The Influence of Engagement in Value Co-Creation on E-Learning Experience and Student Satisfaction: An Empirical Study

The concept of value originates from the business marketing literature; however, it has been successfully applied to the HE sector (Bowden & D’Alessandro, 2011; Diaz-Mendez & Gummeson, 2012; Dollinger et al., 2018). Value has been long studied in various contexts; thus, the concept is diversely understood. In this paper, we adopt a definition of value nested in the service-dominant logic (Vargo & Lusch, 2008), which states that the value is an improvement in system well-being that results from interactions among actors and application of resources (Vargo et al., 2008). Value is phenomenological, multidimensional, emergent and always co-created (Vargo et al., 2017). Additionally, the process of value co-creation is defined as ‘joint collaborative activities by parties involved in direct interactions, aiming to contribute to the value that emerges for one or both parties’ (Grönroos, 2012, p. 1520).

In the HE context, the above characteristics of value and value co-creation are of particular importance as they entail a shift from a traditional approach of ‘marketing to consumers’ towards a ‘marketing with stakeholders’ (Vargo & Lusch, 2008). First, there are many actors participating in the process of value co-creation, not limited to examples such as students, lecturers, administrative staff, and officials, but also encompassing external stakeholders, such as government, companies and parents. However, the core relationship occurs between the student and the lecturer (Diaz-Mendez & Gummeson, 2012), and this perspective is adopted in this paper. Moreover, value is constantly negotiated between the participants of the process, who bring their own operant resources and use the platform of products and services offered by the HE institutions (Prahalad & Ramaswamy, 2004) that include study programmes, learning experiences, examinations and more. Finally, co-creation experiences are subjective, unique to each participant and affected by cognitive, affective, temporal and contextual influences (Akaka et al., 2015). That includes the influence of other participants and situational factors.

Researchers so far have focussed on various aspects of value and its co-creation. While some of them focus on a narrow understanding of value such as the perceived value of HE (Lai et al., 2012), others investigate value from a co-creation perspective (Bowden & D’Alessandro, 2011; Diaz-Mendez & Gummeson, 2012; Smorvik & Vespestad, 2020). Student engagement is a particularly important factor contributing to the co-creation of the value of educational experience (Maxwell-Stuart et al., 2018). It is defined as ‘the extent of involvement in a range of educationally purposeful in-class and out-of-class activities’ (Dean et al., 2016, p. 327), and it refers to the amount of psychological and physical energy students spend on their university experiences (Clynes et al., 2020). There are various indicators of student engagement: cognitive (e.g. entering deeply into learning on their own), affective (e.g. being interested), conative (giving energy and time) and relational (Dunne & Derfel, 2013). Academic engagement is considered a good predictor of personal development and learning outcomes, and it is related to general satisfaction with college (Zhao & Kuh, 2004). Moreover, actor engagement is considered a microfoundation of the value co-creation experience (Storbacka et al., 2016).

There have also been attempts to understand value co-creation process in HE from an empirical perspective (Dollinger et al., 2018). Two research approaches are present in the literature: one is based on Yi and Gong’s (2013) proposal combining participation and citizenship behaviour (Elsharnouby, 2015), while the other is based on the Ranjan and Read (2016) model combining co-production and value in use as key components of the value co-creation process (Authors, 2018; Dollinger et al., 2018). In this paper, we use the latter of these, with the following components of the value co-creation process: dialogue and access to information as evidence of co-production, involvement, intellectual stimulation and relational aspect as elements of engagement in value in use creation. This model fits the HE context well and incorporates key processes relevant to online learning experience.

The quality of teaching has become a focal aspect for many HE institutions (Yang et al., 2018) as they have been under scrutiny from both consumers and governmental bodies. Quality teaching enables students to engage in quality learning (Byrne & Flood, 2003; Yin et al., 2014), and it is an important determinant of learning experience and outcomes (Prieto-Rodriguez et al., 2016). Due to its strategic importance, many HE institutions have implemented policies and instruments designed to assure the desired quality of teaching and learning (Yin et al., 2014).

