Factors Driving Learner Success in Online Professional Development

This study examined factors that contributed to the success of online learners in an online professional development course. Research instruments included an online survey and learners’ activity logs in an online professional development course for 512 in-service teachers. The findings showed that there were several factors affecting online learners’ success in online professional development. In addition, there were also significant differences between successful and unsuccessful online learners in terms of course login frequency and learning activities viewed.

ISSN 1492-3831 (numérique) Découvrir la revue Citer cet article Vu, P., Cao, V., Vu, L. & Cepero, J. (2014). Factors Driving Learner Success in Online Professional Development. International Review of Research in Open and Distributed Learning,15(3), 120-139. https://doi.org/10.19173/irrodl.v15i3.1714 Résumé de l'article This study examined factors that contributed to the success of online learners in an online professional development course. Research instruments included an online survey and learners' activity logs in an online professional development course for 512 in-service teachers. The findings showed that there were several factors affecting online learners' success in online professional development. In addition, there were also significant differences between successful and unsuccessful online learners in terms of course login frequency and learning activities viewed.

Introduction
Professional development refers to the process of learning and keeping up-to-date in one's area of expertise both for personal development and for career advancement.
Those who engage in professional development are interested in increasing their own skills/knowledge, enhancing their ability to do their work, and lifelong learning.
Professional development includes all the natural learning experiences and those conscious and planned activities which are intended to be of direct or indirect benefit to the individual, group or school and which contribute through these to the quality of education in the classroom. (Day, 1999, p. 4) In teacher education, professional development generally refers to ongoing learning opportunities available to teachers and other education personnel. In the United States, the need for professional development of school staff came to the forefront in the 1960's (Murphy-Latta, 2008). With schools today facing numerous complex challenges -from working with an increasingly diverse population of students, to meeting rigorous academic standards and goals, to integrating new technology in the classroomauthorities continue to stress the need for teachers to be able to enhance and build on their instructional knowledge. Under these challenges, the education and professional development of teachers is considered as the central component of educational improvement (Hawley & Valli, 1999).
It is reported that the ongoing, job-embedded, professional growth of teachers will lead to high achieving schools (Kelleher, 2003). Essentially, professional development has been adopted as a policy solution to improving the number of highly qualified teachers as well as helping all students to achieve high academic standards (Colbert, Brown, Choi, & Thomas, 2008).

Online Professional Development (OPD)
Online teacher professional development (OPD) is popular due to the need for professional development that can fit teachers' busy schedules and that provides access, as well as ongoing support, to important resources not otherwise affordable or even available locally (Dede et. al, 2009). OPD provides flexibility by allowing participants, irrespective of location, to manage educational pursuits with work and personal responsibilities (Stanford-Bowers, 2008). In addition, OPD can be offered in various forms: distance learning classrooms enabling individuals to participate in a class via video conferencing with the goal of making the online experience as close as possible to an in-class experience; an online asynchronous course negating the need for all the participants of a course to be available at the same time and allowing participants to complete course requirements according to their individual schedule; and self-paced

