An investigation of Taiwan University students' perceptions of online academic help seeking, and their web-based learning self-efficacy

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An investigation of Taiwan University students' perceptions of online academic help

seeking, and their web-based learning self-ef

ﬁcacy

Kun-Hung Cheng

a,b,

⁎

, Chin-Chung Tsai

c

a

Digital Content Production Center, National Chiao Tung University, Hsinchu, 300, Taiwan

b_{Graduate Institute of Applied Science and Technology, National Taiwan University of Science and Technology, #43, Sec. 4, Keelung Rd., Taipei, 106, Taiwan} c

Graduate Institute of Digital Learning and Education, National Taiwan University of Science and Technology, #43, Sec. 4, Keelung Rd., Taipei, 106, Taiwan

a b s t r a c t

a r t i c l e i n f o

Article history: Accepted 18 April 2011 Available online 29 April 2011 Keywords:

Online academic help seeking Web-based learning self-efﬁcacy Information searching Formal query Informal query

This study was conducted to investigate Taiwan University students' perceptions (including experience, confidence and preference) of online academic help seeking (OAHS) and students' level of web-based learning self-efficacy (WLSE). Two instruments, OAHS questionnaire, consisting of information searching, formal and informal query scales, and WLSE questionnaire, including general and functional scales, were then validated through collecting the responses from 300 university students. Results indicate reciprocal relations between experience, confidence and preference in students' online academic help seeking behaviors. Students' academic help seeking behaviors were related to their general self-efficacy in a web-based course setting. Students' functional WLSE was related to their perceptions of information searching for OAHS. Findings of this study also imply that students' experience of seeking help from informal online channels is prominent when they participate in a web-based course.

1. Introduction

In the early studies of socialization and personality development, help seeking was often viewed as an indicator of dependent,

immature, passive and even incompetent behavior (Nelson-Le Gall,

1985). However, during the past two decades researchers have

indicated that help seeking is positive and beneﬁcial for students (Aleven, Stahl, Schworm, Fisher, & Wallace, 2003; Karabenick, 1998; Lee, 2007; Newman, 2000). With regard to academic help seeking in traditional learning contexts, previous studies have discussed the relationships between help seeking and motivation, achievement

goals, classroom norms, and helper characteristics (Butler, 1998;

Cheong, Pajares, & Oberman, 2004; Karabenick, 2004; Ryan & Pintrich,

1997). Researchers have proposed that students who are in need of

help do not always seek it, and the reason for resisting help seeking is due to the fact that they feel embarrassed, perceive a threat to their self-esteem or fear being considered as“dumb” by others (Karabenick, 1998, 2003; Kozanitis, Desbiens, & Chouinard, 2007; Ryan & Pintrich, 1997).

In distance learning environments, however,Kitsantas and Chow

(2007)in comparing campus-based students with online students, indicated that college students enrolled in online courses present a

higher interest in seeking help from formal sources (i.e., instructors

and teacher assistants).Kumrow (2007)found that nursing students

in a blended learning setting (combining web-based and traditional instruction) were involved in more help seeking and had higher grades than those in the traditional lecture setting. Since Web environments provide less threatening interactions than face-to-face contexts, students have more privacy and opportunities to reﬂect

on and reﬁne comments, ask questions, and search for answers via

electronic sources (Kitsantas & Chow, 2007; Kumrow, 2007).

Help seeking has different behavior patterns. Karabenick and

Knapp (1991)proposed the following ﬁve categories: (a) formal help seeking (e.g., seeking help from school-provided instruc-tional support, instructors or teacher assistants), (b) informal help seeking (e.g., seeking help from peers or knowledgeable friends), (c) instrumental activities (e.g., trying harder, studying more or taking better notes to perform better), (d) lowering performance aspirations (e.g., taking a lighter study load or easier courses), and (e) altering goals (e.g., changing to another school or major). Concerning new technologies integrated into learning contexts, different explanations

for the nature of help seeking emerge.Puustinen and Rouet (2009)

analyzed help seeking from two aspects: the type (i.e., human or non-human) and the location (e.g., physically present or on the Internet). They proposed three types of help seeking situations: (a) the helper is a human (e.g., a teacher), (b) the helper is a human expert communi-cating with the learner via technology (e.g., video conferencing, email or a mobile phone), and (c) the human helper is replaced by a help system.Puustinen and Rouet (2009)further suggested that information searching is one particular type of help seeking.

