Differences in Sports Learning by Digital Literacy Level Among Generation Z: An Application of the Unified Theory of Acceptance and Use of Technology (UTAUT) and Media Richness Theory (MRT)

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

This is a highly commendable piece of research with many virtues. I congratulate the authors of the manuscript for their very orderly and comprehensive presentation of the content. I found the theoretical introduction very enriching. With regard to the development of the methodological framework and the results, despite the high overall quality, I believe it would be appropriate to make some suggestions for improvement:

- First, to complement the description of the sample, it would be useful to include visual references such as descriptive graphs, population pyramids, or other options that serve to define its attributive configuration. 
- Second, it would also be useful to calculate reliability using the Omega index, which offers greater psychometric guarantees.
- Care should be taken with acronyms not described in the text; however obvious they may seem, they should all be presented and defined (not just in a list at the end, but  in the text).
- With regard to the Discussion, both the theoretical and practical parts lack the appropriate depth and richness of the theoretical Introduction. Comparisons with previous work using measurement instruments and with authors who conceptually defined the area of study should be expanded, as was done in the theoretical presentation. It is a common mistake among authors to discuss studies other than those used in the theoretical presentation. In my view, they should share many references.
- Finally, each author's contributions to the study must be clearly specified in accordance with CREDIT guidelines. The way it is presented does not provide the relevant information.

Author Response

Dear Reviewer,

Thank you for your constructive and insightful comments on our manuscript. We greatly appreciate your recognition that the methodological framework development and results demonstrate a consistently high level of quality overall. In response to your valuable suggestions for improvement, we have addressed each point systematically below.

 

Comment 1: First, to complement the description of the sample, it would be useful to include visual references such as descriptive graphs, population pyramids, or other options that serve to define its attributive configuration.

Response 1: We followed the reviewer’s suggestion and added graphical representations of the sample configuration. Instead of only presenting frequencies, line charts were included to illustrate attribute transitions across digital literacy groups, allowing readers to identify structural patterns in the sample.

 

Comment 2: Second, it would also be useful to calculate reliability using the Omega index, which offers greater psychometric guarantees.

Response 2: We appreciate this suggestion. Following the reviewer’s recommendation, McDonald’s ω coefficients were additionally calculated to provide a more robust estimate of internal consistency reliability. The ω values for all constructs exceeded the recommended threshold of .70, indicating acceptable internal consistency.

 

Comment 3: Care should be taken with acronyms not described in the text; however obvious they may seem, they should all be presented and defined (not just in a list at the end, but in the text).

Response 3: Thank you for this comment. We have carefully reviewed the manuscript based on your feedback and revised it accordingly, minimizing the use of abbreviations.

 

Comment 4: With regard to the Discussion, both the theoretical and practical parts lack the appropriate depth and richness of the theoretical Introduction. Comparisons with previous work using measurement instruments and with authors who conceptually defined the area of study should be expanded, as was done in the theoretical presentation. It is a common mistake among authors to discuss studies other than those used in the theoretical presentation. In my view, they should share many references.

Response 4: Thank you for this important comment. We agree that the initial manuscript emphasized empirical differences more strongly than theoretical integration. Accordingly, the Discussion section has been substantially revised to directly reconnect the findings with the theoretical foundations introduced earlier.

Specifically, we expanded the discussion to (1) interpret digital literacy as a conditioning mechanism within UTAUT belief formation rather than a simple antecedent variable, and (2) reinterpret Media Richness Theory by demonstrating that perceived richness emerges from the interaction between media affordances and user competence. Through these revisions, the manuscript now clarifies that the contribution is not the introduction of a new construct but the theoretical linkage between technology acceptance cognition and media experience under intra-generational competence variation.

Therefore, the paper now positions its contribution as a boundary-specification and integrative extension of UTAUT and MRT rather than a simple confirmation of existing models.

 

Comment 5: Finally, each author's contributions to the study must be clearly specified in accordance with CREDIT guidelines. The way it is presented does not provide the relevant information.

Response 5: Thank you for this comment. The Author Contributions section has been revised in accordance with the CRediT guidelines. Each author’s role is now clearly specified by contributor category to provide transparent information regarding their individual contributions.