Literature Review
Online education literature is often characterized by its focus on "how to" teach online and how to optimally utilize the various features available in most instructional platforms, generally based on authors' experiences teaching in this setting or on instructors' feedback. There is less evidence of student-oriented analysis such as online student behaviors, performances, attitudes, or preferences (Beaudoin, Kutz, & Eden, 2009 The Characteristics of Successful Online Learners Palloff and Pratt (2001) listed the characteristics of successful online learners.
According to the researchers, successful learners are seen as volunteers seeking further education, having higher expectations, being more self-disciplined, older, enjoying learning for its own sake, demonstrating good thinking skills, able to work independently with limited structure, and recognizing the value of interacting with other online peers.
Boyd (2004)  characteristics, which successful online students tend to exhibit and possess. In terms of technical issues, a successful online student must possess appropriate technology and the skills to use that technology effectively. Regarding environmental factors, students must have an appropriate management of time and space, as well as support from significant others. As far as personal factors are concerned, the students must possess a healthy balance between autonomy and interactivity, self-motivation and self-discipline, and a high level of integrity. Finally, the students must possess various learning characteristics such as a more independent learning style that tends toward a more selfdirected learning orientation, as well as better-than-average reading and writing skills.
Recently, Beaudoin, Kutz, and Eden (2009) administered a 58-item survey to 318 respondents in four cohorts: Western (mostly the U.S.), Japan, Mexico, and Israel. One of the research problems of the study was to find out the items critical to learner success in e-learning. The questionnaire listed 10 items generally considered to be critical elements for successful online learning and then asked respondents to add two additional ones of their own. It should be noted that as participants were from different countries, it is possible that they had different responses because of their respective cultures. As a result, the researchers reported their findings according to cohorts.
The majority of the participants indicated that success of online learners ultimately depended more on self-determination than on institutional support. Except for the Mexican respondents, the strongest determinants for success among these online learners were related to learner attributes such as self-motivation, followed by time management, then capacity to learn with limited support. This result would indicate that, for most of these students, online learning success emanates from the learner, rather than from characteristics related to the learning environment such as courses.
The least critical items to the respondents were: ability to cope with unstructured settings, familiarity with technology, and relationships with other online learners.
In agreement with findings by Beaudoin et. al (2009), Sun (2014 reported results obtained from qualitative and quantitative data that online learning success came from learners. The participants in Sun commented that self-motivation, self-directed learning, and self-regulation of learning were the key factors in online learning success. The factor of self-regulation of learning includes skills such as setting goals, orienting action accordingly, planning, monitoring, asking for help when needed, trying out different strategies, and reflecting (Guichon, 2009;Hurd, 2006;Wang, 2010).
Learner self-efficacy is critical in online learning (Cho & Jonassen, 2009;Cho, Shen, & Laffey, 2010) and can be a key factor in this challenging learning environment (Hodges, 2008). A significant, moderate, and positive relationship between online technological self-efficacy and online academic achievement was found in McGhee (2010). Womble (2008) found a significant and positive correlation between e-learning self-efficacy and e-learner satisfaction. In addition, computer self-efficacy was a significant predictor of online learners' satisfaction and their intention to take future online courses (Lim, 2001 Successful participants on average spent 4 hours and 59 minutes attending and/or watching the web-videoconferencing sessions in Adobe Connect while unsuccessful counterparts only spent 2 hours and 18 minutes.
Significant differences were also found in passing rates across institutions and disciplines. The number of successful participants was significantly higher in particular institutions. Academics from particular specialty areas were more likely to drop out.
However as not all institutions and disciplines had a sufficiently large sample size, more research is needed to generalize the conclusion that institutional and disciplinary differences influence learner success. In terms of technological competencies, the researchers did not find any indication that the technological pedagogical content knowledge appeared to affect the retention of participants on the OPD program. Indeed, previous experience with technology did not seem to impact upon engagement and retention. Methodology Data for this study were collected from two different sources for the triangulation purpose to increase the reliability and validity of the findings. Those sources included an online survey and learners' activity logs in an online professional development course for 512 in-service teachers. Heiervang and Goodman (2011) held that online surveys may have advantages in terms of the speed and cost of data collection as well as data quality. However, they may be biased by low and selective participation. To minimize the disadvantages of the online survey, we used learners' activity logs as an existing data source. According to Shultz, Hoffman, and Reiter-Palmon (2005), existing data are objective and relatively easy to transfer and store, but they are also not always a perfect fit between what the researchers are trying to measure and the purposes for which the data were collected. To reduce the drawbacks of those sources of data, the triangulation process was used. According to Maxwell (2005), the triangulation process of collecting information from different sources using a variety of methods reduced the risk that conclusions would reflect systematic biases and allowed a broader understanding of the study's issues. The comparison of data gathered supported the triangulation process and therefore enhanced internal validity. Efforts to control any threats to theoretical validity were also conducted by collecting and drawing attention to any discrepant data or alternative explanations.

Data Collection Procedures
In 2013, we hosted an open online professional training course in computer-assisted language learning (CALL) for 512 in-service language teachers from 23 countries. This six week long course was the first course of our professional development course series whose goal was to improve language teachers' technology competences. At the end of the training course, 153 learners who completed the course with the total grade of at least 80 out of 100 were granted a certificate of successful completion in our CALL course. We had access to these 153 learners' email addresses to contact them and invite them to participate in this study. Within a month of three times of sending emails asking for their participation, 142 (93%) responded to our online survey.
The online survey had three questions. The first question asked about participants' age range. We took the age ranges popularly used by the Gallop Poll as follows for our study. A reliability test was conducted for the total data to identify whether the grades on the lists had acceptable internal consistency. The grade list was tested using Cronbach's alpha. The resulting alpha value was .88 which according to George and Mallery (2009) indicates good internal consistency reliability. One independent-samples t-test was run to identify whether there were any significant differences in terms of course login frequency between the two groups of participants with highest grades and lowest grades  The second technique is "Key-Word-In-Context" (KWIC). KWIC is based on a simple rule: If you want to understand a certain concept, look at how it is used in the context.
Simply put, in this technique, researchers identify key words and then systematically find the corpus of text to look for all the connections and relationships of the words or phrases in the context.
As shown in Figure 3, "Self-discipline" was considered the most decisive factor leading to success in online professional training (90/93 respondents). The second factor was "School administrators' expectation" (89/93 respondents). This factor was not included in our list of important factors leading to successful online learners found in studies by Boyd (2004) and Beaudoin, Kurtz, and Eden (2009)

