task choice (Cassidy & Eachus, 2002)

amount of effort one puts on a task (Bandura, 1986); (Cassidy & Eachus,

2002)

persistence or perseverance when faced with obstacles (Bandura, 1986;

Cassidy & Eachus, 2002)

behavior (Bandura, 1986)

motivation (Bandura, 1986); (Cassidy & Eachus, 2002)

performance (Bandura, 1986); (Joo, Bong, & Choi, 2000)

attitudes (Bandura, 1986)

outcome expectations (Bandura, 1986)

success or failure (Cassidy & Eachus, 2002; Kreitner & Kinicki, 2001)


40/87

40

nature of feedback received (Kreitner & Kinicki, 2001)

psychosocial functioning (Bandura, 1986)

perceived e-learning barriers (Mungania, 2003)

Level of Education

The majority of the respondents had a Bachelors degree (36.8 percent) closely

followed by those with a high school diploma (36.5 percent) as illustrated below.

Stanton (1998) reported that nearly two-thirds of distance learners possess college

degrees. Over a third of this studys sample (36.5 percent) hold a bachelors degree.

The results also reveal what Sheets (1992) posited that the education background of

distance students ranges from less than high school to completion of a university

degree and beyond. This sample was a highly diverse group in terms of level of

education, ranging from high school education to doctoral level.

Feldhaus (1999) found that the diversity of educational background was the most

significant factor causing barriers in this study of two-way audio-video courses.

However, the findings of this study reveal no significant relationship between the level of

education an employee has had and the e-learning barriers. This could mean that ones

level of education does not determine whether somebody will be successful online or

not. Having a higher level of education does not necessarily mean that one will be a

successful online learner. There are other factors that come into play. For example,

there is a significant relationship between an employees level of education,

organization, and ethnicity.


41/87

41

Education

Specialistdegree

Nohighschooldiplo

Master'sdegree

Highschooldiploma

Doctorate

Bachelor'sdegree

Count

400

300

200

100

0

57

153

316318

Figure 16:Responses by Level of Education

Work Position

The results indicate that the respondents work in various capacities in

management (32.8 percent) with the majority of employees being support staff (43.7

percent) as illustrated in the bar graph below.

In general, distance students tend to be employed (Keegan, 1996) and this was

the case for this studys sample. Various occupations were represented in the sample

with a majority being support staff (43.7 percent) and 32.8 percent were managers or

administrators. The finding that job position was not a significant predictor of e-learning

barriers is similar to Sheets (1992) finding that occupational status of learners does not

significantly relate to program completion.

Job position is significantly correlated with owning a computer with Internet

connection, a fact that brings forth affordability issues. Stanton (1998) found that half ofall Internet users are professionals or managers.

Although some of these variables do not indicate direct or significant

relationships, their ability to influence e-learning indirectly should not be ruled out. For

example, job position and study location were significantly correlated with each other.

However, unless one is in a financial position to afford a computer and also to be able to


42/87

42

pay Internet costs that accompany e-learning, then their study location options, access,

and frequency of use could be limited.

Work Position

Teacher/Instructor

Supportstaff

Non-com

missionedoff

Manage

r/Administrato

Com

mis

sionedOfficer

Count

400

300

200

100

0

Figure 17: Responses by Work Position

Location of Study

The respondents were asked to indicate where they do most of their online

learning. The majority of the respondents take their online courses in various locations:

in the office (55.8%)

both at home and in the office (26.4%)

at home (15.7%)

at other locations (1.5%)

The relationship with perceived barriers was not significant indicating that the

location where an employee undertakes e-learning does not significantly influence ones

perception of e-learning barriers. Study location was significantly correlated to owning of

a computer that has Internet connectivity, a variable that determines ones study

location options. For example, unless one has a computer at home that has Internet

connection, then s/he would not be able to access content.


43/87


44/87

44

Prior E-learning Experiences

The respondents differed in the amount of e-learning courses they have had.

Although a majority had taken online courses before (83%) there were somenewcomers, accounting for 17% of the sample.

64% have only had online courses at their current organization while 34% had

had online courses elsewhere. Prior experience with e-learning did not emerge as a

significant predictor of barriers. Whether or not an employee has taken online courses

before is not a significant predictor of e-learning barriers.

