Learning Strategies for Success
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LEARNING STRA TEGIES FOR SUCCESS INA WEB-BASED COURSE A Descriptive Exploration
Haihong Hu University of North Elorida
Jennifer Gramling Florida State University
Web-based distance instruction has become a popular del ¡very method for education. How are leaming strat- egies helping make the connection between Web-based technologies and educational goals? The purpose of tbis study was to examine leamers" use of self-regulated learning strategies in a Web-based course. Twelve students from an information studies online course participated in a semislructured survey abiiut their leaming strategies. The contení analysis oftbe survey responses revealed tbat self-regulated leaming strategies in tra- ditional siUiations could be identified in students' online leaming. Participants' responses also indicated that they considered goal-sening/lime- or etïbn-management and cognitive strategies the most helpful ones for them to perform successfully in the course. This article may offer insights to instructors and designers of the distance leaming environment, and also provide suggestions for future research.
In Web-based distance education courses, individuals are able to participate at their con- venience with little to no supervision. The learner control inherent in these courses is usu- ally considered a positive feature to enhance motivation (Reeves, 1993). However, research has shown that leamer control is associated with a number of negative outcomes, such as less time spent on task and the use of poor learning strategies (Brown, 2001; Williams, 1993). Another factor, learners' self-regula- tion, is a powerful predictor for their academic achievement (Ley & Young, 1998; Pintrich &
Groot. 1990), and it also has a positive effect on leamers' motivation (Kitsantas, Reiser, & Doster, 2003; Lan, 1996; Schunk, 1996; Zim- merman & Kitsantas, 1996). New leaming environments, such as Web-based instruction, require proactive and active ieaming to con- stmct knowledge and skills. Schunk & Zim- merman (1998) mentioned distance education as an area that lends itself well to self-regula- tion. They claimed that "self-regulation seems critical due to the high degree of student inde- pendence deriving from the instructor's physi- cal absence" (p. 231). Therefore, a number of
• Haihong Hu, Department of Leadership. Counseling, and Instructional Technology, College of Education and Human Services, University of North Florida, Jacksonville. FL 32224. E-mail: baihong70rayahoo.com
The Quarterly Review of Distance Education, Volume 10(2). 2009, pp. 123-134 ISSN 1528-3518 Copyright € 2009 Infomiation Age Publishing, Inc. All rights of reproduction in any form reserved.
124 The Quarterly Review of Distance Education Vol. 10, No. 2, 2009
researchers (Keller. 1999; McMahon & Oliver, 2001; Zimmerman, 2000) have proposed uti- lizing self-regulatory strategies to promote online learners' motivation and understanding. Studies that address the use of se If-regulated learning strategies in Web-based courses, however, are limited (Whipp & Chiarelli, 2004). The present study was designed to pre- liminarily explore learners' use of self-regu- lated leaming strategies in an online environment.
THEORETICAL FRAMEWORK
Self-Regulated Learning (SRL)
Over the last decade, leamers' self-regula- tion of their cognition, motivation, and behav- iors to promote academic achievement has been a topic of increasing interest in the field of education (Bandura, 1986; Schunk, 1996; Zimmemian, 1990, 1998). Driscoll (2000) refers to se If-regulation as skills that leamers use to "set their own goals and manage their own leaming and performance" (p. 304). Zim- memian (1990) defines self-regulated leaming with three distinctive features: learners" appli- cation of self-regulated leaming strategies, their sensitivity to self-evaluative feedback about leaming effectiveness, and their self- generated motivational processes. Researchers found that leamers who reported more exten- sive use of SRL strategies demonstrated higher academic achievement (Lan, 1996; Schunk, 1982, 1996; Schunk & Swartz, 1993; Zimmer- man & Kitsantas, 1996; Zimmerman & Marti- nez-Pons, 1986), more positive motivation (Schunk, 1982, 1996; Schunk & Ertmer. 1999; Schunk & Swartz. 1993; Zimmerman & Kit- santas, 1996, 1999). and greater persistence (Lan. 1996) than leamers who used the similar strategies less often.
