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• 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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Perceptions, Challenges and Effectiveness of Modular Distance Learning Approach to The Academic Performance of Humanities and Social Sciences (HUMSS) Students of Botolan National High School

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The COVID-19 pandemic has necessitated a significant shift towards modular distance learning in education systems worldwide. In the Philippines, the Department of Education has developed Self-Learning Modules (SLMs) to ensure quality primary education for all learners during the pandemic. This research study aims to identify the challenges and effectiveness of the modular distance learning approach on the academic performance of Grade 12 Humanities and Social Sciences students at Botolan National High School. Employing a descriptive research design, data were collected through a validated questionnaire and analyzed using weighted arithmetic mean, frequency, percentage distribution, and Pearson-r correlation. The study found that the majority of student-respondents were female, aged 17.31 years old, and achieved very satisfactory academic grades. The students perceived the modular distance learning approach as agreeable, with self-motivation being the most challenging aspect. The ability to express ideas was the most effective aspect, while the ability to answer without pressure was the least effective. The study found no significant relationship between student's perceptions of the modular distance learning approach and their academic performance. Based on the findings, the study recommends using the modular distance learning approach and developing policies to address students' mental health issues. Furthermore, further research is needed to investigate teacher readiness and technology competency, as well as other variables not covered in this study, to improve the effectiveness of the modular distance learning approach. The study demonstrates that despite the limitations caused by the pandemic, modular distance learning can be an efficient alternative to traditional face-to-face education.

Article Details

Modular Learning: 8 Tips for Effective Online Teaching

Table of contents.

Due to the COVID-19 pandemic, many teachers in affected areas worldwide suddenly faced the task of getting their instructional materials ready to facilitate modular learning as a strategy for the sustained delivery of education to their students. I am one of these teachers, but the possibility of teaching the students exclusively online did not deter me because I have already worked on my instructional modules designed for online delivery.

Since 2012, and during COVID-19 times, I gradually developed a learning model for effective modular learning. I call it the Blended Website Learning Model, an innovative learning system that I immediately put to use at the beginning of the pandemic.

So if you’re someone willing to innovate in your modular learning approach and make the teaching and learning process more efficient and less time-consuming, I dedicate this article to you. You may work on the tips gradually until you become comfortable with them. 

Once you can apply these eight tips to your classes, I assure you that you will not be spending endless hours checking your papers and getting frustrated with the inability of your students to keep up. Once in place, you will spend less effort and time to work on your instructional materials for modular learning in the new normal. 

Besides, today’s trends follow a digital path as global technological innovations occur at light speed. Teachers have to keep up to be relevant.

Given the experience I gathered through the years, I would like to share eight tips on modular learning. These tips will somehow ease the teachers’ struggle for something they are not mentally and technically ready to face. The pandemic has changed the way teaching is carried out.

I start this discussion by defining modular learning, asynchronous versus asynchronous delivery of lessons, problems encountered, and solutions to those problems.

Earlier, I synthesized the lessons learned and the corresponding fixes in a learning model – the  Blended Website Learning Model  for more effective achievement of desired learning outcomes or most essential learning competencies (MELCs) for each course. You may refer to this model later on.

What is Modular Learning?

Modular learning, as the word connotes, uses learning modules that facilitate student learning by themselves. Modular learning is a form of distance learning that uses Self-Learning Modules (SLM) based on the most essential learning competencies (MELCS) developed by the teachers with the aid of curriculum developers.

The modules include sections on motivation and assessment that serve as teachers’ and students’ guides to achieve desired competencies. Feedback mechanisms aid teachers in monitoring student achievement and identify those who require follow-up interventions.

Self-paced learning modules can educate learners through carefully written guideposts that direct the learner on what action to take. The contents of the learning module follow a particular learning model that makes instruction effective. 

Upon our department chair’s advice, I used the 4H or  Experiential Learning Model  (ELM) based on the Experiential Learning Theory developed by educators for more than a century. I am not an education graduate. Hence, I have to study ELM carefully.

8 Tips to Achieve the Course Outcomes in Modular Learning

1. write your instructional tips to students online.

Teaching is a repetitive exercise. So what I did is to write articles about the lessons I teach and publish them online. I update those articles once in a while to ensure their relevance.

Although educational articles on almost anything under the sun can be found online, I find some tips lacking credibility and proper documentation. Thus, I embarked on my blogging platform (this website) to house my tips for students on specific topics I teach in the classroom.