E-learning Experience

FirstO

nlineCourse

C

oursebefore2001

C

oursein2001

C

oursein2002

Count

500

400

300

200

100

0

148

393

118

200

Figure 20. E-learning Experience


45/87

45

Prior E-learning Outside Present Organization

YesNo

Count

600

500

400

300

200

294

556

Figure 21. Prior E-learning Outside Current Organization

Total number of Online Courses Taken

The respondents were asked to indicate the total number of courses they have

taken online. The results indicate that a majority (80%) has had less than 10 online

courses. Number of courses taken did not emerge as significant predictor of barriers.

Total Online Courses Taken

Over30

26-3021-25

16-2011-15

6-101-5

Count

600

500

400

300

200

100

0 433962

168

530

Figure 22. Total Number of Online Courses Taken


46/87

46

Overall Rating of E-learning Experiences

Overall, a majority of the employees are pleased with the e-learning experiences

(86.5%) compared to 10% who rated their experiences as negative. Such positive

ratings are good news for all e-learning stakeholders.

Overall Rating of E-learning Experiences

positivenegative

COUNT

800

600

400

200

0

748

87

Figure 23: Overall Rating of E-learning Experiences


47/87

47

Barrier Reduction Strategies

It may be difficult to completely eliminate barriers but they definitely can and

should be reduced. Below are some of the recommendations based on a synthesis of

the findings and from the literature. Organizations can use this list as a checklist to

determine which facets need to be modified.

Know Your Target Audience and Their Expectations

Barrier: Irrelevant content that does not meet learners expectations

The starting point for any distance learning provision should be identified learners

needs (Hawksley & Owen, 2002). Therefore, employers need to:

o Determine the demographic makeup and background characteristics of the e-

learning audience.

o Conduct a needs assessment on the needs of learners before content is

developed.

o Course descriptions should be well written so that employees know in advance

what to expect from the course.

o Pre-entry guidance is one of the most critical success factors for distancelearning (Hawksley & Owen, 2002).

o Customize course content to meet the needs of the audience. This can be

accomplished through design. Having a master course and opening other

The various baggage that these students bring, their

perceptions of the learning experiences, and the coping and

adapting processes they develop must be addressed to gain an

understanding of how better to meet the diverse needs of the

distance student (Feldhaus, 1999, p.4).


48/87

48

sections of the same course specifically tailored to the needs of a particular

audience.

Cultural sensitivity: Take into consideration the culture of the target audience. Provide an array of courses to cater for various career stages. If courses are

unavailable internally, provide employees with other advanced training sources.

Employee expectations should be managed. It is important to let the employees

know that not all courses can be delivered online.

Provide Training and Development Opportunities

Barrier: Unpreparedness or lack of appropriate skills and knowledge

Successful e-learning demands social, cognitive, and behavioral skills. Although

self-efficacy judgments are functionally related to action, a number of factors can

affect the strength of the relationship (Bandura, 1986, p. 395). Perceived efficacy by

itself can affect the level of motivation but it does not produce performance if one

lacks the necessary sub-skills (Bandura, 1986). That is why it is important to provide

training if skills are lacking. For example, computer skills and time management

skills are critical for successful e-learning

Provide tips or an orientation course that will make learners aware of how tosucceed online.

Employees require both skills and high self-efficacy (Bandura, 1986)

Knowledge and constituent skills are necessary but insufficient for accomplished

performances, therefore, interventions need to be in place that can promote self-

efficacy--the bridge between skills, action, and outcome.

Strategies for Improving Employee Self-Efficacy

Barrier: Low self-efficacy or anxiety about ones ability to be a successful e-learner

Among the different aspects of self-knowledge, perhaps none is more influential

in peoples everyday lives than conceptions of their personal efficacy (Bandura, 1986,

p.390). In the context of this study, the influence of self-efficacy on e learning, which is

significantly related to barriers has several implications. Self-efficacy arises from the


49/87

49

gradual acquisition of complex cognitive, social, linguistic, and/or physical skills through

experience (Gist, 1987 cited in Kreitner & Kinicki, 2001).

