research articles on blended learning

• Research article
• Open access
• Published: 06 February 2017

Blended learning effectiveness: the relationship between student characteristics, design features and outcomes

• Mugenyi Justice Kintu   ORCID: orcid.org/0000-0002-4500-1168 1 , 2 ,
• Chang Zhu 2 &
• Edmond Kagambe 1  

International Journal of Educational Technology in Higher Education volume  14 , Article number:  7 ( 2017 ) Cite this article

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This paper investigates the effectiveness of a blended learning environment through analyzing the relationship between student characteristics/background, design features and learning outcomes. It is aimed at determining the significant predictors of blended learning effectiveness taking student characteristics/background and design features as independent variables and learning outcomes as dependent variables. A survey was administered to 238 respondents to gather data on student characteristics/background, design features and learning outcomes. The final semester evaluation results were used as a measure for performance as an outcome. We applied the online self regulatory learning questionnaire for data on learner self regulation, the intrinsic motivation inventory for data on intrinsic motivation and other self-developed instruments for measuring the other constructs. Multiple regression analysis results showed that blended learning design features (technology quality, online tools and face-to-face support) and student characteristics (attitudes and self-regulation) predicted student satisfaction as an outcome. The results indicate that some of the student characteristics/backgrounds and design features are significant predictors for student learning outcomes in blended learning.

Introduction

The teaching and learning environment is embracing a number of innovations and some of these involve the use of technology through blended learning. This innovative pedagogical approach has been embraced rapidly though it goes through a process. The introduction of blended learning (combination of face-to-face and online teaching and learning) initiatives is part of these innovations but its uptake, especially in the developing world faces challenges for it to be an effective innovation in teaching and learning. Blended learning effectiveness has quite a number of underlying factors that pose challenges. One big challenge is about how users can successfully use the technology and ensuring participants’ commitment given the individual learner characteristics and encounters with technology (Hofmann, 2014 ). Hofmann adds that users getting into difficulties with technology may result into abandoning the learning and eventual failure of technological applications. In a report by Oxford Group ( 2013 ), some learners (16%) had negative attitudes to blended learning while 26% were concerned that learners would not complete study in blended learning. Learners are important partners in any learning process and therefore, their backgrounds and characteristics affect their ability to effectively carry on with learning and being in blended learning, the design tools to be used may impinge on the effectiveness in their learning.

This study tackles blended learning effectiveness which has been investigated in previous studies considering grades, course completion, retention and graduation rates but no studies regarding effectiveness in view of learner characteristics/background, design features and outcomes have been done in the Ugandan university context. No studies have also been done on how the characteristics of learners and design features are predictors of outcomes in the context of a planning evaluation research (Guskey, 2000 ) to establish the effectiveness of blended learning. Guskey ( 2000 ) noted that planning evaluation fits in well since it occurs before the implementation of any innovation as well as allowing planners to determine the needs, considering participant characteristics, analyzing contextual matters and gathering baseline information. This study is done in the context of a plan to undertake innovative pedagogy involving use of a learning management system (moodle) for the first time in teaching and learning in a Ugandan university. The learner characteristics/backgrounds being investigated for blended learning effectiveness include self-regulation, computer competence, workload management, social and family support, attitude to blended learning, gender and age. We investigate the blended learning design features of learner interactions, face-to-face support, learning management system tools and technology quality while the outcomes considered include satisfaction, performance, intrinsic motivation and knowledge construction. Establishing the significant predictors of outcomes in blended learning will help to inform planners of such learning environments in order to put in place necessary groundwork preparations for designing blended learning as an innovative pedagogical approach.

Kenney and Newcombe ( 2011 ) did their comparison to establish effectiveness in view of grades and found that blended learning had higher average score than the non-blended learning environment. Garrison and Kanuka ( 2004 ) examined the transformative potential of blended learning and reported an increase in course completion rates, improved retention and increased student satisfaction. Comparisons between blended learning environments have been done to establish the disparity between academic achievement, grade dispersions and gender performance differences and no significant differences were found between the groups (Demirkol & Kazu, 2014 ).

However, blended learning effectiveness may be dependent on many other factors and among them student characteristics, design features and learning outcomes. Research shows that the failure of learners to continue their online education in some cases has been due to family support or increased workload leading to learner dropout (Park & Choi, 2009 ) as well as little time for study. Additionally, it is dependent on learner interactions with instructors since failure to continue with online learning is attributed to this. In Greer, Hudson & Paugh’s study as cited in Park and Choi ( 2009 ), family and peer support for learners is important for success in online and face-to-face learning. Support is needed for learners from all areas in web-based courses and this may be from family, friends, co-workers as well as peers in class. Greer, Hudson and Paugh further noted that peer encouragement assisted new learners in computer use and applications. The authors also show that learners need time budgeting, appropriate technology tools and support from friends and family in web-based courses. Peer support is required by learners who have no or little knowledge of technology, especially computers, to help them overcome fears. Park and Choi, ( 2009 ) showed that organizational support significantly predicts learners’ stay and success in online courses because employers at times are willing to reduce learners’ workload during study as well as supervisors showing that they are interested in job-related learning for employees to advance and improve their skills.

The study by Kintu and Zhu ( 2016 ) investigated the possibility of blended learning in a Ugandan University and examined whether student characteristics (such as self-regulation, attitudes towards blended learning, computer competence) and student background (such as family support, social support and management of workload) were significant factors in learner outcomes (such as motivation, satisfaction, knowledge construction and performance). The characteristics and background factors were studied along with blended learning design features such as technology quality, learner interactions, and Moodle with its tools and resources. The findings from that study indicated that learner attitudes towards blended learning were significant factors to learner satisfaction and motivation while workload management was a significant factor to learner satisfaction and knowledge construction. Among the blended learning design features, only learner interaction was a significant factor to learner satisfaction and knowledge construction.

The focus of the present study is on examining the effectiveness of blended learning taking into consideration learner characteristics/background, blended learning design elements and learning outcomes and how the former are significant predictors of blended learning effectiveness.

Studies like that of Morris and Lim ( 2009 ) have investigated learner and instructional factors influencing learning outcomes in blended learning. They however do not deal with such variables in the contexts of blended learning design as an aspect of innovative pedagogy involving the use of technology in education. Apart from the learner variables such as gender, age, experience, study time as tackled before, this study considers social and background aspects of the learners such as family and social support, self-regulation, attitudes towards blended learning and management of workload to find out their relationship to blended learning effectiveness. Identifying the various types of learner variables with regard to their relationship to blended learning effectiveness is important in this study as we embark on innovative pedagogy with technology in teaching and learning.

Literature review

This review presents research about blended learning effectiveness from the perspective of learner characteristics/background, design features and learning outcomes. It also gives the factors that are considered to be significant for blended learning effectiveness. The selected elements are as a result of the researcher’s experiences at a Ugandan university where student learning faces challenges with regard to learner characteristics and blended learning features in adopting the use of technology in teaching and learning. We have made use of Loukis, Georgiou, and Pazalo ( 2007 ) value flow model for evaluating an e-learning and blended learning service specifically considering the effectiveness evaluation layer. This evaluates the extent of an e-learning system usage and the educational effectiveness. In addition, studies by Leidner, Jarvenpaa, Dillon and Gunawardena as cited in Selim ( 2007 ) have noted three main factors that affect e-learning and blended learning effectiveness as instructor characteristics, technology and student characteristics. Heinich, Molenda, Russell, and Smaldino ( 2001 ) showed the need for examining learner characteristics for effective instructional technology use and showed that user characteristics do impact on behavioral intention to use technology. Research has dealt with learner characteristics that contribute to learner performance outcomes. They have dealt with emotional intelligence, resilience, personality type and success in an online learning context (Berenson, Boyles, & Weaver, 2008 ). Dealing with the characteristics identified in this study will give another dimension, especially for blended learning in learning environment designs and add to specific debate on learning using technology. Lin and Vassar, ( 2009 ) indicated that learner success is dependent on ability to cope with technical difficulty as well as technical skills in computer operations and internet navigation. This justifies our approach in dealing with the design features of blended learning in this study.

Learner characteristics/background and blended learning effectiveness

Studies indicate that student characteristics such as gender play significant roles in academic achievement (Oxford Group, 2013 ), but no study examines performance of male and female as an important factor in blended learning effectiveness. It has again been noted that the success of e- and blended learning is highly dependent on experience in internet and computer applications (Picciano & Seaman, 2007 ). Rigorous discovery of such competences can finally lead to a confirmation of high possibilities of establishing blended learning. Research agrees that the success of e-learning and blended learning can largely depend on students as well as teachers gaining confidence and capability to participate in blended learning (Hadad, 2007 ). Shraim and Khlaif ( 2010 ) note in their research that 75% of students and 72% of teachers were lacking in skills to utilize ICT based learning components due to insufficient skills and experience in computer and internet applications and this may lead to failure in e-learning and blended learning. It is therefore pertinent that since the use of blended learning applies high usage of computers, computer competence is necessary (Abubakar & Adetimirin, 2015 ) to avoid failure in applying technology in education for learning effectiveness. Rovai, ( 2003 ) noted that learners’ computer literacy and time management are crucial in distance learning contexts and concluded that such factors are meaningful in online classes. This is supported by Selim ( 2007 ) that learners need to posses time management skills and computer skills necessary for effectiveness in e- learning and blended learning. Self-regulatory skills of time management lead to better performance and learners’ ability to structure the physical learning environment leads to efficiency in e-learning and blended learning environments. Learners need to seek helpful assistance from peers and teachers through chats, email and face-to-face meetings for effectiveness (Lynch & Dembo, 2004 ). Factors such as learners’ hours of employment and family responsibilities are known to impede learners’ process of learning, blended learning inclusive (Cohen, Stage, Hammack, & Marcus, 2012 ). It was also noted that a common factor in failure and learner drop-out is the time conflict which is compounded by issues of family , employment status as well as management support (Packham, Jones, Miller, & Thomas, 2004 ). A study by Thompson ( 2004 ) shows that work, family, insufficient time and study load made learners withdraw from online courses.

Learner attitudes to blended learning can result in its effectiveness and these shape behavioral intentions which usually lead to persistence in a learning environment, blended inclusive. Selim, ( 2007 ) noted that the learners’ attitude towards e-learning and blended learning are success factors for these learning environments. Learner performance by age and gender in e-learning and blended learning has been found to indicate no significant differences between male and female learners and different age groups (i.e. young, middle-aged and old above 45 years) (Coldwell, Craig, Paterson, & Mustard, 2008 ). This implies that the potential for blended learning to be effective exists and is unhampered by gender or age differences.

Blended learning design features

The design features under study here include interactions, technology with its quality, face-to-face support and learning management system tools and resources.

Research shows that absence of learner interaction causes failure and eventual drop-out in online courses (Willging & Johnson, 2009 ) and the lack of learner connectedness was noted as an internal factor leading to learner drop-out in online courses (Zielinski, 2000 ). It was also noted that learners may not continue in e- and blended learning if they are unable to make friends thereby being disconnected and developing feelings of isolation during their blended learning experiences (Willging & Johnson, 2009). Learners’ Interactions with teachers and peers can make blended learning effective as its absence makes learners withdraw (Astleitner, 2000 ). Loukis, Georgious and Pazalo (2007) noted that learners’ measuring of a system’s quality, reliability and ease of use leads to learning efficiency and can be so in blended learning. Learner success in blended learning may substantially be affected by system functionality (Pituch & Lee, 2006 ) and may lead to failure of such learning initiatives (Shrain, 2012 ). It is therefore important to examine technology quality for ensuring learning effectiveness in blended learning. Tselios, Daskalakis, and Papadopoulou ( 2011 ) investigated learner perceptions after a learning management system use and found out that the actual system use determines the usefulness among users. It is again noted that a system with poor response time cannot be taken to be useful for e-learning and blended learning especially in cases of limited bandwidth (Anderson, 2004 ). In this study, we investigate the use of Moodle and its tools as a function of potential effectiveness of blended learning.

The quality of learning management system content for learners can be a predictor of good performance in e-and blended learning environments and can lead to learner satisfaction. On the whole, poor quality technology yields no satisfaction by users and therefore the quality of technology significantly affects satisfaction (Piccoli, Ahmad, & Ives, 2001 ). Continued navigation through a learning management system increases use and is an indicator of success in blended learning (Delone & McLean, 2003 ). The efficient use of learning management system and its tools improves learning outcomes in e-learning and blended learning environments.

It is noted that learner satisfaction with a learning management system can be an antecedent factor for blended learning effectiveness. Goyal and Tambe ( 2015 ) noted that learners showed an appreciation to Moodle’s contribution in their learning. They showed positivity with it as it improved their understanding of course material (Ahmad & Al-Khanjari, 2011 ). The study by Goyal and Tambe ( 2015 ) used descriptive statistics to indicate improved learning by use of uploaded syllabus and session plans on Moodle. Improved learning is also noted through sharing study material, submitting assignments and using the calendar. Learners in the study found Moodle to be an effective educational tool.

