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A Case Study Analysis of Factors that Influence Attrition Rates in Voluntary Online Training Programs
Abstract
This article examines utilization of online training courses in a Midwest-based landscaping company in the United States. The company had implemented online training to facilitate employee development for their 5,000 employees who were in locations throughout the United States. The courses had been in place for about a decade before the organization attempted to evaluate their effectiveness. In the 14-month process of collecting data to evaluate course effectiveness, researchers discovered that only 21% of employees who enrolled in online training during this time period actually completed the training. This finding surprised researchers and company management and motivated an investigation into the causes underlying this high rate of attrition. Attrition survey data revealed that attrition was not due to dissatisfaction with course design, technology, or content. Rather, lack of time available both at work and at home was the principal factor that contributed to course attrition. Additional contributing factors included course enrollment procedures, low employee motivation, and employee turnover. Recommendations for implementation of online training in organizational settings are offered.
... The online course needs to have a high degree of usability to support participation in the program. Usability is a measure of how easily learners can complete the essential tasks associated with the course, such as enrolling in the course platform, navigating through the course, uploading assignments, posting in forums, watching video clips, or submitting quiz answers (Gamage et al., 2015;Heidig et al., 2015;Long et al., 2009). Learners who can complete these tasks with ease are more likely to be satisfied with the course, while those who struggle are less likely to be motivated to engage with course content and less likely to finish the course (Cho et al., 2009;Long et al., 2009). ...
... Usability is a measure of how easily learners can complete the essential tasks associated with the course, such as enrolling in the course platform, navigating through the course, uploading assignments, posting in forums, watching video clips, or submitting quiz answers (Gamage et al., 2015;Heidig et al., 2015;Long et al., 2009). Learners who can complete these tasks with ease are more likely to be satisfied with the course, while those who struggle are less likely to be motivated to engage with course content and less likely to finish the course (Cho et al., 2009;Long et al., 2009). While usability is essential for every online course, it may matter more in short, intensive courses, such as an online orientation, as learners are unwilling to invest much time learning a system they will only use briefly (Mulvaney, 2020). ...
... If a learner regularly encounters technology problems, their ability to learn course content and meet course objectives is at risk (Karthik et al., 2019). They may skip content or entire sections of the course or give up on completing the course altogether (Long et al., 2009). For learners who were not feeling particularly motivated to begin with, technology problems significantly increase the likelihood they will abandon a course (Cidral et al., 2018). ...
While asynchronous, self-paced online orientation programs are not brand new in the field of orientation, transition and retention, COVID-19 forced many institutions to rapidly create a program for the first time to help welcome fall 2020 students. Using the community of inquiry model as a framework, this literature review explores the research related to orientation and online learning in an effort to identify the principles, practices and processes that can help a student affairs professional to design an effective and engaging online orientation program, or enhance an existing program.
... Allowing faculty to fully engage in the module on their schedule is one benefit of self-paced faculty development courses [27]; however multiple benefits can be derived from taking part in a live discussion group or having other face-to-face interaction that complements online learning material and reduces the steep attrition observed in voluntary online training modules [28][29][30]. Once the entire AIM/Beach Mentor Program is rolled out, comparing future quiz scores from faculty members who opt for the self-paced option as compared to those who select the facilitated discussion may elucidate if the pressure to watch the videos 'on time' to meet the discussion deadline reduces retention about the material presented. ...
... Sessions for both cohorts were intentionally held in the middle of the semester so the program did not overlap with either the first weeks of instruction or final exams. Attrition in voluntary online training programs has been attributed to lack of professional and personal time, as opposed to a lack of interest in the material [30], and it may be that as AIM/Beach Mentor course continued, participants were more pressed for time. Completion of online training is also contingent upon the need or perceived value of the course by faculty members [31], making advertising of the program important to achieve buy-in by key stakeholders on campus. ...