Self-efficacy reflects what individuals believe they can do with the skills they

possess (Eastin & LaRose, 2000). Because perceived self-efficacy operates partiallyindependently of underlying skills (Bandura, 1986), it is important to look beyond

training as a way of reducing barriers. Other strategies that can promote self-efficacy

are required but how can this be accomplished? Tap into the four sources of self-

efficacy namely (1) prior experiences, (2) vicarious experiences, (3) verbal persuasion,

and (4) affective or physical arousal (Bandura, 1986).

Assess e-learners self-efficacy

Although one might be successful in other endeavors, it does not necessarily mean

that one is confident about e-learning. Therefore, determine the self-efficacy level of

e-learners and put measures that enhance self-efficacy in place through the four

interventions below.

Provide Continued Positive Experiences

Prior experiences (success or failure) are the most powerful source of self-efficacy

(Bandura, 1986; Campeau & Higgins, 1995; Cassidy & Eachus, 2002). Prior experience and self-efficacy are related thus every employees initial online

experiences should be as positive as possible because that could determine future

undertakings.

Staff or coworkers with certain skills or extensive experience can provide personal

coaching and support to ensure positive experiences.

Provide Vicarious Experiences

Observing the success or failure of models (Campeau & Higgins, 1995; Cassidy &

Eachus, 2002) doing similar tasks (in this case e-learning) can strongly influence

ones self-efficacy (Kreitner & Kinicki, 2001).


50/87

50

Consider pairing up successful e-learners who can serve as mentors to new online

learners. One of the organizations uses subject matter experts (SMEs) within the

organization as facilitators and content writers.

Create e-learning communities where people can come together for support andexperience sharing.

Verbal persuasion

Self-efficacy can be influenced by verbal persuasion. Supervisors, peers, significant

others, senior and middle managers must be advocates of e-learning.

Verbally persuade employees of the value and credibility of e-learning.

Use positive reinforcement.

Provide feedback that could nurture self-efficacy.

Managers have an important role in motivating learners to continue with online

learning (Pollard & Hillage, 2001). Managers must go the extra mile to pat learners

on the back, give them recognition, and encourage them to learn with their peers.

(Cross, 2000) cited in (Pollard & Hillage, 2001).

Physical and Affective Arousal

Emotional arousal such as anxiety influences self-efficacy (Campeau & Higgins,1995; Cassidy & Eachus, 2002; Kreitner & Kinicki, 2001)

Create interest in e-learning through recognition and praise that arouses emotions

Offer awards or certificates upon successful completion

Provide Incentives for E-learning

Barrier: Lack of motivation or incentives for e-learners

Having skills and high self-efficacy is not enough (Bandura, 1986). Persons may

possess constituent skills and a strong sense of efficacy that they can execute them

well, but they still choose not to perform the activities because they have no

incentives to do so (Bandura, 1986, p.395).

Self-efficacy also does not translate into action whenever people do not have access

to necessary physical resources such as equipment or financial resources.


51/87

51

Physical or social constraints further impose limits on what people can do (Bandura,

1986).

Skills are not enough, resources are equally important. The discrepancy between

internal factors (peoples capabilities) and external factors (resources) should beresolved

Notify employees of certificates offered upon completion

Access especially for employees in lower-level paying jobs and in remote locations

should be taken into account. The US army is an example of an employer that offers

an incentive to e-learners by offering free laptops.

Employers could follow the US Army model or go even further to pay for Internet-

related costs especially for employees in remote locations such as in developing

countries where phone and Internet connection costs are high.

The E-learners Challenge for Responsibility

Barrier: Employees low self-efficacy and lack of responsibility

Learner outcomes depend largely on self-efficacy beliefs (Bandura, 1986). Those

with self-doubt or low self-efficacy are quick to quit if their initial efforts prove deficient

(Bandura, 1986). In the e-learning arena, participants with low self-efficacy are likely to

quit e-learning altogether if they have encounter barriers in the process. Therefore,employees need to know that:

In social, intellectual, and physical pursuits, those who judge themselves highly

efficacious will expect favorable outcomes, self-doubters will expect mediocre

performances of themselves and thus negative outcomes (Bandura, 1986, p.392).

