Online or face-to-face? Students' experiences and preferences in e-learning

Internet and Higher Education 13 (2010) 292–297

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Internet and Higher Education

Online or face-to-face? Students' experiences and preferences in e-learning Manuela Paechter ⁎, Brigitte Maier Department of Psychology, University of Graz, Universitaetsplatz 2, 8010 Graz, Austria

a r t i c l e

i n f o

Article history: Accepted 9 September 2010 Keywords: e-learning Online learning Face-to-face learning Experiences in e-learning

a b s t r a c t Which aspects of e-learning courses do students experience as being favorable for learning? When do students prefer online or face-to-face learning components? These questions were the subject of a research study in a sample of 2196 students from 29 Austrian universities. The students completed a questionnaire on their experiences attending an e-learning course, on their perceived achievements, and on their preferences for online or face-to-face learning components. Students appreciated online learning for its potential in providing a clear and coherent structure of the learning material, in supporting self-regulated learning, and in distributing information. They preferred face-to-face learning for communication purposes in which a shared understanding has to be derived or in which interpersonal relations are to be established. An especially important result concerns students' perceptions of their learning achievements: When conceptual knowledge in the subject matter or skills in the application of one's knowledge are to be acquired, students prefer face-toface learning. However, when skills in self-regulated learning are to be acquired, students advocate online learning. © 2010 Elsevier Inc. All rights reserved.

1. Introduction Over the past few years, digital media have enriched the teaching and learning experiences and have become commonplace with university students and lecturers. Within only a few years, the use of e-learning, i.e. the application of digital media for teaching and learning (Liaw, Huang, & Chen, 2007), has increased rapidly. In Austria, joint endeavors have been made in the last ten years by universities to introduce e-learning (mostly online components in blended learning classes). Promotional programs with financial support by the government have been established to encourage universities to improve tertiary education by e-learning. These initiatives resulted in a variety of best-practice examples for elearning and course development strategies (Pflichter, 2006). The advancement of e-learning at universities was also influenced by the development of technical support, e.g., by the widespread introduction of learning management systems (such as Blackboard, WebCT, Moodle applications etc.) (Alexander & Golja, 2007; Coates, James, & Baldwin, 2005). In a socio-demographic survey carried out in 2006, 3729 students from various Austrian universities were asked how often they use learning management systems in their courses. In the social and business sciences, 60% of students reported using such

⁎ Corresponding author. Tel.: +43 316 380 8542, +43 316 380 5083; fax: +43 316 380 9805. E-mail addresses: [email protected] (M. Paechter), [email protected] (B. Maier). 1096-7516/$ – see front matter © 2010 Elsevier Inc. All rights reserved. doi:10.1016/j.iheduc.2010.09.004

systems ‘sometimes’ or ‘frequently’. In other subjects, between 30 and 40% of students reported using such systems ‘sometimes’ or ‘frequently’ (Unger & Wroblewski, 2007). Yet, even though the application of e-learning at universities has increased rapidly, little is known about students' experiences and preferences in e-learning. Until recently, research focused on single aspects of students' experiences and opinions such as the interaction with the instructor, the quality of a specific course, or learning with a specific learning management system (cf. Alexander & Golja, 2007; Lester & King, 2009). Mostly, only one or few courses or a single institution were investigated (Coates et al., 2005; Lee, Yoon, & Lee, 2009). Few studies investigated larger sample sizes or samples from more than one institution (e.g., Alexander & Golja, 2007). Also, there is a lack of studies which investigate students' experiences of the combination of face-to-face and online learning components (e.g., Bliuc, Goodyear, & Ellis, 2007). The aims of the current study were to obtain a comprehensive view of students' experiences and preferences in e-learning in Austria, to investigate which learning experiences contribute most to course satisfaction, and to investigate for which purposes students prefer online components and for which they prefer face-to-face components in a blended learning course. The objective of the study was not to examine specific courses but to survey a large and representative sample of students attending Austrian universities in order to obtain a broad picture of their experiences in e-learning. Therefore, a survey was conducted including a sample of 2196 students from all universities in Austria that offer e-learning courses and from a selection of universities of applied sciences.