Mentoring is key to ensure success of the high impact practice of undergraduate-led research and scholarly activities; however, most faculty and staff members are not trained in the best practices of mentoring undergraduate students. The National Institutes of Health-funded Building Infrastructure Leading to Diversity (NIH BUILD) Initiative at California State University Long Beach is developing an online mentor training program with a coordinated discussion group to refine mentoring skills across faculty and staff from all disciplines. Faculty and staff members participated in two pilots of the Advancing Inclusive Mentoring (AIM) Program, where participants watched training videos and came together to discuss mentoring: either face-to-face (spring 2020) or virtually (fall 2020). Participants indicated that the videos and discussion were engaging and reported that AIM provided useful information on communicating with their own mentees as well as with any student on campus. Participants also reported that AIM provided strategies to work with students from diverse backgrounds and strengthened their commitment to inclusive mentoring. Finally, participants indicated that they would recommend AIM to colleagues and that the program was not only beneficial to their mentoring, but also that they would put into practice techniques that they had learned. There were some differences in usage, but no significant differences in participants’ ratings of the program across the two delivery formats. Thus, the AIM Program with facilitated discussion appears to provide a useful mentor training experience in both in-person and virtual formats. Because this unique program is intentionally inclusive to faculty and staff mentors across all disciplines, the goal is that this training will ultimately benefit student success across campus.
... Few studies have focused on how computer anxiety affects distance training dropout and persistence (e.g., Long et al., 2009;Stiller & Köster, 2016;Stiller & Bachmaier, 2017a, 2017b. Long et al. (2009) investigated a training course for employees of a Midwest-based landscaping company in the U.S. and found no differences between dropout students and training completers. ...
... Few studies have focused on how computer anxiety affects distance training dropout and persistence (e.g., Long et al., 2009;Stiller & Köster, 2016;Stiller & Bachmaier, 2017a, 2017b. Long et al. (2009) investigated a training course for employees of a Midwest-based landscaping company in the U.S. and found no differences between dropout students and training completers. In contrast, Stiller and Köster (2016) reported a higher level of computer anxiety with dropout employees compared to persisting employees, but later studies revealed no differences between dropout and persisting students in a distance teacher-training environment about media education (Stiller & Bachmaier, 2017a, 2017b. ...
One focus of distance learning research is to explore the extent that learner characteristics and skills determine learning outcomes and to elaborate predictive models of performance. Modern approaches can benefit from objective data, such as various time indices and frequencies of learner actions, provided by log systems catching online traces to identify learners that are in threat of performance loss. This approach might result in better online diagnostics and intervention methods when the mechanisms behind log data are known. Following this idea, the current study gained objective and subjective study time parameters and explored how study time is connected to learner characteristics and learning by using a script-based modularized distance-training course about media education. Data was collected from 379 trainee teachers. Given a calculated workload of 60-90 min per training module, students were clustered into two groups: learners having spent less than 25 min for at least one of their completed modules (n = 118; short study time group) and learners having spent more than 25 min for each completed module (n = 261; long study time group). The first goal was to investigate the extent that study time is relevant for learning process and success. Groups were compared in their ratings of content difficulty, difficulty of studying, invested effort, and experienced pressure while learning, and their test performance. Differences between groups were found in all variables. The long study time learners experienced less content difficulty, studying difficulty, and pressure while learning, but reported more effort and showed higher performance. The second goal was to explore the effect of learner characteristics on study time. Groups were compared in their domain-specific prior knowledge, intrinsic motivation, computer attitude, computer anxiety, and use of learning strategies. Long study time learners showed a higher level of motivation, competences in metacognitive learning strategies, and strategy use for arranging an adequate learning environment. These findings revealed that study time is indicative of problematic students that could be targets for interventions.
... Current studies such as those by Chang et al. (2017), however, confirm a significant negative correlation. In addition, CANX was also related to higher dropout (Stiller & Köster, 2016, but also see Long et al., 2009;Stiller & Bachmaier, 2017a, 2017b, and lower performance levels (Desai, 2001;Hauser et al., 2012;Saadé & Kira, 2006;Sam et al., 2005;Stiller & Bachmaier, 2018). ...