Erom a social-cognitive point of view, self- regulatory processes and beliefs consist of three cyclical phases: forethought, perfor- mance or volitional control, and self-reflection (Zimmerman, 1998, 2000). According to Zim- merman, the forethought phase happens before
efforts to learn, and sets the stage (goals and plans) for leaming. Performance or volitional control processes occur during leaming efforts, and concerns concentration and perfor- mance monitoring. Self-reflection processes take place after leaming efforts. The results from self-reflection or evaluation affect learn- ers' reactions to that experience. As a result, these self-reactions complete the self-regula- tory cycle by influencing forethought of subse- quent leaming efforts.
From a general expectance-value perspec- tive, self-regulated leaming involves both the "will" and the "skill" (Pintrich & Schrauben, 1992). The "skill" component of the general expectancy-value model of SRL consists of three major categories of strategies, including: metacognitive strategies (planning, goal set- ting, monitoring and seif-evaiuation), cogni- tive strategies for leaming and comprehending the materials (rehearsal, elaboration and orga- nization), and resource-management strategies (help seeking, environmental management strategies and time management). Further- more, the "will" or the various motivational aspects, including self-efTicacy and goal orien- tation, are believed to facilitate and influence the use of these cognitive, resource-manage- ment, and metacognitive strategies.
Every leamer is self-regulated to some degree in his or her académie leaming, but there are remarkable differences among stu- dents (Zimmerman, 1998). Systematic use of metacognitive, motivational, cognitive strate- gies is a key feature of most self-regulated leamers. Therefore, students' level of self-reg- ulation may eventually decide whether their leaming experiences will become frustrating or fulfilling.
Self-Regulation in Web-Based Distance Education
Web-based courses can be accessed by any eligible individual from any location, and asynchronous course components are available 24 hours a day, at the learner's convenience. Web-based distance instruction has become a
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Learning Strategies for Success in a Web-Ba'ied Course
popular delivery method for education because of these features. Se If-regulation, however, is essential for distance education students' suc- cess. Students are held more accountable for their own learning. Furthermore, they must cultivate the self-discipline to access the course communication tools on a regular basis to avoid falling behind with assignments (Simonson, Smaldino. Albright, & Zvacek, 2000).
One of the major problems existing in Web- based distance education is a high attrition rate (Zielinski. 2000). Various studies have reported such factors as lack of time and envi- ronment management skills (Kember, Mur- phy. Siaw, & Yuen, 1991 ; Osborn, 2001), low self-motivation (Osborn, 2001; Parker, 2003). lack of cognitive learning strategies (Chyung, 2001; Kember et al., 1991), discomfort with individual learning (Ejortoft, 1995), and low learner self-efficacy on using the technology for distance education program (Chyung, 2001; Osbom, 2001) are causing students to drop out of distance programs.
Several researchers have studied the influ- ence of se If-regulatory behaviors on learning in the online mode, hut most of these studies focused on identifying se if-regulatory strate- gies as predictors for achievement. King. Hamer, and Brown (2000) conducted a study to measure students' perceptions concerning the effect of technology and student self-regu- latory skills in two distance education courses. A factor analysis of the data indicated that two constructs attributed to online learning success were study skills and goal setting. Eom (1999) identified SRL strategies that learners already possess were related to the effectiveness of learning in a computer-networked hypertext/ hypermedia environment. His results demon- strated that metacognitive and motivational strategies significantly infiuenced the predic- tion of achievement, while cognitive and self- management strategies did not exhibit signifi- cant effects. However, these studies assume that participants in distance education employ the same SRL strategies for traditional instruc- tion in their learning. Very few studies have
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explored which SRL strategies are used in Web-based courses to address the unique chal- lenges of the online learning environment (Whipp & Chiarelli, 2004).
Research Questions
With the proliferation of distance educa- tion, more and more leamers are taking online courses. A reasonable question to ask is how do students study in these online courses'? Do online students who are working indepen- dently employ any learning strategies to help achieve learning outcomes? Can our existing understanding about SRL be applied to this new learning environment? This study was designed to use our current knowledge about SRL as a basis for exploring answers to these general questions and to identify issues that might warrant further investigation. This study combined Zimmerman"s (1998, 2000) social cognitive model, which outlines the key sub- processes for SRL, and Pintrich's (1995) gen- eral expectancy-value model of SRL, which offers a closer examination of each specific category of strategies utilized in the processes, as a theoretical framework. With regard to this theoretical framework, this study used the fol- lowing research questions to guide the investi- gation.
