Examining Blended Learning Adoption Towards Improving Learning Performance in Institutions of Higher Education

The significance of ICT for education is increasing as the year progresses for institutions. As such digital learning platforms are being adopted such as MOOC as suggested in the literature (Cheng et al., 2017; Liu et al., 2018) to facilitate online learning by employing (e.g., Small Private Online Course (SPOCs)) to improve learning. Learning has mostly been traditionally linked with face-to-face (F2F) presence of classrooms, pen-and-paper, textbooks, physical teachers, and examinations (Anthony et al., 2022). However, ICT has rapidly transformed learning by supporting teaching using various technologies. An integration of ICT through internet-enabled tools such as Blackboard with methods such as on-campus classroom is referred to as blended learning (Bokolo Jr et al., 2020; Gaol & Hutagalung, 2020; Monk et al., 2020). Academics such as Lothridge et al. (2016) recommends that a successful delivery of BL encompasses of 80% online learning followed by 20% classroom instruction that relates to online content.

Additionally, BL moves the focus from teaching centric to learning based which support students to become more engaged in the educational process and more interested and, as a result, it improves their perseverance and commitment (Aguti et al., 2014; Sari & Karsen, 2016). Thus, in universities, colleges, and polytechnics BL integration usually involves F2F and other corresponding online learning delivery methods. Normally, students attend traditional lecturer-directed F2F classes with computer mediated tools to create a BL environment in gaining experiences and also promote learners’ learning success and engagement (Baragash & Al-Samarraie, 2018). Moreover, BL provide motivating and meaningful learning through different asynchronous and synchronous teaching strategies such as forums, social networking, live chats, webinars, blog, etc. that provides more opportunities for reflection and feedback from students (Dakduk et al., 2018; Vanslambrouck et al., 2019).

According to Baragash and Al-Samarraie (2018) BL initiatives integrated in institutions will result to different learning outcomes. However, research on the outcomes on students’ learning performance, particularly in integrating synchronous and asynchronous blended initiatives, have not been adequately researched. Thus, it is assumed that learners’ perception to accept integrating BL and its impact on their learning performance in the context of institutions of higher education has not been sufficiently investigated. Correspondingly, inadequate attention has been paid to students’ attitude and intention to accept certain BL delivery modes (Baragash & Al-Samarraie, 2018; Ghazal et al., 2018). Correspondingly, Anthony et al. (2019) maintains that online learning in BL approach should be not less than 20% nor more than 79%. Accordingly, Fig. 1 illustrates information about BL approach required to understand F2F and online components for BL integration.

Figure 1 depicts F2F and online learning activities. Online activities comprise of learning resources such as reference material, reading materials, discussion forum, simulations, wordbook, message board, web links, tutorials, quizzes, online writing tool, etc. (Anthony et al., 2019). On the other hand, physical teaching entails laboratory activities, discussions, individual/group, lectures, presentation, and assessment skill practices carried out for the teacher to investigate the educational performance of the learners.

The significance of ICT for education is increasing as the year progresses for institutions. However, student perception and support for accepting BL approaches for learning is still lacking irrespective of the increasing number of innovative approaches employed in BL environments (Ismail et al., 2018). This sub-section reviews prior studies that employed TAM and IS success model to examine BL acceptance in institutions of higher education. The selected studies are presented in Table 1.

Table 1 indicates that previous studies (Gong et al., 2004; Ozkan & Koseler, 2009; Ahmed, 2010; Tselios et al., 2011; Al-Busaidi, 2012; Hassanzadeh et al., 2012; Lin & Wang, 2012; Tahar et al., 2013; Padilla-MeléNdez et al., 2013; Isa et al., 2015; Mohammadi, 2015; Yeou, 2016; Ghazal et al., 2017, 2018; Al-Rahmi et al., 2018; Fisher et al., 2018; Ismail et al., 2018; Teo, 2019) employed TAM and/or IS success model to investigate the relationship between variables that influence students acceptance of BL. Regardless of these observations, little is still known about how these variables contributes to the improving students’ learning performance (Ghazal et al., 2018). As demands for BL approaches by institutions continue to expand, it is important to identify the influential determinants related to students’ perceptions of BL integration and BL acceptance. This is because the outcome of BL integration relies on its sustained usage and satisfaction of students. Thus, it is important to investigate the relevant determinants vital for promoting learning (Ghazal et al., 2018). Therefore, empirical evidence is required to clearly show how certain variables can contribute to improve students’ acceptance of BL. Hence, this study fills the gap in knowledge by developing a model grounded by TAM and IS success model similar to prior studies (Al-Busaidi, 2012; Ghazal et al., 2018) to develop a model to examine the determinants that influence students’ perception towards BL acceptance and BL integration as a mode of study to improve learning performance.