Cite as: Stiller, K. D., & Wager, S. (2023). Modelling e-learning acceptance of clinical staff using the General Extended Technology Acceptance Model for E-Learning. The Online Journal of Distance Education and e-Learning, 11, 3084-3106. https://tojdel.net/journals/tojdel/articles/v11i04/v11i04-11.pdf ****** Companies still increasingly rely on online training to train employees continuously, effectively, and efficiently. The intention of employees in using e-learning, however, is influenced by various factors. In this study, the influence of external factors on the acceptance of online training was examined in an operational context according to the General Extended Technology Acceptance Model for E-Learning. In this model, computer experience, computer self-efficacy, computer anxiety, perceived enjoyment, and subjective norm were included as important external factors that have been shown to be relevant in numerous empirical studies. In operational contexts, few studies to date have investigated the acceptance model and even less in Europe or Germany. To investigate the influence of external factors, data of 113 employees from a medical institution were collected after participation in an online training course by means of an online questionnaire and were evaluated by regression analyses. The predictors computer experience, perceived enjoyment, and subjective norm were the strongest predictors of perceived usefulness (R2 = 0.59 of the complete model). The perceived ease of use was best explained by the factors computer experience, computer self-efficacy, computer anxiety, and enjoyment (R2 = 0.43 of the complete model). The attitude towards using e-learning and the intention to use e-learning in this study were mainly influenced by perceived usefulness (R2 = 0.67 and R2 = 0.59 of the complete models, together with perceived ease of use). Overall, the acceptance model was largely confirmed in this study.
... Among the students that accepted the course invitation (n = 102), the completion rate was 28%, higher than other similar studies reporting rates of participation in voluntary, online courses. 38,39 This completion rate reflects the optional, uncredited nature of the course, with limited incentives for students other than their own interests. Eighty-three percent of the PHPB student population work at least part-time, with most maintaining full-time employment outside their coursework. ...
OBJECTIVES
This study investigates the efficacy and feasibility of an asynchronous, peer-to-peer health disparities enrichment course on postbaccalaureate prehealth students’ knowledge, behaviors, and reaction to course materials.
INTRODUCTION
Growing awareness of social inequities has prompted educators of prehealth and medical students to explore student education by addressing systemic healthcare issues. This cross-sectional study assessed reactions, learning, and self-reported behavior changes in students after taking the course “Social Determinants, Disparities, and Preparing for the Future of Healthcare” (SDDH).
METHODS
The curriculum was designed by prehealth postbaccalaureate students for their peers. Course goals were to educate participants on social determinants of health and to build cultural and structural competence in their roles as future healthcare professionals. SDDH is an asynchronous, noncredit-bearing, 5-h online course with 10 modules covering various topics. The Kirkpatrick Model was used to assess the effectiveness of the curriculum, alongside qualitative and quantitative analyses of student performance.
RESULTS
Out of the 102 active students in the prehealth program that accepted the invitation to join, 29 students successfully completed the course (rate of completion = 28%). On average, students expressed positive reactions and attitudes toward the course and experienced an observable increase in knowledge assessment scores upon curriculum completion ( P-value = .0002). Students’ self-reported observations demonstrated sustained behavioral change 3 months after course completion.
CONCLUSION
It is critical to educate prehealth students on health disparities, structural, and cultural competence. A course such as SDDH may help prehealth students build effective communication skills for advocacy and develop an empathetic, patient-centered approach earlier on in their career pursuit. Some barriers to students completing the entire course include its length, uncredited status, and voluntary self-enrollment.
... The high attrition rate is something that needs to be addressed going forward, but is consistent with voluntary courses in similar fields. 22 Attrition may be addressed by: granting students credit towards a degree program or a certificate; choosing the right time to deliver the course, as per specific cohort feedback; utilizing a hybrid format to allow for remote attendance by some individuals some of the time; connecting with interested students/groups, such as those at the Schools of Engineering and Business. ...
Background/Objective
A growing number of biomedical doctoral graduates are entering the biotechnology and industry workforce, though most lack training in business practice. Entrepreneurs can benefit from venture creation and commercialization training that is largely absent from standard biomedical educational curricula. The NYU Biomedical Entrepreneurship Educational Program (BEEP) seeks to fill this training gap to prepare and motivate biomedical entrepreneurs to develop an entrepreneurial skill set, thus accelerating the pace of innovation in technology and business ventures.