In blended learning set ups, face-to-face experiences form part of the blend and learner positive attitudes to such sessions could mean blended learning effectiveness. A study by Marriot, Marriot, and Selwyn ( 2004 ) showed learners expressing their preference for face-to-face due to its facilitation of social interaction and communication skills acquired from classroom environment. Their preference for the online session was only in as far as it complemented the traditional face-to-face learning. Learners in a study by Osgerby ( 2013 ) had positive perceptions of blended learning but preferred face-to-face with its step-by-stem instruction. Beard, Harper and Riley ( 2004 ) shows that some learners are successful while in a personal interaction with teachers and peers thus prefer face-to-face in the blend. Beard however dealt with a comparison between online and on-campus learning while our study combines both, singling out the face-to-face part of the blend. The advantage found by Beard is all the same relevant here because learners in blended learning express attitude to both online and face-to-face for an effective blend. Researchers indicate that teacher presence in face-to-face sessions lessens psychological distance between them and the learners and leads to greater learning. This is because there are verbal aspects like giving praise, soliciting for viewpoints, humor, etc and non-verbal expressions like eye contact, facial expressions, gestures, etc which make teachers to be closer to learners psychologically (Kelley & Gorham, 2009 ).

Learner outcomes

The outcomes under scrutiny in this study include performance, motivation, satisfaction and knowledge construction. Motivation is seen here as an outcome because, much as cognitive factors such as course grades are used in measuring learning outcomes, affective factors like intrinsic motivation may also be used to indicate outcomes of learning (Kuo, Walker, Belland, & Schroder, 2013 ). Research shows that high motivation among online learners leads to persistence in their courses (Menager-Beeley, 2004 ). Sankaran and Bui ( 2001 ) indicated that less motivated learners performed poorly in knowledge tests while those with high learning motivation demonstrate high performance in academics (Green, Nelson, Martin, & Marsh, 2006 ). Lim and Kim, ( 2003 ) indicated that learner interest as a motivation factor promotes learner involvement in learning and this could lead to learning effectiveness in blended learning.

Learner satisfaction was noted as a strong factor for effectiveness of blended and online courses (Wilging & Johnson, 2009) and dissatisfaction may result from learners’ incompetence in the use of the learning management system as an effective learning tool since, as Islam ( 2014 ) puts it, users may be dissatisfied with an information system due to ease of use. A lack of prompt feedback for learners from course instructors was found to cause dissatisfaction in an online graduate course. In addition, dissatisfaction resulted from technical difficulties as well as ambiguous course instruction Hara and Kling ( 2001 ). These factors, once addressed, can lead to learner satisfaction in e-learning and blended learning and eventual effectiveness. A study by Blocker and Tucker ( 2001 ) also showed that learners had difficulties with technology and inadequate group participation by peers leading to dissatisfaction within these design features. Student-teacher interactions are known to bring satisfaction within online courses. Study results by Swan ( 2001 ) indicated that student-teacher interaction strongly related with student satisfaction and high learner-learner interaction resulted in higher levels of course satisfaction. Descriptive results by Naaj, Nachouki, and Ankit ( 2012 ) showed that learners were satisfied with technology which was a video-conferencing component of blended learning with a mean of 3.7. The same study indicated student satisfaction with instructors at a mean of 3.8. Askar and Altun, ( 2008 ) found that learners were satisfied with face-to-face sessions of the blend with t-tests and ANOVA results indicating female scores as higher than for males in the satisfaction with face-to-face environment of the blended learning.

Studies comparing blended learning with traditional face-to-face have indicated that learners perform equally well in blended learning and their performance is unaffected by the delivery method (Kwak, Menezes, & Sherwood, 2013 ). In another study, learning experience and performance are known to improve when traditional course delivery is integrated with online learning (Stacey & Gerbic, 2007 ). Such improvement as noted may be an indicator of blended learning effectiveness. Our study however, delves into improved performance but seeks to establish the potential of blended learning effectiveness by considering grades obtained in a blended learning experiment. Score 50 and above is considered a pass in this study’s setting and learners scoring this and above will be considered to have passed. This will make our conclusions about the potential of blended learning effectiveness.

Regarding knowledge construction, it has been noted that effective learning occurs where learners are actively involved (Nurmela, Palonen, Lehtinen & Hakkarainen, 2003 , cited in Zhu, 2012 ) and this may be an indicator of learning environment effectiveness. Effective blended learning would require that learners are able to initiate, discover and accomplish the processes of knowledge construction as antecedents of blended learning effectiveness. A study by Rahman, Yasin and Jusoff ( 2011 ) indicated that learners were able to use some steps to construct meaning through an online discussion process through assignments given. In the process of giving and receiving among themselves, the authors noted that learners learned by writing what they understood. From our perspective, this can be considered to be accomplishment in the knowledge construction process. Their study further shows that learners construct meaning individually from assignments and this stage is referred to as pre-construction which for our study, is an aspect of discovery in the knowledge construction process.

Predictors of blended learning effectiveness

Researchers have dealt with success factors for online learning or those for traditional face-to-face learning but little is known about factors that predict blended learning effectiveness in view of learner characteristics and blended learning design features. This part of our study seeks to establish the learner characteristics/backgrounds and design features that predict blended learning effectiveness with regard to satisfaction, outcomes, motivation and knowledge construction. Song, Singleton, Hill, and Koh ( 2004 ) examined online learning effectiveness factors and found out that time management (a self-regulatory factor) was crucial for successful online learning. Eom, Wen, and Ashill ( 2006 ) using a survey found out that interaction, among other factors, was significant for learner satisfaction. Technical problems with regard to instructional design were a challenge to online learners thus not indicating effectiveness (Song et al., 2004 ), though the authors also indicated that descriptive statistics to a tune of 75% and time management (62%) impact on success of online learning. Arbaugh ( 2000 ) and Swan ( 2001 ) indicated that high levels of learner-instructor interaction are associated with high levels of user satisfaction and learning outcomes. A study by Naaj et al. ( 2012 ) indicated that technology and learner interactions, among other factors, influenced learner satisfaction in blended learning.

Objective and research questions of the current study

The objective of the current study is to investigate the effectiveness of blended learning in view of student satisfaction, knowledge construction, performance and intrinsic motivation and how they are related to student characteristics and blended learning design features in a blended learning environment.

Research questions

What are the student characteristics and blended learning design features for an effective blended learning environment?

Which factors (among the learner characteristics and blended learning design features) predict student satisfaction, learning outcomes, intrinsic motivation and knowledge construction?

Conceptual model of the present study

The reviewed literature clearly shows learner characteristics/background and blended learning design features play a part in blended learning effectiveness and some of them are significant predictors of effectiveness. The conceptual model for our study is depicted as follows (Fig.  1 ):

Conceptual model of the current study

Research design

This research applies a quantitative design where descriptive statistics are used for the student characteristics and design features data, t-tests for the age and gender variables to determine if they are significant in blended learning effectiveness and regression for predictors of blended learning effectiveness.

This study is based on an experiment in which learners participated during their study using face-to-face sessions and an on-line session of a blended learning design. A learning management system (Moodle) was used and learner characteristics/background and blended learning design features were measured in relation to learning effectiveness. It is therefore a planning evaluation research design as noted by Guskey ( 2000 ) since the outcomes are aimed at blended learning implementation at MMU. The plan under which the various variables were tested involved face-to-face study at the beginning of a 17 week semester which was followed by online teaching and learning in the second half of the semester. The last part of the semester was for another face-to-face to review work done during the online sessions and final semester examinations. A questionnaire with items on student characteristics, design features and learning outcomes was distributed among students from three schools and one directorate of postgraduate studies.

Participants

Cluster sampling was used to select a total of 238 learners to participate in this study. Out of the whole university population of students, three schools and one directorate were used. From these, one course unit was selected from each school and all the learners following the course unit were surveyed. In the school of Education ( n  = 70) and Business and Management Studies ( n  = 133), sophomore students were involved due to the fact that they have been introduced to ICT basics during their first year of study. Students of the third year were used from the department of technology in the School of Applied Sciences and Technology ( n  = 18) since most of the year two courses had a lot of practical aspects that could not be used for the online learning part. From the Postgraduate Directorate ( n  = 17), first and second year students were selected because learners attend a face-to-face session before they are given paper modules to study away from campus.

The study population comprised of 139 male students representing 58.4% and 99 females representing 41.6% with an average age of 24 years.

Instruments

The end of semester results were used to measure learner performance. The online self-regulated learning questionnaire (Barnard, Lan, To, Paton, & Lai, 2009 ) and the intrinsic motivation inventory (Deci & Ryan, 1982 ) were applied to measure the constructs on self regulation in the student characteristics and motivation in the learning outcome constructs. Other self-developed instruments were used for the other remaining variables of attitudes, computer competence, workload management, social and family support, satisfaction, knowledge construction, technology quality, interactions, learning management system tools and resources and face-to-face support.

Instrument reliability

Cronbach’s alpha was used to test reliability and the table below gives the results. All the scales and sub-scales had acceptable internal consistency reliabilities as shown in Table  1 below:

Data analysis

First, descriptive statistics was conducted. Shapiro-Wilk test was done to test normality of the data for it to qualify for parametric tests. The test results for normality of our data before the t- test resulted into significant levels (Male = .003, female = .000) thereby violating the normality assumption. We therefore used the skewness and curtosis results which were between −1.0 and +1.0 and assumed distribution to be sufficiently normal to qualify the data for a parametric test, (Pallant, 2010 ). An independent samples t -test was done to find out the differences in male and female performance to explain the gender characteristics in blended learning effectiveness. A one-way ANOVA between subjects was conducted to establish the differences in performance between age groups. Finally, multiple regression analysis was done between student variables and design elements with learning outcomes to determine the significant predictors for blended learning effectiveness.

Student characteristics, blended learning design features and learning outcomes ( RQ1 )

A t- test was carried out to establish the performance of male and female learners in the blended learning set up. This was aimed at finding out if male and female learners do perform equally well in blended learning given their different roles and responsibilities in society. It was found that male learners performed slightly better ( M  = 62.5) than their female counterparts ( M  = 61.1). An independent t -test revealed that the difference between the performances was not statistically significant ( t  = 1.569, df = 228, p  = 0.05, one tailed). The magnitude of the differences in the means is small with effect size ( d  = 0.18). A one way between subjects ANOVA was conducted on the performance of different age groups to establish the performance of learners of young and middle aged age groups (20–30, young & and 31–39, middle aged). This revealed a significant difference in performance (F(1,236 = 8.498, p < . 001).

Average percentages of the items making up the self regulated learning scale are used to report the findings about all the sub-scales in the learner characteristics/background scale. Results show that learner self-regulation was good enough at 72.3% in all the sub-scales of goal setting, environment structuring, task strategies, time management, help-seeking and self-evaluation among learners. The least in the scoring was task strategies at 67.7% and the highest was learner environment structuring at 76.3%. Learner attitude towards blended learning environment is at 76% in the sub-scales of learner autonomy, quality of instructional materials, course structure, course interface and interactions. The least scored here is attitude to course structure at 66% and their attitudes were high on learner autonomy and course interface both at 82%. Results on the learners’ computer competences are summarized in percentages in the table below (Table  2 ):

It can be seen that learners are skilled in word processing at 91%, email at 63.5%, spreadsheets at 68%, web browsers at 70.2% and html tools at 45.4%. They are therefore good enough in word processing and web browsing. Their computer confidence levels are reported at 75.3% and specifically feel very confident when it comes to working with a computer (85.7%). Levels of family and social support for learners during blended learning experiences are at 60.5 and 75% respectively. There is however a low score on learners being assisted by family members in situations of computer setbacks (33.2%) as 53.4% of the learners reported no assistance in this regard. A higher percentage (85.3%) is reported on learners getting support from family regarding provision of essentials for learning such as tuition. A big percentage of learners spend two hours on study while at home (35.3%) followed by one hour (28.2%) while only 9.7% spend more than three hours on study at home. Peers showed great care during the blended learning experience (81%) and their experiences were appreciated by the society (66%). Workload management by learners vis-à-vis studying is good at 60%. Learners reported that their workmates stand in for them at workplaces to enable them do their study in blended learning while 61% are encouraged by their bosses to go and improve their skills through further education and training. On the time spent on other activities not related to study, majority of the learners spend three hours (35%) while 19% spend 6 hours. Sixty percent of the learners have to answer to someone when they are not attending to other activities outside study compared to the 39.9% who do not and can therefore do study or those other activities.

The usability of the online system, tools and resources was below average as shown in the table below in percentages (Table  3 ):

However, learners became skilled at navigating around the learning management system (79%) and it was easy for them to locate course content, tools and resources needed such as course works, news, discussions and journal materials. They effectively used the communication tools (60%) and to work with peers by making posts (57%). They reported that online resources were well organized, user friendly and easy to access (71%) as well as well structured in a clear and understandable manner (72%). They therefore recommended the use of online resources for other course units in future (78%) because they were satisfied with them (64.3%). On the whole, the online resources were fine for the learners (67.2%) and useful as a learning resource (80%). The learners’ perceived usefulness/satisfaction with online system, tools, and resources was at 81% as the LMS tools helped them to communicate, work with peers and reflect on their learning (74%). They reported that using moodle helped them to learn new concepts, information and gaining skills (85.3%) as well as sharing what they knew or learned (76.4%). They enjoyed the course units (78%) and improved their skills with technology (89%).