I made sure that the tips I gave use the latest information or reliable references online for my students to refer to for further reading. Besides, many of the legitimate and well-referenced material are behind a paywall which my students do not have the means to purchase. Nevertheless, there are free, open-access articles that anyone can access with extra effort.

2. Compress and upload instructional materials on a fast-loading website

I uploaded all of my instructional modules in pdf on a fast-loading website I created at the beginning of the pandemic. I compress each module in the free pdf compressor provided by ilovepdf.com . Compressing the modules makes downloading into students’ smartphones easy. The small files also save them bandwidth, thus reduced data consumption in their internet subscription.

I studied website development for quite a while, anticipating the emphasis on modular learning in the future. I started with Webnode sometime in 2012. Webnode uses drag-and-drop technology, which works for a beginning website developer like me. I even purchased a domain name for my free account on that website.

However, after several years of use, I found the technology lacks the flexibility I need. I want to maintain an independent website without the costly upgrades when the traffic exceeds my subscription. Hence, I shifted to an independently hosted WordPress.org Content Management System (CMS) platform. But not before I practiced in the WordPress.com website.

WordPress as a Tool in Modular Learning

I used WordPress to develop the simple but fast-loading website that students can easily load on their cellphones. It scores an almost perfect speed of 99% in both mobile and desktop (Figure 1).

I used Neve, a WordPress theme with no frills nor bloat software, to delay loading. All instructional modules are instantly available to students after entering the password I gave them.

The instructional material website simply works. No frills, no fuss.

Anyone can easily create a WordPress website in minutes. Just have your email and password ready to create an account in WordPress.com for free. You can create your website later, like what I did when I first started. As you practice using the free WordPress website, you will get to be familiar with how websites work.

You may listen to the simple instruction in the video I give below. Knowing how to create your website will give you more opportunities to become digitally savvy. Modular learning will be much more easily as you gain experience and expertise.

3. Use a Learning Management System to assess student performance

I had a limited two-day training on the use of Moodle before the COVID-19 pandemic began. By a stroke of luck, I could use the LMS as a modular learning tool in the middle of the semester when the government declared a nationwide Enhanced Community Quarantine (ECQ) to stem the brewing spread of the dreaded virus.

Using a Learning Management System (LMS) such as the free, open-source Modular Object-Oriented Dynamic Learning Environment (MOODLE) can help a lot in designing quizzes and periodic examinations. The once time-consuming task of checking the students’ quizzes and periodic examinations is done real time.

Using a Learning Management System (LMS) such as the free, open-source Modular Object-Oriented Dynamic Learning Environment (Moodle™) can help a lot in designing quizzes and periodic examinations. The once time-consuming task of checking the students’ quizzes and periodic examinations is done real time .

Students get their quiz or exam results in a matter of seconds. Once they submit their quiz, long exam, or midterm or final exam, they get the results right away.

I give students two chances of taking the quiz or major examination, mindful of the glitch that students experience while taking the assessment. Last semester, the internet connection of some students break while taking the quiz. Hence, it is good practice to give them another chance. Further, giving the students another chance to take the quiz provides them an opportunity to correct their answers and establish mastery of the subject matter.

I pushed my knowledge of Moodle further, not by just being a user, but by studying the process of its installation, mainly as part of my hobby and partly as a challenge to create a website to house the LMS myself. Having my own Moodle site gives me the independence and freedom to innovate.

I realized I can create an independent Moodle site on my GoDaddy server. In short, I figured that the only thing I need to put Moodle to work was to register a unique domain name. I hosted Moodle in the same platform where my blogging site, Simplyeducate.me, is being hosted. The LMS had virtually a free ride as a sub-domain.

I don’t mind spending a little more for my convenience. It’s an investment to save time and effort. In addition, I learn and enjoy the new functionality as I implement the system.

Moodle takes time to load; it’s slow

Although Moodle was designed to house complete learning modules for learners, my students have trouble accessing it. I had the impression that Moodle, being an open source project, had too many functionalities that made it heavy to load. Also, many of my students use cellphones in accessing the lessons online.

After spending considerable time looking for answers online and tweaking the Moodle website, I gave up, even though I successfully enhanced the speed of the LMS. I cannot make the Moodle site load faster without adding more investment in Random Access Memory (RAM) capacities and having it work on a Solid State Drive (SSD). I have a limited budget for this expense.