⁎ Corresponding author at: Graduate Institute of Applied Science and Technology, National Taiwan University of Science and Technology, #43, Sec. 4, Keelung Rd., Taipei, 106, Taiwan. Tel.: + 886 3 5729903.

E-mail addresses:kuhu@mail.nctu.edu.tw(K.-H. Cheng),cctsai@mail.ntust.edu.tw

(C.-C. Tsai).

Contents lists available atScienceDirect

Internet and Higher Education

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Currently, computers and the Internet are considered as being rich information tools and resources for assisting learning activity. For

instance, Mäkitalo-Siegl, Kohnle and Fischer (2011) examine the

effect of integrating Information and Communication Technology (ICT) into inquiry learning task on students' help seeking processes. In

Mäkitalo-Siegl and Fischer's (2011)study, they assert that learners could acquire different help resources by the support of technology in informal learning situations. However, they also indicate that research with regard to help seeking behavior outside of the classroom has hardly been discussed. Therefore, the present study focuses on university students' help seeking through the Internet when they encounter academic problems (e.g., homework problem) in formal or informal learning situations (e.g., at school or home). Based on the

statements about information searching proposed byPuustinen and

Rouet (2009), and theﬁve help seeking behavior patterns addressed byKarabenick and Knapp (1991), this study considers that online academic help seeking (OAHS) consists of not only information searching but also formal and informal queries. OAHS in this study is considered as the spontaneous behavior of requesting assistance from others through the Internet; therefore, the other three help seeking

behavior patterns proposed by Karabenick and Knapp (1991),

instrumental activities, lowering performance aspirations and altering goals, are not included in this study. Moreover, the Internet is an open environment through which students could search for information or ask human experts about academic problems, unlike help functions, which are limited in certain learning systems. Consequently, the third

help seeking situation addressed byPuustinen and Rouet (2009), a

human helper replaced by a help system, is also not included in this survey.

In addition, previous studies indicate that students who spend more time using the Internet may increase their preferences for web-based learning environments (Chu & Tsai, 2009; Chuang & Tsai, 2005). Students with more Internet experience tend to display more positive Internet attitudes and conﬁdence in its usage (Chu & Tsai, 2009; Peng, Tsai, & Wu, 2006; Wu & Tsai, 2006). That is, experience of using Internet may positively relate to preference and conﬁdent of using it. Furthermore,

Liang and Tsai (2008)found that students' preferences for constructivist web-based learning environments might be facilitated by their con ﬁ-dence in using the Internet. For example, students with higher conﬁdence in using the Internet express more preference to explore multiple sources of information, engage in an inquiry activity or probe the nature of

knowledge in web-based learning environments. Also, Chu and Tsai

(2009)concluded that conﬁdence in using the Internet is a mediating variable in the correlation between Internet experience and the learners' preference for web-based learning environments. The result shows that learners spending more time on the Internet practice may possess strong conﬁdence in the utilization of Internet, who may prefer to learn in a web-based learning environment. Accordingly, the current study pro-poses that there are reciprocal correlations among the experience,

conﬁdence and preference of students' online learning behaviors,

including academic help seeking. By investigating students' OAHS experience, conﬁdence and preferences, their relevant ideas toward OAHS may be fully interpreted to assist instructional design.

Help seeking behavior can also be conceptualized as one kind of

self-regulated learning strategy (Karabenick & Newman, 2006;

Kitsantas, 2002; Zusho, Karabenick, Bonney, & Sims, 2007). There is some evidence that students' self-regulated learning strategies are related to their learning self-ef_{ficacy (}Pintrich & Schunk, 2002; Wang & Lin, 2007). That is, students with higher learning self-efficacy would tend to use more sophisticated self-regulated learning strategies (e.g., planning, monitoring, or help seeking).“Self-efficacy” refers to one's beliefs and expectations regarding one's ability to perform a task required to achieve specific outcomes (Bandura, 1997). Researchers have also found that students who tend to seek help more frequently would have higher academic self-efficacy than those who rarely seek help (Karabenick & Knapp, 1991; Ryan & Pintrich, 1997).