1. What SRL strategies do students use in a Web-based course?
2. What strategies do students think are the most helpful to their success in a Web- based course?
METHOD
Participants
This pilot study took place at a large South- eastern university in the U.S. during the sum- mer semester 2005. Participants were 12 volunteer students enrolled in an online Tech- nologies for Information Services course for information studies majors. These volunteers
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had an average age of 24.58 years. Six of them were seniors, 5 were juniors, and 1 was a soph- omore. Eight were females and 4 were males. Five were African Americans, 1 was Asian American, 3 were Caucasians, 2 were Hispan- ics, and 1 was from another ethnic back- ground. These participants had an average GPA of 2.89 and an average registration for 9 credit hours. They spent an average of 4.38 hours weekly studying for this course, while they also worked 20-30 hours per week. Five of these volunteers had family responsibilities that affected their time for studying in this course. Eleven of the participants thought they were competent with PC and Macintosh, 11 with Internet, 12 with e-mail, 8 with asynchro- nous discussion, and 7 with synchronous dis- cussion. Seven of these volunteers had never taken online courses before, three had taken 1, one had taken 2, and one had taken 4.
Context
The Technologies for Information Services course focused on the application of computer hardware, software, and information systems for the provision of information services. The course content included recent technical devel- opments with examples of real-world software applications. It also examined the principles by which computer systems and their networks support information seekers. It used a textbook entitled Using Information Technology: A Practical Introduction to Computers & Com- munications (Williams & Sawyer, 2001). Stu- dents' grades were determined by participation (10%), 11 weekly activity reports (50%), a project resource list (10%) and a final project (30%). Participation scores consisted mainly of synchronous weekly discussions on relevant topics, and weekly asynchronous class activi- ties. These activities included reading the text- book and supplementary materials, viewing PowerPoint lectures posted in course Web site, and completing the activity reports and proj- ects.
By the end of the semester, students were supposed to be able to explain the essential
concepts and components of current informa- tion technology systems, including operating systems, user interfaces, hardware, and com- munications, and extend them to emerging contexts. Furthermore, they were expected to summarize the history, evolution, and charac- teristics of information technology. They were also required to describe the basics of network topology as well as the primary uses of net- works and networking within the context of information provision.
Data Collection and Analysis
This descriptive study used qualitative methods to examine students" use of self-regu- lated learning in a Web-based course. A small group of students were selected as participants. An online survey with 13 open-ended ques- tions was created using informal interviews with 5 faculty and 5 online students to discuss the general features of Web-based courses and to explore students leaming strategies, plus information obtained from a review of litera- ture on the cyclical process of learning (Zim- merman, 1998, 2000). This study was conducted as a pilot test to test the validity of the instrument and the feasibility of the research process.
Through the use of the online questionnaire, panicipants were asked to describe their goals in the course, their plan(s) for reaching their goals, how they usually completed assign- ments, how they read textbook and online materials, their obstacles and how they over- came them, their distractions and how they dealt with them, how they arranged time for studying, how they verified their understand- ing and progress in the course, and what strat- egies they deemed most helpful. Participants' answers to the online open-ended survey ques- tions were the primary data source. Course syl- labus, assignment descriptions, and student Web pages were used to contextualize the researchers' understanding of participants" answers to online survey questions. The sur- vey was conducted 4 weeks after the semester began, and participants had 7 days to complete
Learning Strategies for Succe,ss in a Web-Based Course 127
the survey, which was accessible to partici- pants through a Web link in an e-mail sent by the fust author.
