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Journal Article

Conceptualization and Measurement of Perceived Risk of Online Education

01 Jan 2011-The Academy of Educational Leadership Journal (The DreamCatchers Group, LLC)-Vol. 15, Iss: 4, pp 1
TL;DR: In this article, Allen et al. developed a scale for measuring multiple dimensions of perceived risk in online education programs and found that social factors constitute an important dimension of the perceived risk associated with online education.
Abstract: INTRODUCTION Online education (OE) is coming of age. Over the past few years, a stream of technological innovations, from video streaming to virtual online classrooms, has allowed educational institutions and their faculty members the opportunity to experiment with new teaching methods and to offer new types of degree programs beyond the traditional classroom setting. As a result, students are able to enhance their knowledge and to earn degrees without leaving their jobs and families, and in some cases, without setting foot on a college campus. Today's OE programs can allow students to attain their educational goals in a manner that is flexible, convenient and cost effective (Furst-Bowe & Dittmann, 2001; Anderson, Banks & Leary, 2002). The question is, how do they perceive this opportunity? That is, do students perceive online programs as comparable to on-campus work, or do they perceive such offerings as higher risk alternatives? Recent trends appear to suggest that perceptions of OE are becoming more positive. In the five year period from 2002-2007, the number of online students more than doubled (Allen & Seaman, 2008). During the fall 2007 term, nearly 3.9 million students, approximately 20-25% of all students in U.S. colleges, took at least one online course. While many of these students are off-campus students with a wide variety of ages, work experience and family circumstances, about half of all online enrollments are estimated to be traditional students seeking online courses for reasons of convenience (Mayadas, Bourne and Bacsich, 2009). Most of these students are at public institutions; more than two-thirds of all higher education institutions in the United States have implemented some form of online offerings (Allen & Seaman, 2007). Yet, research has shown that the perceptions of people about risk rarely coincide with the actual risk of certain activities (Kaspar, 1979). Moreover, in the context of OE, there is no comprehensive research that measures the way that people assess multiple aspects of risk in relation to their intention to enroll. That is, they may be attracted to this form of education for its convenience, while at the same time, concerned about its effectiveness, their ability to communicate with other students, or their likelihood of success. Understanding these factors is important in the short run, because they may differentially affect students' intention to enroll in online classes at all or their decision to enroll in one program versus another (Campbell and Goodstein, 2001). In the long run, a better understanding of the risks associated with OE may help faculty and administrators to influence the learning process in a positive way. For instance, if social factors constitute an important dimension of the perceived risk associated with OE, then programs can be designed to enhance interaction throughout the learning process using processes that range from old-fashioned team assignments to technologically driven virtual classrooms. Consequently, this study takes the first steps in developing a scale for measuring multiple dimensions of perceived risk in OE programs. The study is organized as follows: First, it describes the notion of perceived risk in OE and defines the types of perceived risk in the OE context. Second, the study creates the item pool that matches the potential dimensions of perceived risk in the OE context and ensures construct validity by using focus groups and a panel of experts to judge the face validity of the construct. Third, the study relates the dimensions of perceived risk to a variety of student demographics to see how different students view online education. THE NOTION OF PERCEIVED RISK IN OE Mitchell (1998) defines risk as "the variation in the distribution of possible outcomes, their likelihood and their subjective values" (Mitchell, 1998). The decision to enroll in an online class involves risk because doing so could lead to unexpected or uncertain consequences, some of which could be negative. …
Citations
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Journal ArticleDOI
TL;DR: In this article, the authors explore how the personality traits of hospitality students are associated with their level of anxiety and how their learning experience is affected by the recent COVID-19 pandemic.
Abstract: The recent COVID-19 pandemic has forced all teaching and learning activities to shift to online platforms. Hospitality students are not exempted from this transition even though they are used to offline learning environment and often take a blended learning of theoretical and practical components. This sudden change has caused disruptions in their learning process and created all kinds of anxieties. Thus, this study aimed to explore how the personality traits of hospitality students are associated with their level of anxieties and how their learning experience is affected. A survey was conducted in Hong Kong shortly after the affected semester ended. Results showed that students with high levels of agreeableness and openness to experience perceive a high degree of learning, technical, and financial anxiety. By contrast, students with high levels of conscientiousness, extraversion, and neuroticism partially sense a low degree of these anxieties. Results also revealed that a low degree of learning and financial anxiety can enhance students’ perceived online learning and consequently improve student satisfaction. Theoretical development and managerial implications are further discussed.

