In the open and distance learning (ODL) system, widely scattered learners across various age groups often feel isolated. New-age media-enabled co-creation can help reduce this isolation. However, fostering collaborative academic engagement to break this isolation presents challenges for ODL institutions. Therefore, understanding the perceptions of the ODL teachers and learners on this issue is essential.
The study adopted the triangulation method, collecting primary data from 198 learners at Krishna Kanta Handiqui State Open University (KKHSOU). A focus group discussion with members of the academic staff provided qualitative insights. The instrument consisted of 23 statement items and was statistically analyzed using factor analysis, one-way ANOVA and Tukey post-hoc tests with SPSS version 26.0.
Collaborative academic engagements were found to be significantly influenced by differences in the perceptions of learners across age groups towards the academic delivery process and new-age media platforms. Various dimensions like learner genuineness and effectiveness of support services also have implications for reducing isolation.
This study opens new avenues in the literature on co-creation and new-age media platforms in the context of ODL. This provides useful insights to educators on breaking isolation among the learners and involves them in the academic processes. The human approach as always will remain enduring.
Introduction
Involving learners as co-creators in academic processes has gained importance in higher education, fostering motivation and a sense of “democratic citizenship” (Bovill et al., 2016; Riva et al., 2022; Ansell et al., 2023). Previous research highlights the benefits of a collaborative approach, such as enhanced engagement, motivation, meta-cognitive awareness, identity, teaching experiences, student–staff relationships and graduate attributes (Nygaard et al., 2013; Cook-Sather et al., 2014). However, some researchers argue that the reasons for involving learners in co-creation have not been adequately addressed (Zepke, 2014). Moreover, their involvement as co-creators in open and distance learning (ODL) poses challenges for educators due to isolation and limited in-person interaction. However, the Digital India program, launched on July 1, 2015, has transformed information dissemination through new digital platforms (https://csc.gov.in/digitalIndia). By 2017, 62% of the urban and 14% of the rural population in India had Internet access (Kanwar, 2017). With advancements in telecommunications, India is now considered the world’s largest connected democracy, with over 700 districts having 5G coverage (Chandrasekhar, 2023) and predictions suggest 1.6 billion Internet users by 2050 (Basuroy, 2023). This highlights the need for educators to understand new media platforms to facilitate co-creation with learners, necessitating insight into the perceptions of ODL teachers and students (Reyna et al., 2017). ODL institutions can greatly impact a country’s educational landscape by raising the gross enrollment ratio (GER) in higher education and reaching diverse age groups, thereby contributing to social progress. One such institution is Krishna Kanta Handiqui State Open University (KKHSOU), which is situated in the state of Assam, India, and offers a variety of undergraduate, postgraduate and doctoral programs. This paper aims to explore aspects of co-creation in the context of KKHSOU.
Conceptualizing co-creation – its constructs and areas
Researchers have highlighted the positive impact of feedback on teaching improvement and therefore, described current learners as co-creators and change agents in academic processes, particularly in quality assurance and course design (Werder and Otis, 2010; Delpish et al., 2010; Dunne and Zandstra, 2011; Luescher-Mamashela, 2013; Rock et al., 2015; Bovill, 2014). Learners can play significant roles in curriculum design (Cook-Sather et al., 2014; Kandiko Howson and Weller, 2016; Huxham et al., 2017) and can be involved in assessment (Deeley, 2014) and evaluation (Bovill et al., 2010). Involving learners in academic delivery fosters responsibility and shifts them from passive recipients to active contributors (Cook-Sather et al., 2014). The concept of “Design Thinking” introduced by Peter Rowe in 1987, could effectively engage learners in collaborative academic affairs (McCarthy, 2020).
Some researchers have noted that current learners' participation as co-creators in higher education is often overlooked due to teachers' reluctance to disrupt established academic processes (Mann, 2008).
University experience and co-creation
Learners' experiences with the university significantly influence their active involvement in co-creation at two levels: core and supplementary. The core level involves the student’s direct learning experience (Clemes et al., 2008), while supplementary factors include the quality of the physical environment (Parahoo et al., 2013), library facilities and technology (Mavondo et al., 2004), university layout (Ford et al., 1999), social environment (Clemes et al., 2008) and campus climate (Elliott and Healy, 2001). However, the application of these factors in ODL remains to be contextualized.