M. Paechter, B. Maier / Internet and Higher Education 13 (2010) 292–297

2. Theoretical background When designing courses with e-learning components or instructions in general, instructors are faced with many considerations and decisions which affect how students experience instruction and how they construct and process knowledge. These decisions about the didactic design of a course may refer to different fields of instruction. Quality assurance systems describing desirable characteristics of elearning (Ehlers, 2004; Young & Norgard, 2006) as well as general instructional models (Brophy, 1999) distinguish the following fields of instruction:

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(Concannon, Flynn, & Campbell, 2005; Garrison et al., 2000; Nagel & Kotzé, 2010). 5) Individual learning processes: E-learning students may receive ample opportunities to practice and apply what they are learning. Self-regulation of learning is an important characteristic of elearning courses. Students have choices regarding the time, place, and the regulation of learning processes in general (Nagel & Kotzé, 2010; Narciss, Proske, & Körndle, 2007). 3. Method and sample Three questions were addressed in the current study:

1) Learning outcomes: Learning outcomes can be described as competences which students are to achieve (Weinert, 2001). Students may acquire different facets of competences: Factual and conceptual knowledge within a field of study, methodical knowledge including skills required for problem solving and scientific practice (e.g., literature research), social and personal competences, and/or media competence. Factual and conceptual knowledge refers to understanding classifications, theories, or models; methodical knowledge refers to the application of subject-specific skills, techniques, and methods (Anderson & Krathwohl, 2001). In university courses, students should not only acquire conceptual and methodical knowledge, but also social and personal competences (e.g., competences in team work, in the self-regulation and monitoring of one's learning processes; HRK, 2004). 2) Course design, learning material, and electronic course environment: Brophy (1999) assumes that the structure and coherence of the curriculum components and of the learning material are a major factor for facilitating meaningful learning. In e-learning, the quality of the learning environment contributes in part to the success of a course. Additionally, the ease of using a learning management system may affect course satisfaction (Chang & Tung, 2008; Shee & Wang, 2008), performance in the course (Lee & Lee, 2008), and the decision to continue or to drop out of a course (Chiu, Hsu, Sun, Lin, & Sun, 2005; Levy, 2007). 3) Interaction between students and an instructor: Instructors must perform a variety of tasks in the process of teaching, e.g., supporting students by providing a structure of the learning content, providing feedback of accomplishments, stimulating students' motivation to process and reflect on content, and lastly providing assistance to enable them to engage in learning activities (Brophy, 1999). Garrison, Anderson, and Archer (2000) describe these activities as teaching presence: Instructors support students to connect ideas, to apply new ideas, and to build understanding. Such mental engagement leads to the experience of cognitive presence in a course. The interaction between students and an instructor also supports motivation and the establishment of a social relationship. Therefore, not only is the exchange of information regarding educational content important for learning, but also social information. E-learning opportunities to exchange socio-emotional information may influence students' engagement, motivation, satisfaction, and the decision to continue a course (Johnson, Hornik, & Salas, 2008; Richardson & Swan, 2003). 4) Interaction with peer students: This aspect comprises discursive communication processes in which students exchange information on the learning contents and socio-emotional information. Students benefit in the following ways: working in small groups to construct understanding, from mutual socio-emotional support, and from learning within a cohesive and positive learning environment (Brophy, 1999). Mutual support and the feeling of group cohesion are related to students' experience of social presence, their engagement in team work, motivation to participate in a learning environment, and course satisfaction