This sub-section aims to identify how BL approach integrated by students can be enhanced based on BL quality, information quality, and service quality derived from IS success model.

The selected institutions integrate similar BL approaches in their educational procedure (hybrid face to face and digital based learning). The BL courses in the selected institutions ranges from 30% F2F to about 70% online learning in virtual classes. Moreover, each of the selected institutions currently integrates Learning Management Systems (LMS) such as Moodle as their official e-learning platforms. Therefore, the target sample for this research included students registered in blended courses. The students were selected due to their familiarity and experience with blended settings (both face to face and digital based learning). For ethical consideration the first section of the questionnaire specifies an introduction of the research study and permission was collected from the participants to voluntary participate in the study. In this study only the needed information was collected from the participants. Moreover, no personal data was collected from the respondents that can disclose the identity of the respondents and all data was securely stored offline.

The data were gathered through an online survey questionnaire as data collection instrument via “Lime survey platform”. The questionnaire instrument was developed in English language by experts to improve the validity of the instrument to confirm the accuracy of the instrument (see Table 6 in appendix). Then the tool was deployed in real time and access to the questionnaire was mailed to respondents for pre-testing testing. Next, pre-test was implemented, and data was gathered from 59 learners to assess if the students understand the questions and test the reliability and validity of questionnaires instruments. Findings from the pre-test showed that the Cronbach’s alpha value is greater than 0.7. Later, requests to take part in the main survey, as well as access to the online questionnaire, was delivered to learners from January-March 2019. The data collection entails a cross-sectional survey of randomly selected students across higher education in Malaysia as seen in Table 2.

The main sample for this research consists of students registered in blended courses. The questionnaire included demographic question measured using ordinal measurement (see Table 6 in appendix).

The questionnaire instrument measures how BL is currently integrated by the students in their institutions based on a Likert scale (see Table 7 in appendix). Lastly, the questionnaire measures the opinion of the learners in regard to BL deployment similarly based on a Likert scale. The instrument was designed grounded on current and validated instruments from previous studies (that employed TAM and information systems success model in BL) to measure both F2F and online learning. After data was gathered 1,811 respondents were collected, but 642 samples were eliminated due to missing options amounting to a total of 1,169 usable samples. The samples related to how BL is currently integrated by the students in their institutions and assessment of the perception of the students regarding BL acceptance were not completely provided by the respondents and thus were removed to avoid bias as these items were important and these responses were included may impact the validity and reliability of the findings.

The survey data was evaluated using structural equation model-partial least square method which is a variance-based method that aids the analysis of path of latent variables in a model. Structural equation model-partial least square was employed as it is regard as a comprehensive statistical method that is suitable for compound models that consist of relationships among variables. Structural equation model-partial least square employs two primary analyses, the first is the assessment of the measurement model assessed by checking the convergent validity, reliability, and discriminant validity. Next, it involves the analysis of the hypotheses of the structural model. SmartPLS software and Statistical Package of Social Science (SPSS) was employed as the research tools that was used to code and analyze the collected data.

Validity assesses the extent to which determinants in a model varies from other determinates in the identical model (Yeou, 2016). Reliability measures the degree to which the determinants give same results that are reliable and free from error (Yeou, 2016). Convergent validity evaluates whether items can effectively reflect their analogous determinant (Mohammadi, 2015). Convergent validity entails the assessment of construct validity and reliability. The reliability of the model determinants was evaluated by considering the internal uniformity measured by assessing the Average Variance Extracted (AVE) which indicates to the amount of variance a construct describes from its elements.