Learners' Login Analysis
Learners' login frequency.
The online professional training course lasted over 42 days (six weeks). In many cases, based on the interludes within a day, we could assume that learners logged into the course several times per day. However, this counting method may not be completely accurate because many interludes were not obvious. Therefore, we decided to count all of the login attempts in one day as one login attempt/unit. For example as shown in the login log below, one learner may have logged into the online course three times or four times on Monday, July 01, 2013, but we counted it as only one login attempt/unit.  Following the general section were six sections or weekly modules for six weeks. Each weekly module had an approximately 20-minute video-based lecture. The second learning activity in each weekly module was "Learning Resources" where learners found reading articles and web-based tools related to the topic of the week. The third learning activity was "Weekly Assignment" where learners did and submitted their assignments.
To identify learning activities viewed by learners in the two groups, the researchers gave each learning activity a specific code. For example, the learning activity "Bulletin Board" was coded as A while "General Discussion Forum" was coded as B. All those learning activities were input into a Microsoft Excel sheet to calculate the total number for each learning activity. As shown in Figure  This factor was actually in line with what previous researchers (Boyd, 2004;Beaudoin, Kutz, & Eden, 2009) found in their studies. Second, they understand that they need to complete the course because it is their school administrators' expectation. It is interesting that this factor was not found in any previous studies about the influence of school administrators' expectation on in-service teachers' performances in online professional development. Cavanagh (2013) reported that more and more principals participate in online tools for professional growth. This, in turn, might bring about positive effects on teachers' professional development. They also need to be able to learn with limited support. This probably explained why the only two learning activities Problems" and "Virtual Office Hours" as shown in the learners' login data analysis.
They could manage to find the answer or solution to their problem by themselves through participating more often in forums or viewing the lectures. "Course login frequency" is another factor leading to success. This finding in the online survey was confirmed by the data shown in the learners' login log indicating that learners in Group A logged into the online course three times more than their peers in Group B. Literally, learners in Group A logged into their course almost every day and viewed every learning activity quite equally, except "Technical Problems". There is no finding in the literature to confirm this result, but a quite similar finding in a study by Rienties, Brouwer, and Lygo-Baker (2013) validated this phenomenon. In their study, they found that successful participants in an OPD module on average spent 4 hours and 59 minutes attending and/or watching the web-videoconferencing sessions while unsuccessful counterparts only spent 2 hours and 18 minutes. Another factor that online learners need to have to be successful in OPD is "Familiarity with technology". This factor is clearly illustrated in the learners' login data. While learners in Group A viewed the "Technical Problem" forum less often, learners in Group B viewed "Technical Problems" much more frequently.

Significance of the Study
The study triangulated the perceptions of participants and their actual activities in an OPD course. Therefore, the profile of successful OPD learners is not simply imagined and created by learners. In addition, the study validates previous findings regarding characteristics of online learners and contributes to the scarcity of scholarship on the topic. The findings of this study have several implications for school administrators, OPD organizers and trainers, and in-service teachers in OPD. First of all, the "school administrator's expectation" factor provides an implication for school districts to consider communicating a clear message to in-service teachers about their expectations when teachers pursue OPD. For instance, participants in OPD should submit a report or statement and/or certificate of OPD completion to their school administrators after the training. Second, not everyone can successfully take online learning in general and OPD for in-service teachers in particular. Before offering an OPD for in-service teachers, OPD organizers and trainers need to be aware that OPD participants need to have certain personal characteristics and skills such as "Self-discipline" and "Familiarity with technology". In other words, before conducting online professional development training, OPD organizers or trainers may create a checklist for in-service teachers to identify if they are suitable for OPD.

Limitations of the Study
The study focused on selected factors of successful online learners as reported in previous research. It is not possible to include all factors that might affect learners' success in the OPD setting. In addition, as answers to the factor survey were anonymous, the researchers did not take cultural perspectives into consideration. It is