Editor’s Note: Global adoption of distance learning impacts traditional institutions of higher learning. It raises new questions about  pedagogy, the changing role of teachers and learners, and academic support requirements. China is experiencing revolutions in its economic and educational systems yet requirements for distance learning are strikingly similar to those of other industrialized nations.

An Empirical Study on Academic Achievement and Utilization of Support Provisions by Tertiary English Language E-learners in China

Tong Wang, Charles K. Crook

China, United Kingdom

Abstract

This paper explores the utilization patterns of different achieving e-learners in their interaction with the institutional support provisions in the context of tertiary English language online education in China. Specifically, the project addresses three research issues: 1) What is the demographic picture for high, average, and low achievers of tertiary English language elearning in China? 2) Are there statistical differences in the utilization of support provisions among the three groups? 3) Which variables are correlated with e-learners’ academic achievement?  115 randomly selected Chinese tertiary e-learners participated in a questionnaire survey. Descriptive, comparative, and correlation analyses were conducted and important findings were yielded. The paper calls for in-depth research into the elearning process and learning ecologies for the purpose of informing and optimizing learner support system design for elearning.

Keywords: academic achievement, learner support, English language online education, system design.

Acknowledgement

This project is part of the eChina-UK elearning overarching research program
sponsored by HEFCE of the UK and the Ministry of Education of China.

Background

Online education has been regarded by many governments and organizations as an important educational mode which can contribute significantly to lifelong learning in a knowledge society (Aceto et al., 2004; Alhabshi & Hakim, 2003; Bell, 2002; Bello, 2003; Gudmundsson, 2004; Helios, 2005; Hernes, 2003; Juma, 2003; Kappel, 2002; Kerrey & Isakson, 2000; Kwok et al., 1999; Lewis, 2002; Mason, 2003; MoE, 1996, 2004; Moore & Tait, 2002; Sangra, 2003; Tabs, 2003; Taylor, 2003; The European ODL Liaison Committee, 2004; UNESCO, 2002; Wang, 2006; Zhang, 2003). Hence, its development has been given unprecedented importance, despite concerns and hesitation of various forms at various levels. This is also true of China. China Ministry of Education (MoE) coined a special term for online education - - “modern distance education” (xian dai yuan cheng jiao yu in Mandarin pronunciation), emphasizing the technological element employed by this mode of education. As in many nations, China joined the campaign of promoting the panacea-looking phenomenon and has been undergoing an eventful but rewarding learning process of experimentation.

In 1998, China’s MoE endorsed the mission of developing tertiary online education and put it in The Action Plan for Innovating Education in the 21st Century (Ding, 2005). This was approved in 1999 by the State Council and modern distance education (online education) made its debut in government documentation in China. The year 1998 witnessed the birth of the first group of tertiary online institutes with the Chinese MoE accrediting four prestigious universities as the very first pioneers experimenting with tertiary online education. Until 2003, a total of 68 universities/ organizations were approved in piloting tertiary online education in the Chinese Mainland, of which 67 were universities (MoE, 2002) and one was China Central Radio TV University (CCRTVU). The number of the pilot organizations is the same at the present time.

Among the 68 tertiary online institutions, 12 universities offered English language online degree programs by 2004 (Wang, 2004). By November of 2005, the number of universities rose to 20, based on website search results and confirmed by telephone interviews. By June of 2006, three more universities joined the 2005 school list in providing online degree programs in English language education. According to web search results in 2005, only two foreign languages were taught online within China: English and Japanese. English is the more popular foreign language taught via the Internet.

Introduction to Learner Support at BeiwaiOnline

This section introduces one particular Chinese online institute which serves as the research site for the authors to explore their research questions.

Beijing Foreign Studies University (BFSU), one of the top ranking universities in China, was approved in 2000 by the MoE to run tertiary online education. As the most prestigious foreign languages education university, BFSU has produced two thirds of Chinese ambassadors and earned fame as “the cradle of diplomats and dreamland of foreign language learning” in China. Upon receiving its license, BFSU set up the Institute of Online Education (BeiwaiOnline) to offer English language education programs at both diploma and post diploma BA levels. With the first group of online students enrolled in 2001, BeiwaiOnline took off and developed into the second biggest single-mode online institute (second to CCRTVU) in China in terms of the registered student number in the major of English language education.

Besides student size, BeiwaiOnline is unique among its 67 domestic counterparts in several aspects. The founding rationale of the institute drew upon the resource-based theory and the ecological approach  (Gu, 2006). The theories were then translated into the overarching guidelines for the system design and administration phases (termed as the “6-word principle” within the institute): resource, service, quality, process, monitoring, and outcome. System design was heavily stressed in the first five years of this institute. By 2005, the institute had mature systems in place: resources development, learner support, tutor support, quality assurance, and assessment. The Internet and multimedia technologies were employed in delivering learning resources and facilitating interaction, creating a blended learning system for the e-learners.