The AVE must be higher than or equivalent to the score of 0.5 as suggested by Hair et al. (2016); Anthony et al. (2020). The reliability is measured based on the Construct Reliability (CR) and Cronbach’s alpha value which must be higher than 0.70 (Anthony Jr et al., 2018). The factor loadings value of each indicator is also taken into consideration, which offer support to assess convergent validity of all indicators which is expected to be greater than the threshold score of 0.50 as recommended by Al-Busaidi (2012). Table 3 shows that the model determinants’ reliability (greater than 0.7) and AVE (higher than 0.5) are above the recommended values for all variables. Besides, Table 3 also displays the standard deviations (SD) and mean of the determinants. The SD scores are near to 0 and lower than 3, suggesting that replies from the respondents are not distributed. Results from Table 3 shows the mean score based on the 5-point Likert Scale (1 to 5), response from the respondents. For mean value 1 = least important, 2 = fairly important, 3 = important, 4 = very important, and 5 = most important. Where the mean value for the Likert scale collected from the students suggest that the mean scores are higher than 2.5 as advised by Anthony Jnr (2019) which is reflected as a significant criterion to determine student acceptance of BL (Anthony Jr et al., 2018).

The discriminant validity assesses if two constructs statistically vary from each other (Mohammadi, 2015). Thus, Fornell and Larcker (1981) suggest the deployment of AVE to assess discriminant validity. To assess the discriminant validity of all determinants, Fornell and Larcker (1981) propose that the square root of AVE of each variable should be higher than the correlations shared between the variables and other variables in the model. Moreover, the value should be higher than 0.5 as suggested by Hair et al. (2016). When the average variance extracted score is higher than 0.5, it is suggested that the determinant comprises a minimum of 50% of the measured variation (Anthony Jr, 2019).

In Table 4 this study presents the discriminant validity for all determinants are specified in the designed model (see Fig. 2), to help assess if there is any Inter-determinants correlation among these determinants and if any to what extent as previously employed in prior BL studies (Al-Busaidi & Al-Shihi, 2012; Anthony et al., 2021; Dakduk et al., 2018). Thus, the results presented in Table 4 suggest that the model variables fulfill that imperative, as the square root value of the average variance extracted on the sloping is greater than the associations with other determinants and each score is greater than 0.5. Thus, all variables have a reasonable discriminant validity score greater than 0.5.

This subdivision assesses the relationships in the model in confirming the hypotheses of the model as shown in Fig. 2. The research model assessment is evaluated by checking the path coefficients (β) score which estimates the correlation among variables grounded on their degree of significance (p-value) which is substantial if p =  < 0.050 when quantified using partial least squares path modeling to measures the weights of the determinants. Moreover, the measurement of determination referred to R² score is employed to determine the predictive significance of the research model. Then, the path coefficients (t-value) are utilized to evaluate the impacts of the model hypotheses, which is linked to the associated significances and regression coefficients as shown in Table 5. A bootstrapping procedure of 5000 samples was applied to check the significance level of the model relationship paths (t-value). Also, t-value should be higher than 1.96 as mentioned by Hair et al. (2016).

Results from Fig. 3 and Table 5 depict the significance testing of the model hypotheses presented in Fig. 2. H1 states that BL integration will positively influence perceived usefulness of BL. Results from Table 5 show that H1 path coefficient is 0.262 (t = 7.009, β = 0.655, p = 0.000), therefore supporting H1 since t-value is greater than 1.96 benchmark and path coefficient is higher than 0 (Anthony Jr, 2019). Similarly, H2 states that BL integration will positively influence perceived ease of use of BL. Results from Table 5 further suggest that H2 path coefficient is 0.732 (t = 34.118, β = 0.730, p = 0.000), therefore supporting H2. Next, H3 states that perceived usefulness will positively influence students’ attitude towards using BL. Accordingly, results from Table 5 disclose that the hypothesis is significant where path coefficient is 0.292 (t = 7.591, β = 0.678, p = 0.000). Similarly, results from Table 5 reveal that perceived usefulness positively influence students’ intention to use BL (H4) with path coefficient of 0.221 (t = 7.126, β = 0.688, p = 0.000). Likewise, the results confirm H5 which suggest that perceived ease of use positively influence perceived usefulness of BL with path coefficient of 0.538 (t = 15.479, β = 0.723, p = 0.000). Furthermore, results reveal that H6 which posit that perceived ease of use positively influence students’ attitude towards using BL is statistically significant with path coefficient of 0.537 (t = 15.299, β = 0.749, p = 0.000).