Awareness of ones efficacy could help to bridge the gap between ones knowledge

and skills and to translate them into appropriate courses of action (in this case e-

learning).

E-learners must understand their roles and responsibilities in e-learning because

outcomes are not disconnected from actions, rather, most outcomes flow from

actions (Bandura, 1986).


52/87

52

Ones behavior largely determines the outcomes one experiences. Employees

therefore need to realize that their behavior in e-learning like in other lifes events

affect their outcomes.

Test alternative forms of behavior and strategies to determine which ones lead tosuccess by trying different techniques and behaviors for learning online.

Be aware of the link between their self-efficacy and outcomes.

Efficacy is not a fixed act. Different skills are required, thus engaging in life-long

learning is a must.

While time management training can be taught to help with procrastination, it lies

upon the individual to take control of their time.

Online learners do not understand how their role changes with e-learning since this

is a great source of concern and stress (Ullrich, 1998). Role ambiguity occurs when

there is a lack of clarity between an individual and others regarding what is expected

of them (Ullrich, 1998 citing Spreitzer, 1996). Such ambiguity can affect a learners

belief in his/her capacity to perform and hurt ones self-confidence (Ullrich, 1998).

Provide adequate communication and advising opportunities to reduce role

ambiguity. Ullrich (1998) warns that unless there is high-self confidence in learners

and clear, concise and timely communication, resistance will occur and this could

result in a failure of online programs.

Cater for Multiple Learning Styles

Barrier: Preference for other instructional delivery techniques

Use a blended delivery approach by providing alternative delivery methods e.g.

blend online courses with face-to-face instruction and other media.

Provide learning materials in various formats such as hard copy/manual or on a CD-

ROM, audio, video, among others.

Assess the e-learners learning styles. There are various inventories that can be

used to evaluate learning styles. Refer to Ahn (1999) for more on learning styles.

Recommend employees to take learning style surveys and used the results in

decision making as to whether online courses are suitable for ones learning style.

Design online courses taking into account multiple learning styles.


53/87

53

Pay Attention to Course design

Barrier: Content inconsistency, illogical, and unclear

Learners need to see the link between the course and the results. This could be

achieved through providing adequate instructions, linking course assessments to

content and providing feedback.

Provide written directions or rationale behind the organization of the content and link

among content, exams, and results.

E-learning materials design should have some consistency in the look and feel

The training team needs to be up-to-date with course developments, constantly

revising wrong content and updating outdated content.

Provide the e-learner with choices on how to manage their files. For example,

provide downloading options, printed course materials, pdf files, among others.

Instructions Must Be Clear and Logical

Barrier: Confusion from instructions and navigation procedures

Give clear instructions informing the e-learners about how to save their work and

continue at a later date or time. Most students lose their data or track because

whenever they resume, they have to start all over.

Provide clear instructions at the beginning of the course/module on how to navigate

the course.

Streamline the instructions sent to employees about logging in. for example, the

course names, whether there is a space between login names, whether to use lower

or upper case should be standard and communicated in a consistent manner

Ensure that all the information communicated to the employees is clear and

unambiguous

Provide clear instructions on how the learners can keep their materials organized

Explain the learning process including the format. Graphics and course maps are

good visual guides

Use Red flags whenever confusion is evident or could occur.


54/87

54

Watch for Information Overload

Barrier: Information overload and discrepancy in requirements

Balance the workload between instructor-led courses and online courses

Re-evaluate the appropriateness of all the content for inclusion in a module andremove any unnecessary information

Follow-up During and After Training

Barrier: E-learners are not aware of their status and progress

Change the employees status once a course is completed

Ensure that a learner is aware of how s/he is doing by posting grades, providing

written feedback

Provide employees with the ability to view how many and which courses one has

completed. The system should be configured to give such information

Record progress made by the e-learners and make this information available to the

participants.

Quality must not be compromised

Barrier: Poor course quality, low expectations, and little rigor

Raise course expectations to motivate employees to take the online courses Course content should be of high quality to keep employees motivated to take them.

Providing hands-on activities that require higher level learning skills like analysis,

synthesis, and application.