1) How do students evaluate their experiences in e-learning classes (either pure online or blended learning classes)? It was assumed that due to instructional characteristics of e-learning (e.g., the need to use learning management systems, differences in the interaction among students or between the instructor and students, etc.) students would give distinct (favorable or unfavorable) evaluations of their experiences. 2) Which learning experiences contribute most to course satisfaction? The most important predictors for course satisfaction were investigated by means of explorative regression analysis. 3) For which purposes do students prefer online learning components and for which face-to-face learning components? It was assumed that students would prefer online and face-to-face components for different instructional purposes. In an empirical study, students' experiences in e-learning and their preferences for online learning or face-to-face learning components were assessed by a quantitative questionnaire. For the development of the questionnaire, a pilot study was conducted in which qualitative online interviews with 446 students were carried out. The questions in the interviews focused on students' experiences in the five fields of instruction. In a content analysis (Frederickson, Reed, & Clifford, 2005; Mayring, 2003) students' answers were categorized and the frequency of answers in the categories was determined. Based on the results of the content analysis, a quantitative questionnaire was developed. It included descriptions of learning experiences, assessment of learning achievements, a rating of the overall satisfaction with a specific elearning course, comparisons of the suitability of online learning and face-to-face learning sessions, and demographic questions. Students from all Austrian universities offering e-learning courses (pure online classes as well as blended learning classes) and from at least one university of applied sciences from each federal state in Austria were recruited. Lecturers and organizational units that offer support for e-learning were informed about the survey and were asked to inform students about it. The questionnaire employed in the research could be filled in via the internet. Upon request by the lecturers or organizational units, paper versions were sent out. Altogether, 2196 students from 16 universities and 13 universities of applied sciences took part. There were 1531 (69.72%) participants who studied at a university and 665 participants who studied at a university of applied sciences (30.28%). All students had in common that they actually attended an e-learning course which they evaluated in the questionnaire. The participating students were enrolled in a large variety of majors. In the group of university students, most participants studied social sciences (51.86%; n = 793), arts (15.63%; n = 239), or natural sciences (11.64%; n = 178); in the group of students at universities of applied sciences, most participants studied subjects combining technological aspects and business education (38.50%; n = 256) or business education and languages (30.08%; n = 200). There were 1361 (62%) female and 821 (37.39%) male participants (0.61% missing values, n = 14). Most students, namely 80.19%, were between 18 and 25 years old, 11.70% were between 25 and 30 years old, 7.88% were 31 and older.

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Most of the participants had already attended more than one elearning course: 20.13% (n = 442) had taken more than four elearning courses, 20.36% (n = 447) three to four, 36.75% (n = 807) one to two courses. Only 11.89% (n = 261) were enrolled in their first elearning course (10.88% missing values, n = 239 students). Students were also asked about the ratio of online and face-to-face components in their course: Only 11.98% (n = 263) of the participants attended a pure online course, 30.83% (n = 677) attended a course in which online components outweighed face-to-face components, 18.94% (n = 416) a course in which online and face-to-face components were equally distributed, and 35.47% (n = 779) a course in which face-to-face components outweighed online components (2.78% missing values, n = 61). 4. Results 4.1. Students' evaluation of their e-learning experiences Students evaluated the e-learning course they were attending at the time of the survey by 25 statements describing positive or negative e-learning experiences on a six-point scale (ranging from 1 “I disagree completely” to 6 “I agree completely”). Each statement belonged to one of the five fields of instruction (course design, interaction between students and an instructor, interaction with peer students, individual learning processes, learning outcomes). Another item assessed students' satisfaction with the course. One-way t-tests (Bortz, 1999) were carried out to investigate the hypothesis that students' evaluations deviate significantly from the mean of the scale (3.5, indicating neither agreement nor disagreement) (compare Table 1). Thus, it was analyzed whether students give distinct favorable or unfavorable evaluations. Bonferroni corrections were carried out for adjustment of multiple comparisons (Bortz, 1999). However, with a sufficiently large sample, already small differences can be found to be statistically significant. Therefore, effect sizes were calculated to determine whether the statistically found differences are of practical concern (Cohen, 1992). It was also investigated whether gender or the age of students influences the evaluations (Paechter, Fritz, Maier, & Manhal, 2007). As no differences were found for these groups, the results for the whole sample are reported in this paper. In all five fields, students gave positive evaluations of their course (all comparisons were significant; compare Table 1). High effect sizes (above 0.8; Cohen, 1992) were found for the structure of the material (M = 4.68), the handling of the learning management system (M = 4.66), and for the variety of communication facilities (M = 5.38) (course design). Also rated high was the accessibility of the instructor (M = 5.37) and his/her expertise (M = 4.94) as well as providing fast feedback (M = 4.99) and counseling and support by the instructor (M = 4.74) (interaction instructor/students), the opportunities to exchange knowledge with peer students (M = 4.69) (interaction with peers), and the acquisition of knowledge in the subject matter (M = 4.68) (learning outcomes). 4.2. Experiences that contribute to course satisfaction The contribution of different kinds of learning experiences resulting in satisfaction with the course was investigated by a hierarchical stepwise regression analysis. The satisfaction with the course was the criterion and the 25 items on learning (compare Table 2) were the predictors. Regression analysis yielded seven significant regression weights (estimations of multicollinearity confirmed the appropriateness of the model). Five items contributed positively to the satisfaction with a course: clarity and structure (β = .228), the acquisition of factual and theoretical knowledge (β = .133), the instructor's expertise in elearning (β = .146), the instructor's support and counseling