28 citations

Journal ArticleDOI
TL;DR: In this article, a study is done by the researchers to understand the impact of perceived risk on youth of Pune on their online shopping, the finding of the study are the buyers have maximum perceived risk regarding financial risk, social risk, time risk and last but not the least, security risk.
Abstract: Although the online shopping is on rise on daily basis, but online shopping is not done by everybody. Perceived risk is one of the big hurdles in online shopping. Measuring this aspect & finding the details of it & implementing the ways to reduce it will increase online shopping. The current study is done by the researchers to understand the impact of perceived risk on youth of Pune on their online shopping. To study, factor analysis as research tool has been taken. The finding of the study are the buyers have maximum perceived risk regarding financial risk, social risk, time risk and last but not the least, security risk. Non shoppers give maximum value to financial risk and Security risk which are common to shoppers also additional two risks are physical risk and psychological risks

13 citations


Additional excerpts

  • ...21)Mohamed, F. A. (2011)....

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Journal ArticleDOI
TL;DR: In this article, the authors investigated how the employees' attributes, capabilities, behavioral control and behavioral intentions affect their intention to become a supply chain manager (SCM), and found that attributes are the most crucial factors for the capabilities of employees to become successful SCM.
Abstract: This study aims to investigate how the employees' attributes, capabilities, behavioral control and behavioral intentions affect their intention to become a supply chain manager (SCM). The study also investigates how employees' capabilities mediate the relationship between attributes and intention to become SCM.,The purposive sampling frame is employed to collect the data, and multiple statistical tools and techniques are used for analyzing the data.,The findings reveal that attributes are the most crucial factor for the capabilities of employees to become successful SCM. Employees' behavioral intention and capabilities have a significant impact on intention, whereas perceived behavioral control has a significant negative impact on it. Also, the result finds that capabilities partially mediate the relationship between attributes and intention to become an SCM.,The study extends the application of employees' intention to become a supply chain manager. The idea collected is based on Malaysia; thus, further study should be extended to assess the impact of employees' attributes, capabilities and behavioral control to become SCM as well as economic performance in other countries.,To the best of the authors' knowledge, this is the first empirical analysis on the relationship between employees' attributes, capabilities, behavioral control and intention to become SCM in the context of Malaysia. The findings will help the top management to select the right people as SCM and improve their attributes, capabilities and behavior so that they become an effective SCM.

12 citations

Journal ArticleDOI
01 Dec 2012
TL;DR: Investigation of key determinants that influence the students| intention to enrol on an online MBA programme and the moderating effect of demographic variables, namely age and gender, to the relationship model shows that intrinsic motivation, computer self-efficacy, acceptance technology and social risk are the four most essential individual determinants of students | intention.
Abstract: This study aims to investigate the key determinants that influence the students| intention to enrol on an online MBA programme and examine the moderating effect of demographic variables, namely age and gender, to the relationship model. 180 questionnaires were distributed to the adult who has obtained at least a Bachelor|s degree and the response rate of 67% was obtained. The analysis was carried out to look at which group is significantly influencing the intention via the multiple regression analysis and tests if the influence moderated by the demographic variables using the hierarchical regression analysis. The findings revealed that three key groups of determinants: individual, technology and the risks perceived, were affecting the students| intention to enrol an online MBA programme. Further analysis shows that intrinsic motivation, computer self-efficacy, acceptance technology and social risk are the four most essential individual determinants of students| intention. It was also found that the influence of perceived risks towards the intention would be stronger among the higher age group. Accordingly, the study provides the policymakers in the field of higher education insight into what is taking place in the domain of virtual campuses and means to set up a sustainable initiatives and strategies for a successful online education.