Within seven years, BeiwaiOnline set up its national network at 46 study centers in 20 provinces (including municipalities and autonomous regions) across China, forming a BeiwaiOnline education network. Program-wise, the organization currently provides four programs: BA, Diploma, Post-Diploma BA, and training.

BeiwaiOnline currently supports learners in pre-enrolment, induction, course learning, graduation and after-graduation. An overview of learner support at BeiwaiOnline is provided in Table 1.

The purpose in choosing this organization as the case of analysis lies in the intent that its learner support system design rationale and experience can serve as a reference for its counterparts as they might face the same or similar challenges.

Table 1
An overview of learner support provisions at BeiwaiOnline

HQs: headquarters; LCs: (local) learning centers

Literature Review

Research literature reveals that a number of variables influence learner achievement in conventional education settings (Eppler & Harju, 1997; Harper & Kember, 1986; Ward, 1994). However, very little has been done to explore the same issues with regard to the characteristics of students studying in an online education environment.

In distance education related literature, Fan et al (1999) compared higher achievers’ knowledge, use, and satisfaction with student support services to those of low achievers in the Open University of Hong Kong. Findings showed support services can have a potentially positive effect on the academic achievement of students. However, observations for the two achieving groups appeared to be very different. They concluded: 1) student characteristics should be taken into consideration for effective support; and 2) promoting the awareness of available support services and strengthening the student counseling was key to enhancing students’ achievement.

Powell et al (1990) examined the relationship between student predisposing characteristics and student success. They proposed that students, on entry, can be "risk stratified" - - that is, if students can be determined as "at risk" of withdrawal/failure or predisposed toward success.

Chan et al (1999) investigated the factors contributing to high achievers’ success and obstacles leading to low achievers’ difficulties in studying at the Open University of Hong Kong. No significant differences were found between the two achievement groups in their reported use of support services. However, time invested in study was an important factor affecting academic success and low achievers seemed to be more adversely influenced by difficulties in learning.

Taplin et al (2001) compared the help-seeking strategies used by higher achievers and low achievers at the Open University of Hong Kong. There were no statistically significant differences between the two groups but there was a tendency for more of the high-achieving students to seek help for personal difficulties relating to their courses.

Taplin and Jegede (2001) investigated gender differences that contributed to successful achievement in distance education. They analyzed responses of 712 high achieving and low achieving students at the Open University of Hong Kong. They found women were more likely to seek help and supportive environments. Under-achieving women were more likely to find it difficult to seek help.

Among the research efforts above, no study specifically examined foreign language e-learners. This research project is an institutional study of tertiary English language online education. It is based on national level findings regarding patterns, issues, and tensions in learner support system design and utilization in Chinese tertiary elearning settings (Wang, 2004, 2005). Three achieving groups are under study: high, average, and low. Their behavioral patterns of using learner support provisions are explored, compared, and analyzed.

Research Design

This section introduces the research questions, method, participants, and analytical methods.

Research questions

Three research questions were designed for online tertiary English language education in China:

1. What is the descriptive picture for high, average, and low achievers in relation to learner demographic information, computer competency, access to the Internet, learning strategies, utilization of support, and perception of elearning outcomes?

2. Are there statistical differences in learner demographics, computer competency, access to the Internet, learning strategies, utilization of support, and perception of elearning outcomes among the three groups of achievers?

3. What variables in the areas of learner demographic information, computer competency, access to the Internet, learning strategies, utilization of support, and perception of elearning outcomes are correlated with e-learners’ academic achievement?

Method

A questionnaire survey was implemented from August 2004 to early 2005. The questionnaire (α=0.84) was the revised version of that used in Wang’s national study on support system design and service utilization in relation to Chinese tertiary English language elearning (2004). The questionnaire contains 30 questions in five areas: learner demographic information, computer competency and access to the Internet, learning strategies, utilization of support provisions, and self-evaluation of elearning outcomes. This method was used for the purpose of capturing how different achieving groups of language e-learners reported their use of support provisions.

Participants

In this research, three groups of BeiwaiOnline students were under study based on their past academic performance in English course examinations: a high achieving group (mean of past English course examination scores ≥ 80), an average achieving group (80 > mean of past English course examination scores ≥ 60), a low achieving group (mean of past English course examination scores < 60). The reason for stratifying the sample in this way is that 60 is the passing score for any course at BeiwaiOnline. Failure to meet this requirement would result in re-taking the course. 80 is the minimum score for academic excellence awards at the institute. The English courses at BeiwaiOnline are divided into English skills courses (focusing on language skills development) and content courses (focusing on culture and language knowledge), both delivered in English. The final course score for each English course is the combination of two parts: online continuous assessment (20 percent of the final course score) and sitting-in examinations (80 percent of the final course score). Both parts are achievement tests in nature. The continuous assessment contains course assignment and unit-based online assessment. The sitting-in final examinations take the conventional format, which are given twice a year at all study centers of BeiwaiOnline.