Studies related to web-based learning have also concluded that students who utilize more sophisticated strategies and exhibit better performance in online information searching tasks usually have higher“Internet self-efﬁcacy” (Joo, Bong, & Choi, 2000; Tsai & Tsai, 2003). For example, inTsai and Tsai's study (2003), while students with high Internet self-ef_{ﬁcacy often use a variety of keywords to}

search relevant information, those with low Internet self-efﬁcacy

were reluctant to try another approaches when the keywords did not work.“Internet self-efficacy” indicates an individual's self-evaluated expectations and confidence in their skills of using the Internet and accomplishing Internet-related tasks (Chu, 2010; Kao & Tsai, 2009; Liang & Tsai, 2008). Based on the aforementioned discussion, this study hypothesizes that there are some correlations between users' online help seeking behavior and their self-efficacy in online, web-based learning contexts. Regarding students' self-efficacy in terms of web-based learning, this study proposes that web-based learning

self-efﬁcacy (WLSE) could include two major components. The ﬁrst one,

named general WLSE, refers to a student's beliefs and confidence in his/her competence to complete online courses academically; the other, labeled functional WLSE, is the confidence in utilizing relevant Internet or computer skills to enroll in and complete web-based courses, similar to the idea of Internet self-efficacy defined previously, but confining the self-efficacy to participating in web-based instruc-tion. Therefore, WLSE, that includes general and functional

self-efﬁcacy, is explored, and then its relationship with university

students' perceptions of OAHS is examined.

In sum, the research purposes of this study are as follows: 1. To develop instruments for assessing university students' OAHS

perceptions and WLSE.

2. To explore the relationships between students' experience,

conﬁdence and preference for OAHS, and to examine the possible

differences among these.

3. To explore the relationships between students' WLSE and perceptions of OAHS.

2. Method 2.1. Sample

The respondents of this study included 300 university students with adequate Internet experience (including 138 males and 162 females) in Taiwan, as all of them were capable of exploring and searching information through the Internet. They were either undergraduate or graduate students, of which 39 were freshmen, 52 were sophomores, 45 were juniors, 63 were seniors and 101 were graduates. All participants were asked to respond to online academic help seeking (OAHS) questionnaire items; at the same time, students who had experience of taking web-based courses were further asked

to respond to a web-based learning self-efﬁcacy (WLSE)

question-naire. Among these respondents, there were 124 students who had taken web-based courses at least once.

2.2. Instruments

In this study, the online academic help seeking (OAHS) question-naire has been developed according to the aforementioned three major behaviors (information searching, formal and informal queries). These three behaviors constitute the three scales of the OAHS questionnaire. Moreover, each OAHS questionnaire item was designed to assess university students' perceptions of three

di-mensions, namely experience, conﬁdence and preference, similar to

those adopted byLee and Tsai (2011). They were asked to rate the

frequency of OAHS (ranging from “always” to “never”) in the

experience dimension, their OAHS conﬁdence level (ranging from

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dimension, and their OAHS favor degree (ranging from “like very

much” to “dislike very much”) in the preference dimension, all of

which used _{ﬁve-point Likert scales. For each item of OAHS}

questionnaire, the respondents had to mark their responses to the three dimensions at once (seeFig. 1). The design of questionnaire format was referred toLee and Tsai (2011, p. 908). A recent study regarding social science studies indicated that data measured byﬁve or seven or ten-point Likert scales generated approximately duplicate results with regard to means and variations of data, and data characteristics (Dawes, 2008). Therefore, this study considered that aﬁve-point Likert scaling method used widely in social science survey research would be best to use to obtain valid data.

After the initial construction of the OAHS questionnaire, two experts in the web-based learningﬁeld commented on it for its face validity. The items of the OAHS questionnaire are presented in

Appendix A. Following are the details of the three scales of the OAHS questionnaire:

1. Information searching: measuring students' perceptions of seeking relevant solutions through search engines (e.g., Google, Yahoo) or expertise websites (e.g., Wikipedia) when encountering academic problems.

2. Formal query: measuring students' perceptions of seeking help from instructors or class assistants through any online channel. 3. Informal query: measuring students' perceptions of seeking help

from knowledgeable peers through the Internet or posting messages on relevant websites for querying unknown experts' help.

The web-based learning self-efﬁcacy (WLSE) questionnaire was

designed by integrating the concept of academic learning self-efﬁcacy

and Internet self-efﬁcacy. Therefore, the WLSE questionnaire

con-sisted of two scales in this study. The general WLSE is based on the motivated strategies for learning questionnaire (MSLQ) proposed by

Pintrich, Smith, Garcia, and McKeachie (1991) and the college

academic self-efﬁcacy scale (CASES) designed byOwen and Froman

(1988). The scale of the general WLSE refers to students' expectations of and conﬁdence in web-based learning in general. A similar version was adopted byTsai (2009). The other scale, the functional WLSE, is

modi_{ﬁed from the Internet self-efﬁcacy survey (ISS) developed by}

Tsai and Tsai (2003). The scale of the functional WLSE indicates students' conﬁdence in using Internet skills to take online courses. The

WLSE questionnaire is presented using a _{ﬁve-point Likert scale.}

Appendix Bshows the items of the WLSE questionnaire. Descriptions of the two scales are as follows:

1. General WLSE: assessing students' self-efﬁcacy about general web-based learning. Thus, the higher the scores, the more conﬁdence in self-perceived ability to complete online courses academically.