Results from Table 5 further confirms H7 that perceived ease of use positively influence students’ intention to use BL with a path coefficient of 0.092 (t = 2.446, β = 0.692, p = 0.015). Next, the results support H8, students’ attitude towards using BL will positively influence their intention to use BL with path coefficient of 0.600 (t = 19.269, β = 0.812, p = 0.000). Moreover, results provide ample support for H9 confirming that students’ intention to use BL is positively influenced by their actual BL use with path coefficient of 0.242 (t = 6.961, β = 0.637, p = 0.000). The results suggest that BL integration positively influence actual BL use (H10) with path coefficient 0.566 (t = 15.747, β = 0.720, p = 0.000), hence H10 is supported. Next, for (H11) actual BL use significantly influence students’ learning performance path coefficient is given as 0.199 (t = 6.381, β = 0.718, p = 0.000) therefore H11 is supported. Finally, for (H12) BL integration positively influence students’ learning performance is also confirmed from the results with path coefficient of 0.717 (t = 26.56, β = 0.861, p = 0.000), thus H12 was also supported. Interestingly, the results suggest that (H2) “BL Integration—> Perceived Ease of Use of BL” with t-value = 34.118 is the most significant relation suggesting that the easiness of BL approaches is the most important variable that influences students to use integrate BL for academic purposes.

In addition, the literature (Baragash & Al-Samarraie, 2018), recommended that \({R}^{2}\) values of 0.67, 0.33, and 0.19 were regarded as excellent, average, and low, respectively. Likewise, Salloum et al. (2019) suggested that the \({R}^{2}\) value should be greater than 0.10 to be acceptable. Thus, results from Table 5 show that the \({R}^{2}\) values range from H1 = 0.429, H2 = 0.534, H3 = 0.460, H4 = 0.473, H5 = 0.522, H6 = 0.560, H7 = 0.479, H8 = 0.659, H9 = 0.405, H10 = 0.518, H11 = 0.515, H12 = 0.742. The result suggests that all \({R}^{2}\) values are higher than 0.1 as recommended by Salloum et al. (2019) and ranges from 0.405 for H9 and 0.742 for H12 indicating that an average to excellent \({R}^{2}\) values (Baragash & Al-Samarraie, 2018). The results empirically confirm that H12 has the strongest effect, thus BL integration impact fully improves students’ learning performance and H9 has the least strong effect highlighting that students’ intention to use BL for academic purpose effects the actual usage of BL for educational activities.

This study examines students’ perception on BL integration and acceptance towards improving learning performance in institutions of higher education. A research model was developed grounded by TAM and IS success model. Data was collected using survey instrument from students in Malaysia universities and colleges to empirically test the model and PLS-SEM was employed to analyze the survey data. The results from this study show a significant relationship between BL integration (system quality, information quality, and service quality) and perceived usefulness of BL. This result is in line with findings from prior studies (Al-Busaidi, 2012; Ozkan & Koseler, 2009). One possible explanation is that system quality is based on the student’s perception in regard to the flexibility, ease of use, interactivity, responsiveness, user-friendliness, and stability of BL approaches which determines the perceived useful of BL (Ghazal et al., 2018; Lin & Wang, 2012). Likewise, the results suggest that the quality of information provided by BL approaches enhances learning which also influence how students perceive the usefulness of BL approaches (Hassanzadeh et al., 2012). Similarly, the result is also analogous with findings from Mohammadi (2015) who revealed that the availability of miscellaneous support that assists learner in a timely manner to address problems originating from the use of BL approaches do influence students perceived usefulness of BL.

Moreover, the study confirms that BL integration (system quality, information quality, and service quality) positively influence perceived ease of use. This result is in parallel with findings from prior studies (Ghazal et al., 2017; Ozkan & Koseler, 2009) where the authors suggested that system quality positively determines system use and students’ satisfaction of BL approach. Likewise, Al-Busaidi (2012) stated that information quality plays a substantial role in the use of BL in relation to the perceived usefulness, perceived ease of use, and student intention to use BL. Additionally, the result is similar to findings from Ghazal et al. (2018) where the researchers confirmed that quality of service improves the acceptance of students to use e-learning in relation to their perceived ease of use and perceived usefulness. Also, results indicate that perceived usefulness of BL has a direct effect on students’ attitude towards using BL. This result is similar to findings from Teo (2019) where the author established that the perceived usefulness has a positive influence on student attitude and intention towards use of BL initiatives. As a consequence, the greater the perceived usefulness of BL approaches, the more significant is the students’ attitude and intention towards usage, hence greater the prospect that BL will be used (Mohammadi, 2015).