According to the internal report (BeiwaiOnline, 2006) about BeiwaiOnline examination analyses, an average of 11.4% of BA and post-diploma BA students could not pass their BA courses; 15.3% of Diploma programs students failed their courses.

This study targets the student population of both BeiwaiOnline BA and diploma programs enrolled from the autumn of 2001 to the spring of 2003. This ensures that participanting students have studied in the BeiwaiOnline system for at least one year and have developed their elearning strategies. The project randomly selected BeiwaiOnline students in their second year and above at 46 study centers across China. Selection results are shown in Table 2. As face-to-face tutorials were not compulsory at Beiwaionline and the target student population was scattered at 46 study centres in 20 provinces in China, it was difficult to conduct the questionnaire survey in a face-to-face manner. Email was the means through which questionnaires were sent and collected. Having considered the low return rates of surveys conducted through email, two instant mobile messages were sent to the sample population as reminders for the purpose of encouraging more returned questionnaires. With the help of the measures above, the return rate for the whole sample population was 25.6%. Chi-square test (p=0.368) informs that there is no statistical difference among the return rates for the three groups.

Table 2
A summary of selection results

 Analytical methods

First, descriptive analysis was conducted to capture the overall picture of learner support utilization by BeiwaiOnline students in general and within each achieving group. This was followed by one-way ANOVA analysis intending to probe the group differences. Last, correlation analysis was administered to examine which variables were correlated with e-learners’ academic performance. All data were processed with SPSS software (version 11.0).

Research Findings

Three types of analyses were administered and the findings were as follows.

1.    Descriptive Findings

Descriptive findings address the first research question of the study.

Research question 1: what is the descriptive picture for high, average, and low achievers in the areas of learner demographic information, computer competency, access to the Internet, learning strategies, utilization of support provisions, and perception of elearning outcomes?

Demographics of e-learners: Females constituted the majority of the student population. Male students made up only 34.8% of BeiwaiOnline learners. More than half of the students had diploma degrees prior to enrolment, one fifths had BA degrees, and less than 4% had secured post BA degrees before starting their learning at BeiwaiOnline.

Education Level: It is clear that the overwhelming majority of BeiwaiOnline learners received higher education at various levels prior to enrollment. Given this context, questions about enrollment motivation might be formed - - what were the major reasons for these adults to choose BeiwaiOnline degree programs? Were they mainly internally and/or externally driven in their choice? The findings inform that both internal and external factors drove the students to choose BeiwaiOnline degree programs. External reasons expressed were getting a degree, getting a better job, and becoming a student of BFSU (one of the top-ranking universities in China); internal motivators were related to good mastery of English and interest in studying English.

Learner computer competency and access to the Internet: Research findings reveal that BeiwaiOnline students had convenient access to the Internet and their computer literacy level was high. 43.5% of students could skillfully use most of the application software; 33% could skillfully use the computer and solve technical problems; 4.3% were professionals in computer technologies. At a less skilled degree, 18.3% of the learners reported that they knew how to use basic application software and therefore could technically survive in the elearning system. In contrast, only 0.9% of the learners expressed that they did not know how to use the computer before enrolment. In summary, BeiwaiOnline students achieved computer literacy prior to enrolment. Regarding learner access to the Internet, 87% of the learners were connected to the Web via ADSL (Asymmetrical Digital Subscriber Loop) and LAN (local Area Network), thus enjoying a relatively fast speed for utilizing online resources and services compared with telephone MODEM access. This can be traced to the institutional entry requirement of student web access and IT literacy. Here, a series of interesting questions might be asked: “could the high IT competence of BeiwaiOnline learners help them become qualified e-learners? Could the technical competence motivate students to take up more online provisions?” From the findings in this research, there seems to be little evidence to prove the correlation between IT competence and online learning behaviors.

Learning strategies: Most BeiwaiOnline adult students worked during the day, so more than half of the learners chose evenings as the major time for learning. 33% of students did not have a regular study time pattern. As a result, they carried out their learning at irregular time slots. 20% of the students could study during the day when they were not busy with work. This does not mean that they got the support from their managers for doing so. A few were in this privileged situation as their bosses gave them the green light in contrast with the majority who had to “steal time” for learning secretly and guiltily. About 12.2% of the early-rising students could use the early hours/minutes for learning. It is worth noting that 4.3% of BeiwaiOnline learners enjoyed more freedom in choosing time for learning, as they were self-employed. Generally speaking, BeiwaiOnline students, as with many learning adults, led a busy working and learning life.