2. Functional WLSE: assessing students' self-efﬁcacy in terms of

utilizing the Internet or computer skills to enroll in web-based courses. That is, the higher the scores, the more con_{ﬁdence in} self-perceived capability of having adequate skills to enroll in online courses.

It should be noted that only those students with experience of web-based courses (n = 124) responded to the WLSE questionnaire, as without relevant experience, the students may not be able to reflect their self-efficacy toward web-based learning. Even though the WLSE questionnaire was designed for measuring the respondents' overall online learning self-efficacy, this study assumed that the students would respond to the WLSE questionnaire according to their experience of certain specific online courses in which they had taken before. 3. Results

3.1. Factor analysis—OAHS

This study utilized the exploratory factor analysis (EFA), principal component analysis with oblique rotation, to clarify the structure of the online academic help seeking and the web-based learning self-efficacy. The factor analysis showed that the subjects' responses on the OAHS questionnaire were grouped into three factors:‘Information searching’, ‘Formal query’, and ‘Informal query.’ In all three dimensions (i.e. experience, confidence, preference) of the OAHS investigation, these scales consisted of the same questionnaire items. There were two items in the information searching scale and four items in the formal and informal query respectively. These items werefiltered by a series of factor analyses. In order to make fair comparisons, the items should be valid across the measurement of the students' experience, confidence and preference of OAHS. Although we surveyed the students' perceptions for three dimensions of OAHS byfive items respectively, in the information searching scale, only two items remained forfinal analysis based on the aforementioned procedure.

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It is revealed in Table 1 that the factors in the experience dimension of the OAHS questionnaire accounted for 61.53% of the variance totally. The eigenvalues of the three factors were larger than one. The overall reliability alphas were 0.76 and 0.55, 0.76, and 0.69 for each scale respectively. For social science research, a Cronbach alpha coefﬁcient even as low as 0.55 can be recognized and accepted for statistical consideration (Hatcher & Stepanski, 1994). Therefore, these scales were deemed to be sufﬁciently reliable to assess students' experience of OAHS.

The factor loadings for each item of the three factors of OAHS con_{ﬁdence are also shown in}Table 1. These factors explained 66.94% of variance totally. The reliability (alpha) coefﬁcients for these scales respectively were 0.65, 0.81, and 0.80, and the overall alpha was 0.81. Moreover,Table 1presents the factor analysis of the preference for OAHS. The three factors accounted for 65.96% of the variance. The overall reliability alpha was 0.77 and 0.62, 0.81, and 0.77 for each scale respectively.

3.2. Factor analysis—WLSE

With regard to the factor analysis results of the WLSE question-naire,Table 2reveals that 10 items are extracted under two factors: ‘general self-efﬁcacy’ and ‘functional self-efﬁcacy’ with eigenvalues of 4.55 and 1.56. The total explained variance was 61.10% which was good enough for explanation. The overall reliability alpha was 0.86, 0.84 and 0.81, respectively, for each scale, making it acceptable in terms of internal consistency.

3.3. Correlation between experience, conﬁdence, and preference for the OAHS factors

Table 3presents the relationships among the university students'

experience, conﬁdence and preference among the OAHS scales. It

reveals that there are signiﬁcantly high correlations among the

students' experience, confidence and preference for each OAHS factor. For example, in the information searching scale, the correlation coef-ficient for the relationships between students' experience and con-fidence, experience and preference, and confidence and preference were 0.57 (p_{b0.01), 0.56 (pb0.01), and 0.68 (pb0.01), respectively.}

Similar high correlation coefﬁcients were also observed among

experience, conﬁdence and preference within the same scale, such

as formal query. That is, university students' experience, conﬁdence and preference for OAHS had reciprocal correlations among each other for each scale.