Learner interactions were seen from three angles of cognitivism, collaborative learning and student-teacher interactions. Collaborative learning was average at 50% with low percentages in learners posting challenges to colleagues’ ideas online (34%) and posting ideas for colleagues to read online (37%). They however met oftentimes online (60%) and organized how they would work together in study during the face-to-face meetings (69%). The common form of communication medium frequently used by learners during the blended learning experience was by phone (34.5%) followed by whatsapp (21.8%), face book (21%), discussion board (11.8%) and email (10.9%). At the cognitive level, learners interacted with content at 72% by reading the posted content (81%), exchanging knowledge via the LMS (58.4%), participating in discussions on the forum (62%) and got course objectives and structure introduced during the face-to-face sessions (86%). Student-teacher interaction was reported at 71% through instructors individually working with them online (57.2%) and being well guided towards learning goals (81%). They did receive suggestions from instructors about resources to use in their learning (75.3%) and instructors provided learning input for them to come up with their own answers (71%).

The technology quality during the blended learning intervention was rated at 69% with availability of 72%, quality of the resources was at 68% with learners reporting that discussion boards gave right content necessary for study (71%) and the email exchanges containing relevant and much needed information (63.4%) as well as chats comprising of essential information to aid the learning (69%). Internet reliability was rated at 66% with a speed considered averagely good to facilitate online activities (63%). They however reported that there was intermittent breakdown during online study (67%) though they could complete their internet program during connection (63.4%). Learners eventually found it easy to download necessary materials for study in their blended learning experiences (71%).

Learner extent of use of the learning management system features was as shown in the table below in percentage (Table  4 ):

From the table, very rarely used features include the blog and wiki while very often used ones include the email, forum, chat and calendar.

The effectiveness of the LMS was rated at 79% by learners reporting that they found it useful (89%) and using it makes their learning activities much easier (75.2%). Moodle has helped learners to accomplish their learning tasks more quickly (74%) and that as a LMS, it is effective in teaching and learning (88%) with overall satisfaction levels at 68%. However, learners note challenges in the use of the LMS regarding its performance as having been problematic to them (57%) and only 8% of the learners reported navigation while 16% reported access as challenges.

Learner attitudes towards Face-to-face support were reported at 88% showing that the sessions were enjoyable experiences (89%) with high quality class discussions (86%) and therefore recommended that the sessions should continue in blended learning (89%). The frequency of the face-to-face sessions is shown in the table below as preferred by learners (Table  5 ).

Learners preferred face-to-face sessions after every month in the semester (33.6%) and at the beginning of the blended learning session only (27.7%).

Learners reported high intrinsic motivation levels with interest and enjoyment of tasks at 83.7%, perceived competence at 70.2%, effort/importance sub-scale at 80%, pressure/tension reported at 54%. The pressure percentage of 54% arises from learners feeling nervous (39.2%) and a lot of anxiety (53%) while 44% felt a lot of pressure during the blended learning experiences. Learners however reported the value/usefulness of blended learning at 91% with majority believing that studying online and face-to-face had value for them (93.3%) and were therefore willing to take part in blended learning (91.2%). They showed that it is beneficial for them (94%) and that it was an important way of studying (84.3%).

Learner satisfaction was reported at 81% especially with instructors (85%) high percentage reported on encouraging learner participation during the course of study 93%, course content (83%) with the highest being satisfaction with the good relationship between the objectives of the course units and the content (90%), technology (71%) with a high percentage on the fact that the platform was adequate for the online part of the learning (76%), interactions (75%) with participation in class at 79%, and face-to-face sessions (91%) with learner satisfaction high on face-to-face sessions being good enough for interaction and giving an overview of the courses when objectives were introduced at 92%.

Learners’ knowledge construction was reported at 78% with initiation and discovery scales scoring 84% with 88% specifically for discovering the learning points in the course units. The accomplishment scale in knowledge construction scored 71% and specifically the fact that learners were able to work together with group members to accomplish learning tasks throughout the study of the course units (79%). Learners developed reports from activities (67%), submitted solutions to discussion questions (68%) and did critique peer arguments (69%). Generally, learners performed well in blended learning in the final examination with an average pass of 62% and standard deviation of 7.5.

Significant predictors of blended learning effectiveness ( RQ 2)

A standard multiple regression analysis was done taking learner characteristics/background and design features as predictor variables and learning outcomes as criterion variables. The data was first tested to check if it met the linear regression test assumptions and results showed the correlations between the independent variables and each of the dependent variables (highest 0.62 and lowest 0.22) as not being too high, which indicated that multicollinearity was not a problem in our model. From the coefficients table, the VIF values ranged from 1.0 to 2.4, well below the cut off value of 10 and indicating no possibility of multicollinearity. The normal probability plot was seen to lie as a reasonably straight diagonal from bottom left to top right indicating normality of our data. Linearity was found suitable from the scatter plot of the standardized residuals and was rectangular in distribution. Outliers were no cause for concern in our data since we had only 1% of all cases falling outside 3.0 thus proving the data as a normally distributed sample. Our R -square values was at 0.525 meaning that the independent variables explained about 53% of the variance in overall satisfaction, motivation and knowledge construction of the learners. All the models explaining the three dependent variables of learner satisfaction, intrinsic motivation and knowledge construction were significant at the 0.000 probability level (Table  6 ).

From the table above, design features (technology quality and online tools and resources), and learner characteristics (attitudes to blended learning, self-regulation) were significant predictors of learner satisfaction in blended learning. This means that good technology with the features involved and the learner positive attitudes with capacity to do blended learning with self drive led to their satisfaction. The design features (technology quality, interactions) and learner characteristics (self regulation and social support), were found to be significant predictors of learner knowledge construction. This implies that learners’ capacity to go on their work by themselves supported by peers and high levels of interaction using the quality technology led them to construct their own ideas in blended learning. Design features (technology quality, online tools and resources as well as learner interactions) and learner characteristics (self regulation), significantly predicted the learners’ intrinsic motivation in blended learning suggesting that good technology, tools and high interaction levels with independence in learning led to learners being highly motivated. Finally, none of the independent variables considered under this study were predictors of learning outcomes (grade).

In this study we have investigated learning outcomes as dependent variables to establish if particular learner characteristics/backgrounds and design features are related to the outcomes for blended learning effectiveness and if they predict learning outcomes in blended learning. We took students from three schools out of five and one directorate of post-graduate studies at a Ugandan University. The study suggests that the characteristics and design features examined are good drivers towards an effective blended learning environment though a few of them predicted learning outcomes in blended learning.

Student characteristics/background, blended learning design features and learning outcomes

The learner characteristics, design features investigated are potentially important for an effective blended learning environment. Performance by gender shows a balance with no statistical differences between male and female. There are statistically significant differences ( p  < .005) in the performance between age groups with means of 62% for age group 20–30 and 67% for age group 31 –39. The indicators of self regulation exist as well as positive attitudes towards blended learning. Learners do well with word processing, e-mail, spreadsheets and web browsers but still lag below average in html tools. They show computer confidence at 75.3%; which gives prospects for an effective blended learning environment in regard to their computer competence and confidence. The levels of family and social support for learners stand at 61 and 75% respectively, indicating potential for blended learning to be effective. The learners’ balance between study and work is a drive factor towards blended learning effectiveness since their management of their workload vis a vis study time is at 60 and 61% of the learners are encouraged to go for study by their bosses. Learner satisfaction with the online system and its tools shows prospect for blended learning effectiveness but there are challenges in regard to locating course content and assignments, submitting their work and staying on a task during online study. Average collaborative, cognitive learning as well as learner-teacher interactions exist as important factors. Technology quality for effective blended learning is a potential for effectiveness though features like the blog and wiki are rarely used by learners. Face-to-face support is satisfactory and it should be conducted every month. There is high intrinsic motivation, satisfaction and knowledge construction as well as good performance in examinations ( M  = 62%, SD = 7.5); which indicates potentiality for blended learning effectiveness.

Significant predictors of blended learning effectiveness

Among the design features, technology quality, online tools and face-to-face support are predictors of learner satisfaction while learner characteristics of self regulation and attitudes to blended learning are predictors of satisfaction. Technology quality and interactions are the only design features predicting learner knowledge construction, while social support, among the learner backgrounds, is a predictor of knowledge construction. Self regulation as a learner characteristic is a predictor of knowledge construction. Self regulation is the only learner characteristic predicting intrinsic motivation in blended learning while technology quality, online tools and interactions are the design features predicting intrinsic motivation. However, all the independent variables are not significant predictors of learning performance in blended learning.

The high computer competences and confidence is an antecedent factor for blended learning effectiveness as noted by Hadad ( 2007 ) and this study finds learners confident and competent enough for the effectiveness of blended learning. A lack in computer skills causes failure in e-learning and blended learning as noted by Shraim and Khlaif ( 2010 ). From our study findings, this is no threat for blended learning our case as noted by our results. Contrary to Cohen et al. ( 2012 ) findings that learners’ family responsibilities and hours of employment can impede their process of learning, it is not the case here since they are drivers to the blended learning process. Time conflict, as compounded by family, employment status and management support (Packham et al., 2004 ) were noted as causes of learner failure and drop out of online courses. Our results show, on the contrary, that these factors are drivers for blended learning effectiveness because learners have a good balance between work and study and are supported by bosses to study. In agreement with Selim ( 2007 ), learner positive attitudes towards e-and blended learning environments are success factors. In line with Coldwell et al. ( 2008 ), no statistically significant differences exist between age groups. We however note that Coldwel, et al dealt with young, middle-aged and old above 45 years whereas we dealt with young and middle aged only.

Learner interactions at all levels are good enough and contrary to Astleitner, ( 2000 ) that their absence makes learners withdraw, they are a drive factor here. In line with Loukis (2007) the LMS quality, reliability and ease of use lead to learning efficiency as technology quality, online tools are predictors of learner satisfaction and intrinsic motivation. Face-to-face sessions should continue on a monthly basis as noted here and is in agreement with Marriot et al. ( 2004 ) who noted learner preference for it for facilitating social interaction and communication skills. High learner intrinsic motivation leads to persistence in online courses as noted by Menager-Beeley, ( 2004 ) and is high enough in our study. This implies a possibility of an effectiveness blended learning environment. The causes of learner dissatisfaction noted by Islam ( 2014 ) such as incompetence in the use of the LMS are contrary to our results in our study, while the one noted by Hara and Kling, ( 2001 ) as resulting from technical difficulties and ambiguous course instruction are no threat from our findings. Student-teacher interaction showed a relation with satisfaction according to Swan ( 2001 ) but is not a predictor in our study. Initiating knowledge construction by learners for blended learning effectiveness is exhibited in our findings and agrees with Rahman, Yasin and Jusof ( 2011 ). Our study has not agreed with Eom et al. ( 2006 ) who found learner interactions as predictors of learner satisfaction but agrees with Naaj et al. ( 2012 ) regarding technology as a predictor of learner satisfaction.

Conclusion and recommendations

An effective blended learning environment is necessary in undertaking innovative pedagogical approaches through the use of technology in teaching and learning. An examination of learner characteristics/background, design features and learning outcomes as factors for effectiveness can help to inform the design of effective learning environments that involve face-to-face sessions and online aspects. Most of the student characteristics and blended learning design features dealt with in this study are important factors for blended learning effectiveness. None of the independent variables were identified as significant predictors of student performance. These gaps are open for further investigation in order to understand if they can be significant predictors of blended learning effectiveness in a similar or different learning setting.

In planning to design and implement blended learning, we are mindful of the implications raised by this study which is a planning evaluation research for the design and eventual implementation of blended learning. Universities should be mindful of the interplay between the learner characteristics, design features and learning outcomes which are indicators of blended learning effectiveness. From this research, learners manifest high potential to take on blended learning more especially in regard to learner self-regulation exhibited. Blended learning is meant to increase learners’ levels of knowledge construction in order to create analytical skills in them. Learner ability to assess and critically evaluate knowledge sources is hereby established in our findings. This can go a long way in producing skilled learners who can be innovative graduates enough to satisfy employment demands through creativity and innovativeness. Technology being less of a shock to students gives potential for blended learning design. Universities and other institutions of learning should continue to emphasize blended learning approaches through installation of learning management systems along with strong internet to enable effective learning through technology especially in the developing world.

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Kintu, M.J., Zhu, C. & Kagambe, E. Blended learning effectiveness: the relationship between student characteristics, design features and outcomes. Int J Educ Technol High Educ 14 , 7 (2017). https://doi.org/10.1186/s41239-017-0043-4

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The Hustisford school district in rural Wisconsin wasn’t an obvious candidate for blended learning before the pandemic. There were no immediate plans for a districtwide 1-to-1 computing initiative, and about 1 of every 3 students did not have reliable internet access at home.

Then the pandemic hit and Hustisford, like countless districts around the country, had to shift quickly to virtual instruction. That meant buying devices, handing out wireless hotspots, and making big changes to teaching practices.