But Moodle is a good performance assessment site that enhances modular learning

I found the assessment function of Moodle very useful, so I kept it as an assessment site that students will log on once they are ready. Another advantage is that the LMS enables me to prepare my quizzes easily and checks the quizzes and periodic exams automatically. I just record the points my students get in Excel to give the corresponding percentages on the different assessment criteria.

That functionality surely saved me time in checking the students’ performance. It’s even better than administering questions in a face-to-face learning session. It worked well for me serving as an assessment site. I just set the period wherein the quiz will be available to students.

Also, the system can shuffle the questions and the answers in the exam. Each student has a different set of questions and answers, ensuring a unique performance record.

4. Conduct regular short synchronous meetings to remind and update the students

I conduct regular, synchronous meetings with my students to give them a feel of classroom ambiance; it simulates a face-to-face interaction. While most of my students can attend the meeting via Zoom, a video teleconferencing software program, several of them could not connect to the internet for valid reasons.

Among the valid reasons I have learned from my students for their inability to connect during synchronous meetings are the following:

• poor internet connection,
• exhausted data allocation,
• attending to emergencies, and

Recording of synchronous meetings

Recognizing these student difficulties, I always record the proceedings of the synchronous meetings. I upload the zoom video in MP4 format in mediafire.com , the cloud service I have been using for easy access. Then I provide a link to the fast website I created for the instructional materials.

Once the students have the opportunity to go online after resolving their issues during synchronous meetings, they are able to access the proceedings of the meeting. The poor internet connection can be remedied by going online during non-peak hours. Midnight until the early hours of the morning appears to have fewer users online.

The recorded videos do not last more than an hour. Making them short saves bandwidth as well as limits file size to a manageable size that students can download with ease.

5. Follow-up students through Messenger

Almost everyone has an account on Facebook together with Messenger nowadays. I tell my students to communicate with me through Messenger if there are concerns that they need me to know.

During Zoom sessions, some students could not easily express their burdens while others listen. Hence, they can send private messages to prevent getting embarrassed for their queries.

Since most of my work is done online, I can readily see the notifications that I have messages from my students. I consider the communication part of my consultation time. It also presents an opportunity to empathize with the students on their unique concerns.

So far, Messenger has become an effective tool to connect with students and give them support, especially in crucial times. Also, it is easy to find them online if I need to issue additional instructions related to the subjects I teach.

6. Use an Ishikawa diagram to contextualize the Most Essential Learning Outcomes

Given the considerable time that students have to devote to keeping up with their subjects, I design my modules as briefly as I can muster without sacrificing the essential outcomes of the modules. I present these outcomes in an Ishikawa or fishbone diagram at the beginning of the semester.

Figure 2 presents an Ishikawa diagram showing the learning outcomes I prepared for my students. The diagram visualizes the expected competencies that students could gain during the semester. Guided by the outline, they will see their pace in context while performing the tasks at hand. Seeing the goal serves as motivation for them to go on.

The fishbone diagram motivates the students concerning the overall outcome of the things that they do each learning session. One learning activity progresses to another one that leads towards the goal of learning.

Hence, the process of modular learning becomes meaningful to students. Incremental, modular learning transpires.

7. Give generous time for achievement of MELCs

I give a generous time of at least two weeks for students to achieve the expected learning outcomes. Giving them leeway to perform and reflect on their assigned tasks facilitates retention and helps them perform at their very best.

Writing many tasks without enough time to ponder or reflect on their work leads to a half-baked performance. Thus, less than stellar work dampens the motivation to do things in the best way they can.

Seeing some prescribed MELCs as part of modular learning online, I get the impression that they’re more applicable to face-to-face interactions. Chances are, the students become overstressed with tasks to do without the focused guidance of their teachers, making online learning a mechanical activity fixated on compliance.

8. Use a Feedback table

To keep track of student performance and encourage them to perform within the time frame, I prepared a feedback table to show what stage they were already in. Whenever I meet the students during synchronous meetings, I present the feedback table to the class and ask them if I have recorded their submissions correctly.

Some of my students would tell me they have submitted, but I could not verify their submissions. Perhaps failing to upload is due to a poor internet connection. Given the real-time feedback I get via Messenger, they try again until they have successfully uploaded. I confirm that I have received their outputs. Thus, the student’s anxiety because of failure to upload the required submissions is eliminated or minimized.