Participants' responses to questions were transcribed and the texts coded and analyzed using Q. S. R. NVIVO software. To examine participants' answers lo survey questions, the researchers followed the guidelines for qualita- tive content analysis (Chi, 1997), using an inductive constant comparative method (Gla- ser & Strauss, 1967) because the purpose of the study is to understand the strategies used during a learning process. The first author read participants' answers to survey questions sev- eral times and highlighted comment units or references (i.e., word(s). phrase(s) or sen- tence(s)) (hat described a type ofleaming strat- egy (open-coding) to capture main ideas, themes. Then, she began with a search for pat- terns within the data on each of the partici- pants, and then across all participants (axial coding) to portray relationships. Finally, she summarized the leaming strategies used in the process with the patterns found across all par- licipants. Using Zimmerman's (1998, 2000) social cognitive and Pintrich's (1995) general expectancy-value models of SRL, a coding scheme was created based on (he responses (o survey questions. The first author and a (rained coder tested in parallel the coding scheme on a sampling of participants' responses and then refined it and applied it (o all the responses from all participants. Refer (o Table 1 for a final version oflhe coding scheme.
To determine the inter-rater reliability for the coding scheme, an independent coder was trained to use the coding systems, and compar- isons were made between coding of the survey responses made by the independent coder and the first author. The inter-ra(er reliability for the coding scheme was found to be about 90%. Each survey response was (hen coded indepen- dendy by (he first author and the trained coder using the coding scheme (hat included defini- tion and example of each strategy to compare to (he exact words in the responses. The first author and the trained coder resolved all dis- agreements on the references through further
reading of the raw data and discussion. After all answers to survey questions were coded, the data from individual participants were examined by coding category. Next, the data were examined across patticipants by coding category.
In this study, a member checking was con- ducted by inviiing a participant in the s(udy (o verify (he accuracy of (he findings and appro- priateness of discussion. The participant con- sidered (he study procedures were described in sufficient de(ails and (he results were clearly reported, especially the quotes helped validate and reinforce the points.
RESULTS
Strategies Reported by Participants
In (heir answers to the open-ended ques- tionnaire, participants mainly reported using all three categories (me(acogni(ive, cognitive, and resource management) of strategies included by Pintrich (1995) in the "skill" com- ponent of SRL. This content analysis of the data indicated (hat par(icipants in (his study not only employed some strategies (hat successful students use in traditional leaming environ- ments, but also revised their SRL strategies (Whipp & Chiarelli, 2004) to adapt to (heir Web-based course se(ting. Results derived from the analysis of s(ra(egies are shown in Table 1.
Metacognitive Strategies
Wi(hin the category of metacognitive s(ra(- egies, participants reported using goal setting (9 references), strategic planning (9 refer- ences), se If-monitoring (30 references) and self-evaluation (8 references).
Self-monitoring was (he most Irequendy repor(ed (30 references) s(rategy within the metacognitive category. Participants took some measures (o moni(or their learning pro- cess, which was dependant on tlie s(abili(y of
12fi The Quarteriy Review of Distance Education Vol. 10. No. 2, 2009
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130 The Quarterly Review of Distance Education Vol. 10. No. 2. 20(W
the technologies, as well as their own compre- hension of the materials
ln regard to self-evakiation/reflection. par- ticipants reported on their perceived criteria for evaluation, which is unique to online courses, and their actual strategies to evaluate performance, which were also modified to suit the online learning environment. As a result, participants believed their success was based on the teacher"s standards and their perfor- mance in a group as a whole, as exemplified by the following responses: "The approach mostly depends on the teacher and the way he/ she likes the assignments to be presented." and •'1 work pretty well on group assignments depending on the members in the group. If they are focused then I can work great, if not then there will be some issues."
Cognitive Strategies
in this study, cognitive strategies were the most frequently ( ] 2 cases, 60 references) reported by participants in all the responses to survey questions.
Most of the cognitive strategies reported were similar to the ones students generally use for traditional instruction. Overall, the most frequently used strategies were rereading (16 references), note-taking (11 references) and visualizing (7 references), and 7 participants gave 10 references about using the audio por- tion of their lecture in various situations for study.
Generally speaking, most participants were using less complex cognitive strategies, mainly rehearsal strategies (11 cases, 46 refer- ences) (e.g., rereading), while fewer partici- pants used more advanced organization (7 cases, 7 references) (e.g., fiash cards) and elab- oration strategies (5 cases. 7 references) (e.g., visualizing).