Now, Hustisford’s teachers are regularly using tools like Kahoot, a game-based learning platform, YouTube videos, and even TikTok as part of in-person classroom lessons, said Heather Cramer, the district superintendent. More significantly: a handful of teachers took the initiative to flip their classrooms, allowing students to learn new material at home via online tools and spending class time on group work, class discussions, or digging deeper into the material.

“That’s something that we’ve really, really lacked in the past,” Cramer said. “The kids didn’t have that technology at home to be able to do that research and bring that all together.”

The pandemic and the increasing use of technology in K-12 education it prompted has added renewed energy to the blended learning movement as most students are now learning in school buildings. About two-thirds of educators are expecting their use of the approach to increase during the 2021-22 school year, according to a July survey by the EdWeek Research Center. Nearly 30 percent said they were betting it would “increase a lot.” Just 14 percent expected it to decline.

Blended learning is an approach that leverages both digital tools and face-to-face instruction to offer a more personalized learning experience for each student. Students are typically given greater control over the time, place, and/or pace of learning and often participate in new instructional approaches, such as flipped classrooms . The approach is usually built on the premise that students will be attending classes in school buildings.

Thanks in part to a device-buying binge in the first year of the pandemic, fueled by federal relief dollars, 74 percent of educators surveyed by the EdWeek Research Center in March said their districts had invested “a lot” in devices since the pandemic started, with nearly another quarter saying their districts had invested at least “some” money.

At the same time, teachers became much more adept at using technology. Eighty-eight percent of teachers said their ability to use tech improved during the 2020-21 school year , according to the March survey.

Blended learning and the ‘new normal’ picking up momentum

In some cases, educators are taking the initiative to continue instructional practices they started using during the pandemic. For instance, teachers in California’s San Marcos school district are much more likely to record their lessons and post them online for students than they were before COVID, said the district’s director of educational technology, Stephanie Casperson. That allows teachers to flip their classroom or gives students a chance to review lessons if they need help understanding a concept.

Even school social workers and music teachers are making these instructional videos, she said. “Before COVID, it was mostly my American Sign Language teachers who did videos,” Casperson said.

Before the pandemic, only two or three teachers at Corunna High School near Flint, Mich., were very comfortable using blended learning approaches, said Barry Thomas, the principal. Now, it’s more like eight to 10 of the school’s roughly 30 teachers, he said.

Corruna teachers are now more apt to record their lessons so that students can go back and review them, and the school’s math department has embraced online platforms like Khan Academy to supplement their own instruction.

“They’ve found things in the course of this last year and a half that they really have liked,” Thomas said. “And now it’s just part of their normal operation.”

But some educators are cautious about embracing too much digital instruction.

“I’m not going to force anybody to do more blended learning,” said Scott Clayton, the principal of Scofield Magnet Middle School in Stamford, Conn. “Most children have a device or a cellphone. And now we’re putting a Chromebook in front of them or a laptop. It’s increasing screen time.”

Districts put greater emphasis on professional development for blended learning.

Yet as teachers’ level of interest in, and use of, blended learning has risen, districts and schools are making it a higher priority for professional development. More than half of the district leaders and principals who said they were planning to offer some remote instruction next school year in a survey by the EdWeek Research Center this summer—58 percent—said they plan to offer training on the strategy. That’s compared with just over 30 percent who said they were likely to work with teachers on remote instruction or teaching kids in-person and online simultaneously (so-called concurrent teaching), the next most popular approaches.

“Demand on our end has been explosive,” said Kareem Farah, the chief executive officer for the Modern Classroom Project, a nonprofit that works with educators on blended, self-paced, mastery-based instruction.

The organization has trained 2,300 teachers through a virtual mentoring program, which was at capacity last school year. And a free online course on blended learning launched at the start of the pandemic went from 500 users initially to 30,000.

But despite an influx of federal funding that can be used for professional development, there are logistical challenges to getting teachers hooked up with blended learning training. The San Marcos School district, for instance, is running up against a nationwide substitute teacher shortage, making it difficult to find time to get teachers out of the classroom for training.

And for some teachers, there’s a big temptation to revert back to traditional instruction.

“The initial shift is kind of almost been like, ‘We want to go back to exactly what we were doing before’,” said Justin Cutts, the principal of Whitney High School in Rocklin, Calif. “Which is, to me, a little bit of a disappointment. We had the math department burn through, like, 12 [packages] of paper in the first two weeks of school. How did we go [through] the last year and a half, and now we’re gonna go back to breaking copiers again?”

Blended learning for acceleration and remediation

There has been significant concern among educators and policymakers about students falling behind academically due to the pandemic. Half of teachers said their students were behind where they would be in a typical year, according to a survey of 1,042 teachers conducted this spring by the Clayton Christensen Institute , a nonprofit research organization that promotes innovation in education and other fields.

It’s unclear how much of a role technology can play in helping students regain their academic footing, through either acceleration or remediation, at least during class time.

School and district leaders surveyed by the EdWeek Research Center this summer were most likely to say their students would be able to use online tools for acceleration and remediation at home more frequently than before. Less popular: Offering intensive tutoring that incorporates digital tools more often than in the past.

About another quarter of district and school leaders surveyed aren’t planning to use blended learning at all to help accelerate instruction, or for remediation.

Some districts are trying a multipronged approach.

California’s Whitney High School is having some of its students catch up using a mix of software, courses specifically geared toward helping students who are behind in either math or language arts, and even smaller classes to help students who have failed multiple subjects.

While the district has used “bits of pieces of this system,” it has never been as comprehensive as it is this school year,” said Cutts, the principal.

But some schools are taking a more-cautious approach to blended learning.

For instance, even though he and his school have embraced the use of technology for teaching and learning, Clayton, the principal from Connecticut, doesn’t think it’s necessarily the best strategy for making sure that students have the background information they need to access grade-level content.

“If anything instructionally will shift, it’s this move toward an acceleration model of learning, which is not about technology,” he said, referring to the practice of refreshing students on just the learning they need to access grade-level content. “That’s about instructional practices. It’s about teachers not relying on remedial instruction because they feel as if students have somehow lost learning over the [last] year.”

More educators are experimenting with flipped classrooms

Teachers are now more likely these days to try out an intensive form of blended learning—the so-called flipped classroom—in which students cover class content online at home and in-person instruction is used for discussions, projects, and practice, the Christensen Institute survey found.

Eighteen percent of teachers said they were planning to use the model after the pandemic, compared with 12 percent who said they used it before the pandemic.

For instance, last school year, when most schools were using hybrid instructional approaches, some 5th grade teachers at Winchester Trail Elementary School in Canal Winchester, Ohio, began to shift to a flipped model. The principal, Max Lallathin, who encouraged teachers to give the arrangement a shot, is hoping to see it used in his school more often this school year.

“It’s a timesaver for the kids because they can go right in” and begin discussing content, he said. “If they watch a scientific video, they can go right into the scientific method the next day, instead of watching the video in class.”

But despite all the trends showing teachers’ technology skills rising and increasing use of blended learning approaches, some educators worry about backsliding this school year.

“My biggest fear was that we’d go back to business as usual this [school] year, and that teachers would stop using some of the technology” that they mastered during the pandemic, Casperson said. “And I think that’s a fear of pretty much every ed-tech director that I’ve talked to.”

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The Research Alliance for New York City Schools

Exploring the Evidence on Virtual and Blended Learning

Chelsea farley (2020).

The Research Alliance has developed an overview of research and practical guidance on strategies to implement remote teaching and learning, as well as strategies that combine virtual and in-class instruction. While not a complete summary of the relevant literature, our overview provides links to a variety of useful articles, resources, and reports. We hope this material can inform school and district leaders’ planning and support their ongoing assessment of what has and has not been effective, for whom, and under what conditions.

Key Takeaways from the Research Alliance’s Review

• Eight months into the COVID-19 pandemic, there is still an enormous need for data and evidence to understand how the school closures that took place in NYC and around the country—and how the various approaches to reopening—have affected students’ academic, social/emotional, and health outcomes. New research is needed to inform critical policy and practice decisions. (Below we highlight specific kinds of data that would help answer the most pressing questions.)
• Past research about online learning is limited and mostly focused on post-secondary and adult education. The studies that do exist in K-12 education find that students participating in online learning generally perform similarly to or worse than peers who have access to traditional face-to-face instruction (with programs that are 100% online faring worse than blended learning approaches). It is important to note that this research typically compares online learning with regular classroom instruction—rather than comparing it to no instruction at all—and that these studies took place under dramatically different conditions than those resulting from COVID-19.
• Studies of blended learning, personalized learning, and specific technology-based tools and programs provide hints about successful approaches, but also underscore substantial “fuzziness” around the definition of these terms; major challenges to high-quality implementation; and a lack of rigorous impact research.
• Teaching quality is more important than how lessons are delivered  (e.g., “clear explanations, scaffolding and feedback”);
• Ensuring access to technology is key , particularly for disadvantaged students and families;
• Peer interactions can provide motivation and improve learning outcomes  (e.g., “peer marking and feedback, sharing models of good work,” and opportunities for collaboration and live discussions of content);
• Supporting students to work independently can improve learning outcomes  (e.g., “prompting pupils to reflect on their work or to consider the strategies they will use if they get stuck”, checklists or daily plans); and
• Different approaches to remote learning suit different tasks and types of content.

Our overview highlights these and other lessons from dozens of relevant studies. It also underscores the need for more rigorous evidence about the implementation and impact of different approaches to remote and blended learning, particularly in the context of the current pandemic. To begin to fill these knowledge gaps,  the Research Alliance strongly encourages schools and districts—including the NYC Department of Education—to collect, analyze, and share data about :

• COVID-19 testing results,
• Professional development aimed at helping teachers implement remote and blended learning,
• Students’ attendance and engagement (online and in person),
• Students’ social and emotional wellbeing,
• Students’ and families’ experiences with remote and blended instruction,
• Teachers’ experiences with remote and blended instruction, and—critically—
• What students are learning, over time.

All of this should be done with an eye toward pre-existing inequalities—especially differences related to race/ethnicity, poverty, home language, and disability. These data are crucial for understanding how COVID-19 has affected the educational trajectories of different groups of students and for developing strong policy and practice responses. 

Read our full overview here . This document was initially released in May and updated in November of 2020.

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• v.18(1); 2016 Jan

The Effectiveness of Blended Learning in Health Professions: Systematic Review and Meta-Analysis

1 Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College of Huazhong University of Science &Technology, Wuhan, China

Weijun Peng

Weirong yan, associated data.

E-tables 1-7.

Blended learning, defined as the combination of traditional face-to-face learning and asynchronous or synchronous e-learning, has grown rapidly and is now widely used in education. Concerns about the effectiveness of blended learning have led to an increasing number of studies on this topic. However, there has yet to be a quantitative synthesis evaluating the effectiveness of blended learning on knowledge acquisition in health professions.

We aimed to assess the effectiveness of blended learning for health professional learners compared with no intervention and with nonblended learning. We also aimed to explore factors that could explain differences in learning effects across study designs, participants, country socioeconomic status, intervention durations, randomization, and quality score for each of these questions.

We conducted a search of citations in Medline, CINAHL, Science Direct, Ovid Embase, Web of Science, CENTRAL, and ERIC through September 2014. Studies in any language that compared blended learning with no intervention or nonblended learning among health professional learners and assessed knowledge acquisition were included. Two reviewers independently evaluated study quality and abstracted information including characteristics of learners and intervention (study design, exercises, interactivity, peer discussion, and outcome assessment).

We identified 56 eligible articles. Heterogeneity across studies was large (I 2 ≥93.3) in all analyses. For studies comparing knowledge gained from blended learning versus no intervention, the pooled effect size was 1.40 (95% CI 1.04-1.77; P< .001; n=20 interventions) with no significant publication bias, and exclusion of any single study did not change the overall result. For studies comparing blended learning with nonblended learning (pure e-learning or pure traditional face-to-face learning), the pooled effect size was 0.81 (95% CI 0.57-1.05; P< .001; n=56 interventions), and exclusion of any single study did not change the overall result. Although significant publication bias was found, the trim and fill method showed that the effect size changed to 0.26 (95% CI -0.01 to 0.54) after adjustment. In the subgroup analyses, pre-posttest study design, presence of exercises, and objective outcome assessment yielded larger effect sizes.

Conclusions

Blended learning appears to have a consistent positive effect in comparison with no intervention, and to be more effective than or at least as effective as nonblended instruction for knowledge acquisition in health professions. Due to the large heterogeneity, the conclusion should be treated with caution.

Introduction

Electronic learning (e-learning) has quickly become popular for health education [ 1 - 3 ], especially since the emergence of the Internet has allowed its potential to be realized [ 4 ]. E-learning can not only transcend space and time boundaries and improve convenience and effectiveness for individualized and collaborative learning, but also provide reusable and up-to-date information through the use of interactive multimedia [ 3 , 5 - 9 ]. However, it also suffers from disadvantages such as high costs for preparing multimedia materials, continuous costs for platform maintenance and updating, as well as learners’ feelings of isolation in virtual environments [ 8 , 10 , 11 ]. Traditional learning must be conducted at a specific time and place and is considered vital in building a sense of community [ 12 , 13 ]. Blended learning, defined as the combination of traditional face-to-face learning and asynchronous or synchronous e-learning [ 14 ], has been presented as a promising alternative approach for health education because it is characterized as synthesizing the advantages of both traditional learning and e-learning [ 8 , 15 , 16 ]. Moreover, blended learning has shown rapid growth and is now widely used in education [ 17 , 18 ].