Regulate learners pace by using locks to ensure quality standards. By design, the

some sessions could be locked if the learner does not meet the standards (grade or

submissions) required at a previous section.

Provide reference materials (online and off-line).

Transfer of Training

Barrier: Translating knowledge into action

Close the gap between knowledge and action by providing opportunities for e-

learners toapply what they have learned.


55/87

55

Tests and Assessments

Barrier: Inappropriate or tests that do not add value

Ensure that test instructions are clear and not confusing.

Ensure that the order in which questions are presented matches the content covered Ensure that the questions are specific and relate to the course content.

Standardize the response times by specifying the period within which learners

should expect feedback.

Create questions that require analysis, synthesis and application. One employee

said, I would like to see more-hands on exercises to learn the computer

techniques.

Ensure that the homework is valuable to the learning process and that it relates to

the content.

Provide feedback or answers to questions by providing automated feedback.

Various strategies include providing answers to multiple choice questions, an

explanation as why an answer is correct or refer learner back to the content.

Instructors must be Competent Online Course Facilitators

Barrier: Facilitators lack of knowledge, skills, and positive attitude towards e-learning

Instructors/facilitators should be well versed with the system and provide immediatesolutions to problems faced.

Instructors or online facilitators should be more available and visible to online

learners to maintain learner-instructor interactions.

Instructors are not technical experts but they should be trained on technology.

Facilitators must have access to resources such as a help-desk in case of need

Notify learners of other help resources if used phone or email contact, hours of

operation, office hours, and nature of problem solved by each resource.

Instructors should provide immediate feedback and stipulate the period of time (in

hours or days) within which they will respond to learners questions.

Facilitators must have positive attitudes towards e-learning and become its

advocates.


56/87

56

Organizational Culture and Internal Support

Barrier: An organizational culture that does not value or support e-learning

Acceptability is a key issue and Keegan (1996) thus each organization should

determine the internal acceptability of DE courses and programs and seek internalsupport.

Management must buy-in into e-learning by recognizing its value and become its

advocates (ASTD & Masie, 2001).

Include employees in the decision-making process involving e-learning. This could

help with their buy-in into e-learning program

Evaluating the esteem of your e-learning program in your organization

Determine the need for cultural change especially with regard to e-learning and work

towards reducing resistance.

Establish or Maintain Credibility of E-learning

Barrier: Credibility and esteem of e-learning

Conform to the constraints of regulatory and accrediting practices (Moran &

Myringer, 1999). Organizations are faced with a challenge of determining the

credibility of off-the-shelf or internal online courses.

Ensure that employees are aware of whether online course certificates arerecognized in the organization. One employee indicated interest in this issue saying,

I would appreciate more information on the legitimacy of course credit and

certifications.

Conform to accreditation (local, national, and field-specific) standards to ensure

quality and credibility of online courses and programs.

Review the criteria about recognizing online course certificates. Some organizations

in this study did not recognize online course credentials acquired elsewhere.


57/87

57

International threats demand highlighting because withinfrontiers, there are usually structures for the regulation or self-

regulation of university activities, but there is less regulation acrossfrontiers and less still in cyberspaceRegulatory frameworks arestill in their infancy within national boundaries, never mindbeyond. It remains to be seen how far codes are followed or enforcedand we have little in the way of consumer protection for the virtualstudent.

(Harry & Perraton, 1999, p.5)

Plan and have a Policy for E-learning DE changes instructional organization and delivery, models of instruction, student

services, marketing, manner of teaching and learning, administrative policies, and

procedures (Broskoske & Harvey, 2000).

Give attention to e-learning planning and policy implementation since they are some

of the most critical success factors for distance learning (Hawksley & Owen, 2002)

Do a thorough needs analysis to determine what the issues that were not included in

the planning

Some of the barriers indicated policy limitations. Pay attention to these policy

development areas: academic, fiscal/administration, geographic service area,

governance, labor-management, staff, community, legal, student support services,

technical, cultural, and evaluation (Berge, 1998; Gellman-Danley & Fetzner, 1998;

King, Nugent, Russell, Eich & Lacy, 2000).