(β = .133), and the support for cooperative learning and group work (β = .072). Two items contributed negatively to satisfaction, namely difficulties in maintaining one's learning motivation (β = −.148) and Table 1 Students' experiences, learning outcomes, and satisfaction in e-learning. Items Course design The learning environment offers e-mail, chat, newsgroups and/or other communication facilities for the interaction with other course participants. The course itself and the learning material are clear and well structured. The learning environment is easy to handle. I often have to deal with technical problems (e.g., errors of the software, slow access to the internet). The course is demanding with regard to the organizational and temporal effort. Interaction with the tutor When I need advice from my tutor I can easily get in contact with her/him via e-mail, chat, forum etc. My tutor has a high expertise in the implementation of e-learning courses. My tutor gives fast feedback via e-mail, chat, newsgroups and/or other communication facilities. My tutor supports and counsels me with regard to my learning processes. I miss the personal contact with my tutor. Due to the online communication in the course personal relations are neglected. Interaction with peer students I can easily and fast exchange knowledge with other course participants via e-mail, chat, newsgroups etc. There are ample opportunities in the course to establish personal contact with other participants. The online communication tools facilitate establishing new contact with other students. Learning in groups and cooperation with other learners are fostered in the course (e.g., by group activities, discussions etc.). The communication with media complicates group work. Individual learning processes I decide on my own at what times and where I am learning (e.g., at the university, at home). I can decide on my own about the pace of learning and the use of learning strategies. The learning environment offers the possibility to control my increase in knowledge (e.g., via tests). I find it difficult to motivate myself and to maintain learning motivation in the course. Learning outcomes I acquire (conceptual) knowledge in the subject matter of the course. I learn to apply my knowledge to different problems. I acquire skills in the self-regulation of learning. I acquire skills in using the internet for scientific work routines (e.g., online research). I acquire skills in communication with media. Overall satisfaction (ranging from 1 = very low to 6 = very high)

M

SD

n

t

d

5.38 1.11 2180

78.939 1.69

4.68 1.24 2178

44.433 0.95

4.66 1.35 2151 39.865 0.86 2.71 1.56 2179 −23.727 0.51

3.79 1.37 2175

9.937 0.21

5.37 0.99 2172

88.349 1.90

4.94 1.12 2170

59.712 1.28

4.99 1.25 2150

55.102 1.19

4.74 1.26 2160

45.422 0.98

2.42 1.47 2179 −34.134 0.73 3.13 1.62 2164 −10.500 0.23

4.69 1.31 2181

42.401 0.91

4.42 1.40 2179

30.738 0.66

2.91 1.53 2168 −17.873 0.38

3.96 1.56 2171

13.769 0.30

3.18 1.56 2174

−9.611 0.21

4.51 1.61 2174

29.214 0.63

4.38 1.43 2174

28.473 0.61

3.15 1.78 2152

−9.036 0.19

3.05 1.53 2170 −13.709 0.29

4.68 1.16 2162

47.491 1.02

4.27 1.26 2159

28.148 0.61

4.27 1.37 2161

26.204 0.56

4.26 1.48 2178

23.814 0.51

4.18 1.55 2176 4.41 1.25 2072

20.477 0.44 33.382 0.73

M = mean, SD = standard deviation, n = sample size, t = t-scores, d = effect size.

