CHAPTER II. LITERATURE REVIEW
E- Learning
ABSTRACT
The purpose of this study is to explore how task technology fit (TTF) of e-learning influences employees’ learning and training transfer. Through an empirical study of a case company’s e-learning program for new recruits, this research examines whether the fit between the e-learning technology and employees’ realistic tasks has an effect on employees’
learning effectiveness. To fulfill the study objectives, the researcher worked with one of the largest real estate agencies in Taiwan, which was nicknamed the S Company for anonymity, to collect data needed. Survey questionnaires containing demographics, measures of visual-verbal learning style and task technology fit of e-learning were administered to S Company’s 151 new real estate agents who completed the training for new-hires in the period between June and August of 2011.
Data for the outcome variables of the study, the e-learning test scores and the training transfer scores of each trainee were provided by the S company. Exploratory factor analysis result showed the factor structure of the TTF measure to be composed of three distinct components: content, technology and presentation of e-learning. Hierarchical regressions were used to test the direct effect of TTF on learning outcome and training transfer, as well as the mediating effect of learning outcome between TTF and training transfer. These hypotheses were supported which implied the importance of ensuring TTF when using e-learning to train employees. The moderating effect of visual-verbal learning style on the TTF-learning outcome connection, however, was not supported, due to small variances in agents’ homogeneous learning style.
Keywords: E-learning, task-technology fit, learning outcome, training transfer, real estate agents
TABLE OF CONTENTS
ABSTRACT….. ... I TABLE OF CONTENTS ... II LIST OF TABLES ... IV LIST OF FIGURES ... V
CHAPTER I. INTRODUCTION ...1
Background of the Study ... 1
Purpose of Study ... 4
Research Questions ... 6
Delimitations and Limitations ... 7
CHAPTER II. LITERATURE REVIEW ...9
E-Learning ... 9
Task Technology Fit ... 14
Learning Effectiveness ... 26
Learning Style ... 38
CHAPTER III. RESEARCH METHODS ... 43
Research Framework ... 43
Research Hypotheses ... 44
Research Design ... 44
Measurement ... 47
III
CHAPTER IV. ANALYSIS AND RESULTS ... 57
Descriptive Statistics of Task Technology Fit ... 57
Correlations ... 60
Regression for Hypothesis Testing ... 62
CHAPTER V. CONCLUSIONS AND SUGGESTIONS ... 69
Conclusions ... 69
Practical Implications ... 71
Limitations ... 74
Future Research Suggestions ... 75
REFERENCES.. ... 77
APPENDIX. RESEARCH QUESTIONNAIRE ... 88
LIST OF TABLES
Table 2.1. Types of E-learning Materials in S Company ... 19
Table 2.2. Summary of Learner Characteristics—Transfer Link ... 21
Table 2.3. Dimensions Items of Task Technology Fit ... 24
Table 2.4. Summary of Six Evaluation Models ... 27
Table 2.5. Summary of the Intervention Design—Transfer Link ... 35
Table 2.6. Visual-verbal Learning Style Dimension ... 41
Table 2.7. Strength Level Scale ... 42
Table 3.1. Sample Description ... 45
Table 3.2. Sample Item for Each Dimension of Task Technology Fit ... 47
Table 3.3. Reliabilities of Dimensions of Task Technology Fit Model ... 49
Table 3.4. Summary of Exploratory Factor Analysis Results for Task Technology Fit ... 50
Table 3.5. Reliability ... 52
Table 3.6. Sample Items for Learning Style: Visual-verbal Learners... 54
Table 4.1. Descriptive Statistics－Question Items of TTF ... 58
Table 4.2. Correlation Analysis Results ... 61
Table 4.3. Results of Regression Analysis of Hypothesis 1 ... 62
Table 4.4. Results of Regression Analysis of Hypothesis 2 (3rd months) ... 63
Table 4.5. Results of Regression Analyses of Hypothesis 3 (3rd months) ... 64
Table 4.6. Results of Regression Analyses of Hypotheses 2, 3 (2nd months) ... 66
Table 4.7. Results of Regression Analyses of Hypothesis 4 ... 67
Table 4.8. Descriptive Statistics—Distribution of Visual-verbal Preference ... 68
V
LIST OF FIGURES
Figure 2.1. Western model of e-learning implementation ... 11
Figure 2.2. Task technology fit model. ... 15
Figure 2.3. Learning in the workplace... 32
Figure 3.1. Research framework ... 43
CHAPTER I. INTRODUCTION
In this chapter, the background, rationale, research questions, and research delimitations and limitations of this study are introduced. The background focuses on current e-learning implementation on workforce and that in realty industry. The rationale explains the reason why the study is conducted. Research questions and delimitations and limitations are addressed.