Furthermore,Table 3shows that there are signiﬁcantly moderate correlations between the students' formal and informal queries for OAHS in the dimensions of experience (r = 0.41, pb0.01), conﬁdence

(r = 0.46, pb0.01) and preference (r=0.30, pb0.01). These results

indicate that students with more experience, con_{ﬁdence or preference} for seeking help from teachers or class assistants were inclined to have more experience, conﬁdence or preference for seeking help from knowledgeable peers through the Internet or posting messages on relevant websites for querying unknown experts' help. However, according toTable 3, it was found that there were relatively low or no correlations between information searching and formal or informal queries for OAHS. This seems to suggest that information searching does not play an important role in OAHS query behavior. The information searching behavior may be independent from the formal and informal online query behaviors.

3.4. Comparisons of experience, conﬁdence, and preference for the OAHS factors

To further understand the university students' OAHS perceptions, it is interesting to compare their experience, conﬁdence, and pref-erence on the OAHS scales. Through a series of ANOVA and post-hoc

tests, Table 4 shows that the university students' conﬁdence was

higher than their experience of information searching for OAHS. It also

revealed that the students' conﬁdence was stronger than their

preferences and experiences of formal and informal queries for OAHS. That is, the university students showed a certain degree of high

conﬁdence in seeking academic help online, but actually they may

have less experience of and preference for asking questions formally

Table 1

Rotated factor loadings and Cronbach'sα values for the OAHS experience, conﬁdence and preference scales (n=300).

Item Experiencea _Conﬁdenceb _Preferencec

Factor 1 Factor 2 Factor 3 Factor 1 Factor 2 Factor 3 Factor 1 Factor 2 Factor 3 Factor 1: information searching

Information searching 1 .841 .862 .873

Information searching 2 .727 .824 .788

Factor 2: formal query

Formal query 1 .873 .928 .890

Formal query 2 .630 .732 .722

Formal query 3 .617 .642 .754

Formal query 4 .863 .818 .810

Factor 3: informal query

Informal query 1 .707 .893 .823 Informal query 2 .491 .732 .646 Informal query 3 .804 .774 .752 Informal query 4 .796 .711 .830 Reliability coefﬁcient (α) 0.55 0.76 0.69 0.65 0.81 0.80 0.62 0.81 0.77 Eigenvalue 1.38 3.33 1.45 1.27 1.57 3.86 1.40 3.41 1.79 a

Overallα=0.76, total variance explained=61.53%.

b

Overallα=0.81, total variance explained=66.94%.

c

Overallα=0.77, total variance explained =65.96%.

Table 2

Rotated factor loadings and Cronbach'sα values for the WLSE scales (n=124).

Item Factor 1 Factor 2

Factor 1: general self-efficacy (mean=3.30, SD=0.65) General self-efficacy 1 .694 General self-efficacy 2 .815 General self-efficacy 3 .872 General self-efficacy 4 .704 General self-efficacy 5 .833 Factor 2: functional self-efficacy (mean=3.76, SD=0.60)

Functional self-efficacy 1 .500 Functional self-efficacy 2 .797 Functional self-efficacy 3 .950 Functional self-efficacy 4 .586 Functional self-efficacy 5 .742 Reliability coefficient (α) 0.84 0.81 Eigenvalue 4.55 1.56

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or informally. In addition, according toTable 4, the university students scored much higher on the searching scale than on the formal and informal query scales for all three dimensions of experience, con-ﬁdence and preference. Compared with their formal and informal query behavior, they were more inclined to search for information online when encountering academic problems.

3.5. Correlation between the factors of OAHS and WLSE

To examine the hypothesis that there are relations between

students' help seeking behaviors and their self-efﬁcacy in online

learning contexts, the correlations between the university students' OAHS and WLSE were further explored in this study, with the results

presented in Table 5. It was found that their general WLSE had

relatively high correlation with their conﬁdence in information

searching (r = 0.37, pb0.01). There were signiﬁcant positive correla-tions between the students' general WLSE and their informal queries for OAHS in the three dimensions. Moreover, the students' experience of and preference for formal queries in OAHS had a relationship with their general WLSE. In sum, all three types of students' online help seeking behaviors were related to their general WLSE. Furthermore,

Table 5indicates that the students' experience (r = 0.26, pb0.01),

conﬁdence (r=0.55, pb0.01), and preference (r=0.36, pb0.01) for

information searching for OAHS had signiﬁcant relationships with

their functional WLSE. That is, university students who had stronger experience, con_{fidence, and preferences for information searching for} OAHS, especially confidence in information searching, would tend to have higher self-efficacy for functional WLSE.