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M. Paechter, B. Maier / Internet and Higher Education 13 (2010) 292–297 Table 2 Hierarchical stepwise regression analysis for variables predicting course satisfaction. Items The course itself and the learning material are clear and well structured. I acquire expertise in the subject matter of the course. My tutor has a high expertise in the implementation of e-learning courses. I find it difficult to motivate myself and to maintain learning motivation in the course. My tutor supports and counsels me with regard to my learning processes. The course is demanding with regard to the organizational and temporal effort. Learning in groups and cooperation with other learners are fostered in the course (e.g., by group activities, discussions etc.).

B

SE B

β

Table 3 Students' comparisons of the suitability of online and face-to-face learning sessions.

p

Items

.231

.023

.228

b.001

.145

.023

.133

b.001

.164

.025

.146

b.001

Course design Clarity and explicit structuring of the course and learning contents. Favorable cost–benefit ratio of effort and learning outcomes.

−.122

.017

−.148

b.001

.133

.022

.133

b.001

−.070

.018

−.077

b.001

.072

b.001

.057

0.16

β = β-weight; p = p-value.

investment of time and organization necessary for the course (β = −.077). Multiple regression coefficient was R = .553 and the model explained 30.30% of variance.

M

SD

t

d

o

0.66 1.41 2090

21.293 0.47 X

0.38 1.40 2086

12.559 0.27 X

Interaction with the tutor Fast feedback from the tutor. 0.40 1.80 Counseling and support of learning − 0.30 1.58 by the tutor. Possibility to establish personal − 0.66 1.72 contact with the tutor. Easy and fast accessibility to 0.09 1.72 the tutor. Interaction with peer students Easy and fast exchange of information and knowledge with other course participants. Support of cooperative learning and group work with other course participants. Possibility to establish positive social relations with other course participants.

n

2095 2114

10.360 0.23 X − 8.830 0.19 X

2101 − 17.660 0.38 2085

0.66 1.75 2110

f

X

2.383 n.s.

17.322 0.38 X

− 0.65 1.52 2114 − 19.628 0.43

X

− 1.43 1.42 2121

X

−46.416 1.01

4.3. Students' preferences for online or for face-to-face components For various objectives of a course and a learning situation, (e.g., clarity and an explicit structure of a course) students were to compare whether this objective can be better achieved in an online learning session or in a face-to-face learning session. Furthermore, students evaluated whether different kinds of learning outcomes can be better achieved either online or face-to-face. Students evaluated 19 items on a six-point scale ranging from “better in face-to-face learning sessions” (−3) to “better in online learning sessions” (+ 3). Oneway t-tests with Bonferroni adjustments were carried out for each item to investigate the hypothesis that the mean value of students' evaluations deviates significantly from the mean of the scale (0 reflecting indifference between face-to-face learning and online learning; compare Table 3). Effect sizes were calculated to determine whether the statistically found differences are of practical concern. It was also investigated whether gender or the age of students influences the evaluations (Paechter et al., 2007). No differences were found for these groups. According to the students' assessments, clarity and a clearly arranged structure of the learning and course material (M = 0.66) as well as a favorable cost–benefit ratio of effort and learning outcomes (M = 0.38) can be better ensured by online learning components (course design). Concerning the interaction with the instructor as well as the interaction among peer students, students differentiate clearly between various objectives in learning and teaching processes. The distribution of information to other students (M = 0.66) as well as providing fast feedback by the instructor (M = 0.40) are more efficient in online learning components. However, establishing positive social relations with other students (M = −1.43) or the instructor (M = −0.66) and cooperative learning (M = −0.65) need face-to-face sessions. Students regard online learning components as being more suitable when the flexibility of learning (M = 1.33; M = 1.03), opportunities for exercises (M = 1.24) and for monitoring of one's learning processes (M = 1.06) are to be supported. With regard to learning outcomes, students ascribe advantages to face-to-face learning when knowledge and skills in the subject matter (M = −0.43), in scientific work routines (M = −0.20), in the application of one's knowledge (M = −0.46), or in communication and cooperation (M = −0.63) are to be acquired. Only with regard to expertise in selfregulated learning (M = 0.88), students see advantages in online learning components.