Background of the Study
Training is an important issue in business for cultivating the company’s human resources.
In order to facilitate employees’ learning of job-related competencies, organizations usually spend an immense amount of time and money on training. According to a recent American Society for Training and Development study, U.S. organizations spend more than $125 billion annually on employee training and development (Paradise, 2007). Facing the trend of e-commerce, more and more firms start to develop their internal operation system with more technological and highly connected network facilities for making work more efficient.
Information and communication technology (ICT) has grown exponentially during the past two decades around the globe, which leads changes in nearly every field of practice including human resource development (Teng, Bonk, Bonk, Lin, & Michko, 2009).
Masie (2008) provided a survey reported on how employees currently learn at work and how their learning preferences are changing; the result showed that e-learning was ranked as the second most frequently used learning tool/method next to reading in the workplace. In other words, the majority of employees today rely heavily on self-directed and asynchronous resources such as e-learning, to learn for work(Cho, Park, Jo, Jeung, & Lim, 2009). As one of the most technologically advanced societies, Taiwan provides a fertile ground to study the impact of ICT applications. By 2008, 68.1% of the population of Taiwan had accessed the
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Internet (Taiwan Network Information Center, 2008). According to a report from the Economist Intelligence Unit (2010), Taiwan’s e-learning readiness was ranked 3rd in Asia and 12th in the world. It reflects a mature ICT environment for Taiwanese companies to reap the benefit and savings from implementing e-learning systems.
In recent years, the challenge for companies is to improve the e-learning content and its deployment towards employees (Baudoin, 2010). Studies of e-learning effectiveness as a training method have focused more on educational field, for example, distance e-learning course at schools. In addition, studies of e-learning implementation on business usually face the conflicts of benefits between implementing e-learning and traditional instructions. As high-tech industries such as the electronic and computer manufacturers tend to train engineers or technicians through e-learning to cut down the learning process, e-learning of traditional industries and service industries are relatively neglected or underestimated. Since Taiwan develops into a post-industrialized society, the service industries have gained importance in serving as a major economic force, and thus deserve attention from learning technologists to look into the effectiveness of e-learning for training service personnel.
Real estate industry, as one of most talent needed service industries, has extremely competitive market in Taiwan. The recent trend also shows an eagerness to exploit the internet to enhance visibility to more customers. Most real estate companies have developed an official website for customers to access real estate information. The booming real estate websites is an indication that the traditional transaction skill of face to face (FTF) communication has now started to blend with computer-mediated communication (CMC).
For the increasing needs on competencies of using computer or web-based systems, real estate companies have begun to incorporate e-learning in their training. S Company, the case company in this study and a multinational company with branches in Asia and Japan, has been developing its e-learning program which is implemented on web-based platform since 2004. It is expected to save the spending of agents’ traffic time and learning period.
Four main functions built in the e-learning platform of S Company, which is called
“E-School”, including “Learning Center”, “Learning Interaction Center”, “Unit Development Center” and “Learning Management Center”. For “Learning Center”, learners can check out the course list and see which course is interested to them, and they can directly register. Most information of e-learning courses is attained in this function. After the learners successfully register, the detailed information such as the duration or the instructor, etc., of each course will be shown on the screen. It benefits the real estate agents to check the required courses or those they need anytime as long as they have their computers connected to “E-School”. For
“Learning Interaction Center”, learners can share their opinions, reflections, and other experiences through posting words on the discussion board or through chat room. “Unit Development Center” is for users who are supervisors to check their subordinates’ learning records. Learning Management Center” is for HR managers to see the class information. It is because they need to monitor if the figures of attending people are acceptable and take it as one of standards of rating a course.
Xiao (1996) pointed out that policy makers tend to applied training and believe that the improvement of knowledge, skill, and attitude (KSA) after the training will make workers become more competent, and in turn, increase productivity. Blume, Ford, Baldwin, and Huang (2010) indicated that despite the large investments in and potential benefits of training, organizational decision makers are often not sure to what extent employees perform differently once back on the job. In other words, whether the training program improves employees’ learning effectiveness is the main focus when companies conduct training.
Thence, the need to evaluate a training program becomes essential for realizing the learners’
learning effectiveness.
Goldstein (1986) noted that well-developed programs can provide relevant learning experiences and improve trainees’ capacity, enabling them to work more efficiently. Since the utilization of a particular feature of technology tools relies on the distinctiveness of the
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assigned task (Agnihotri & Troutt, 2009), the e-learning courses of S Company are expected to correlate to house agents’ tasks. Therefore, the “fit” between e-learning courses and employees’ tasks should be identified. This study conducts Goodhue and Thompson (1995) task technology fit (TTF) model to understand the employees’ perceived TTF of S Company’s e-learning courses.