Time frames for study among BeiwaiOnline students: Confronted with the multiple commitments both at work, in professional development, and in family, possessing and applying effective metacognitive strategies is vital to the working students. Failure of managing self and time well will create problems and challenges for their study. The research findings reveal some major difficulties confronted by BeiwaiOnline learners during their learning: heavy study load, not knowing how to manage time well, not knowing how to use BeiwaiOnline resources and services, feeling lonely during study, difficult course content, and not having autonomous learning methods.

Strikingly, the difficulty of course contents did not loom large as the major factor (ranked as the fifth difficulty) hindering the learning outcome. In relation to time management, question 14 in the questionnaire asked the participants to assess their time management ability, 54.3% of the respondents reported “average”, 8.7% expressed “poor”, another 8.7% chose “none”, and 24.8% opted for “strong”.

Multiple signals for different roles in the institute. For e-learners, it is important to enhance their metacognitive strategies so as to ensure a successful elearning experience. For resources developers and tutors, it is necessary to examine whether the course material or delivery are best designed or conducted from the perspective of learner support. For administrators and administration staff, it is crucial to explore whether the learner support system design and provisions need to be critically reviewed. Immediate questions might be formed about the deeper reasons for the self-reported deficiency of metacognitive strategies on the part of the learners: is it due to the lack of support services at the institute? Is it due to the sub-standard quality of the provisions? Is it due to students’ high expectations of themselves? Is it due to the flaws or limitations with course design and/or assessment?

Utilization of support provisions: As to students’ view on learner support services provided by the institute, 83.4% of the learners were “basically” or “very satisfied” with the services. 68% of the students expressed their hope to “get more web-based services” while in actual deeds they utilized more of the offline provisions. Top five most participated learner support services at BeiwaiOnline are listed in Table 3.

Table 3
Top five most participated learner support services at BeiwaiOnline

It is clear that the institute provided resources and services and that the students were basically satisfied with these. However, uptake was not high. The discrepancy between “the services are there” and “the learners do not come often” calls for serious thinking about the deeper reasons. It might reflect students’ understanding of the institute’s intentions in its support services or students’ hopes but somehow the actual uptake of the support provisions was proved otherwise. It might indicate some design problems not only with learner support system but also with other systems as well within the elearning framework.

Learner perception of elearning outcomes: When asked about students’ self-perception of online learning outcome, the students expressed their opinions as follows. The development of self-directed learning strategies top their progress list followed by English proficiency level, confidence in learning, cognitive strategies, and belongingness to the institute. The reported enhancement of self-directed learning strategies proves the two-directional relationship between learner autonomy and successful elearning.

This study also aims at discovering whether different achievement groups employ different learner support services and study strategies. After acquiring the overall picture for all BeiwaiOnline learners, comparative and correlation investigations among the different achieving groups were conducted. With the help of these analyses, the authors intend to explore what variables are correlated with e-learners’ academic performance. Two steps are taken in analysis: comparative analysis to locate where the differences lie among the three groups and correlation analysis to detect the strength of association between the variables and learner achievement score. Each step of analysis is introduced below.

2.    Comparative Findings

Comparative analyses address the second research question of the study.

Research question 2: Are there statistical differences in the areas of learner demographic information, computer competency and access to the Internet, learning strategies, utilization of support provisions, and perception of elearning outcomes among the three groups of achievers?

In this study, there are 37 variables falling into the areas of learner demographic information, computer competency and access to the Internet, learning strategies, use of support provisions, and perception of elearning outcomes. In order to detect which variables statistically distinguish the three achieving groups, one-way ANOVA test was administered and ten out of 37 variables were identified being statistically significant among the three groups. However, caution needs to be taken in interpreting the results due to chance factor in multiple statistical testing.

The one-way ANOVA test results reveal that the three achieving groups were statistically different in three areas: metacognition (manifested in time management, self-management, resource and service use, confidence in elearning), affect (sense of belongingness), and socialization (interaction with peers and tutors). The high achieving group excels in the means of the ten variables in all of the three areas compared with the average and low achieving groups. The low achieving group achieves the lowest mark for most of the variables (Table 4).

Table 4
A summary of descriptive findings about the achieving groups

HAG = high achieving group; AAG = average achieving group; LAG = low achieving group

Multiple comparisons Scheffe test (Table 5) results inform that the variance lies mainly between the high achievers and low achievers. Based on the multiple comparisons results, it is paramount to pay attention to scaffolding the low achieving group in the ten variables detected to be statistically different among the groups.

Table 5
Multiple comparisons Scheffe test results for the achieving groups