Individual learning processes Flexibility of learning with regard to time and place. Flexibility with regard to about learning strategies and pace of learning. Opportunities for exercising and applying one's knowledge. Opportunities for monitoring one's learning outcomes. Support for maintaining learning motivation. Learning outcomes Acquisition of skills in scientific work procedures. Acquisition of conceptual knowledge in the subject matter. Acquisition of skills in the application of one's knowledge and of using one's knowledge in practice. Acquisition of skills in communication and cooperation. Acquisition of skills in self-regulated learning.

1.33 1.32 2092

46.231 1.01 X

1.03 1.36 2092

34.870 0.76 X

1.24 1.22 2110

46.669 1.02 X

1.06 1.33 2121

36.545 0.79 X

−0.25 1.46 2102

−7.715 0.17

X

−0.20 1.56 2123

−6.255 0.14

X

−0.43 1.46 2116

−13.657 0.30

X

−0.46 2.42 2106

−8.699 0.19

X

−0.63 1.62 2105

−17.802 0.39

X

0.88 1.40 2055

28.951 0.63 X

M = mean, SD = standard deviation, n = sample size, t = t-scores, d = effect size, o = better in online learning sessions; f = better in face-to-face learning sessions; n.s. = not significant comparison.

5. Discussion For the study, students were recruited from all Austrian universities which offer e-learning courses and from a sample representing universities which specialize in applied sciences. Participants were enrolled in all major subjects offered at universities and universities of applied sciences. Therefore, the results of this research can be seen as a good indicator for e-learning as a whole in Austria. All in all, students reported a high degree of satisfaction with their course and gave favorable evaluations of e-learning in their universities. For the design of e-learning, it is important to know which course characteristics are important for students' satisfaction. In the current study, few variables contribute positively to satisfaction. They concern instructor characteristics (expertise and support for learning), the acquisition of expertise by the students, and the

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teaching material. These findings support recent studies from different countries in which also instructor characteristics and the acquisition of expertise contributed to learners' satisfaction (Ellis, Ginns, & Piggott, 2009; Lee et al., 2009). The participants of the current study gave clear evaluations on which learning objectives and learning processes are better supported by online components and which are better supported by face-to-face components. In the following, the findings are discussed according to the five fields of instruction. Course design: Clarity and a coherent structure of the learning contents were regarded as an advantage of e-learning materials. This finding of the study supports results on clarity and the ease of using a learning management system. Such factors may affect course satisfaction (Chang & Tung, 2008; Naveh, Tubin, & Pliskin, 2010; Shee & Wang, 2008) and performance in the course (Lee & Lee, 2008). Interaction among students: Previous research on e-learning renders mixed views on the interaction of students in e-learning courses. On the one hand, multiple advantages are attributed to online communication tools. They offer opportunities to structure communication and support collecting and sharing knowledge (Dennis, Wixom, & Vandenberg, 2001), and encourage quiet or introvert students to participate in discourse (Liaw, Chen, & Huang, 2008; Wen & Tsai, 2008). Other research studies, however, argue against such a positive view and are rather concerned with how obstacles in online communication such as restrictions in the exchange of socioemotional information and in social presence can be overcome. They emphasize the advantage of face-to-face learning and its potential in providing socio-emotional information (Harrington & Loffredo, 2010; Johnson et al., 2008; Westbrook, 2006). In the current study, students advocated to use different communication scenarios for different objectives. With respect to knowledge acquisition, students differentiate the dissemination of information from cooperative learning situations. In these situations with high cognitive presence, learners achieve understanding and develop cognitive and social skills through mutual feedback and debate (Fletcher & Major, 2006; Paulus, 2007; Sweeney, O'Donoghue, & Whitehead, 2004). Students preferred written online communication when information is disseminated among students (compare also results of Paulus, 2007; Sweeney et al., 2004). Face-to-face communication was preferred in situations in which the interaction goes beyond the mere dissemination of information, such as when learners have to agree on a shared meaning and/or to come up with a joint solution, or when social relations with other course participants are established. Interaction between students and an instructor: In a study on students' satisfaction with online or face-to-face tutorial support in distance education, students favored face-to-face over online support (Price, Richardson, & Jelfs, 2007). The current study partly confirms these results but gives a more differentiated view of students' preferences. Students preferred a choice of communication facilities including faceto-face communication for the interaction with a tutor. They appreciated the fast exchange of information by means of online communication, e.g., the possibility of obtaining fast feedback about assignments. They, however, preferred face-to-face contact when the discourse with the instructor serves to develop knowledge, e.g., when the instructor is to facilitate the acquisition of knowledge and the application of adequate learning strategies. Students furthermore advocated face-to-face communication for establishing a positive interpersonal relation with the instructor, an aspect in learning which is important for the maintenance of learning motivation (Price et al., 2007). The results on the interaction with the instructor mirror the results on the interaction among students. The students preferred face-to-face contact with either students or the instructor in situations where ideas are exchanged and knowledge is developed (situations with a high degree of cognitive presence) and in situations where socio-emotional relations are established (situations with a high degree of social presence). They prefer online contact when a fast exchange between