Since individual characteristic also forms the model of TTF, this study also intends to find out the role that individual differences play in the learning process. Research on trainee characteristics that influence training outcomes is various and relates to either personality or to motivation such as conscientiousness, self-efficacy, motivation to learn, learning goal orientation, performance goal orientation, and instrumentality of training (Tziner, Fisher, Senior, & Weisberg, 2007). As many studies of learning styles have been booming to explain individual differences on training, researchers found out that when instruction was matched to learner’s cognitive style, it leads to better performance of learning. Therefore, except some demographic factors such as age, gender, education background, and job experience, etc., this study implements Felder’s index of learning styles (ILS) as the measurement to examine the effects of individual characters on the relationship between e-learning and training effectiveness.
Purpose of Study
The purpose of this research is to evaluate e-learning courses for new employees of S Company based on Goodhue and Thompson’s (1995) task technology fit model as well as Felder and Soloman’s index of learning style. Because of the high need of collecting sales data and the difficulties encountered in measuring the effects of sales training, it is important to make the determination of sales training effectiveness. Thus, a critical need is to determine if performance following the training, and to assess the performance with measurable organization results so that it contributes to the human resource development of the
organization (Honeycutt, Ford, & Rao, 1995).
Gilley, Eggland, and Gilley (2002) indicated that “evaluation is a process, not an event, that involves all key decision-makers, stakeholders, and influencers, and should be influenced by a clear understanding of the organization’s performance and business needs, as well as its strategic goals and objectives.” The concept exhibits the importance of evaluating a company’s training system after it is being constructed. Since organizations have recognized the usefulness of e-learning and have had high expectations of its quality, e-learning evaluation enables organizations to check increased benefits from e-learning (Cho et al., 2009).
MacDonald and Thompson (2005) stated that evaluation in e-learning has become a crucial issue, as evaluation plays an important role in improving the quality of e-learning and in justifying technology use in education. Since technology provides many useful tools to solve daily tasks, it is very important to understand the relationship between tasks and technology, which can have a significant impact on technology use and subsequent outcomes (cited by Yu & Yu, 2010). Also, organizations can consider e-learning as an organizational strategy that develops human resources and improves competitive advantages for overall business goals through systematic evaluation (Macpherson, Elliot, Harris, & Homan, 2004).
Technology Fit (TTF) is a theory that describes performance impacts of an information system (Dwyer, 2007). Therefore, by examining employees’ perceived task technology fit, this research expects to analyze the effects of e-learning courses on learning effectiveness.
Except of the fit between task and e-learning, the trainees’ individual differences have been studied in plenty amount of literature. As individual characteristics are included in TTF model, this study intends to explore the role of learners’ characteristics such as age, gender, and learning style, etc. that interacts in training process. Hosford and Siders (2010) indicated that research into individual learning style has been carried out for decades, most with a claims that understanding learning styles can facilitate and improve learning outcomes, many
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of these claims have been criticized for being based on little or no empirical evidence.
However, as e-learning courses are usually ill-judged for lacking interaction with trainees, the researcher assumes that trainees’ learning preferences may affect their satisfaction with e-learning. Therefore, this study also explores the influence employees’ learning styles may have on learners’ learning outcomes.
The result of this study will inform the S Company in order to improve its e-learning course and the researcher expects to find out whether the e-learning courses fulfill the new employees’ training needs and improve their learning outcomes and training transfer.
Theoretically, this study will also empirically test the validity of the task technology fit model when e-learning is treated as a technology to improve human performance. Meanwhile, the reliability and validity of Felder and Soloman’s ILS instrument is also testified in this study.
Research Questions
Based on the research purpose, the research questions are stated as following:
1. Do characteristics of S company’s e-learning system fit those of agents’ tasks?
2. Does task technology fit of e-learning have an influence on learning outcome?
3. Does task technology fit of e-learning have an influence on training transfer?
4. Does employees’ learning outcome mediate the relationship between task technology fit and training transfer?
5. Does employees’ learning style moderate the relationship between task technology fit and learning outcome?
Delimitations and Limitations
This study will specifically focus on the e-learning courses in the training system of S Company. The sample was limited to new real estate agents recruited from June to August of 2011 who participated in e-learning courses administered by S Company. Since the study used a quantitative method, the research instrument was a survey questionnaire distributed to real estate agents during new agent training. Additional data such as agent’s test scores and training transfer scores were provided by human resource managers of S company. The survey participants were asked to provide their names for tracking the courses they attended.