One of the interesting findings of the study is that the perceived usefulness of BL has a positive effect on students’ intention to use BL. A possible interpretation is that the perceived usefulness measures the degree to which students believe that their educational activities will be enhanced by integrating BL (Isa et al., 2015). Correspondingly, findings from previous studies (Davis, 1989; Teo, 2019) suggested that the perceived usefulness significantly determines the extent to which a student believes that using BL approaches would improve their academic efficiency. The results support the conclusion made by Al-Busaidi (2012); Yeou (2016); Ghazal et al. (2018) that perceived ease of use significantly influence perceived usefulness of BL. This result seems quite reasonable since perceived ease of use of BL relates to the degree to which the students expect that BL use will comprises of less effort or free of difficulty in learning (Ismail et al., 2018). Also, in accordance with Tselios et al. (2011); Mohammadi (2015); Teo (2019) the results suggest that the perceived ease of use has a direct effect on student attitude towards use of BL in improving educational activities. This result is also in line with findings from Ghazal et al. (2017), where the authors found that BL approaches supports the students to apprehend the easiness of BL and feels relaxed to learn via online or F2F mode.

In addition, the results indicate that the perceived ease of use has a positive effect on student intention to use BL. This result is similar to findings from prior studies (Ghazal et al., 2018; Ismail et al., 2018) which confirmed that the perceived ease of use impacts both perceived usefulness, intention to use, and attitude of students towards using BL. Another interesting observation relates to the effect of attitude towards students’ intention to use BL, where the results confirm this hypothesis. One possible explanation is that the attitude is based on the student’s experiences which may be negative or positive feelings encountered in using BL approaches. This result is similar to findings from prior studies (Ismail et al., 2018; Teo, 2019), where the results from the researchers suggested that the students’ attitude is an important factor that influences of BL usage as it entails not only the value, understanding, and knowledge of technology, but also learners’ ability to integrated BL initiatives. Hence, students who exhibit a positive attitude toward the use of BL are more likely to perceive its value and subsequently use BL for educational purposes, thus influencing BL acceptance (Ghazal et al., 2018). In this study, intention to use BL is found to be a significant variable that influences actual use of BL by students. This result is consistent with the studies undertaken by Mohammadi (2015); Al-Rahmi et al. (2018) where the authors highlighted that intention to use embodies the extent and manner in which BL is utilized by students.

Furthermore, the results suggest that the student’s intention to use BL is significantly influenced by perceived usefulness and perceived ease of use of BL. This result is also analogous with findings from Teo (2019) which suggested that students are more likely to continue using BL if their level of learning with BL and the perceived usefulness of BL are high. Similarly, students’ intention to use BL to a large extent is influenced by their current use satisfaction (Hassanzadeh et al., 2012). Likewise, this result is parallel to prior study (Al-Busaidi, 2012) which revealed that student’s continuous intention to use BL is significantly determines by its actual use. The results showed significant relationships between BL integration (system quality, information quality, and service quality) and actual BL use. This result is similar to findings from prior studies (Padilla-MeléNdez et al., 2013; Teo, 2019), which confirmed that the system quality which assesses the technical success of BL approaches should improve and facilitate learning. Also, the information quality which provides quality resources delivered through BL approach to students should also be accessible in different format and lastly service quality which requires provision of quality end users supports to students who use BL for educational purposes. Thus, the result confirms what Hassanzadeh et al. (2012) concluded in their study suggesting that the current BL approach integrated by institutions will influence student perception towards actually using BL for educational purpose.

Another notable observation is the relation between actual use and learning performance, where the results confirm this hypothesis suggesting that actual use of BL significantly influences learning performance of students. A possible interpretation is that actual use of BL is based on how interactive and intrinsically interesting BL activities are to the student who derives pleasure and enjoyment in learning (Teo, 2019). Furthermore, actual use of BL could be reflected as a part of the facilitating factor that determines the learning performance (Padilla-MeléNdez et al., 2013). Lastly, based on BL integration impact on learning performance, it is evident that system quality, information quality, and service quality are components that positively determine students learning performance in BL environment. Thus, the results confirm the hypothesis that BL integration influence learning performance.