Online co-creation and the age of new media
Online platforms like Facebook, YouTube, WhatsApp and LinkedIn have transformed knowledge sharing, peer discussions and co-creation, offering alternatives to traditional sources (Hoffman et al., 1995; Cheng et al., 2011; Baima et al., 2022). Research shows that online co-creation fosters innovation in product and service development (Prahalad and Ramaswamy, 2004; Füller et al., 2009). In higher education, social media is popular among students in developing countries like Malaysia, serving as an effective online learning resource (Moorthy et al., 2019; Bukhari et al., 2020). In India, ODL learners favor platforms like Facebook and WhatsApp, finding them beneficial (Choudhury et al., 2023). Fagerstrøm and Ghinea (2013) noted increased learner engagement at a Norwegian University College through a Facebook group for various interests, enabling open discussions and value sharing. Similar findings by Stevenson et al. (2015) highlighted students in Finland, Austria and Germany co-creating educational videos, benefiting future students and academic staff. However, Internet connectivity issues in remote areas may hinder information flow on social media (Khairuddin et al., 2020).
Research questions and hypotheses
Given the mixed findings on the importance and challenges of co-creation, four research questions (RQs) have been formulated for investigation at KKHSOU. Corresponding hypotheses for RQ2, RQ3, and RQ4 have also been developed for testing. Unlike traditional face-to-face learners, ODL learners come from diverse age groups, and efforts have been made to capture their perceptions accordingly.
Do the academic staff of KKHSOU consider that current learners’ direct involvement in various academic processes will produce long-term learner-centric outcomes?
Do the current learners consider the effectiveness of academic services delivered by KKHSOU as a reason for co-creation?
There is no significant difference in the mean scores of perceptions of current learners belonging to various age groups toward co-creation concerning the effectiveness of the delivery of academic services of KKHSOU.
Do the current learners of KKHSOU consider their learning experience at KKHSOU as a reason for co-creation?
There is no significant difference in the mean scores of perceptions of current learners of KKHSOU belonging to various age groups toward their learning experience as a reason for co-creation.
How effective co-creation is on the use of new-age media among the current learners and academic staff of KKHSOU?
There is no significant difference in the mean scores of perceptions of current learners of KKHSOU belonging to various age groups toward co-creation on the use of new-age media platforms.
Methodology
The study employs triangulation – a mixed research design that incorporates both quantitative and qualitative methods – to gain deeper insights into co-creation. Since a single method may not adequately capture a phenomenon (Johnson and Onwuegbuzie, 2004; Greene, 2008), triangulation is used to address the research questions and explore the mechanisms underlying co-creation.
Quantitative study
Quantitative data were collected via a structured questionnaire shared in official WhatsApp groups among undergraduate (UG) and postgraduate (PG) learners in the disciplines of commerce and management. The programs include Bachelor of Business Administration (BBA), Bachelor of Commerce (B.Com), Master of Business Administration (MBA) and Master of Commerce (M.Com). There are 409 enrolled learners for the 2022–23 session.
An extensive review of literature on learner engagement, university experiences and online co-creation informed the development of a research instrument. Semi-formal discussions with faculty members helped finalize this instrument, which included three multiple-choice questions and 23 Likert-scale statements (Cooper et al., 2018; Beri, 2003). Google Forms were used to gather opinions from 198 learners (response rate: 48.41%) out of 409 in the disciplines of commerce and management for the 2022–23 academic year, with the majority of responses from the MBA program (139) compared to BBA (11), B.Com (30) and M.Com (18). A pilot study tested the questionnaire among 20 learners, achieving a Cronbach’s Alpha of 0.844 for reliability (Nunnally, 1975). Minor adjustments were made to some statements, and the final instrument was analyzed using Cronbach’s Alpha, descriptive statistics, factor analysis and one-way ANOVA with SPSS version 26.0.