Resource Management Strategies
The resource management strategies reported by participants included time man- agement (16 references), effort regulation (11
references), environment management (13 ref- erences), and help seeking (22 references).
Help seeking strategies was the most fre- quently (22 references) reported in this cate- gory. Overall, the most frequently used strategies were using the Internet (7 refer- ences), informing/asking a teacher, TA or tutor (6 references), and referring to other sources (e.g. family, friends) (4 references). Only one participant gave 2 references about an online- specific help-seeking strategy, using course discussion boards/peers to understand difftcult contents.
Not being able to locate a textbook (3 cases) at a local bookstore caused some anxiety in this class, but positive help seeking helped ease learners' anxiety. The following e.xcerpt demonstrates participants' employment of help-seeking strategies in this online environ- ment.
P7: The only confusion and I would not say obstacle is when I could not find the text book assigned in neither of the book- stores in town, but once I contacted the TA 1 was able to acquire the book in no time.
Perceived Most Helpful Strategies
Generally, participants reported two broad categories of strategies: cognitive strategies (7 cases, 7 references) and goal setting/effort con- trol/time management (5 cases, 5 references), as their perceived most helpful strategies.
Most of the goal setting strategies reported were adopted from the features of this Web- based distance learning course, but not many references for this type of strategies were refiected in participants' responses. Within the 9 references made by 5 participants, they mainly reported using discussion board ques- tions (4 references) and assignments (3 refer- ences) as immediate goals to complete course tasks and to find the focus for their work. Additionally, they coordinated online and offline coursework on the basis of these imme- diate goals.
Learning Strategies for Success in a Web-Based Course 131
The data suggest that getting assignments done on time or ahead of the schedule was cru- cial to the participants in this online course. The value of completing tasks on time and keeping up with coursework was conveyed by one participant: "The goals I'm working for in this course is to become more familiar with IT tools. The plan I choosing to achieve this goal is to stay on top of things and study."
Participants arranged their time for study around their working schedule. Among the 8 participants who worked more than 20 hours per week. 1 planned to study during the day, 4 planned to study during the night, and 2 gave indefmite answers. Five participants specifi- cally designated different time for different types (online or offline) of coursework.
Examining the fmal grades of the 6 partici- pants who worked more than 31 hours weekly, 3 received B's, and 2 received C*s and I received a D. The two participants who received C's provided indefinite answers to questions about time management strategies, while the two participants who received the highest scores (88 in a class average of 80.7) were also within this working-hour category, but expressed definite plans for time manage- ment. The contrast In their time management was illustrated with the following responses:
PI: Well I am never really offline, even when I am doing my course work I check the discussion and email regularly. Therefore I do not have a time of day or days of week were I usually do online/ offlie [sic] work. (Received a 79.4 for course score).
P7:1 do my offline coursework in the mom- ing (3am) hours because I work better in the morning than in the evenings. My online coursework I do throughout the day—whenever 1 get at least two hours of break. (Received an 88 for course score)
Family responsibilities (e.g., small children) can cause obstacles in online courses because
many distance learners study at home and need to take care of family. In this study, 5 (42%) of the 12 panicipants reported having family responsibilities that affected their time for studying for this course. Three of these 5 par- ticipants had definite plans for time manage- ment and received well above average scores (83, 88, 88 in a class average of 80.7). These following excerpts describe how one of these participants utilized time and environment management and effort regulation strategies to overcome difficulties and to accomplish leam- ing outcomes (a final score of 83).
Q: Do you expect to meet any obstacles in the course? What are they? When faced with obstacles in the course, what will
I you do to overcome these obstacles?
A: I tend to meet obstacles in all my courses with two small children. For instances, this past weekend my son and myself have been sick which makes it hard to keep on track. To compensate for my time lost studying I will have to stay up late a couple of nights this week to catch up.
Q: What time of day and day(s) of the week do you usually do your offline course- work? Why? What time of day and day(s) of the week do you usually do
' your online coursework? Why?