The feedback table finds support in Dr. Tali Sharot’s book on changing people’s behavior. It emphasizes the importance of feedback to change people’s behavior.

I invite you to listen to the highly motivating speech of Dr. Sharot in TED Talk that can change not only your student’s behavior towards the assigned tasks but also your ingrained habits. The lecture emphasizes the importance of feedback.

The feedback table instantly tells me potential problems and takes corrective measures before they get worse. Students exert more effort to keep up with their classmates once they notice that some of their classmates have already accomplished the modules. Modular learning becomes more effective with a monitoring system like this.

Figure 3 provides an example of a feedback table where you can quickly troubleshoot submission problems and ensure that no student is left behind.

Modular Learning is here to Stay

Whether the pandemic will last for quite a time, online modular learning will become the norm rather than an exception. The educational system has already shifted to Education 4, in tune with  Industry 4.0 , where interconnectivity through the Internet of Things (IoT), lies at its core.

Despite the setbacks experienced by teachers on the  effects of modular learning , we must be progressive in our thinking. The challenges are not without answers as technology progresses. Most students can access a laptop, or virtually everyone can access a cell phone, to download educational materials like the ones I make available on my IM website.

Although some of my students are hundreds of miles away, or even on an island, they can still access my instructional modules using their cell phones. I make online learning easy for them by applying the tips I previously gave—make the website load faster by compressing images and videos and make my instructional modules simpler to follow. I focus on a few but crucial and  most essential  learning outcomes. 

Stop being bookish. This time it’s online learning, not face-to-face classes where you cram in everything you want to the detriment of your students.

A 30-minute or less synchronous meeting is more than enough to brief your students about the module, the expected learning outcomes, and ask a few questions to get their feedback on the modules and constraints on their performance.

Advanced countries are already eyeing the many uses of  machine learning , and interest is growing in getting a degree in this field. Are our students ready to become part of this technological development?

In the information age, teachers are no longer what they used to be. We are now facilitators and innovators of learning through online modular learning as the information age changed the way people gain information.

We must undo the belief that we are the authorities of knowledge. Digital technology has shaped how we live, learn, and navigate this increasingly automated world.

Kudos to all teachers! Let’s rock the world of online modular learning.

© P. A. Regoniel 22 June 2021

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About the author, patrick regoniel.

Dr. Regoniel, a faculty member of the graduate school, served as consultant to various environmental research and development projects covering issues and concerns on climate change, coral reef resources and management, economic valuation of environmental and natural resources, mining, and waste management and pollution. He has extensive experience on applied statistics, systems modelling and analysis, an avid practitioner of LaTeX, and a multidisciplinary web developer. He leverages pioneering AI-powered content creation tools to produce unique and comprehensive articles in this website.

Thank you for your comment. Teaching in the new normal requires constant innovation and a change in mindset.

Thank you so much for sharing this! The different modes of learning in this new normal are somehow confusing, but this really helped. I also appreciate the tips you gave on how to teach effectively in modular learning!

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STHE EFFECT OF MODULAR LEARNING ON THE ACHIEVEMENT OF GRADE 8 STUDENTS IN PHYSICS

Due to Corona Virus pandemic that the Philippines are facing right now, Department of Education and the National Government decided and implemented the use of distance learning for the students this school year. Which is a learning delivery mode where interaction takes place between the teacher and the students who are geographically remote from each other during instruction. This means lessons will be delivered outside the traditional face-to-face setup. Based on the survey, 7 out of 10 parents and learners would likely use modular learning approach because of lack of gadgets and other resources for online learning. This action research focuses on the study of the effectiveness of modular learning on the achievement and performance of selected group of grade 8 students in Science subject at San Roque National High School particularly in Physics.

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Psychology and Education , nathanie maghanoy

This study aimed to determine the students' feedback and challenges encountered on modular distance learning and its relationship to their academic performance in Science from the different schools of Alamada North Cotabato during the Covid-19 pandemic. The study used the descriptive-correlational research design. The respondents of the study were grade 8 students of Alamada. The data gathered from the survey questionnaire were analyzed using appropriate statistical tools. Based on the findings of the study, it is found that the respondents have positive feedback on the use of modular distance learning in terms of the module content, strategies, learning activities, and assessments; they Sometimes experienced challenges like a lack of internet connection to supplement their readings, too many household chores and difficulty in staying motivated on the use of Modular Distance Learning. There is no significant difference in the feedback in utilizing modular distance learning when categorized according to age, sex, and monthly income. There is no significant relationship between feedback and the academic performances of the respondents in terms of strategies, learning activities, and assessments. However, module content is significantly related to their academic performance.