Qualitative study
Qualitative data were collected through a Focus Group Discussion (FGD) with eight pre-selected faculty members from different schools of studies at KKHSOU. This followed the analysis of quantitative findings to gain additional insights on co-creation related to the research questions.
Findings and interpretation
Factor analysis
Factor analysis was conducted to identify key factors related to co-creation in educational services on the ODL platform amid new-age media. The KMO measure of sampling adequacy is 0.748 (above 0.5), and Bartlett’s test of Sphericity is not significant (p < 0.01), indicating the appropriateness of the analysis. Using principal component analysis, three components were extracted, as shown in Table 1.
Total variance explained
| Component | Initial eigenvalues | Extraction sums of squared loadings | Rotation sums of squared loadings | ||||||
|---|---|---|---|---|---|---|---|---|---|
| Total | % of Variance | Cumulative % | Total | % of Variance | Cumulative % | Total | % of Variance | Cumulative % | |
| 1 | 7.797 | 33.901 | 33.901 | 7.797 | 33.901 | 33.901 | 5.394 | 23.453 | 23.453 |
| 2 | 3.044 | 13.236 | 47.137 | 3.044 | 13.236 | 47.137 | 3.668 | 15.947 | 39.400 |
| 3 | 2.289 | 9.952 | 57.089 | 2.289 | 9.952 | 57.089 | 3.137 | 13.641 | 53.041 |
| Extraction method: principal component analysis | |||||||||
| Component | Initial eigenvalues | Extraction sums of squared loadings | Rotation sums of squared loadings | ||||||
|---|---|---|---|---|---|---|---|---|---|
| Total | % of Variance | Cumulative % | Total | % of Variance | Cumulative % | Total | % of Variance | Cumulative % | |
| 1 | 7.797 | 33.901 | 33.901 | 7.797 | 33.901 | 33.901 | 5.394 | 23.453 | 23.453 |
| 2 | 3.044 | 13.236 | 47.137 | 3.044 | 13.236 | 47.137 | 3.668 | 15.947 | 39.400 |
| 3 | 2.289 | 9.952 | 57.089 | 2.289 | 9.952 | 57.089 | 3.137 | 13.641 | 53.041 |
| Extraction method: principal component analysis | |||||||||
Source(s): Table by authors
The instrument contained 23 items. A rotated component matrix with Varimax rotation was performed to retain significant ones for further analysis. Following Jolliffe (1972), factors with loadings above 0.70 were retained. Insignificant statements were omitted, resulting in three extracted components: Component 1 (C1): Delivery of ODL service; Component 2 (C2): Teaching-learning approach and Component 3 (C3): Isolation. The statements are labeled as Si, i = 1, 2, 3, …, n, with findings presented in Table 2.
Rotated component matrix
| Factor Mapping | Statements (S) | C1 Delivery of ODL service | C2 Teaching-learning approach | C3 Isolation |
|---|---|---|---|---|
| S1C1 | The counseling sessions are very useful. I exchange my views with the counselors on the subject of discussion during the counseling sessions and also get my doubts cleared | 0.847 | ||
| S2C1 | I provide feedback on the counseling sessions held which are well accepted and promptly addressed by the university | 0.866 | ||
| S3C1 | My sharing of ideas and views during the counseling sessions makes me confident and I feel accepted in the academic process at the university | 0.774 | ||
| S4C1 | I am constantly guided in my project work/dissertations/assignments/field work by my teachers of the university/counsellors in my study center | 0.866 | ||
| S5C3 | I do not get proper guidance on the academic and examination-related information from the study center | 0.710 | ||
| S6C3 | The arrogant behavior of the support staff in my study center restricts me from approaching them | 0.795 | ||