Studies conducted so far have proven that students are able to evaluate various aspects of teaching quality in a multidimensional and reliable manner (Byrne & Flood, 2003). Dimensions of student experience that are studied include good teaching, clear goals and standards, appropriate workload and assessment, and perceived skills obtained through the course (Yin et al., 2014). Good teaching refers to teacher interaction and presentation and the quality of feedback given to students, while clear goals and standards reflect whether students are aware of what is expected of them. An appropriate workload allows an assessment of students’ perception of the reasonability of the amount of work they need to do, and an appropriate assessment focusses on the extent to which students are encouraged to understand the material rather learn by rote (Asonitou et al., 2018; Byrne & Flood, 2003).

Recently, HE institutions have placed increasing importance on student satisfaction (Grace et al., 2012), and it has been frequently pronounced within university mission statements and marketing strategies (Elliot & Shin, 2002). Satisfaction has been conceptualised in many ways; however, there are two common elements (Grace et al., 2012): it is an emotive variable emerging from an evaluative response to product and non-product performance (Tanner, 1996); and it is an outcome variable of service quality perception (Cronin et al., 2000). In HE context, course quality reflects students’ perception of all course aspects, while student satisfaction results from the evaluation of course- and non-course-related aspects. Thus, student satisfaction can be defined as a ‘student’s emotional and behavioural response to course appraisal’ (Grace et al., 2012), and it is considered a measure of the overall student experience (Gibson, 2010). Studies show that student satisfaction is linked to students’ motivation and retention (Elliot & Shin, 2002), persistence (Allen & Seaman, 2011; Gibson, 2010), self-confidence (Letcher & Neves, 2010), word-of-mouth communication and willingness to donate to the university as alumni (Parahoo et al., 2013).

Over that last decade, many HE institutions have accepted online courses as a legitimate component of their programmes in response to a growing student demand for online learning (Parker et al., 2011). This trend has become progressively more popular due to an increased access to the Internet (Bates, 2019), and the convenience and flexibility typically associated with participation in online courses (Croxton, 2014), as well as a growing need for lifelong learning among the population (Parahoo et al., 2016). However, despite the growing popularity of online learning, many educators question its value, rigour and overall quality (Allen & Seaman, 2011). Previous studies of online learning investigated its success and failure factors (Bolliger & Halupa, 2018) and determinants of student performance and satisfaction (Kuo et al., 2013). Research suggests that students respond positively to online courses (Judson et al., 2017) and that online learning works best when planned and combined with other forms of learning (Besser et al., 2020).

Figure 1 presents a theoretical model that is proposed and tested in this study.

Figure 1.

The study was conducted in 2021 in a large public university in Poland, with the use of an online surveying tool placed at a Moodle platform used for online teaching. The research sample comprises 532 undergraduate and graduate business students, who participated in the study for course credits. The collected surveys were checked for missing data and the right answer to the trap question placed towards the end of the questionnaire. After this step, 15 surveys were excluded from further analysis.

Of the sample, 67.3% were female and 32.4% male (Table 1), and while 69.4% of the respondents were aged under 24 years, only 5.8% were aged over 30 years; the oldest study participant was 48 years. The majority of participants were graduate students.

To measure the variables included in our theoretical model, we used validated scales adapted from the existing literature.

To measure value co-creation, we used the scale developed by Dziewanowska (2018), which is suited for the HE context. According to this model, the value co-creation consists of five factors: dialogue between student and institution, being informed about institution policy, involvement and intellectual and relational aspects of studying experience.

The e-learning experience was measured with the course experience questionnaire (CEQ), which we adapted to the online context (Ramsden, 1991; Wilson et al., 1997). The questionnaire comprises of five factors: good teaching, clear goals and standards, appropriate workload, appropriate assessment, and generic skills.

The items for satisfaction measurement were based on the study of Oliver (1980), and they reflect general satisfaction, word of mouth and intention of further participation in online courses.