Clearly define the e-learning audience and its benefits and drawbacks so that all

employees are informed. Some groups should not feel privileged or unprivileged as

a result of taking online courses.

Provide Resources for E-learning

Barrier: Inadequate resources for e-learning


58/87

58

Good online learning requires adequate learner support. Knowledge, skills, and self-

efficacy are not enough. Resources are a critical success factor for distance learning

(Hawksley & Owen, 2002). Show commitment to e-learning by providing adequate

resources such as: Lack of time is a major barrier thus time for e-learning just like instructor-led training

must be prioritized by allowing study opportunities during office-hours.

Provide financial support for e-learning

Provide reference materials

Provide technical support

Provide internal support for e-learning.

Provide technology such as desktop computers, laptops, or labs for e-learning

purposes.

Communication on Course Offerings and Registration Issues

Barrier: Communication breakdown, insufficient course information and courses

Expand the utilization of e-learning from just instructional content delivery but also

for information purposes. Rossette (2002) posits the big tent view approach to e-

learning that goes beyond instructional delivery.

Mentors or a help desk offering career guidance for employees taking online coursesin need for more information about online courses.

Provide course descriptions that help the employees to know the benefits of taking a

particular course.

Inform employees of the type of instructional delivery method used for the courses

offered.

Update instructions and communication to ensure that employees are informed

about online courses and how to enroll.

Management should ensure that employees are informed of available courses. This

could be achieved through a catalogue of online courses and other communication

avenues already in place.

Provide a wider array of online courses.


59/87

59

Streamline registration functions with an easy enrollment procedure to online

courses

Employees should be able to easily find available online courses, duration,

prerequisites, enrollment dates, if there is an online facilitator, among others. Follow-ups with those on waiting lists in case employees have to wait before they

can enroll in online courses.

Increase the number of sections available for a particular course so that employees

willing to take a course do not have to wait.

Review the human resources needs in order to provide more courses.

Increase the overall number of e-learning computer courses offered. Computer

courses seem popular and this was a common need mentioned by employees in

different organizations.

Create an online course catalogue where employees can view the online courses

offered.

Categorize courses to make it easy to search.

Provide information about course completion requirements.

Technology Training and Interaction with Technology

Barrier: Limited technological skills and anxiety towards technology Provide early and continued exposure to technology: Litchfield, Oakland, &

Anderson (2002) suggested the possibility that the current Information Age

environment has a positive effect on self-efficacy with the Web. This is an indication

that the preponderance of technology and especially computers and the Internet in

todays organizations could be having a positive impact on employees as evident in

their strong self-efficacious beliefs. Therefore provide numerous opportunities for

employees to interact with e-learning technology.

Provide training or a demonstration (online, CD, video, or by print) on how to register

for an online course

Provide computer training on commonly used skills in e-learning such as how to

manage files and deal with online content might be necessary. There seems to be a

competency problem with printing, downloading and navigation.


60/87

60

Provide free demonstration courses where employees can practice their skills and

gain familiarity with online courses.

Access to Course ContentBarrier: Unreliable technology and inconsistent access

Provide single log-in password to avoid numerous passwords that cause confusion

and limit entry.

Before engaging in e-learning or choosing the type of media and during the

instructional design and the organization must keep in mind the location of the

employees and consider the possible technological barriers that may result from

their location and equipment availability.

Those targeting international audiences must pay attention to geographical,

infrastructural, language, and government policy barriers that could negatively

impact access.

Limit the size of graphic images or file sizes which impede downloads or the number

of downloadable items by reducing their size, and test courses on slow computer

(characteristic of what employees have at home).

Provide the technology needed by employees to learn while at work especially for

those without adequate access at home. Computers or laptops, or a study lab couldbe helpful.

Access problems relating to downloads can be fixed by providing up-to-date

information about the files/programs needed before a course begins to avoid

employees missing courses that they are interested in taking.

Course Navigation

Barrier: Inconsistent and poor navigation

Provide a course map or a table of content or a resource page that contains all the

links in a

Date post:	07-Apr-2018
Category:	Documents
Upload:	navin1797
View:	216 times
Download:	0 times

Elearning Report

Documents