| S7C1 | The self-learning materials (SLMs), video lectures and academic information on the university website provide adequate knowledge and are very effective. I do not need any personalized services from the university/study center | 0.719 | ||
| S8C3 | While pursuing the academic program at KKHSOU, many times I feel neglected and isolated | 0.819 | ||
| S9C3 | The increase in the number of WhatsApp groups/Telegram groups created by the university makes me confused. Therefore, I do not participate in these social media platforms | 0.806 | ||
| S10C2 | Being a learner of commerce and management, I feel that case-based interactive teaching-learning approaches would be more useful | 0.846 | ||
| S11C2 | Conducting Facebook Live sessions by teachers of KKHSOU will be beneficial for the learners | 0.739 | ||
| Extraction method: principal component analysis | ||||
| Rotation method: Varimax with Kaiser normalization | ||||
| Factor Mapping | Statements (S) | C1 | C2 | C3 |
|---|---|---|---|---|
| S1C1 | The counseling sessions are very useful. I exchange my views with the counselors on the subject of discussion during the counseling sessions and also get my doubts cleared | 0.847 | ||
| S2C1 | I provide feedback on the counseling sessions held which are well accepted and promptly addressed by the university | 0.866 | ||
| S3C1 | My sharing of ideas and views during the counseling sessions makes me confident and I feel accepted in the academic process at the university | 0.774 | ||
| S4C1 | I am constantly guided in my project work/dissertations/assignments/field work by my teachers of the university/counsellors in my study center | 0.866 | ||
| S5C3 | I do not get proper guidance on the academic and examination-related information from the study center | 0.710 | ||
| S6C3 | The arrogant behavior of the support staff in my study center restricts me from approaching them | 0.795 | ||
| S7C1 | The self-learning materials (SLMs), video lectures and academic information on the university website provide adequate knowledge and are very effective. I do not need any personalized services from the university/study center | 0.719 | ||
| S8C3 | While pursuing the academic program at KKHSOU, many times I feel neglected and isolated | 0.819 | ||
| S9C3 | The increase in the number of WhatsApp groups/Telegram groups created by the university makes me confused. Therefore, I do not participate in these social media platforms | 0.806 | ||
| S10C2 | Being a learner of commerce and management, I feel that case-based interactive teaching-learning approaches would be more useful | 0.846 | ||
| S11C2 | Conducting Facebook Live sessions by teachers of KKHSOU will be beneficial for the learners | 0.739 | ||
| Extraction method: principal component analysis | ||||
| Rotation method: Varimax with Kaiser normalization | ||||
Source(s): Table by authors
The rotated component matrix cannot be directly used to test the proposed hypotheses because the factor loadings are not independent of measurement units. Therefore, component scores were estimated using the Anderson–Rubin method, as shown in Table 3.
Component score coefficient matrix
| Statement item serial number | Component | ||
|---|---|---|---|
| 1 | 2 | 3 | |
| S1 | 0.188 | −0.082 | 0.011 |
| S2 | 0.188 | −0.067 | 0.034 |
| S3 | 0.184 | −0.100 | 0.020 |
| S4 | 0.207 | −0.124 | −0.009 |
| S5 | 0.064 | 0.074 | −0.011 |
| S6 | −0.026 | 0.027 | 0.215 |
| S7 | −0.009 | 0.055 | 0.251 |
| S8 | 0.009 | 0.110 | −0.037 |
| S9 | 0.001 | 0.149 | 0.072 |
| S10 | 0.160 | −0.048 | 0.077 |
| S11 | 0.004 | 0.046 | 0.259 |
| S12 | −0.083 | 0.215 | −0.008 |
| S13 | 0.071 | −0.011 | 0.259 |
| S14 | −0.092 | 0.266 | 0.048 |