With the introduction of blended learning, increasing research has focused on concerns about its effectiveness. Three original research articles reporting on quantitative evaluations of blended learning were published in the 1990s [ 19 - 21 ], and then many were published after 2000 [ 16 , 22 - 29 ]. A quantitative synthesis of these studies could inform educators and students about evidence for, and factors influencing, the effectiveness of blended learning.

Rowe et al’s systematic review reported that blended learning has the potential to improve clinical competencies among health students [ 30 ]. In another systematic review, McCutcheon et al suggested a lack of evaluation of blended learning in undergraduate nursing education [ 31 ]. Several reviews have also summarized the evaluation of e-learning in medical education, but none separated blended learning from pure e-learning [ 32 - 34 ]. Furthermore, these systematic reviews were limited to only some areas or branches of health education; there has been no quantitative synthesis to evaluate the effectiveness of blended learning in all professions directly related to human and animal health.

Therefore, our study aimed to identify and quantitatively synthesize all studies evaluating the effectiveness of blended learning for health professional learners who were students, postgraduate trainees, or practitioners in a profession directly related to human or animal health. We conducted two meta-analyses: the first summarized studies comparing blended learning with no intervention, and the second explored blended learning compared with nonblended learning (including pure e-learning and traditional face-to-face learning). We also aimed to explore factors that could explain differences in learning effectiveness across characteristics of participants, interventions, and study designs. Based on previous research, we hypothesized that learning outcomes would be improved through exercises, cognitive interactivity, and peer discussion [ 35 - 38 ]. Exercises contain cases, quizzes, self-assessment test, and other activities requiring learners to apply knowledge acquired from the course [ 33 ]. Cognitive interactivity reflects cognitive engagement required for course participation, and multiple practice exercises, essays, and group collaborative projects account for high interactivity [ 38 ]. Peer discussion includes instructor-student or peer-peer face-to-face discussion that might arise in a typical lecture, and synchronous or asynchronous online communication such as discussion boards, email, chat, or Internet conferencing [ 33 ].

Reporting Standards

We conducted and reported our study according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines [ 39 ] (see e-Table 7 in Multimedia Appendix 1 ) and meta-analyses of observational studies in epidemiology [ 40 ].

Eligibility Criteria

Inclusion criteria for studies were based on the PICOS (population, intervention, comparison, outcome, and study design) framework [ 39 ]. Studies were included only if they (1) were conducted among health professional learners, (2) used a blended learning intervention in the experimental group, (3) involved a comparison of blended learning with no intervention or nonblended learning, (4) included quantitative outcomes with respect to knowledge assessed with subjective (eg, learner self-report) or objective assessments (eg, multiple-choice question knowledge test) of learners’ factual or conceptual understanding of the course, and (5) were randomized controlled trials (RCTs) or nonrandomized studies (NRSs), which are widely used in health profession education [ 33 ]. Studies in any language and of any publication type were included. Gray literature was searched in CENTRAL and ERIC.

Studies were excluded if they did not compare blended learning with nonblended learning or no intervention, did not report quantitative outcomes with respect to knowledge, used a single-group posttest-only design, were not conducted with health professional learners, evaluated pure e-learning instead of blended learning, or used the computer only for administrative purposes. Reviews, editorials, or meeting abstracts without original data were also excluded.

Data Sources

To identify relevant studies, we conducted a search of citations in Medline, CINAHL, Science Direct, Ovid Embase, Web of Science, CENTRAL, and ERIC. Key search terms included delivery concepts (eg, blended, hybrid, integrated, computer-aided, computer-assisted; learning, training, education, instruction, teaching, course), participants’ characteristics (eg, physician*, medic*, nurs*, pharmac*, dent*, cme, health*), and study design concepts (eg, compar*, trial*, evaluat*, assess*, effect*, pretest*, pre-test, posttest*, post-test, preintervention, pre-intervention, postintervention, post-intervention). The asterisk (*) was used as a truncation symbol for searching. For instance, evaluat* retrieved entries containing the following words: evaluate, evaluation, or evaluative, etc. E-Table 1 in Multimedia Appendix 1 describes the complete search strategy for each database. The last date of search was September 25, 2014. In addition, all references of included studies were screened for any relevant articles.

Study Selection

Using these criteria, QL and FZ independently screened all titles and abstracts and reviewed the full text of all potentially eligible abstracts. Conflicts between these reviewers were resolved through discussion with other members of the research group until a consensus was obtained.

Data Extraction

QL and FZ developed a form (based on the Cochrane Consumers and Communication Review Group’s data extraction template), pilot-tested it on 10 randomly selected included publications, and refined it accordingly. Using the same form, data related to the following issues were extracted independently by QL and FZ: first author’s name, year of publication, country where the intervention was conducted, study design, study subjects, sample size, specific health profession of the intervention, comparison intervention, intervention duration, exercises, interactivity, peer discussion, outcome assessment, conflict of interest (whether there was a conflict of interest), and funding from company (whether funding was obtained from a source that had a direct interest in the results). Disagreements were resolved through discussion with another research team member until agreement was reached. If the required data for the meta-analyses were missing from the original report, attempts were made to obtain the information by contacting the corresponding authors by email.

Quality Assessment

Recognizing that many nonrandomized and observational studies would be included, the methodological quality of the studies was evaluated using a modified Newcastle-Ottawa Scale (also called the Newcastle-Ottawa Scale-Education), which is an instrument used to appraise the methodological quality of original medical education research studies, typically in the process of a literature review of a field or topic in medical education [ 33 , 41 - 43 ]. Each study could receive up to 6 points and was rated in the following five domains:

• Representativeness: the intervention group was “truly” or “somewhat” representative of the average learner in this community (1 point).
• Selection: the comparison group was drawn from the same community as the experimental cohort (1 point).
• Comparability of cohorts (2 points possible): These include nonrandomized two-cohort studies (further classified into “controlled for baseline learning outcome [eg, adjusted for knowledge pretest scores; 1 point]” and “controlled for other baseline characteristics [1 point]”) and randomized studies (further classified into randomized [1 point] and allocation concealed [1 point]).
• Blinding: outcome assessment was blinded (1 point). These include (1) blinded if the assessor cannot be influenced by group assignment; (2) assessments that do not require human judgment (eg, multiple-choice tests or computer-scored performance) are considered to be blinded; (3) one-group studies are not blinded unless scoring does not require judgment or authors describe a plausible method for hiding the timing of assessment; (4) participant-reported outcomes are never blinded.
• Follow-up: subjects lost to follow-up were unlikely to introduce bias; small number lost (75% or greater follow-up) or description provided of those lost (1 point).

In addition, we evaluated the quality of evidence with the Grades of Recommendation, Assessment, Development, and Evaluation (GRADE) instrument [ 44 - 53 ]. GRADE identifies five factors that may decrease the quality of evidence of studies, and three factors that may increase it. RCTs start with a high rating and observational studies with a low rating. Ratings are modified downward due to (1) study limitations (risk of bias) [ 47 ], (2) inconsistency of results [ 50 ], (3) indirectness of evidence [ 51 ], (4) imprecision [ 49 ], and (5) likely publication bias [ 48 ]. Ratings are modified upward due to (1) large magnitude of effect, (2) dose response, and (3) confounders likely to minimize the effect. Evaluating these elements, we determine the quality of evidence as “high” (ie, further research is very unlikely to change our confidence in the estimate of effect), “moderate” (ie, further research is likely to have an important impact on our confidence in the estimate of effect and may change the estimate), “low” (ie, further research is very likely to have an important impact on our confidence in the estimate of effect and is likely to change the estimate), or “very low” (ie, we are very uncertain about the estimate).

Data Synthesis

Analyses were carried out for knowledge outcomes using Stata Version 12.0 and R 3.1.2. The standardized mean difference (SMD; Hedges g effect sizes), converted from means and standard deviations from each study, was used [ 33 , 54 ]. When the mean was available but the standard deviation (SD) was not, we used the mean SD of all other included studies. As the overall scores of included studies were not the same and SMD could eliminate the effects of absolute values, we adjusted the mean and SD so that the average SD could replace the missing value of SD.

The I 2 statistic was used to quantify heterogeneity across studies [ 55 ]. When the estimated I 2 was equal to or greater than 50%, this indicated large heterogeneity. As the studies incorporated are functionally different and involve different study designs, participants, interventions, and settings, a random-effects model allowing more heterogeneity was used. Meta-analyses were conducted and forest plots were created. To explore publication bias, funnel plots were created and Begg’s tests were performed. To explore potential sources of heterogeneity, we performed multiple meta-regression and subgroup analyses based on factors selected in advance, such as study design, country socioeconomic status, participant type, duration of intervention, randomization, quality score, exercises, interactivity, peer discussion, outcome assessment, and intervention of the control group. Moreover, we performed sensitivity analyses to test the robustness of findings.

The search strategy identified 4815 citations from the databases, and 642 duplicates were removed. After scanning the titles and abstracts, 225 were found to be potentially eligible. Then, full texts were read for further assessment, and 62 remained. For 12 articles without accessible full texts and 6 without sufficient quantitative data (mean knowledge scores), we tried contacting the authors by email but received no reply. Thus, 56 publications were included, among which one publication compared blended learning with both no intervention and nonblended instruction ( Figure 1 ). No more relevant articles were found by reviewing the references of the included articles. E-Table 2 in Multimedia Appendix 1 includes the references of articles excluded based on full text (n=163) and insufficient quantitative data reported (n=6).

Study selction process.

Study Characteristics

In the meta-analysis, we included 13 publications representing 20 interventions published from 2004-2014, which compared blended learning with no intervention and included 2238 health professional participants [ 22 - 24 , 56 - 65 ]. The number of participants ranged from 6 [ 61 ] to 817 [ 62 ], and the duration of the intervention ranged from 24 hours [ 63 ] to one semester [ 58 ].

We included 44 publications representing 56 interventions comparing blended learning with nonblended learning published from 1991 to 2014 that covered 6110 health profession participants [ 16 , 19 - 21 , 25 , 26 , 28 , 29 , 63 , 66 - 100 ]. There was 1 pre-posttest one-group intervention, 27 posttest-only two-group interventions, and 28 pre-posttest two-group interventions. The number of participants ranged from 14 [ 72 ] to 609 [ 84 ], and the duration ranged from 1 hour [ 101 ] to 1 year [ 77 ].

Components or features of the study intervention were mostly “Web-based+ face-to-face”, “e-learning+ class session”, and “Web-based online instruction+ off-line instruction (review of the core contents on the online program, case analysis, small group discussion, and miscellaneous activities)”. “Modality or technology” varied, such as “Moodle, on-site workshops”, “asynchronous discussion forums, a live audio and text-based online synchronous session (Centra); online modules (Macromedia Breeze)”. More than 80% of the interventions were measured using objective assessment, which included multiple choice questions, true or false questions, matching questions, and essays. For most studies, there was no delay between the end of the intervention and the posttest. Table 1 summarizes the key features and e-Table 3 in Multimedia Appendix 1 describes the detailed information.

Summary description of included studies.

Study Quality

All of the intervention groups in the included studies were representative of average learners. Ten percent (2/20) of no-intervention controlled studies and 98% (55/56) of nonblended learning controlled studies selected the control group from the same community as the experimental group. Nearly a third (30%, 6/20) of the no-intervention controlled studies and 46% (26/56) of nonblended learning controlled studies reported blinded outcome assessment. All of the no-intervention controlled studies (100%) and 96% (54/56) of nonblended learning controlled studies reported completeness of follow-up. The mean (SD) quality score was 3.40 (0.82) for no-intervention controlled studies, and 4.45 (0.78) for nonblended learning controlled studies. The results of the quality assessment are shown in e-Table 4 in Multimedia Appendix 1 .

Quantitative Data Synthesis

Comparisons with no intervention.

As effect sizes larger than 0.8 were considered to be large [ 102 ], the pooled effect size (SMD 1.40; 95% CI 1.04-1.77; Z =7.52, P <.001) suggests a significantly large effect. However, significant heterogeneity was observed among studies ( P <.001, I 2 =94.8%, 95% CI 93.1-96.0), and individual effect sizes ranged from -0.12 to 4.24. Figure 2 shows detailed results of the meta-analysis. The test of funnel plots ( Figure 3 ) indicated no significant publication bias among studies (Begg’s test P =.587). Based on risk of bias and large effect, we graded the quality of evidence as moderate. E-Table 5 in Multimedia Appendix 1 provides the GRADE evidence profile. E-Table 6 in Multimedia Appendix 1 contains the mean, standard difference, and number of participants for both blended learning and no intervention/nonblended learning.

Forest plot of blended learning versus no intervention.

Funnel plot of blended learning versus no intervention.