9 citations


Cites background or methods from "Conceptualization and Measurement o..."

  • ...According to Mohamed and Hassan (2008), online learning provides the flexibility to those who have competing responsibilities and priorities of work, family and school and, hence, they are able to obtain degrees without setting their foot in a college campus, avoid travelling long distances leaving…...

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  • ...Five items, which are adapted from the research study of Saadé et al. (2009); and Mohamed and Hassan (2008) are identified as measurement scales for the DV....

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  • ...Four constructs with the total of 14-item scale, are adapted from a study conducted by Mohamed and Hassan (2008)....

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  • ...Four factors, i.e., performance risk, time-loss risk, psychological and source risk were found strongly predictive of online education enrolment according to Mohamed and Hassan (2008)....

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01 Jan 2019
TL;DR: Employee Resistance to Disruptive Technological Change in Higher Education by Barbara Ann Miller MBA, Open University, UK, 2007 Doctoral Study Submitted in Partial Fulfillment of the Requirements for the Degree of Doctor of Business Administration Walden University April 2019 as discussed by the authors.
Abstract: Employee Resistance to Disruptive Technological Change in Higher Education by Barbara Ann Miller MBA, Open University, UK, 2007 Doctoral Study Submitted in Partial Fulfillment of the Requirements for the Degree of Doctor of Business Administration Walden University April 2019 Abstract Employees can be resistant to work-based change, specifically when the change is due to disruptive or new technology. The purpose of this descriptive phenomenological study was to explore the lived experiences of 20 Swiss-based educational employees adapting to online technologies introduced in their workplaces. Disruptive innovation theory provided the conceptual framework for the study. Data were collected using semistructured interviews with 20 purposely selected participants from 3 Swiss-based higher education campuses. The modified Van Kaam method was used to organize and analyze the data. Four themes from participants’ responses were identified: educational employees are not resistant to technology-based change, educational employees can move forward and become excited even when frustrated, educational managers should develop commitment and a project-based focus to reduce additional expenditure of time and effort, and continued experience and personal development can enable technology use and reduce resistance. Findings from the study may be used to reduce employees’ resistance to technological-based change in higher education. The successful development and use of online education tools by educators provides society with choices, mobility, flexibility, and a personalized approach to learning.Employees can be resistant to work-based change, specifically when the change is due to disruptive or new technology. The purpose of this descriptive phenomenological study was to explore the lived experiences of 20 Swiss-based educational employees adapting to online technologies introduced in their workplaces. Disruptive innovation theory provided the conceptual framework for the study. Data were collected using semistructured interviews with 20 purposely selected participants from 3 Swiss-based higher education campuses. The modified Van Kaam method was used to organize and analyze the data. Four themes from participants’ responses were identified: educational employees are not resistant to technology-based change, educational employees can move forward and become excited even when frustrated, educational managers should develop commitment and a project-based focus to reduce additional expenditure of time and effort, and continued experience and personal development can enable technology use and reduce resistance. Findings from the study may be used to reduce employees’ resistance to technological-based change in higher education. The successful development and use of online education tools by educators provides society with choices, mobility, flexibility, and a personalized approach to learning. Employee Resistance to Disruptive Technological Change in Higher Education by Barbara Ann Miller MBA, Open University, UK, 2007 Doctoral Study Submitted in Partial Fulfillment of the Requirements for the Degree of Doctor of Business Administration Walden University April 2019 Dedication I dedicate this study to my family, friends, fellow business leaders, and educators. All have offered support, interest, curiosity, and learning needed to write and reach this milestone. I also dedicate the outcome to my feline companions as they checked on me often. Acknowledgments I would like to acknowledge all professors at Walden University who have guided me in courses, residencies, and the final doctoral process. I would especially like to thank Dr. Abou-Robieh, my committee chair, for his continuous ideas, supporting comments, and patience. My review committee members have also offered valued support, suggestions, and learning. I would also like to thank all those who participated in the study of their valuable experiences, the research site directors for allowing me access, and my employers for having faith in supporting my continuous professional development. Thank you also to my doctoral study APA and grammar editors. I also acknowledge all qualitative and especially phenomenological researchers. The domain is both critical in the search for knowledge and the understanding of human behavior. I encourage business leaders to take part in similar qualitative research that can offer valuable insights into the human dimension of business-based dilemmas.