| S15 | 0.083 | 0.057 | −0.061 |
| S16 | 0.057 | 0.048 | −0.128 |
| S17 | 0.045 | 0.092 | −0.033 |
| S18 | 0.012 | 0.085 | 0.080 |
| S19 | 0.104 | 0.003 | 0.039 |
| S20 | 0.007 | 0.145 | −0.021 |
| S21 | −0.092 | 0.235 | 0.016 |
| S22 | −0.084 | 0.178 | 0.045 |
| S23 | 0.080 | 0.005 | 0.165 |
| Extraction method: principal component analysis | |||
| Rotation method: Varimax with Kaiser normalization | |||
| Component scores | |||
| Statement item serial number | Component | ||
|---|---|---|---|
| 1 | 2 | 3 | |
| S1 | 0.188 | −0.082 | 0.011 |
| S2 | 0.188 | −0.067 | 0.034 |
| S3 | 0.184 | −0.100 | 0.020 |
| S4 | 0.207 | −0.124 | −0.009 |
| S5 | 0.064 | 0.074 | −0.011 |
| S6 | −0.026 | 0.027 | 0.215 |
| S7 | −0.009 | 0.055 | 0.251 |
| S8 | 0.009 | 0.110 | −0.037 |
| S9 | 0.001 | 0.149 | 0.072 |
| S10 | 0.160 | −0.048 | 0.077 |
| S11 | 0.004 | 0.046 | 0.259 |
| S12 | −0.083 | 0.215 | −0.008 |
| S13 | 0.071 | −0.011 | 0.259 |
| S14 | −0.092 | 0.266 | 0.048 |
| S15 | 0.083 | 0.057 | −0.061 |
| S16 | 0.057 | 0.048 | −0.128 |
| S17 | 0.045 | 0.092 | −0.033 |
| S18 | 0.012 | 0.085 | 0.080 |
| S19 | 0.104 | 0.003 | 0.039 |
| S20 | 0.007 | 0.145 | −0.021 |
| S21 | −0.092 | 0.235 | 0.016 |
| S22 | −0.084 | 0.178 | 0.045 |
| S23 | 0.080 | 0.005 | 0.165 |
| Extraction method: principal component analysis | |||
| Rotation method: Varimax with Kaiser normalization | |||
| Component scores | |||
Source(s): Table by authors
Based on the factor scores in Table 3, component-wise scores were calculated for each respondent. These scores were then used to test the proposed hypotheses through one-way ANOVA, with results presented in Table 4.
Results of ANOVA based on component scores
| Source of variance | Sum of squares | df | Mean square | F | Sig. | |
|---|---|---|---|---|---|---|
| A-R factor score 1 for analysis 1 | Age | 11.541 | 3 | 3.847 | 4.024 | 0.008 |
| Error | 185.459 | 194 | 0.956 | |||
| Total | 197.000 | 197 | ||||
| A-R factor score 2 for analysis 1 | Age | 2.143 | 3 | 0.714 | 0.711 | 0.546 |
| Error | 194.857 | 194 | 1.004 | |||
| Total | 197.000 | 197 | ||||
| A-R factor score 3 for analysis 1 | Age | 15.666 | 3 | 5.222 | 5.587 | 0.001 |
| Error | 181.334 | 194 | 0.935 | |||
| Total | 197.000 | 197 |
| Source of variance | Sum of squares | df | Mean square | F | Sig. | |
|---|---|---|---|---|---|---|
| A-R factor score 1 for analysis 1 | Age | 11.541 | 3 | 3.847 | 4.024 | 0.008 |
| Error | 185.459 | 194 | 0.956 | |||
| Total | 197.000 | 197 | ||||
| A-R factor score 2 for analysis 1 | Age | 2.143 | 3 | 0.714 | 0.711 | 0.546 |
| Error | 194.857 | 194 | 1.004 | |||
| Total | 197.000 | 197 | ||||
| A-R factor score 3 for analysis 1 | Age | 15.666 | 3 | 5.222 | 5.587 | 0.001 |
| Error | 181.334 | 194 | 0.935 | |||
| Total | 197.000 | 197 |
Source(s): Table by authors
Table 4 shows that the F value for co-creation and academic delivery services is 4.024, significant at p < 0.01. This indicates a significant difference in perceptions among current learners from different age groups (20–25, 26–31, 32–37, and 38+) regarding the effectiveness of KKHSOU’s academic services. Thus, the null hypothesis of no significant difference is rejected. A Tukey post-hoc test revealed significant differences between the 20–25 and 32–37 age groups for factor score 1, indicating varied opinions on co-creation in academic delivery services.
Conversely, the F value for co-creation and teaching-learning practices is 0.711, indicating no significant differences in perceptions among age groups. Therefore, the null hypothesis is not rejected, suggesting that current learners have similar views on learning practices.