students and the instructor or between peer learners is important. One might explain these results by the general structure of e-learning courses where the instructor supports learning and communication among the participants themselves and where the learners become more dependent on each other (Collison, Elbaum, Haavind, & Tinker, 2000). Support of individual learning processes and learning outcomes: Elearning offers multiple opportunities for self-regulated learning. Learners can process material in accordance with their individual preferences at any time and from any place; they may select and examine material from a large pool of information (Artino & Stephens, 2009; Narciss et al., 2007). In the current study, students advocated elearning components not only for its flexibility with regard to time and place. They also appreciated online components for their possibilities for exercising and applying one's knowledge and for applying metacognitive self-regulation strategies such as monitoring one's learning progress. As a result, students believed that the acquisition of skills in self-regulated learning can be better supported in online learning than in face-to-face learning sessions. However, students' appreciation of opportunities for self-regulated learning does not necessarily mean that they apply effective strategies. Students' engagement in self-regulated learning often results in surface learning and shallow processing strategies (Huon, Spehar, Adam, & Rifkin, 2007). Learning outcomes: Even though students appreciated e-learning for its opportunities for self-regulated learning, for exercising, and for monitoring one's learning outcomes, they gave critical evaluations on the acquisition of conceptual and methodical knowledge in online learning components. Only when skills in self-regulated learning are to be acquired, students preferred online learning components. When conceptual knowledge in the subject matter, skills in the application of one's knowledge and of using one's knowledge in practice, knowledge and skills in using scientific work routines, or in communication are to be acquired, students favored face-to-face learning components over online learning components. This view can be explained by the results on the interaction with the instructor. Students preferred face-to-face contact when the discourse with the instructor serves to build up knowledge. The results of the regression analysis emphasize that interaction and a discourse in which a shared meaning is constructed are regarded as crucial for course satisfaction. For the design of e-learning courses, it can be recommended to implement face-to-face components in which the instructor obtains the role of a facilitator of learning processes and in which students receive explicit feedback of their accomplishments. The instructor should provide for opportunities to develop knowledge together and students should obtain the opportunity to demonstrate their knowledge and to develop a mental model on a subject matter. 6. Implications of the study All aspects considered, the results speak for a blended learning design in which the advantages of online learning and face-to-face learning are combined. The results can be seen as recommendations of how to combine face-to-face learning components with online learning components from students' point of view. Students' recommendations refer to several fields of instruction: With regard to the interaction among learners, students advocate face-to-face learning components for cooperative learning situations when learners have to agree on a shared meaning and/or to come up with a joint solution. They prefer online learning components for the dissemination of information. The participants of the study give similar recommendations for the interaction with the instructor: They advocate face-to-face learning components when the discourse with the instructor becomes important for the development of knowledge but appreciate fast online feedback. An important finding concerns learning outcomes: Students are critical of online learning and advocate face-to-face learning components for the acquisition of