7 citations


Cites background from "Conceptualization and Measurement o..."

  • ...Burgi (2009), Mohamed et al. (2011), and Seaman (2011) have examined how the Internet has influenced learning and has changed the way universities supply education....

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References
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Journal ArticleDOI
01 Jan 1973
TL;DR: In this paper, a six-step framework for organizing and discussing multivariate data analysis techniques with flowcharts for each is presented, focusing on the use of each technique, rather than its mathematical derivation.
Abstract: Offers an applications-oriented approach to multivariate data analysis, focusing on the use of each technique, rather than its mathematical derivation. The text introduces a six-step framework for organizing and discussing techniques with flowcharts for each. Well-suited for the non-statistician, this applications-oriented introduction to multivariate analysis focuses on the fundamental concepts that affect the use of specific techniques rather than the mathematical derivation of the technique. Provides an overview of several techniques and approaches that are available to analysts today - e.g., data warehousing and data mining, neural networks and resampling/bootstrapping. Chapters are organized to provide a practical, logical progression of the phases of analysis and to group similar types of techniques applicable to most situations. Table of Contents 1. Introduction. I. PREPARING FOR A MULTIVARIATE ANALYSIS. 2. Examining Your Data. 3. Factor Analysis. II. DEPENDENCE TECHNIQUES. 4. Multiple Regression. 5. Multiple Discriminant Analysis and Logistic Regression. 6. Multivariate Analysis of Variance. 7. Conjoint Analysis. 8. Canonical Correlation Analysis. III. INTERDEPENDENCE TECHNIQUES. 9. Cluster Analysis. 10. Multidimensional Scaling. IV. ADVANCED AND EMERGING TECHNIQUES. 11. Structural Equation Modeling. 12. Emerging Techniques in Multivariate Analysis. Appendix A: Applications of Multivariate Data Analysis. Index.

37,124 citations

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TL;DR: In this paper, the authors discuss the role of measurement in the social sciences and propose guidelines for scale development in the context of scale-based measurement. But, the authors do not discuss the relationship between scale scores and scale length.
Abstract: Chapter 1: Overview General Perspectives on Measurement Historical Origins of Measurement in Social Science Later Developments in Measurement The Role of Measurement in the Social Sciences Summary and Preview Chapter 2: Understanding the "Latent Variable" Constructs Versus Measures Latent Variable as the Presumed Cause of Item Values Path Diagrams Further Elaboration of the Measurement Model Parallel "Tests" Alternative Models Exercises Chapter 3: Reliability Continuous Versus Dichotomous Items Internal Consistency Relability Based on Correlations Between Scale Scores Generalizability Theory Summary and Exercises Chapter 4: Validity Content Validity Criterion-related Validity Construct Validity What About Face Validity? Exercises Chapter 5: Guidelines in Scale Development Step 1: Determine Clearly What it Is You Want to Measure Step 2: Generate an Item Pool Step 3: Determine the Format for Measurement Step 4: Have Initial Item Pool Reviewed by Experts Step 5: Consider Inclusion of Validation Items Step 6: Administer Items to a Development Sample Step 7: Evaluate the Items Step 8: Optimize Scale Length Exercises Chapter 6: Factor Analysis Overview of Factor Analysis Conceptual Description of Factor Analysis Interpreting Factors Principal Components vs Common Factors Confirmatory Factor Analysis Using Factor Analysis in Scale Development Sample Size Conclusion Chapter 7: An Overview of Item Response Theory Item Difficulty Item Discrimination False Positives Item Characteristic Curves Complexities of IRT When to Use IRT Conclusions Chapter 8: Measurement in the Broader Research Context Before the Scale Development After the Scale Administration Final Thoughts References Index About the Author