A; I usually am working on something daily or at least I try to. I usually work on it in the morning at the library three times a week because I don't have my kids then. I also work on it in the evening when my kids are sleeping.
I
DISCUSSION
Based on the findings from this study, the fol- lowing section proposes implications for Web- based course instructors and designers, and suggestions for future research.
132 The Quanerly Review of Distance Education Vol. 10, No. 2, 2009
Goal-setting/effort control/time manage- ment is a combined category of s(rategies per- ceived by participants as the mos( helpful strategies in online leaming. This finding is consis(en( w Í(h (hose of several other studies (Azevedo, Guthrie, & Seiber(, 2004; Hill & Hannafin, 1997; Loomis. 2000) about leaming strategies in online environments, including the finding from a quanti(a(ive s(udy (Loomis, 2000) 0^ the strong correla(ion between time management skills and fmal grades in an online course. From the data in this study, we also found that many online participants were working for pay while taking courses. It seemed that the more a participant works, the more likely he or she would (ry (o complete coursework during the night or at a previously unplanned time. However, it was also discov- ered (ha( working full time itself might not affect s(uden(s' performance. Instructors in a distance educa(ion environment might need to communicate deadlines and due dates clearly, emphasize the use of (ime-managemen(, effort regulation and goal-setting strategies, espe- cially to students who are working full-(Íme or who have family responsibilities.
Cognitive strategies were repor(ed by par- ticipants as another category of (heir mos( helpful strategies. Overall, cognitive strategies were the most frequently reported by partici- pants in all the responses and reading and rep- etition was reported by 25% of the participants. These findings are very similar to wha( Whipp and Chiarelli (2004) found about (heir participants in a Web-based course in that mos( participants were using less complex cognitive strategies, essentially rehearsal strat- egies, while fewer participants used more advanced organization and elaboration strate- gies. Instructors might encourage students to use more sophisticated strategies, such as organization (e.g., concep( mapping and out- lining) and elaboration (e.g., using mnemon- ics, summarizing and reciprocal teaching) for deeper processing of information (Holer, Yu, & Pimrich, 1998). Recommendations can also be made for more online-specific cogni(ive strategies, such as reading while listening to
(he lecture, copying online materials into a (ext editor and rewriting into personal notes, and replaying the lecture, to be more adapted (o the distance education environment.
In this study, (he most frequently reponed help seeking strategies were using the In(eme( and informing/asking a (eacher. TA or tutor. However, only one participant mentioned an online-specific help seeking stra(egy, using course discussion boards/peers to understand difficuU contem. This finding is similar to what Zariski & Styles (2000) Ibund from their interview wi(h 16 law students. They found even though (hese s(uden(s in two online courses used help seeking to deal with techni- cal problems more extensively than (heir coun- terparts in more traditional educational con(ex(s, there was only very limited use of options (e.g., Unit Guide, the Chat Room, Help button, etc.) available in the course site for help seeking. Instructors may need to provide guidelines on help seeking in cyberspace since some of the leamers are not very familiar with (his leaming environmen(. Instructors might want (o encourage online leamers (o u(ilize discussion boards more ac(ively, by set(ing up a forum named Online Office or S(udent Lounge, for help seeking and critical dis- course.
There are many limitations to this pilo( study. The research design could be improved by administering a well-structured question- naire with objective items, followed up by a phone interview or focus group, across several courses later in (he semester. Experimental studies on a large scale are needed to verify some of the speculations from (his study about SRL strategies in distance education, namely, the relationship between work load, time man- agement and achievemen(, (he social aspects (e.g., peer leaming. help seeking, class discus- sions) in online leaming (Whipp & Chiarelli, 2004), and the in(errelated self-regulation and co-regulation, such as in group projects, (hat might happen within (he leamer popula(ions.
Acknowledgment: Many (hanks (o the instnac(or, Alan S(romberg, and the students of
Leaming Strategies for Success in a Web-Based Course 133
this LIS 3353 course, who kindly volunteered lo participate in the study, for their coopera- tion in making this study possible. We also thank Luisa Piéger lor helping us with verify- ing the results.
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