For the agents’ learning outcome score, it came from a test held in the class. The test is designed from the contents of e-learning courses which are knowledge based including agent process, different contracts introduction, blueprint and floor plan mapping, house condition inspection, etiquette and customer service, standard operation procedure, and so on. The score is recorded and considered as a referential indicator of new agents’ performance during their probation.
For the training transfer score, it is graded each month in S Company with different proportion of grades provided from supervisors, senior agents, and tests, etc. The supervisor and senior agents will judge and grade new agents by reviewing their actual performances on the job; for example, the attendance, reflection reports of running each case and the overall knowledge, skill and abilities (KSAs). The test results of e-learning and classroom courses, the behavior on training and so on are also taken into account to make sure the training transfer score is with objective sources.
There are still potential limitations in this study. As S Company is one of few realty companies that implement e-learning, the study may not be necessarily comparable to other realty companies. Additionally, the results which are based on e-learning courses designed for new hired agents may not explain the learning effectiveness of all employees. Furthermore, the training transfer scores in this study only track the employees’ three months performance,
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which may not predict long-term performance in the future. Moreover, instruments of learning style are diverse and ILS is only one of them, which may not explain all employees’
learning preference especially when this study specifically focuses on visual-verbal learning preference by considering the characteristics of e-learning courses and tasks.
CHAPTER II. LITERATURE REVIEW
In this chapter, some terminology are addressed such as e-learning, task technology fit, individual characters and learning effectiveness, which The evaluation on employees’
learning effectiveness will follow the rationale of learning and behavior phase on Kirkpatrick ’s (1987) four levels evaluation model. Also, hypotheses of the research will be stated following the explanation of terminology.
E-Learning
E-learning has been trumpeted in the practitioner literature as one of the fastest growing (Martin, Massy, & Clarke, 2003). In 2009, the training industry was estimated to be worth
$90 billion worldwide, with $20 billion spent on e-learning (ASTD, 2009; Lam, 2009) and the e-learning market will be worth $40 billion by 2012 (Allen & Seaman, 2007; Garavan, Carbery, O’Malley, & O’Donnell, 2010; Insight, 2009; Jones, Moeeni, & Ruby, 2005).
Definitions of e-learning could be found in plenty of literature. Some of these definitions are listed as following:
1. Henry (2001) defined e-learning as the appropriate application of the Internet to support the delivery of learning, skills and knowledge in a holistic approach not limited to any particular courses, technologies, or infrastructures.
2. E-learning is defined as “the use of Internet technologies to deliver a broad array of solutions that enhance knowledge and performance” (Rosenberg, 2001, p. 28).
3. E-learning is Internet-enabled learning including the components of content delivery in multiple formats, management of the learning experience, and a networked community of learners, content developers and experts(Gunasekaran, McNeil, & Shaul, 2002).
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4. E-learning can be defined as a combination of training methods (Welsh, Wanberg, &
Brown, 2003).
5. E-learning is a set of methods which is designed for training in companies (Welle-Strand
& Thune, 2003).
6. E-learning can be defined as a “media training” (DeRouin, Fritzsche, & Salas, 2005).
7. E-learning is “a combination of content and instructional methods delivered by media elements such as words and graphics on a computer intended to build job-transferable knowledge and skills linked to individual learning goals or organizational performance”
(Mayer & Colvin, 2007).
Wallace, Kupperman, Krajcik, and Soloway (2000) found that it is considered a complex and difficult process for students to seek online information; to develop content comprehension for students and teachers through the internet is challenging. Ligorio (2001) indicated that only when students well knew the technologies and tools associated with each communication style, online learning activities with the various communication styles are considered valuable. Therefore, researchers concluded that previous research on e-learning specifically focuses on several issues: (1) the implementation of e-learning as an optional learning tool, (2) the learning process of e-learning and (3) learners’ acceptance of the mode and technology of e-learning (Davis, Bagozzi, & Warshaw, 1989; Hung & Cho, 2008;
Urquhart et al., 2005).
Through experiences in the West, most companies have understood that e-learning cannot be seen as a separate tool or technique but has to be integrated as part of daily jobs of employees and managers (Ali & Magalhaes, 2008). Figure 2.1 shows the model modified from Ali and Magalhaes (2008) who integrated literature of e-learning implementation found in Western economies.
Figure 2.1. Western model of e-learning implementation. Adopted from “Barriers to implementing e-learning: a Kuwaiti case study,” by Ali and Magalhaes (2008), International Journal of Training and Development, 12(1), p.40.
Rapid changing competitive environments
Rapid technological change ENVIRONMENTAL
TRENDS
Increased HR development efforts
Increased KM capacity E-LEARNING
ENABLERS
KEY E-LEARNING DRIVER
Capacity to respond to
Capacity to respond to