This result is analogous with findings from previous studies (Fisher et al., 2018; Tahar et al., 2013) which revealed that BL practice integrated in universities has a direct effect on user satisfaction can also affect the success of students in improving their grades and learning performance. Thus, the quality of information, services and systems related to blended syllabus course content output presented to student and learning resources provided to students are key determinants that influences students learning performance (Lin & Wang, 2012). Accordingly, results from this study indicates that BL approaches integrated in universities and colleges should offer individual, tangible, timely, reliable, responsive, and professionally customized services, which may influence the quality of information system service and impact on students’ perceptions and acceptance of BL usefulness.

With the increased emphasizes on institutions of higher education to improve the quality of teaching and learning, BL is integrated to provide universities and colleges with the medium to store, share, and manage educational resources and knowledge. BL integration provides proficient medium to teach and train students. The success of BL integration in universities and colleges is initiated by management in the institutions, but its survival and success in future depends on the students’ acceptance and use. This study employed TAM and IS success model to develop a model that identifies how BL approach integrated by students can be enhanced and further investigate the determinants that influence student perception towards BL acceptance. Moreover, this study explores on how student learning performance can be improved in BL environment. Theoretically, this study employed TAM to provide insightful information regarding students’ behavioral patterns towards BL acceptance in universities, colleges, and polytechnics towards improving student learning performance.

Accordingly, this study offers substantial findings for BL academicians, educationalist, and practitioners, by comprehensively examining the critical determinants that influences students’ acceptance of BL. Finding from this study provides a road map for institutions to foster BL approaches to improve student acceptance and satisfaction of F2F and online learning. Overall, the findings statistically establish that BL integration contributes to improve student perceptions, attitude, and intention to use BL to improved academic performance. Given the implicit relationship between BL integration, acceptance, and learning performance these significant results and can be utilized by decision-makers and educational agencies to improve BL pedagogies. The derived associated items for perceived usefulness, perceived ease of use, attitude towards use, behavior intention to use, actual system use, and learning performance as seen in the questionnaire items provides benchmark indicators to be employed by Malaysia institutions of higher education and in other countries to assess the current BL acceptance of students in universities and colleges.

The model developed in this study is also vital to be employed in institutions of higher education as a reference tool for integrating BL initiatives in Malaysia and also has the potential implications for achieving self-directed students to suit the lifelong learning. Further implications from this study suggest that perceived usefulness and perceived ease of use have significant direct impact on students’ attitude to use BL. Moreover, student’s attitude towards BL, intention to use BL, and actual BL use were significant in determining students’ perceptions of accepting BL as a mode of study. Thus, university administration should initiate programs that increase the knowledge and awareness of learners as part of a strategy to promote the continued use of BL in order to move research and practice of deploying IT for education in universities and colleges.

This study was envisioned to provide a clearer guide on how institutions of higher education in Malaysia and beyond can achieve system quality, information quality, service quality in their current BL environment as seen in the questionnaire items. Practically, this study adopted IS success model to provide understandings into the current state of BL integration to enhance students learning performance. In addition, institutions integrating BL should improve the quality of deployed system, quality of information, and support services provided. The results suggest that students play a key role on BL integration, thus students should show positive attitude toward BL. Moreover, institutional administration needs to ensure that students are trained well and have good awareness regarding their perception towards the ease and usefulness of BL, because if students consider BL to be difficult to use they may become unwilling to use it, consequently undermining the potential of IT integration to improve learning performance in universities, colleges, and polytechnics. Likewise, institutional administration should constantly improve the quality of BL and ensure its reliability, capability, richness, flexibility, interactivity, and speed towards improving learning activities.

Findings from the study also suggest that the success of BL integration positively influences students’ intention to continuously use BL. Therefore, once students use BL and they perceive it to be useful and easy, and accept it, they will continue to use it. Hence, students’ actual use of BL is an important component for its survival and attainment of improved learning conditions. Furthermore, in order to increase students’ overall acceptance of BL, current approach should be improved to effect changes in the perceived usefulness of BL. Moreover, lecturers should show how BL would improve learning and improve students’ knowledge. To do so, specific care should be carried out to provide user-friendly, up-to-date, and useful blended course content. Respectively, the results suggest that system quality, information quality, and service quality of BL approach integrated actually contribute to students’ positive experience and acceptance of BL. Hence, it is required that the quality of blended services need to be deployed with interactive ICT applications, which may contribute to the improvement of the learning quality, thus resulting to students having a positive perception towards BL acceptance.