Gloria Elena Maquiran

Proceedings of SOCIOINT 2021 8th International Conference on Education and Education of Social Sciences

Tarhata S . Guiamalon , SITTIE ALMIRAH ALON

To give consideration of the learners in rural areas where the internet inaccessible for online learning, Modular Learning modality is currently used by all public schools in the Philippines. A modular earning is a form of distance learning that uses Self-Learning Modules (SLM) and is one of the highly convenient for most of the typical Filipino students. It was also the most preferred learning system of the majority of parents/guardians for their children. The SLM is based on the most essential learning competencies (MELCS) provided by the Department of Education. The study was conducted to determine the issues and concerns on the use of Modular Distance Learning Modality among teachers. Of the ten different public elementary schools within the district of Buluan, Dvision of Maguindanao I, It found out that teachers are well-oriented and prepared to perform their tasks and functions on modular distance learning education in times of pandemic. They also have enough trainings and skill development necessary to effectively and efficiently do their job. Parents/guardian can able to support their children in the new learning modality but some of them are hampered because of incapability of facilitating and explaining the modules provided for their children. The study shows the elementary schools have given sufficient funds and resources and it is utilized in its proper allocation. These schools were located at Buluan where strategically located in the southern tip of the Maguindanao Province of Bangsamoro Autonomous Region in Muslim Mindanao (BARMM). It is composed of seven barangays occupying a total land area of 69,950 hectares. It has a substantial share of the famous Buluan Lake.

IJMRAP Editor

During this pandemic, several schools opted for modular remote education. One of the elementary schools that selected Modular Distance Learning (MDL) as their primary mode of instruction for various reasons is Antipuluan Elementary School, a public elementary school in the Municipality of Narra, Palawan, the Philippines. However, the usage of this modality, which is unknown to many, has presented difficulties for everyone-including school staff, students, and their parents. Hence the conduct of this study. This quantitative research employed a Descriptive-Correlational Approach and involved 15 elementary teachers, 141 pupils, and 141 parents as the main data sources. A researcher-made questionnaire was used to collect data, which was then analyzed using mean, standard deviation, and Pearson product-moment correlation. The study found that the extent of Modular Distance Learning modality implementation was High, teachers', pupils', and parents' degrees of acceptance of the MDL implementation were High, and there was a strong relationship between the teachers' degree of acceptance of MDL implementation and the degree of its implementation. The perceived effects of MDL implementation have a direct relationship with the degree of their acceptance by teachers and parents.

International Journal of Multidisciplinary: Applied Business and Education Research

Erdee Cajurao

This study aimed to examine the challenges encountered by science teachers in implementing modular distance learning and the coping strategies they employed to address these challenges. Using a mixed-method research approach, data were collected through a survey of thirty-eight Junior High School science teachers in Mandaon District in Masbate, Philippines. Findings revealed that the implementation of modular distance learning presented various challenges, including technical problems, distribution and retrieval difficulties, student utilization issues, and unreliable assessment results. To cope with these challenges, teachers employed various strategies, including attending ICT training, asking for technical assistance, developing income-generating projects, and utilizing differentiated instruction and targeted assessments. The study also highlights the need for more parental involvement, adequate funding for schools, clear instructions and guidance to students, and proper monitori...

Psychology and Education

This study aimed to determine the perceptions of the Mathematics teachers and Grade 6 pupils on the modular distance learning modality and the academic performance of Grade 6 in Bagong Nayon I Elementary School SY. 2021-2022 which could serve as basis for developing an intervention program. The descriptive method of research with the survey questionnaire was used. The respondents consisted of 252 pupils and 30 teachers.It was found out that the teacher and the Grade 6 pupils' perceptions on the modular distance learning modality is evident by the grand weighted mean of 3.57 and 3.60 respectively, both are verbally interpreted as strongly agree. Likewise, there was no significant difference in the perceptions of the two groups of respondents. Moreso, the level of academic performance of Grade 6 pupils in Mathematics was satisfactory with the weighted mean of 83.50. Furthermore, there was no significant relationship between the perception of the Grade 6 pupils and the level of academic performance in Mathematics on the Modular Distance Learning Modality.An intervention program was proposed based on the results of the study.