Methods
The NYU BEEP Model was developed and implemented with funding from NIDDK and NCATS. The program consists of a core introductory course, topic-based interdisciplinary workshops, venture challenges, on-line modules, and mentorship from experts. Here, we evaluate the efficacy of the core, introductory course, “Foundations of Biomedical Startups,” through the use of pre/post-course surveys and free-response answers.
Results
After 2 years, 153 participants (26% doctoral students, 23% post-doctoral PhDs, 20% faculty, 16% research staff, 15% other) have completed the course. Evaluation data show self-assessed knowledge gain in all domains. The percentage of students rating themselves as either “competent” or “on the way to being an expert” in all areas was significantly higher post-course ( P < 0.05). In each content area, the percentages of participants rating themselves as “very interested” increased post-course. 95% of those surveyed reported the course met its objectives, and 95% reported a higher likelihood of pursuing commercialization of discoveries post-course.
Conclusion
NYU BEEP can serve as a model to develop similar curricula/programs to enhance entrepreneurial activity of early-stage researchers.
... Most studies about distance learning have investigated the influence of computer anxiety on learning, based on the assumption that anxiety directly influences self-efficacy, which influences computer usage and performance (Desai, 2001;Hauser, Paul, & Bradley, 2012;Saadé & Kira, 2009;Sam et al., 2005). These studies have found that computer anxiety is related to higher dropout (Stiller & Köster, 2016, but also see Long et al., 2009;Stiller & Bachmaier, 2017, lower levels of perceived ease of use of learning environments (Abdullah & Ward, 2016;Baki, Birgoren, & Aktepe, 2018), and lower performance levels (Desai, 2001;Hauser et al., 2012;Saadé & Kira, 2009;Sam et al., 2005;Stiller & Bachmaier, 2018). Blignaut et al. (2005) summarized that computer anxiety was often conceptualized in the early research on computer anxiety as a component of attitude and that the concepts of computer anxiety and negative attitude toward computers were used interchangeably. ...
Cite as: Stiller, K. D., & Bachmaier, R. (2019). Predicting ease of studying and learning success from learner characteristics in a distance training for in-service teachers. The Online Journal of Distance Education and e-Learning, 7, 295-309. Available from https://tojdel.net/journals/tojdel/articles/v07i04/v07i04-04.pdf
****** Abstract: How to support students in successful learning is one of the persisting problems of distance and online learning. One research focus that can inform educators is to explore the extent that learners’ characteristics and skills determine learning. Thus, this study explores the effects of domain-specific prior-knowledge, intrinsic motivation, computer attitude, computer anxiety, and learning management skills on learning in a training course about media pedagogy for teachers. The data were collected from 49 in-service teachers who answered various questionnaires and took knowledge tests. By using regression analyses, we investigated the extent that the selected learner characteristics account for ratings of content difficulty, studying difficulty, experienced pressure/tension, and effort/importance while learning and for performance. Content difficulty was best predicted by computer anxiety and studying difficulty by computer anxiety and intrinsic motivation. The experienced pressure/tension was best predicted by intrinsic motivation and time management skills. Effort/importance was best predicted by meta-cognitive skills and performance by meta-cognitive skills and prior knowledge.