Meta-Regression and Subgroup Analysis

We investigated a multiple regression model with each possible source of heterogeneity (I 2 _res=85.33%, adjusted R 2 =48.89%; I 2 _res means residual variation due to heterogeneity) and found that the outcome assessment ( P =.03) was a potential source of heterogeneity ( Table 2 ). Studies with objective outcome assessments had larger pooled effect sizes. Furthermore, subgroup analyses were performed to evaluate the sources of heterogeneity. A statistically significant interaction favoring pre-posttest two-groups designs and pre-posttest one-group designs was found ( P for interaction<.001), which was consistent with the result of the meta-regression. Statistical differences existed between the groups of participants ( P for interaction<.001). Nonrandomized studies had larger effects than randomized ones ( P for interaction=.01). The effect size was significantly larger for blended learning with objective assessment than with subjective assessment ( P for interaction=.005). However, we did not find support for the hypotheses regarding subgroup interactions across levels of exercises ( P for interaction=.92).

Subgroup analysis of blended learning versus no intervention.

a P for interaction means the P of heterogeneity between groups.

Sensitivity Analyses

Exclusion of any single study did not change the overall result, which ranged from 1.24 (95% CI 0.91-1.57) to 1.48 (95% CI 1.14-1.83).

Comparisons With Nonblended Learning

The pooled effect size (SMD 0.81; 95% CI 0.57-1.05; Z =6.59, P <.001) significantly reflected a large effect, and significant heterogeneity was observed among studies ( P< .001, I 2 =94.6%, 95% CI 93.7-95.5). Figure 4 shows detailed results of the main analysis. The test of asymmetry funnel plot ( Figure 5 ) indicated publication bias among studies (Begg’s test P =.01). The publication bias may have been towards larger studies with generally large magnitudes of effects. The trim and fill method indicated that the effect size changed to 0.26 (95% CI -0.01 to 0.54) after adjusting for publication bias, which suggested that blended learning was at least as effective as nonblended learning. Based on risk of bias, publication bias, and large effect, we graded the quality of evidence as low. E-Table 5 in Multimedia Appendix 1 provides the GRADE evidence profile.

Forest plot of blended learning versus non-blended learning.

Funnel plot of blended learning versus non-blended learning.

A multiple regression model for each possible source of heterogeneity was conducted (I 2 _res=94.59%, adjusted R 2 =-26.38%), and no significant source of heterogeneity was found ( Table 3 ). Furthermore, subgroup analyses were performed to evaluate the sources of heterogeneity. We found both pre-posttest two-group studies and pre-posttest one-group studies showed larger effects than posttest-only studies ( P for interaction<.001). It was shown that the presence of exercises could yield a larger SMD ( P for interaction=.49). Studies with objective assessments yielded a larger effect than studies with subjective assessments ( P for interaction=.01). Studies without conflicts of interest yielded a larger effect than those with conflicts of interest ( P for interaction<.001). However, high interactivity and presence of peer discussion did not yield larger effect sizes ( P for interaction>.85).

Subgroup analysis of blended learning versus nonblended learning.

Exclusion of any single study did not change the overall result, which ranged from 0.70 (95% CI 0.48-0.92) to 0.86 (95% CI 0.63-1.10).

Principal Findings

This meta-analysis shows that blended learning has a large consistent positive effect (SMD 1.40, 95% CI 1.04-1.77) on knowledge acquisition compared with no intervention, which suggested that blended learning was very effective and educationally beneficial in health professions. Moreover, we also found that blended learning had a large effect (SMD 0.81, 95% CI 0.57-1.05) in comparison with the nonblended learning group. This means that blended learning may be more effective than nonblended learning, including both traditional face-to-face learning and pure e-learning. Possible explanations could be as follows: (1) compared with traditional learning, blended learning allows students to review electronic materials as often as necessary and at their own pace, which likely enhances learning performance [ 8 , 16 ], and (2) compared with e-learning, blended learning learners are less likely to experience feelings of isolation or reduced interest in the subject matter [ 8 , 11 , 103 ]. However, publication bias was found in the nonblended learning comparison group, and the trim and fill method showed that the pooled effect size changed to 0.26 (-0.01 to 0.54), which means blended learning is at least as effective as nonblended learning. To the best of our knowledge, this may be the first meta-analysis to reveal the effectiveness of blended learning for knowledge acquisition in health professions, which includes all those directly related to human and animal health.

However, large heterogeneity was found across studies in both no-intervention and nonblended comparisons, and the subgroup comparisons partially explained these differences. The heterogeneity may be due to variations in study design, outcome assessment, exercises, conflict of interest, randomization, and type of participants. We found that effect sizes were significantly higher for studies using pre-posttest designs than posttest-only designs, which suggested that the former improved learning outcomes relative to the latter. As pretests may inform instructors about the knowledge learners have acquired before the course, which is considered to be one of the most important factors influencing education [ 104 ], they allow instructors to determine learning objectives and to prepare course materials accordingly [ 105 ]. Therefore, it is necessary for educators to administer pretests to learners to prepare well for courses. We also found that studies with objective assessments yielded a larger effect than those with subjective assessments. In contrast, Cook et al reported no difference between objective and subjective assessments in knowledge scores [ 33 ]. This is probably due to differences in personality traits of learners, as people with greater confidence tend to give higher ratings on subjective assessments than people who are less confident [ 106 ]. Thus, educators should objectively assess learners instead of using subjective evaluations.

Additionally, effect size was found to be significantly larger for blended courses with exercises versus no exercises, which was consistent with the results of a previous study conducted by Cook et al in 2006, which found that continuity clinics had higher test scores when using a question format compared to a standard format [ 37 ]. Thus, it is necessary for educators to include exercises in their teaching, such as cases and self-assessment questions. However, we failed to confirm our hypothesis that presence of peer discussion and high interactivity would yield larger effect sizes. Although we found statistical differences between the RCTs and NRS in the no-intervention comparison, it could probably be due to chance as there were only two RCTs (130 participants) included. Differences between studies with conflicts of interest and those without conflicts of interest in nonblended comparisons could be also due to chance, as only two studies with conflicts of interest (612 participants) were included. The remainder of the high heterogeneity may arise from other characteristics, such as individual learning styles, study intervention, assessment instrument, and ongoing access to learning materials [ 33 , 107 , 108 ], for which detailed information was not available in the included studies. As Wong et al cited in their review, different modes of course delivery suit different learners in different environments [ 109 ].

Our samples consisted of various health professional learners (nurses, medical students, nursing students, physicians, public health workers, and other health professionals) across a wide variety of health care disciplines, such as medicine, nursing, ethics, health policy, pharmacy, radiology, genetics, histology, and emergency preparedness. Moreover, we found medium or large effects for the pooled effect sizes of almost all subgroup analyses exploring variations in study design, participant type, randomization, quality scores, exercises, interactivity, and peer discussion. Thus, our results suggest that health care educators should use blended learning as a teaching component in various disciplines and course settings.

Strengths and Limitations

Our meta-analysis also has several strengths. Evaluations of the effectiveness of blended learning for health professions are timely and very important for both medical educators and learners. We intentionally kept our scope broad in terms of subjects and included all studies with learners from health professions. We searched for relevant studies in manifold research databases up to September 2014. The systematic literature search encompassed multiple databases and had few exclusion criteria. We also conducted all aspects of the review process in duplicate.

However, there are limitations to consider. First, although we searched gray literature in two databases (CENTRAL and ERIC), gray literature indexed by other databases may have been missed, which could be the reason for the observed publication bias. Second, the quality of meta-analyses is dependent on the quality of data from the included studies. Although the standard deviation of eight interventions was not available due to poor reporting, we used the average standard deviation of other included studies and imputed effect sizes with concomitant potential for error. Third, despite conducting the review and extraction independently and in duplicate, the process was subjective and dependent on the descriptions of the included articles instead of direct evaluation of interventions. Fourth, although the modified Newcastle–Ottawa scale is a useful and reliable tool for appraising methodological quality of medical education research and enhances flexibility for different study designs, it increases the risk of reviewer error or bias due to a certain amount of rater subjectivity. Then, results of subgroup analyses should be interpreted with caution because of the absence of a priori hypotheses in some cases, such as study design, country socioeconomic status, and outcome assessment. Moreover, although the subgroup analyses showed the variability of participant types, socioeconomic status of country, intervention duration, interactivity, peer discussion, and study design of RCT or NRS did not make a difference in the overall results, the large clinical heterogeneity and inconsistent magnitude of effects across studies makes it difficult to generalize the conclusions. In addition, as variability of study interventions, assessment instruments, circumstances and so on, which were not assessed, could be potential sources of heterogeneity, the results of both meta-analyses should be treated with caution. Furthermore, publication bias was found in the meta-analysis with the nonblended comparison. Although we used the trim and fill method for adjustment, the results should be treated with caution.

Implications

Our study has implications for both research on blended learning and education in health professions. Despite the fact that conclusions could be weakened by heterogeneity across studies, the results of our quantitative synthesis demonstrated that blended learning may have a positive effect on knowledge acquisition across a wide range of learners and disciplines directly related to health professions. In summary, blended learning could be promising and worthwhile for further application in health professions. The difference in effects across subgroup analyses indicates that different methods of conducting blended courses may demonstrate differing effectiveness. Therefore, researchers and educators should pay attention to how to implement a blended course effectively. This question could be answered successfully through studies directly comparing different blended instructional methods. Thus, such studies are of critical importance.

Studies comparing blended learning with no intervention suggested that blended learning in health professions might be invariably effective. However, although observational studies yielded a large effect size, the quality of evidence was lower due to their inherent study design limitations. Additionally, owing to the small number of RCTs, the meta-analysis did not meet the optimal size (imprecision) and therefore, quality of evidence was ranked lower. Thus, despite the consistency of effect and no significant reporting bias, the evidence of the no-intervention comparison was of moderate quality, which means further research is likely to have an impact on our confidence in the estimate of effect and may change the estimate, and RCTs with large samples may modify the estimates. Thus, there is still great value in further research comparing blended learning with no intervention, and RCTs with large samples may modify the estimates. For nonblended comparisons, pooled estimates showed that blended learning is more effective than or at least as effective as pure e-learning and pure traditional learning. However, due to publication bias towards larger studies with generally large magnitudes of effects, the evidence was of low quality, which means further research is very likely to change our estimate. Furthermore, only four studies using e-learning were included. Therefore, the effect of blended learning especially in comparison with e-learning should be evaluated in future research, and studies with small magnitudes of effect should merit publication.

Blended learning appears to have a consistent positive effect in comparison with no intervention and appears to be more effective than or at least as effective as nonblended instruction for knowledge acquisition in health professions. Moreover, pre-posttest study design, presence of exercises, and objective outcome assessment in blended courses could improve health care learners’ knowledge acquisition. Due to the large heterogeneity, the conclusion should be treated with caution.

Acknowledgments

The research leading to these results has received funding from the European Union’s Seventh Framework Programme (FP7/2007-2013) under grant agreement number 281930, ARCADE RSDH. Our research was partly supported by the project “Strengthening Primary Healthcare Workers’ Competence by Using an Internet-based Interactive Platform in Rural China” funded by the Ministry of Science and Technology, China.

Abbreviations

Multimedia Appendix 1

Authors' Contributions: WRY conceptualized and designed the study. QL and FZ performed the review, extraction, and data analysis. QL prepared the first draft of the paper. WRY, WJP, RH, YXL, and FZ contributed to the revision of the manuscript. All authors have read and approved the final manuscript.

Conflicts of Interest: None declared.

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Blended learning in higher education: Trends and capabilities

• Published: 22 February 2019
• Volume 24 , pages 2523–2546, ( 2019 )

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• Robin Castro   ORCID: orcid.org/0000-0001-7029-724X 1  

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Education is a complex system that requires multiple perspectives and levels of analysis to understand its contexts, dynamics, and actors’ interactions, particularly concerning technological innovations. This paper aims to identify some of the most promising trends in blended learning implementations in higher education, the capabilities provided by the technology (e.g., datafication), and the contexts of use of these capabilities. This literature review selected and analyzed forty-five peer-reviewed journal articles. The findings highlight some common capabilities among digital educational technologies. In particular, digital tools or platforms with human-to-machine interaction capabilities may enhance automated processes for blended learning delivery modes. In this context, digital technologies such as video capsules and intelligent tutoring systems may improve learning-teaching activities. First, by providing access to more students and facilitating self-paced online learning activities. Second, by offering an individual path of learning for each student, thus improving out-of-class activities and feedback. Educational technology capabilities (ETC) provide complementary insights to identify the best approach when aligning learning goals in technology-based implementations. Further research will be required to empirically validate these results.

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Data availability

The datasets used and/or analyzed during the current study are available from the corresponding author ([email protected]) on reasonable request.

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Acknowledgments

The author appreciates the helpful comments and suggestions of Xavier Olleros, Majlinda Zhegu, Diego Correa, Oleg Litvinski, and Jose Montes.

This research was partially funded by the Universidad Icesi (Colombia) and an internal grant received from the University of Québec at Montréal - UQAM (Canada).

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Castro, R. Blended learning in higher education: Trends and capabilities. Educ Inf Technol 24 , 2523–2546 (2019). https://doi.org/10.1007/s10639-019-09886-3

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CURRICULUM, INSTRUCTION, AND PEDAGOGY article

Students' perceptions of a blended learning environment to promote critical thinking.