International Journal of Research Studies in Education

jayson velasco

Psychology and Education , ROMEL LAGRIO

The education sector was greatly affected by the global health crisis of COVID-19, resulting in massive changes in our education setup , which contributed to various problems and challenges encountered during the implementation of the modular distance learning modality. This study aimed to determine the strategies and challenges encountered by teachers in implementing modular distance learning and its impact on students' academic performance. A descriptive research design was employed. The researchers utilized an online survey method for data gathering. A total of 60 teachers and 187 selected Grade 7 learners were the study's respondents utilizing total enumeration for teachers and stratified random sampling for learners.The study's findings show that teachers could employ strategies such as setting a submission schedule and creating a group chat with the learners. Moreover, establish the appropriate health and safety protocols and safety nets for learners against violence and abuse at home and in the community, and train school personnel for the Learning Delivery Modality (LMD).On the other hand, teachers professed that printing modules were time-consuming, the distance of the learner's home from the school hindered the teachers in providing technical assistance, and learners needed help following instructions. Parents answered the modules of the learners. The need for printing materials was a significant challenge.Most of the student's grades during the first quarter were within the range of 80-84, which was considered a satisfactory academic performance. Moreover, the results signified a negligible negative correlation between teachers' strategies in implementing modular distance learning and students' academic performance. The study suggests revisiting the school's plans for implementing modular distance learning and strengthening the partnership of the school, parents, and stakeholders.

International journal of research publications

Marivel De Guzman

Gary Garcia

It has been over a year now since the government put a hold on physical gatherings including physical classes due to the health crisis brought by the CoViD-19. And for more than a year of thriving against the pandemic, the government was able to open the economy and some learning institutions up gradually. There has been a lot of modification and adaptation that occurred in order to keep going amidst the crisis, which includes modifying the learning modality of the students in order to instill learning even in a new normal setting. And yet, indeed the firsts will never be easy, during the first phase of the distance learning implemented by the Department of Education (DepEd) on the 6th day of October year 2020, students, parents, and stakeholders were put into the challenge. Distance learning which in form of modular and online learning were the options given to the students nationwide in which purposely implemented to ensure the deliverance of learning despite the geographic location and financial capability of the students’ families to support their needs for the time being. With this, this investigative study has been conducted in order to know and convey the students’ response with regards to distance learning during the first phase of its implementation. Of which the participants were 50 randomly selected Senior High School Students from Agusan Del Sur and Agusan Del Norte and were residing in not so urbanized areas. The study was conducted in a form of qualitative research wherein data were gathered through both physical and online interviews as well as survey questionnaires due to the health protocols and travel restrictions implemented by IATF and which were analyzed through thematic analysis. Upon analyzing the data, it appeared that the distance learning approach is not an ideal learning modality for all. Participants were having a hard time adapting to the new learning setting being far from their peers, they find it hard to learn their lessons without the guidance of their teachers, poor network reception and lack of financial resources is a great factor for them to reach and be reached out by their teachers. Nevertheless, most of the participants choose the notion of academic freeze. Hence, researchers raised a practical aid that can be done to address the problem. In which includes weekly home visitation of teachers to their students to personally address the learning gaps of their students. Keywords: Distance Learning, Modular Learning, Online Learning

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Computer Science > Machine Learning

Title: modular deep learning.

Abstract: Transfer learning has recently become the dominant paradigm of machine learning. Pre-trained models fine-tuned for downstream tasks achieve better performance with fewer labelled examples. Nonetheless, it remains unclear how to develop models that specialise towards multiple tasks without incurring negative interference and that generalise systematically to non-identically distributed tasks. Modular deep learning has emerged as a promising solution to these challenges. In this framework, units of computation are often implemented as autonomous parameter-efficient modules. Information is conditionally routed to a subset of modules and subsequently aggregated. These properties enable positive transfer and systematic generalisation by separating computation from routing and updating modules locally. We offer a survey of modular architectures, providing a unified view over several threads of research that evolved independently in the scientific literature. Moreover, we explore various additional purposes of modularity, including scaling language models, causal inference, programme induction, and planning in reinforcement learning. Finally, we report various concrete applications where modularity has been successfully deployed such as cross-lingual and cross-modal knowledge transfer. Related talks and projects to this survey, are available at this https URL .

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