3.6. Stepwise regression analysis of predicting students' WLSE using OAHS

Through stepwise multiple regression analyses, this study attempted to predict the students' WLSE by using OAHS responses as predictors. That is, for the regression analyses, the dependent variables were the WLSE scales (general and functional WLSE), and the OAHS scales (information searching, formal and informal query)

in the three dimensions (experience, conﬁdence and preference)

were processed as the predicting variables. InTable 6, the stepwise regression model showed that the students' conﬁdence in information

searching (t = 4.15, pb0.001) and experience of informal query

(t = 2.26, pb0.05) were the signiﬁcant predictors for their general

WLSE. Also, the students' conﬁdence in information searching

(t = 7.20, pb0.001) was the sole signiﬁcant predictor explaining

their functional WLSE. As students' confidence is theoretically more related to the construct of their self-efficacy, confidence in searching behavior was an essential predicting variable of general and

functional WLSE in the stepwise regression model. Thisﬁnding also

suggested the important contribution of searching behavior in web-based learning. Besides, the students' experience of informal query for OAHS was the second variable to predict their general WLSE. The result indicated that informal query played a signiﬁcant role in a web-based learning environment.

4. Discussion

This study developed an online academic help seeking (OAHS) questionnaire to assess university students' perceptions (including

experience, conﬁdence and preference) of OAHS, and a web-based

learning self-ef_{ﬁcacy (WLSE) questionnaire to assess students'}

self-efﬁcacy in a web-based learning environment. Through exploratory

factor analysis, it was found that the two instruments were suf_{ﬁciently reliable for investigating university students' perceptions} of OAHS and their WLSE.

The relationships between students' experience, conﬁdence and

preference for OAHS were explored by correlation analysis in the present study. The results showed that those students with more experience tended to possess stronger conﬁdence and preference for information searching, and for formal and informal queries for OAHS, respectively. Therefore, reciprocal relations were found between

experience, conﬁdence and preference in students' online academic

help seeking behaviors. The results of the correlations between formal and informal queries for OAHS revealed that students who had more

experience (or conﬁdence, or preference) of seeking help from

Table 3

Correlation between students' experience, conﬁdence, and preference for the three OAHS factors.

Experience Conﬁdence Preference

Searching Formal query Informal query Searching Formal query Informal query Searching Formal query Informal query

ES 1 EFQ .17⁎⁎ 1 EIQ .20⁎⁎ .41⁎⁎ 1 CS .57⁎⁎ .06 .10 1 CFQ .00 .45⁎⁎ .12⁎ .13⁎ 1 CIQ .08 .19⁎⁎ .58⁎⁎ .26⁎⁎ .46⁎⁎ 1 PS .56⁎⁎ .09 .08 .68⁎⁎ .05 .18⁎⁎ 1 PFQ .10 .54⁎⁎ .12⁎ .12⁎ .64⁎⁎ .21⁎⁎ .18⁎⁎ 1 PIQ .09 .25⁎⁎ .65⁎⁎ .19⁎⁎ .30⁎⁎ .74⁎⁎ .16⁎⁎ .30⁎⁎ 1 n = 300

ES: experience of information searching, EFQ: experience of formal query, EIQ: experience of informal query, CS: confidence of information searching, CFQ: confidence of formal query, EIQ: confidence of informal query, PS: preference of information searching, PFQ: preference of formal query, PIQ: preference of informal query.

⁎⁎ pb.01. ⁎ pb.05.

Table 4

Comparisons of students' experience, conﬁdence, and preference for the three OAHS factors.

(1) Experience (mean, SD) (2) Conﬁdence (mean, SD) (3) Preference (mean, SD) F-value Post-hoc test

Searching 3.52 (0.76) 3.62 (0.70) 3.60 (0.72) 3.54⁎ 2N1 Formal query 2.24 (0.77) 3.05 (0.78) 2.81 (0.72) 196.88⁎⁎⁎ 2N3N1 Informal query 2.28 (0.74) 2.78 (0.79) 2.69 (0.73) 103.90⁎⁎⁎ 2N3N1 n = 300. ⁎⁎⁎ pb.001. ⁎ pb.05.

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instructors would tend to have more experience (or conﬁdence, or preference) of querying peers or unknown experts online. There were relatively low or no correlations between information searching and formal or informal queries for OAHS. Hence, information searching did not play an important role in query behaviors for OAHS, suggesting that querying and searching action were probably different patterns of online help seeking behaviors.