• School of Foreign Languages, Northeast Normal University, Changchun, China

Critical thinking is considered as one of the indispensable skills that must be possessed by the citizens of modern society, and its cultivation with blended learning has drawn much attention from researchers and practitioners. This study proposed the construction of a blended learning environment, where the pedagogical, social, and technical design was directed to fostering critical thinking. The purpose of the study was to find out students' perceptions of the learning environment concerning its design and its influence on their critical thinking. Adopting the mixed method, the study used questionnaire and interview as the instruments for data collection. The analysis of the data revealed that the students generally held positive perceptions of the environment, and they believed that the blended learning environment could help promote their critical thinking in different aspects.

Introduction

The development of critical thinking has drawn attention of the education ministries and institutions of different levels in countries all over the world. In the last two decades, researchers and practitioners have been exploring the ways to integrate critical thinking cultivation into the instruction of different disciplines, proposing strategies and interventions to promote critical thinking, among which blended learning has been widely recognized (e.g., Van Gelder and Bulker, 2000 ; Gilbert and Dabbagh, 2005 ; Yukawa, 2006 ). Blended learning is proposed as focusing on optimizing achievement of learning objectives by applying the “right” personal learning technologies to the “right” person at the “right” time and “right” place ( Singh, 2003 ). A blended learning environment, integrating the advantages of the e-learning method and traditional method, is believed to be more effective than a face-to-face or online learning environment alone ( Kim and Bonk, 2006 ; Watson, 2008 ; Yen and Lee, 2011 ). Studies have been conducted to construct blended learning environments to improve students' critical thinking. Most of them, however, adopted standardized tests or coding schemes to examine the effectiveness of the learning environments on students' critical thinking ( Chou et al., 2018 ), paying less attention to students' perceptions and attitudes. Therefore, the purpose of the current study is to address this gap.

Critical Thinking

There are a vast number of definitions of critical thinking in the literature (e.g., Paul, 1992 ; Ennis, 1996 ; Fisher and Scriven, 1997 ). Despite the emphasis on different aspects, the core of critical thinking entails taking charge of one's thinking to improve it. Paul and Elder's definition and model of critical thinking were adopted in the study. According to Elder and Paul (1994) , critical thinking refers to “the ability of individuals to take charge of their own thinking and develop appropriate criteria and standards for analyzing their own thinking” (p. 34). They proposed that critical thinking is composed of three dimensions: elements of thinking, intellectual standards, and intellectual traits. People demonstrate critical thinking when they use intellectual standards (clarity, precision, accuracy, importance, relevance, sufficiency, logic, fairness, breadth, depth) to measure elements of thinking (purposes, assumptions, questions, points of view, information, implications, concepts, inferences) ( Paul and Elder, 1999 ).

Critical Thinking Cultivation With Information Communication Technology Tools

Studies applying ICT tools to cultivate critical thinking have been increasingly emerging in the literature. The systematic review conducted by Chou et al. (2018) analyzed and reported the trends and features of critical thinking studies with ICT tools. According to the findings of the review, the most often used tools include online discussion (e.g., Cheong and Cheung, 2008 ), coding or game design or Wikibooks creation (e.g., Yang and Chang, 2013 ), and concept or argument maps (e.g., Rosen and Tager, 2014 ). As for the method involved, the studies adopted both quantitative and qualitative research methods (e.g., Shamir et al., 2008 ; Yang, 2008 ; Yang and Chou, 2008 ; Butchart et al., 2009 ; de Leng et al., 2009 ; Yeh, 2009 ). Data from various measurements revealed overall positive results of using ICT tools in critical thinking cultivation (e.g., Yang, 2008 ; Allaire, 2015 ; Shin et al., 2015 ; Huang et al., 2017 ). The findings of the systematic review showed that the critical thinking-embedded activities using ICT tools were more effective than face-to-face activities in developing students' critical thinking ( Guiller et al., 2008 ; Adam and Manson, 2014 ; Eftekhari et al., 2016 ). However, students' prescriptions of the learning design or critical thinking development have not been fully addressed in the literature.

Blended Learning Environment

The concept of blended learning has been defined by several researchers and scholars. For instance, Singh and Reed (2001) defined blended learning as a learning program where more than one delivery mode is being used to optimize the learning outcome and cost of program delivery. According to Thorne (2003) , blended learning is a way of “meeting the challenges of tailoring learning and development to the needs of individuals by integrating the innovative and technological advances offered by online learning with the interaction and participation offered in the best of traditional learning” (p. 2). The above definitions indicate that blended learning can combine the advantages of both traditional face-to-face learning and e-learning and avoid the drawbacks of the two learning modes. The effectiveness of blended learning has been demonstrated by many studies, for example, the findings of a meta-analysis have shown that blended learning brings more positive impact on students learning than online and face-to-face learning ( BatdÄ, 2014 ). Despite the merits of blended learning itself, the effectiveness is determined by the proper design. How to achieve the equilibrium between e-learning and face-to-face modes is crucial to the success of the blended learning environment ( Osguthorpe and Graham, 2003 ).

This study applied the PST model developed by Wang (2008) as the framework for the environment design. As Kirschner et al. (2004) pointed out, an educational system is a unique combination of pedagogical, social, and technological components. PST model thus consists of three key components: pedagogy, social interaction, and technology. According to Wang (2008) , the pedagogical design involves the selection of appropriate content, activities, and the way to use the resources; the social design refers to the construction of a safe and comfortable environment where learners can share and communicate; the technical design provides learners with a technical space of availability, easy access and attractiveness. In any learning environment, the three components play different roles. The technical design offers a basic condition for pedagogical and social design, while the pedagogical and social design is considered as the most important factor that influences the effectiveness of learning ( Wang, 2008 ).

Perceptions of Blended Learning Environment

It has been acknowledged that students' perceptions and satisfaction are important for determining the quality of blended learning environment ( Naaj et al., 2012 ). Studies have been conducted to examine students' views regarding a blended learning environment and factors influencing it. For example, Bendania (2011) study found that students hold positive attitudes toward the blended learning environment and the influencing factors mainly include experience, confidence, enjoyment, usefulness, intention to use, motivation, and whether students had ICT skills. The positive view was also reported in the study done by Akkoyunlu and Yilmaz (2006) , and it was found to be closely related to students' participation in the online discussion forum. Findings from other studies (e.g., Dziuban et al., 2006 ; Owston et al., 2006 ) also revealed students' positive attitudes toward the blended learning environment, and the satisfaction could be attributed to features like flexibility, convenience, reduced travel time, and face-to-face interaction. Some studies, however, reported some negative perceptions of the blended learning environment. For example, the results of the study of Smyth et al. (2012) showed that the delayed feedback from the teacher and poor connectivity of the internet were perceived as major drawbacks of the environment. In another study conducted by Stracke (2007) , lack of reciprocity between traditional and online modes, no use of printed books for reading and writing, and use of the computer as a medium of instruction was considered as major reasons for students withdraw from the blended course. These findings indicate that students' negative attitudes toward the blended learning environment mainly come from the inadequate design ( Sagarra and Zapata, 2008 ).

The review of the above studies indicates that applying ICT tools to cultivate critical thinking has gained much popularity and produced positive results. Few studies, however, focus on students' perceptions of a learning environment designed to promote critical thinking despite the fact that many studies have been conducted to explore students' perceptions of a blended learning environment in general. Therefore, the purpose of the current research is to investigate students' perceptions of a blended learning environment with the orientation of critical thinking development.

Research Design

Research questions.

By adopting the mixed method, this study aims to answer the following two questions:

1. What are students' perceptions of the blended learning environment to promote critical thinking?

2. How do students perceive the impact of the blended learning environment on the development of their critical thinking?

Context and Participants

The study was carried out in the course of Practical English Writing which is a branch of the comprehensive English course for first-year non-English majors at a Normal University in mainland China. The 6-week course adopted a mixed learning mode of classroom face-to-face and online learning. The face-to-face class ran once a week and each class was 90 min. The e-learning tasks were assigned either before or after the class. Six independent learning centers with networked computers were available for students to use and the whole campus was covered with Wi-Fi signal.

The participants of the study involved a total of 90 non-English major students (33 males and 57 females) aging from 18 to 20 in 2020. The students were allocated into classes of Level A after the placement test of English proficiency, which means their English was about higher intermediate level. Adopting the International Critical Thinking Reading and Writing Test ( Paul and Elder, 2006 ), which was developed from Paul and Elders' thinking model, the study assessed students' critical thinking level at the beginning of the course and found that the students' overall critical thinking level was at the lower medium level. But their information literacy level was sufficient to cope with the online platform and the software in the blended learning environment. Before the implementation of the course, the instructor informed the students about the study, and the consent forms were signed by the students.

Environment Design

For the learning environment to achieve the purpose of developing learners' critical thinking, its structural components should be designed to provide favorable conditions for critical thinking cultivation. A systematic review conducted by Lu (2018) has identified a series of favoring conditions that could promote the students' critical thinking, which include (a) critical thinking as one of the teaching objectives, (b) tasks involving the operation of ideas, (c) authentic context, (d) rich and diversified resources, (e) interaction and collaboration, (f) scaffolding and guidance, (g) communicative tools. These conditions were mapped to the design of the components of the PST learning environment model and the designing strategies were generalized from the instruction practice to guide the detailed design of the environmental components.

Pedagogical Design

In terms of the pedagogical design, the thinking skills that can be cultivated were first decided according to the particular learning content. Aiming at promoting the thinking skills, the learning tasks which mostly introduced problems in the “real” context and involve the operation of ideas were designed. Furthermore, rich and diversified resources were provided to the students. The specific strategies of pedagogical design are listed in Table 1 .

Table 1 . Strategies for pedagogical design.

When designing the learning objectives of the activities, the basic concepts and frameworks of critical thinking were introduced to the students, making them aware of its meaning and significace. Furthermore, students were informed of the thinking skills targeted and their importance. When students associated the thinking skills with the tasks, they would try to use the skills to accomplish them.

In order to enable tasks to involve more operations of ideas, writing, discussion, and evaluation activities were given the priority to provide more opportunities for students to communicate with each other and reflect upon their ideas. Besides, the topics of these activities were chosen to induce more collision of ideas. For example, in learning to write complaint letters, students were assigned the roles of customers who made the complaints and the managers who responded to the complaints. In such an activity, students could realize the existence of different perspectives and think more adequately and deeply.

The creation of a relatively real context drew on the following two strategies: One is to provide sufficient details. In the case of the job application writing, details such as the information about the potential employer were provided to the students so that they could consider themselves as “real” potential employees. The other strategy is to create interesting situations. The contexts described were usually attractive to the students, which helped arouse students' interest in completing the tasks.

With the purpose of collecting sufficient and diversified resources, both traditional and online media were included. Since the materials in the textbook are rather limited, the relevant online resources would make complementation for students to have sufficient resources to deal with. To meet the multi-angle nature of resources, the information collected came from different positions and perspectives. For instance, the students were introduced to the websites both for job hunting and recruitment so that they could read information from the perspectives of both employers and potential employees. To help students conduct resource searches by themselves, online resources such as the Online Writing Lab of Purdue University were presented to them to conduct searches. The search was usually directed by a clear question or a problem, and students needed to accurately identify the target source. Some search engines were also introduced to the students, enabling them to compare and select the relevant resources. Students needed to first define what their search objectives were, then assess the search and query results one by one, and finally synthesize the resources to make a reasonable decision.

Social Design

With the purpose of cultivating students' critical thinking in the environment, interactions and collaborations of different types were stressed in the design (see Table 2 ). Furthermore, the scaffold and guidance from the teacher and the peer were designed to provide support to the students.

Table 2 . Strategies for social design.

In designing interaction and collaboration-rich community, the strategies were applied to target both student-student and student-teacher communities. In terms of student-student community, students were grouped according to their levels and the requirements of the activities. Specifically, in a demanding task, students of different academic levels were grouped to ensure the implementation. In a relatively free discussion, students were grouped according to their own will so that they could feel more comfortable sharing their ideas. Also, various types of interactions such as information exchange, discussion, debate were designed. With the change of partners, roles, and tasks, different critical thinking skills were trained. As for the student-teacher community, the student-teacher communication was facilitated through various forms of teacher-student interaction, such as teachers' feedback, office hour, and communications on Tencent QQ, which were necessary to keep students on the right track of developing thinking skills. With various opportunities of communicating with the teacher, students would not feel powerless or frustrated when facing difficult tasks, thus ensuring the achievement of the learning objectives.

Four strategies were employed when designing the scaffolding and guidance. First, the process of thinking was highlighted. When the focus fell on critical thinking processes such as establishing viewpoints, making assumptions, and evaluating information, students had examples to follow when they conducted these activities independently. Second, the role of peers was given full play. In many cases, the demonstration of peers was more direct and effective for the students to develop critical thinking skills. Third, the teacher consciously created a “democratic” classroom and online atmosphere, where students could express their opinions without fearing judgment from the “authority” or other people. Fourth, the teacher established awarding incentives to encourage students to take the initiative to meet challenges and develop thinking. For example, if one student's feedback to others' work was deeper and more thorough, the instructor gave the student more marks and demonstrated the work to the whole class with their permission.