PLS-SEM was employed to validate the measurement and to assess the structural model. The calculations were made with the use of SmartPLS 3.0 software (Ringle et al., 2012). The PLS method is suitable to test models that are exploratory, and does not require multivariate normal data distribution (Ringle et al., 2012). Moreover, it allows the use of 2nd-order constructs, which are present in our study. Both value co-creation and e-learning experience are conceptualised as higher order measures, composed of several 1st-order factors. The SEM procedure consists of two stages: assessment of the measurement model and interpretation of the structural model (Anderson & Gerbing, 1988).

Convergent validity of reflective 1st-order measures was assessed by the size of individual item loadings on the 2nd-order constructs (Gefen & Straub, 2005). The analysis leads to the removal of three items forming an ‘appropriate assessment’ factor from the e-learning experience scale. The loadings of these items were below 0.5. All remaining indicators have factor loadings above 0.650. We have decided to keep seven items with factor loadings between 0.650 and the threshold of 0.70, as the indicators with loadings of 0.4–0.7 should only be deleted if their exclusion from the model increases the composite reliability (CR) to more than 0.7. (Hair et al., 2017). In the case of our model, the Cronbach’s alpha, CR and average variance extracted (AVE) reached values above 0.7, which suggest that the measurement model is reliable (Fornell & Larcker, 1981) (Table 3).

As our model comprises three 2nd-order formative constructs (value co-creation, e-learning experience and stress), the item weights were calculated to confirm their convergent validity. The item weights for all 1st-order constructs were significant (Table 2). The VIF values for 2nd-order constructs are below 3.0, suggesting that multicollinearity should not be a matter of concern (Hair et al., 2017). The discriminant validity of the model was tested with square roots of AVE for each construct as well as HTMT ratio of correlations.

After confirming that our model has satisfactory reliability and validity, we have estimated the parameters of the structural model. The predictive power was estimated with R2 scores and appeared to be high, as its values are 0.304 for e-learning experience and 0.456 for satisfaction (Hair et al., 2012). To assess the significance of path coefficients, the bootstrapping technique with 5,000 subsamples was used (Henseler et al., 2009). As we hypothesised, the value co-creation positively affects e-learning experience (path coefficient = 0.551, t = 17.054, p < 0.0001), supporting H1. Moreover, the e-learning experience is significantly related to satisfaction (path coefficient = 0.676, t = 28.729, p < 0.0001), which provides empirical support for H2 (Table 4).

Our study adds to the growing body of knowledge on value co-creation and e-learning in HE institutions. The results show that students’ engagement in value co-creation was positively related to their perception of e-learning experience (H1 is supported), which is in line with previous findings (Maxwell-Stuart et al., 2018). Further, this supports the findings of Smorvik and Vespestad (2020), who showed that value co-creation can contribute to students’ perception of learning. However, most previous studies were focussed on in-class education and our study extends these results into the online context.

The significance of H2 (p < 0.0001) supports the assumption that the perception of e-learning experience influences student satisfaction. This result is in line with results of studies focussed on services (e.g. Cronin et al., 2000). Kuo et al. (2013) found that learner-instructor interaction and learner-content interaction are predictors of student satisfaction in relation to an online course. This is also supported in our study, as certain sub-dimensions of e-learning experience (i.e. good teaching, appropriate workload, clear goals, and standards) refer to similar matters. The results of our study reinforce the findings of Besser et al. (2020) that student satisfaction with online learning is higher when it is planned and combined with other forms of learning. The general perception of e-learning experience and student satisfaction were rather low in our study, which is also in line with the findings of Bowden and D’Allessandro (2011), who claim that it is the pedagogy, and not the technology, that matters most in classrooms, and further emphasises the need for reflection upon the learning process. These findings emphasise the importance of active participation in various practices performed by actors in the HE ecosystem (Diaz-Mendez & Gummeson, 2012) and confirm the influence of the engagement in value co-creation on student satisfaction in line with the study of Dollinger et al. (2018).