Furthermore, ANOVA tests were implemented to examine the possible differences among the university students' experience, con fi-dence and preference for the OAHS scales. It was found that the university students' confidence was higher than their experience of and preference for OAHS generally, and they scored much higher on the information searching scale than on the formal and informal query scales in all three dimensions. Obviously, the university students present a certain degree of high confidence in seeking help in a web-based environment, but actually they may have less experience and preference for inquiry using formal or informal methods. Therefore, it is important to increase students' experience of or preference for seeking help to enhance their learning strategies. Meanwhile, the students tended to search for information online when they encountered academic problems. These results may suggest that teachers or school administrators should provide online academic help channels freely and try to enhance students' motivation to make queries when they experience academic difficulties, no matter whether they use formal or informal methods.

Moreover, the results of the correlations between the OAHS and the WLSE factors indicate that all of the students' academic help seeking behavior had relationships with their general self-efficacy in a web-based course setting. Due to the fact that help seeking was conceptualized as one kind of self-regulated learning strategy (Karabenick & Newman, 2006; Kitsantas, 2002; Zusho et al., 2007), the results of this study show research evidence that students' regulated learning strategies had interplay with their learning self-ef_{ficacy, as shown by earlier research work (e.g.,}Pintrich & Schunk, 2002; Wang & Lin, 2007). In this study, students' functional WLSE was related to their perceptions of information searching for OAHS. As aforementioned, the functional WLSE factor is similar to Internet self-efficacy in a web-based learning context. The results of this study substantiate the positive relationships between Internet self-efficacy and information searching strategies found by previous studies (Joo et al., 2000; Tsai & Tsai, 2003).

Through stepwise regression analysis, it was found that the

students' conﬁdence in information searching and experience of

informal query could predict their general WLSE. In addition, the students' functional WLSE was only predicted by their conﬁdence in information searching. Since information searching is an important component of online learning environments (Tsai & Tsai, 2003; Tu, Shih, & Tsai, 2008; Van de Vord, 2010), and con_{ﬁdence is highly linked}

with the construct of self-efﬁcacy, the students' conﬁdence in

information searching can well predict their general and functional self-ef_{ﬁcacy in terms of online learning. Furthermore, experience of} informal queries for OAHS is the other variable to predict students' general WLSE. The result of stepwise regression may reveal that the students' experience of seeking help from informal online channels (e.g., knowledgeable peers, unknown experts from the Internet) is prominent when they participate in a web-based course. Students with more experience of OAHS informal querying would tend to show

more general self-efﬁcacy during the web-based learning process.

Kitsantas and Chow's study (2007)addressed that university students would prefer to seek help from formal sources when enrolling in based courses, while this study proposes that instructors or web-based learning administrators should pay more attention to students' OAHS informal queries.

As a whole, the university students were familiar with the strategies of searching information online, while they reflected less experience or confidence or preference of formal and informal query behaviors for OAHS. According to the aforementioned discussions, we suggested that formal and informal query for OAHS should be concerned more by teachers or school administrators, especially informal query which was a variable to predict university students' general WLSE. Meantime, we also found that there was a positive interplay between learners' perception of formal and informal query. Through the enhancement of formal query, it may be helpful for learners to foster the motivation and behaviors of querying informal-ly. For instance, the instructors of web-based course could encourage learners to raise questions through email or message delivering function provided in the web-based learning system as they may encounter academic problems; or the mechanism of personal guidance after class from teachers or assistants could be established online; or designing an e-tutor system which could provide a real-time communication platform for learners to seek help from teachers or assistances without face-to-face embarrassment and threat of self-esteem (Karabenick, 1998, 2003; Kozanitis et al., 2007; Ryan & Pintrich, 1997). The social network communication recently emerged may also be considered to be integrated into the OAHS. An instructor of online course could create his/her social network website (e.g., Facebook, Twitter, Plurk) for an individual or specific course to build a special learning community. As the contact with the web-based course instructor increases in students' daily lives, the interaction between learners and teachers could be enhanced. Also, with teachers' encouragement and guidance of OAHS, the learners

would realize the beneﬁts of querying others through online

channels. By the means of enhancing formal query for OAHS, this study proposes that learners would be used to seek help as they have academic problems no matter from teachers or peers or even unknown experts online. By enhancement of informal query behavior, this study anticipated that learners' self-efﬁcacy toward web-based learning would be improved.