For co-creation concerning the use of new-age media platforms, the F value is 5.58, significant at p < 0.01. This indicates differing opinions among age groups on this topic. The null hypothesis is rejected, and a Tukey post-hoc test showed significant differences between the 20–25 and both the 32–37 and 38+ age groups for factor score 3, indicating varied opinions on co-creation related to new-age media platforms.
The results indicate variations in the use of academic services, with isolation more pronounced among different age groups. This warrants further investigation to identify underlying reasons, which may include behavioral issues at study centers, familiarity with new-age media, the authenticity of learning efforts, media clutter and difficulties attending counseling sessions. A qualitative study was conducted to explore these aspects.
Qualitative study
In addition to the quantitative study, a qualitative study was conducted to explore influences on co-creation through a focus group discussion (FGD) with faculty members. The sample included 8 of 59 faculty members, with an average age of 40. Two were associate professors and the rest were assistant professors, all holding PhD degrees.
The 50-min discussion began with broad inquiries about co-creation and progressed to specific influencing factors. Questions were designed to elicit open-ended responses rather than simple yes/no answers. Participants were prompted to share their views on the need for co-creation and the role of new-age media, with specific questions focusing on effective media use. The following discussion questions were displayed during the session.
- (1)
How and in what areas do the ODL learners feel isolated compared to their counterparts in face 2 face (F2F)?
- (2)
How influential the new media have been in breaking the isolation and facilitating co-creation in the ODL system?
All participants unanimously agreed that co-creation enhances learner engagement and that new media plays an effective role. As the discussion continued, practical issues emerged. A manual content analysis of the FGD responses identified common patterns and grouped them into themes related to co-creation. The themes, dimensions and indicative statements are presented in Table 5.
Themes, dimensions and indicative statements from the FDG
| Theme | Dimension | Indicative statement |
|---|---|---|
| Isolation |
| Genuine learners follow the SLM and engage with videos and the digital library, avoiding isolation The University connects with learners via study centers in provincial colleges, which may cause isolation despite standardized services Study center staff behavior is unhelpful, and helpline responses are inadequate for learner queries |
| Design and delivery of programmes |
| The University website offers adequate information and resources to keep learners engaged SLMs are self-explanatory, and well-supported by YouTube videos, compensating for the lack of teachers Frequent changes in rules and dates create confusion that may hinder co-creation |
| New age media |
| Learners feel confused by receiving messages through multiple channels, hindering the purpose of co-creation Not all learners have digital devices, and connectivity issues limit their use of new-age media |
| Theme | Dimension | Indicative statement |
|---|---|---|
| Isolation | Learner genuineness Intermediation Empathy and behavior | Genuine learners follow the SLM and engage with videos and the digital library, avoiding isolation |
| Design and delivery of programmes | Website SLM Process | The University website offers adequate information and resources to keep learners engaged |
| New age media | Multiplicity and clutter Digital divide | Learners feel confused by receiving messages through multiple channels, hindering the purpose of co-creation |
Source(s): Table by authors
Conclusion
The study underscores the importance of co-creation in promoting active learner involvement at KKHSOU in India. While learner engagement yields positive outcomes, challenges related to connectivity and new-age media persist. Different age groups have varying opinions on co-creation and media use, with connectivity issues and message overload hindering full engagement. Educators play a crucial role in addressing these challenges by ensuring transparent communication and fostering consistent online engagement. Despite efforts, the digital divide remains a significant issue affecting service delivery and learner engagement. Future actions should aim to standardize services, reduce message overload and tackle behavioral and connectivity challenges to enhance co-creation and alleviate learner isolation.
The authors acknowledge Dr Joydeep Baruah, Professor in Economics, Krishna Kanta Handiqui State Open University for his valuable suggestions on the statistical tools used in the paper “Breaking the Isolation: How Influential is Co-creation in Open and Distance Learning on the Use of new media?”
Also, the authors acknowledge the teachers from different schools of studies at Krishna Kanta Handiqui State Open University for their valuable input during the focus group discussion.
References
Competing Interests
Declaration on conflict of interest: The authors declare no conflict of interest.