11,710 citations

Book
05 Jun 1991
TL;DR: Measurement in the Broader Research Context Before the Scale Development After the Scale Administration Final Thoughts References Index about the Author.
Abstract: Chapter 1: Overview General Perspectives on Measurement Historical Origins of Measurement in Social Science Later Developments in Measurement The Role of Measurement in the Social Sciences Summary and Preview Chapter 2: Understanding the "Latent Variable" Constructs Versus Measures Latent Variable as the Presumed Cause of Item Values Path Diagrams Further Elaboration of the Measurement Model Parallel "Tests" Alternative Models Exercises Chapter 3: Reliability Continuous Versus Dichotomous Items Internal Consistency Relability Based on Correlations Between Scale Scores Generalizability Theory Summary and Exercises Chapter 4: Validity Content Validity Criterion-related Validity Construct Validity What About Face Validity? Exercises Chapter 5: Guidelines in Scale Development Step 1: Determine Clearly What it Is You Want to Measure Step 2: Generate an Item Pool Step 3: Determine the Format for Measurement Step 4: Have Initial Item Pool Reviewed by Experts Step 5: Consider Inclusion of Validation Items Step 6: Administer Items to a Development Sample Step 7: Evaluate the Items Step 8: Optimize Scale Length Exercises Chapter 6: Factor Analysis Overview of Factor Analysis Conceptual Description of Factor Analysis Interpreting Factors Principal Components vs Common Factors Confirmatory Factor Analysis Using Factor Analysis in Scale Development Sample Size Conclusion Chapter 7: An Overview of Item Response Theory Item Difficulty Item Discrimination False Positives Item Characteristic Curves Complexities of IRT When to Use IRT Conclusions Chapter 8: Measurement in the Broader Research Context Before the Scale Development After the Scale Administration Final Thoughts References Index About the Author

10,722 citations


"Conceptualization and Measurement o..." refers background in this paper

  • ...correlations greater than .50 with squared multiple correlations of more than .30 ( DeVellis, 1991,...

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  • ...DeVellis (1991) , and Spector (1992) in generating perceived risk in OE item pool, purifying the...

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  • ...satisfaction. This was followed by two focus groups as DeVellis (1991) suggests....

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  • ...conceptual and logical true variance present in the construct (Churchil, 1979; DeVellis, 1991; ...

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Book
01 Jan 1986
TL;DR: In this article, the authors focus on a conceptual understanding of the material rather than proving results and stress the importance of checking the data, assessing the assumptions, and ensuring adequate sample size so that the results can be generalized.
Abstract: This best-selling text is written for those who use, rather than develop, advanced statistical methods. Dr. Stevens focuses on a conceptual understanding of the material rather than proving results. Helpful narrative and numerous examples enhance understanding, and a chapter on matrix algebra serves as a review. Printouts from SPSS and SAS with annotations indicate what the numbers mean and encourage interpretation of the results. In addition to demonstrating how to use the packages effectively, the author stresses the importance of checking the data, assessing the assumptions, and ensuring adequate sample size (by providing guidelines) so that the results can be generalized. The new edition features a CD-ROM with the data sets and many new exercises. Ideal for courses on advanced or multivariate statistics found in psychology, education, and business departments, the book also appeals to practicing researchers with little or no training in multivariate methods. Prerequisites include a course on factorial analysis of variance. It does not assume a working knowledge of matrix algebra.

10,221 citations

Book
26 Nov 1991
TL;DR: The theory of summated rating scales was introduced in this paper, where the authors defined the construct of the scale and designed the scale, and conducted the item analysis to validate reliability and reliability.
Abstract: Introduction Theory of Summated Rating Scales Defining the Construct Designing the Scale Conducting the Item Analysis Validation Reliability and Norms Concluding Remarks

1,701 citations

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What is the perceived risk when purchasing an executive education course?

The provided paper is about the conceptualization and measurement of perceived risk of online education. It does not provide information about the perceived risk when purchasing an executive education course.