Gamification refers to the application of game design elements in non-game environments for the purpose of engaging users, motivating action, facilitating learning, and solving problems. Self-directed electronic learning (SDEL) is one of the favorite learning environments for many adult learners and is an environment where gamification is often applied. However, there is still a “one-size-fits-all” approach to gamification in many e-learning environments, and most gamification is still dominated by PBL (points, badges, leaderboards).Personalization is defined as “the process of changing the functionality, interface, information content, or uniqueness of a system to increase its relevance to the individual”. Personalization gives the user a greater sense of control, and this increased perceived control is related to the level of enjoyment of the user experience. Therefore, there is a need to create a personalized design with “learner-centered” gamification elements.Through user interviews and empirical research, this paper proposes evaluation dimensions for personalized design of SDEL gamification elements from the perspective of “system-user” interaction: Rewards, Entertainment, Social interaction, and Visual appeal, and provides guidance solutions for designers of e-learning platforms to personalize the design of gamification elements.KeywordsSelf-directed Electronic LearningGamification ElementPersonalized Design
Stimulation of Organizational Performance (OP) is a priority in all organizations due to its direct relationship with value creation. Effective electronic Human Resource Management (e-HRM practices) brings success to an organization. A gap exists in the literature on the effect of Workforce Agility (WFA) on organizational outcomes that influence firm behavior. Due to ambiguous outcomes, managers are reluctant to invest in WFA. The telecommunications sector in Jordan is among its greatest performers during the last decade, but growth and revenues have begun to decline in 2012. This negatively affected HR practices using to modern technologies. The main purpose of this study is to investigate the impact of e-HRM on OP and WFA, as well as the mediating effect of WFA on the relationship between e-HRM Usage and OP. Three hundred and thirty-five (335) questionnaires were distributed to sample employees in all Jordanian mobile telecommunication firms (Zain Jordan, Orange Jordan, and Umniah), selected through proportional stratified random sampling. 236 valid questionnaires were retrieved (70.44% response rate).
The study made use of PLS-SEM to conduct rigorous procedures to establish the validity and reliability of the outer model before testing the overall study model. This is in line with the standard SEM data analysis procedure. After the establishment of the validity and reliability of the measurement model, the researcher tested the hypothesized relationships and examined the predictive power of the model to confirm its goodness of fit.
The findings demonstrated support for four out of six hypotheses. In particular, there were significant relationships between E-Recruitment (ER), E-Selection (ES), E-Compensation (ECOP), and E-Performance Appraisal (EPA) with the predicted OP construct, but there was no significant relationship between E-Training (RT) and E-Communications (ECOM) with OP. Also, all research hypotheses concerning significant relationships between e-HRM dimensions and WFA were supported. Additionally, research hypothesis between WFA and OP were significantly supported. There was full mediation for WFA between ET and ECOM with OP as well as a partial mediation for WFA between ER, ES, and EPA with OP. No mediation effect for WFA between ECOP and OP was found. The current study enriches knowledge on the influence of ER, ES, ET, EPA, and ECOM on OP through WFA. Hence, it is recommended that Jordanian mobile telecommunication firms focus on WFA as it changes the relationship between e-HRM practices and OP.
Considerable research has been conducted on the effects of various learning delivery modes in an academic environment. However, the number of studies that look into learning delivery modes effects in professional environment are scarce. In the context of a large professional public-sector organization, this research attempts to identify roles played by prospective participants' perceptions on different learning delivery modes into their decisions on participating in organized training programs. The study focuses on Face-to-Face, Online, and Blended modes of learning to conduct research. It utilizes an online survey to collect and analyze data from past participants of administered training sessions by the organization. By incorporating a combination of qualitative as well as quantitative questions in the survey, the study collects data on participant satisfaction, familiarity, and overall perceptions on various learning delivery modes. The findings from the study identify that participants value social interaction and networking opportunities offered at a training session. It also identifies that even though participants may have their personal preferences towards various learning delivery modes, they are mostly open to the idea of learning in a different mode, provided a conducive learning environment is created.
Although there are many reasons why students dropout of college courses, those reasons may be unique for students who are enrolled in an online program. Issues of isolation, disconnectedness, and technological problems may be factors that influence a student to leave a course. To understand these factors, an online survey was developed to collect data from students who dropped out of an online program. Logistic regression analysis was used to compare various factors between those who persist in the program and those who dropout. The results, based on the dropouts from three cohorts in an online graduate program, show that demographic variables do not predict likelihood of dropping from a program. Instead, the students' reasons for dropping out of an online program are varied and unique to each individual. Recommendations for further study are incorporated in the conclusions.
Employees with access to e-learning courses targeting computer skills were tracked during a year-long study. Employees' perceptions of peer and supervisor support, job characteristics (such as workload and autonomy), and motivation to learn were used to predict total time spent using e-learning. Results suggest the importance of motivation to learn and workload in determining aggregate time spent in e-learning courses. Time in courses predicted subsequent differences in computer-related skill and performance improvement as judged by participants' supervisors. Implications of these findings for the design and administration of e-learning programs are discussed.