Table 5

Correlation between the OAHS and WLSE factors (n = 124).

Experience Conﬁdence Preference

Searching Formal query Informal query Searching Formal query Informal query Searching Formal query Informal query

General WLSE .16 .23⁎⁎ .23⁎⁎ .37⁎⁎ .17 .20⁎ .18 .18⁎ .20⁎

Functional WLSE .26⁎⁎ .15 .01 .55⁎⁎ .20⁎ .13 .36⁎⁎ .14 .10

⁎⁎ pb.01. ⁎ pb.05.

Table 6

Stepwise regression model for predicting students' OAHS based on their WLSE (n = 124). Dependent variables Predicting variables B S.E. β T R General WLSE CS 0.32 0.08 0.35 4.15⁎⁎⁎ 0.42

EIQ 0.17 0.08 0.19 2.26⁎ Constant 1.73 0.32 5.42⁎⁎⁎ Functional WLSE CS 0.46 0.06 0.55 7.20⁎⁎⁎ 0.55

Constant 2.10 0.24 8.67⁎⁎⁎ CS: conﬁdence of information searching, EIQ: experience of informal query.

⁎⁎⁎ pb.001. ⁎ pb.05.

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5. Conclusion and future research suggestion

In conclusion, this study utilized questionnaires to investigate students' self-reported perceptions about OAHS and WLSE. The results could probably depict a general situation of contemporary university students' perceptions of OAHS and their WLSE. The authors suggest that open-ended questionnaires or interviews might be used to acquire more insights into students' OAHS behaviors in further studies. To explore students' self-efﬁcacy in a web-based learning environment, the topics which may be related to WLSE such as the effects of different online course settings, knowledge domains, or other learners' characteristics (e.g., learning styles) should be surveyed further. Besides, this study also proposes that the instruments for

assessing WLSE toward more speciﬁc courses should be developed in

the future. By measuring the learners' self-efficacy in general in the beginning of a certain online course and their web-based learning self-efficacy near the end of the course, the instructor could find out the possible change for the learners' WLSE. Studies concerning the gap between WLSE toward web-based learning in general and WLSE toward a specific course may provide potential insights for the improvement of implementing online courses. Finally, there was a clear limitation in this study. In the information searching scale, only two items remained for the reason that it should be valid across the measurement of the students' experience, confidence and preference of OAHS. Future study could consider adding more items into the information searching scale and performing factor analysis further to construct more valid OAHS questionnaire with additional items.

Acknowledgment

Funding of this research work is supported by National Science Council, Taiwan, under grant numbers NSC 98-2511-S-011-005-MY3 and 99-2631-S-011-001.

Appendix A. The OAHS questionnaire items A.1. Information searching

1. When I have an academic problem, I will seek a relevant solution using search engines (e.g., Google, Yahoo).

2. When I have an academic problem, I will seek a relevant solution using Wikipedia.

A.2. Formal query

1. When I have an academic problem, I will email the instructor or class assistants to make a query.

2. When I have an academic problem, I will query the instructor or class assistants on the web-based course forum or guestbook for a relevant solution.

3. When I have an academic problem, I will query the instructor or class assistants by Instant Message Software (e.g., MSN, Skype). 4. When I have an academic problem, I will query the instructor or

class assistants through possible online channels. A.3. Informal query

1. When I have an academic problem, I will post a message on relevant web forums requesting unknown experts' help.

2. When I have an academic problem, I will ask for peers' help through some popular blog systems (e.g., Plurk, Twitter). 3. When I have an academic problem, I will post a query on relevant

knowledge community websites (e.g., Yahoo! Knowledge). 4. When I have an academic problem, I willﬁnd the proper websites,

forums or Bulletin Board System (BBS) to ask for unknown experts' help.

Appendix B. The WLSE questionnaire items B.1. General WLSE

1. I believe that I can get excellent grades on web-based courses. 2. I believe that I can capture the basic concepts taught in web-based

courses.

3. I believe that I can understand the most dif_{ﬁcult part of web-based} learning materials.

4. I believe that I can do a good job of learning tasks involved in web-based courses.

5. I believe that I can master the learning materials in web-based courses.

B.2. Functional WLSE

1. I believe that I canﬁnd the functions I need in an online learning system.

2. I believe that I can upload assignments to an online learning system before the deadline.

3. I believe that I can download instructional materials from an online learning system.

4. I believe that I can navigate instructional materials in an online learning system at will.

5. I believe that I can email instructors to make queries from an online learning system.

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