Technological Design

Moodle (Modular Object-Oriented Dynamic Learning Environment) was the main platform of the e-learning environment. A composition reviewing and grading software TRP (Teaching Resources Platform) was also used to facilitate teachers' grading of the compositions. TRP mainly focuses on the mistakes related to language and grammar, which could help direct teachers' attention to the composition's structure, logic, coherence, and other aspects. In addition, Tencent QQ, a social networking software frequently used by students, was selected to send messages and notices to students.

As shown in Table 3 , both synchronous and asynchronous instruments were applied to provide sufficient communication among students in designing communicative tools. When designing the synchronous instruments, the instructor used the Tencent QQ, which could conveniently support the simultaneous real-time communication between learners and encourage group members to fully communicate with each other. The discussion board of Moodle was used as asynchronous tools, and sufficient time was given to the students to respond to other people's opinions or solve problems. The students could use the time to find information, consult others and translate complex ideas into words.

Table 3 . Strategies for technological design.

Research Instruments

Learning environment questionnaire.

The questionnaire adapted from the Web-Based Learning Environment Instrument (WEBLEI) was used to elicit the information of students' perception of the learning environment. The original WEBLEI questionnaire was first created and subsequently modified by Chang and Fisher for investigating online learning environments in University settings. The primary purpose of the questionnaire was to capture “students' perception of web-based learning environments” ( Chang and Fisher, 2003 , p. 9). The questions in the WEBLEI questionnaire are able to cover the three elements of the PST learning environment model. The researcher modified the questionnaire according to the context of the current study. The Cronbach alpha coefficients indicated the acceptable reliability of the modified questionnaire (see Table 4 ).

Table 4 . Cronbach alpha coefficients for modified WEBLEI.

In order to explore students' perceived improvement of critical thinking and the in-depth reasons behind students' perceptions of the learning environment and critical thinking instruction, interviews were conducted after the administration of the adapted WEBLEI questionnaire. Eight students were randomly chosen and invited to the interview one by one. The interviews lasted about 30 min and were audio-recorded with the participants' approval.

Data Analysis

Both quantitative and qualitative data were collected for this study. In terms of quantitative analysis, descriptive statistics were used to describe the means, standard deviations. As for qualitative data, the recordings of the interviews were transcribed for content analysis. The content about the perceptions of the environment was categorized with the outline of the learning environment components. Regarding the development of students' critical thinking, the “elements of thinking” from Paul and Elder's thinking model formed the framework for data analysis. The relevant script was examined and coded according to the framework by the researcher and her collegue to generalize the aspects of critical thinking improvement.

Results and Discussion

Students' perceptions of the environment, students' perception of the pedagogical design.

The means and standard deviation scores of students' perception of the pedagogical design are listed in Table 5 . The overall mean score was 3.86 (SD = 0.79), suggesting that students were generally satisfied with the pedagogical design. Item 1 (M = 3.98, SD = 0.80) (The learning objectives are clearly stated), Item 4 ( M = 3.93, SD = 0.83) (Expectations of assignments are clearly stated), and Item 5 (M = 4, SD = 1.00) (Activities are planned carefully) got particularly high scores, which indicates that students were aware of the careful design of the activities, content, and context.

Table 5 . Students' Perceptions of the Environment.

The students' positive attitude toward the pedagogical design was also revealed from the interview, in which they expressed their satisfaction with the design of tasks and contexts. For example, Student A expressed that the course was designed in the way that they needed to “find solutions to the problems” by themselves most of the time and he also enjoyed the discussions in class. Student C recognized the relative authentic contexts of the tasks, which helped her devote herself to the tasks. She mentioned that in learning to write a CV, the teacher asked the students to imagine the situation in which they were about to graduate and hunt a job. “I felt the topic was very relevant to me, so I was motivated to do this task well.” She told the interviewer.

Apart from the positive opinions, some students expressed their concern about the pedagogical design. For example, Student H said, “The online learning added to our workload. Sometimes I was scared of all the online assignments we had to finish after class.” And student G had difficulty adapting to this learning approach. “It seemed that we were learning by ourselves. I am not sure whether I have learned enough knowledge. I would rather learn how to write from the teacher.”

Students' Perception of Social Design

As seen from Table 5 , the overall mean score of the social design was 3.90 ( M = 0.82), indicating students' generally positive attitude toward the social design. The data gathered from the students' interviews also suggested that students were satisfied with the social design. For example, student B mentioned that she always received encouragement and help when dealing with difficult tasks. Item 11 ( M = 4.07, SD = 0.65) (Other students respond promptly to my request), Item 12 ( M = 4.09, SD = 0.91) (The teachers give me quick comments on my work) and Item 14 ( M = 4.07, SD = 0.58) (I was supported by a positive attitude from my teacher and my classmates) scored higher than Item 9 ( M = 3.47, SD = 1.01) (I can ask my teacher what I do not understand) and Item 10 ( M = 3.79, SD = 0.78) (I can ask other classmates what I do not understand). This finding reveals that in the environment, both students and teachers responded to others promptly, but students had considerations when they needed to consult others.

When asked the reason for this, the students suggested that the teacher and the environment did provide them with the opportunity to seek help, but sometimes they felt reluctant to trouble others. Student E mentioned when he found something he failed to understand, he would prefer to figure it out by himself first and then seek help from the teacher and classmates. He told the interviewer: “I thought the teacher was busy, and my classmates were also busy, so I would prefer to figure it out by myself.”

Students' Perceptions of Technical Design

As for the technical design (see Table 5 ), the average score is 3.73 (SD = 0.85), which suggests that the environment provided relatively sufficient technological support to the students. Item 16 ( M = 3.93, SD = 0.92) (The online material is available at locations suitable for me) and Item 19 ( M = 4, SD = 0.97) (I decide when I want to learn) got higher scores, which indicates that students could enjoy the convenience of “anywhere” and “anytime” in the learning environment.

This positive attitude was demonstrated in the interview data collected from Student F who expressed his appreciation for the freedom and the sense of control brought by asynchronous discussion. He said, “I could finish the task at the time that is convenient for me as long as I did not miss the deadline. I like it.”

One thing worth noticing is that the mean score of Item 20 (Using blended learning allowed me to explore the interest of my own) is 3.18 (SD = 0.68), which falls toward the middle of the 1–5 scale. This score reveals that students did not think the resources of the blended learning environment play an important role in exploring their own areas of interest. In the interview, student D expressed that he did not find the resources very interesting, for the range of the topics was rather limited, and he was not attracted by the resources provided.

In sum, students' ratings on different dimensions of the questionnaire suggest that students perceived the productiveness of the learning environment in a generally positive way. This result is consistent with the studies exploring students' perceptions of the blending learning environment in general (e.g., Akkoyunlu and Yilmaz, 2006 ; Dziuban et al., 2006 ; Owston et al., 2006 ; Bendania, 2011 ; Wang and Huang, 2018 ). In the study conducted by Wang and Huang (2018) , a blended environment was also constructed from the pedagogical, social, and technical perspectives. The findings of the study reveal that students are generally positive toward the design of the learning environment. This may suggest that students would perceive the learning environment positively if the elements of the blended learning environment are carefully designed. Despite the generally positive attitudes toward the learning environment, some students expressed their concern about the workload and adaptation to the way of learning in the interview. In study Stracke (2007) , the way of learning was also found to make the students withdraw from the blended course. The findings indicate that some students may need more time to adapt to more student-centered learning.

Students' Perceived Impact of the Blended Learning Environment on the Development of Their Critical Thinking

Drawing mainly on Paul and Elder's framework of thinking elements, the following themes emerged as to the students' perceived improvement of critical thinking after data analysis and are elucidated through students' quotations.

Gaining a Deeper Understanding of the Concept of “Critical Thinking”

In the interview, students talked about their improvement in understanding the concept of critical thinking. For example, Student D expressed that the environment helped him clarify the concept of critical thinking. He used to consider the concept as closely related to “criticizing” because of its Chinese translation and came to realize that it was closer to the concept of “rational thinking.”

Some students also expressed that the course helped them realize the importance of critical thinking. As the teacher clearly informed the students of the specific critical thinking skills each task aimed to cultivate, students realized that “critical thinking is not an abstract concept, but concrete ways of guiding people to solve problems” (Student B).

Using Facts and Evidence to Support One's Own Opinion

In the interview, students also talked about the change they experienced when forming and supporting their opinion. They started to recognize the importance of facts and evidence in their writing. Student E told the interviewer that he learned that supporting ideas were very important to make one's opinion accepted. He said: “In accomplishing the writing tasks of the course, I gradually learned to provide arguments with further explanations, examples and,… maybe some data.”

Some students also suggested that facts and evidence were important for them to convince others in the discussions. Student B said: “In the past when someone disagreed with me, I usually felt sad and angry. I would either remain silent or quarrel with them. In this course, I learned that if I wanted others to accept my opinion, I needed to convince them with evidence such as facts and information.” She also felt excited that her well-presented opinions were accepted several times during the discussion with her team members.

Thinking From Multiple Perspectives

Another perceived effect is thinking from multiple perspectives, which was mentioned by many students. For example, Student A described how a particular activity helped him recognize the importance of different perspectives and how his own writing benefited from a particular activity in the course. “The teacher asked some of us to play the role of employer and I was assigned this role. When I thought from the employer's perspective, I knew what kind of employee I needed… When I wrote my job application letter, I had a very clear idea what to include in my letter.” (Student A) Student F also mentioned that recognizing different perspectives helped him finish writing the complaint letter well. According to him, he not only mentioned the dissatisfaction in the complaint letter but also stated the potential negative impact on the company to which he sent the letter.

Exploring and Clarifying the Purpose Behind the Texts or Behaviors

The interviewees also mentioned that they learned to explore and clarify the purpose behind the texts or behaviors. Some students explained how they started to consider purpose as an important component in their writing. Student H told the interviewer that when the teacher started to teach a new genre, she always asked the students to discuss under what circumstances they could meet or use this type of writing, and why they needed it in the daily life. “In this way, I understand that there should be a clear purpose behind each writing. And… and when I tried to finish my own writing task, I also put the writing purpose into my consideration.” said Student H.

Some students also told the interviewer that they gradually learned to avoid distraction and stick to the purpose when they conducted a discussion. According to student G, the students tended to talk about irrelevant things when they had discussions at the beginning of the course. With the instructors' constant reminding, they could realize whether they strayed from the point and returned to the right track in time at the end of the semester.

In summary, the data from the interview suggest that students could perceive their critical thinking development in different thinking dimensions. Furthermore, according to the students' opinion, their development in critical thinking was also manifested in their writing and even transferred to other activities. As for the promoting factors of the development, the students recognized the importance of learning environment design, especially the pedagogical design and the social design. For example, students attributed their deeper understanding of the concept to the instructor's deliberate introduction of critical thinking and focus on the development of thinking skills in the activity design. Also, they believed that the teachers' guidance and peers' scaffold enabled them to realize the importance of multiple perspectives. These factors were also found to promote students' critical thinking in the systematic review conducted by Chou et al. (2018) . This suggests that designing the elements of the learning environment to provide favorable conditions for critical thinking development could bring positive effects.

Limitations and Implications

This study proposed the construction of a blended learning environment to promote critical thinking in terms of pedagogical, social, and technical design and explored students' perceptions of the environment design and their perceived impact on the improvement of critical thinking. The results of the study suggests that students are generally satisfied with the design of the learning environment, and students considered the learning environment helpful in improving critical thinking. Even though the study made a contribution to the instructional design aiming at critical thinking promotion in a blended learning environment, some limitations should be duly noted. First, because the participants of the study were 90 students in the same University, the relative homogeneity of the context may present a possible connection with the result. Therefore, replication is recommended with larger and more diverse samples. Second, the study was not able to present the relationship between environmental design and critical thinking development quantitively. Further study could focus on the correlation between design strategies and the improvement of specific thinking skills, or the predictive capability of elements design for the promotion of critical thinking.

This study also has some implications for critical thinking cultivation in the instruction of specific disciplines. On the one hand, the cultivation of students' critical thinking requires the detailed design of the blended learning environment. Special attention needs to be paid to pedagogical, social, and technical design covering factors such as learning objectives, student interaction, and ICT tools. On the other hand, students' troubles and challenges such as the extra workload and emotional factors should be taken into consideration when designing the learning environment.

Data Availability Statement

The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author/s.

Ethics Statement

The studies involving human participants were reviewed and approved by School of Foreign Languages, Northeast Normal University. The patients/participants provided their written informed consent to participate in this study.

Author Contributions

DL designed and implemented the learning environment, collected and analyzed the data, and wrote the article.

Conflict of Interest

The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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Keywords: students' perceptions, blended learning environment, critical thinking, design, survey

Citation: Lu D (2021) Students' Perceptions of a Blended Learning Environment to Promote Critical Thinking. Front. Psychol. 12:696845. doi: 10.3389/fpsyg.2021.696845

Received: 18 April 2021; Accepted: 31 May 2021; Published: 25 June 2021.

Reviewed by:

Copyright © 2021 Lu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Dan Lu, lud090@nenu.edu.cn

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