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conceptual and methodical knowledge. This result seems to contradict students' recommendation for exercising and applying one's knowledge in online learning sessions. It might be explained by deficits in the instructional design of the investigated e-learning courses (and of current e-learning practice). Often learning management systems are used for providing learning material in which information is merely presented. There is a lack of interactive learning material which offers opportunities for exercises, applications of one's knowledge, selftests, etc. Instructors should consider the students' recommendation and offer opportunities for self-regulated learning including fast online feedback on learning accomplishments. For the current study, a large and comprehensive sample of students from Austrian universities was recruited. The results of the research can be seen as a description of students' experiences and offer recommendations of how to design e-learning courses under the general conditions at universities (e.g., the availability of only specific learning management systems, the necessity to offer courses to a large number of participants, etc.). However, one has to keep in mind that specific best-practice-examples or specific innovative experimental designs for e-learning were not investigated but instead the broad range of e-learning as it is currently offered in Austrian universities. The study gives a first view of students' evaluations and recommendations for e-learning courses. In the future, the study should be refined: The five instructional fields should be investigated in more detail and it should be analyzed how individual learner variables (e.g., students' major subject, employment, familiar situation, etc.) influence the perception of e-learning. Also, the study should be complemented by the view of e-learning instructors to determine whether instructors' perceptions overlap with students' perceptions. Acknowledgment The authors gratefully acknowledge the financial support provided by the Austrian Federal Ministry of Science and Research. References Alexander, S., & Golja, T. (2007). Using students' experiences to derive quality in an e-learning system: An institution's perspective. Educational Technology & Society, 10(2), 17−33. Anderson, L. W., & Krathwohl, D. R. (2001). A taxonomy for learning, teaching, and assessment. New York: Addison Wesley. Artino, A. R., & Stephens, J. M. (2009). Academic motivation and self-regulation: A comparative analysis of undergraduate and graduate students learning online. The Internet and Higher Education, 12, 146−151. Bliuc, A. -M., Goodyear, P., & Ellis, R. A. (2007). Research focus and methodological choices in studies into students' experiences of blended learning in higher education. The Internet and Higher Education, 10, 231−244. Bortz, J. (1999). Statistik für Sozialwissenschaftler. Berlin: Springer. Brophy, J. E. (1999). Teaching: Educational practices series, Vol. 1, Retrieved from. http:// www.ibe.unesco.org/publications/EducationalPracticesSeriesPdf/prac01e.pdf Chang, S. C., & Tung, F. C. (2008). An empirical investigation of students' behavioural intentions to use the online learning course websites. British Journal of Educational Technology, 39, 71−83. Chiu, C. M., Hsu, M. H., Sun, S. Y., Lin, T. C., & Sun, P. C. (2005). Usability, quality, value and e-learning continuance decisions. Computers & Education, 45, 399−416. Coates, H., James, R., & Baldwin, G. (2005). A critical examination of the effects of learning management systems on university teaching and learning. Tertiary Education and Management, 11, 19−36. Cohen, J. (1992). A power primer. Psychological Bulletin, 112, 155−159. Collison, G., Elbaum, B., Haavind, S., & Tinker, R. (2000). Facilitating online learning. Madison: Atwood Publishing. Concannon, F., Flynn, A., & Campbell, M. (2005). What campus-based students think about the quality and benefits of e-learning. British Journal of Educational Technology, 36, 501−512. Dennis, A. R., Wixom, B. H., & Vandenberg, R. J. (2001). Understanding fit and appropriation effects in group support systems via meta-analysis. MIS Quarterly, 25, 167−193. Ehlers, U. (2004). Quality in e-learning. The learner as a key quality assurance category. European Journal of Vocational Training, 29, 3−15.

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