Reviewer 2 Report

Comments and Suggestions for Authors

In the submitted manuscript "Differences in Sports Learning by Digital Literacy Level among Generation Z: An Application of the Unified Theory of Acceptance and Use of Technology (UTAUT) and Media Richness Theory (MRT)" the authors examine the role of digital literacy in technology-mediated sports learning through an empirical survey. The basic methodological steps for a quantitative cross-sectional study were followed, but there are some issues that need to be addressed:

 

L23-24: the abstract states that "A 32-item survey assessed digital literacy, four UTAUT components... and three MRT components" However, the instrument used is not explicitly identified, please specify whether it is a previously validated instrument or an author-developed tool

L26-29: authors mention that "Confirmatory factor analysis demonstrated acceptable model fit, reliability, and convergent/discriminant validity. Group comparisons showed that higher digital literacy was associated with stronger technology acceptance and richer perceptions of media characteristics" however no numerical (statistics) data supports those statements 

L34: It is highly recommended that the authors 1) include a few more keywords, and 2) ensure these keywords are MeSH terms

L301-307: please indicate wether participants signed an informed consent

L318: same question regarding the questionnaire, does it have a specific name?

L334: it would be helpful to allow for a meaningful interpretation of the  significance of the findings to add the thresholds or conventions used to interpret the magnitude of ηp²

L338: please report the obtained Cronbach's alpha coefficients perhaps in the Results section

L536: there is a "K" letter mistakenly bolded

Author Response

Dear Reviewer,

Thank you very much for your thorough review. We have diligently addressed the points raised in your comments as detailed below.

 

Comment 1: L23-24: the abstract states that "A 32-item survey assessed digital literacy, four UTAUT components... and three MRT components" However, the instrument used is not explicitly identified, please specify whether it is a previously validated instrument or an author-developed tool

Response 1: We added additional relevant prior studies and revised the manuscript to more clearly reflect implications grounded in established research.

 

Comment 2: L26-29: authors mention that "Confirmatory factor analysis demonstrated acceptable model fit, reliability, and convergent/discriminant validity. Group comparisons showed that higher digital literacy was associated with stronger technology acceptance and richer perceptions of media characteristics" however no numerical (statistics) data supports those statements

Response 2: Thank you for this comment. We have revised the Abstract (L26–29) to include the corresponding numerical results that support these statements. Specifically, we now report the CFA statistics, reliability coefficients, and convergent/discriminant validity metrics. In addition, the group-comparison results are now presented with the relevant test statistics and effect sizesthereby providing direct statistical evidence for the reported differences across digital literacy groups.

 

Comment 3: L34: It is highly recommended that the authors 1) include a few more keywords, and 2) ensure these keywords are MeSH terms

Response 3: Thank you for this helpful suggestion. We have revised and expanded the keywords accordingly, and the keyword list has been comprehensively updated to ensure alignment with MeSH terms where applicable.

 

Comment 4: L301-307: please indicate wether participants signed an informed consent

Response 4: Thank you for this comment. We have revised the manuscript to explicitly clarify the informed consent procedure for the online survey. Specifically, participants viewed an online information sheet and provided electronic informed consent by checking an “I agree to participate” box before proceeding to the questionnaire. In addition, the survey was conducted anonymously and no personally identifying information was collected.

 

Comment 5: L318: same question regarding the questionnaire, does it have a specific name?

Response 5: Thank you for this comment. We have clarified that the questionnaire does not represent a newly named instrument; rather, it is an adapted UTAUT-based scale. Specifically, we extracted and used the four core UTAUT determinants of technology acceptance (Performance Expectancy, Effort Expectancy, Social Influence, and Facilitating Conditions) and adapted the item wording to fit the sports learning media context

 

Comment 6: L334: it would be helpful to allow for a meaningful interpretation of the significance of the findings to add the thresholds or conventions used to interpret the magnitude of ηp²

Response 6: Thank you for your helpful suggestion. To interpret the effect size meaningfully, we have added Richardson's (2011) conventional benchmark value for interpreting the size of partial eta squared (ηp2).

 

Comment 7: L338: please report the obtained Cronbach's alpha coefficients perhaps in the Results section

Response 7: Thank you for this comment. We have revised the Results section to explicitly report the obtained Cronbach’s alpha coefficients.

 

Comment 8: L536: there is a "K" letter mistakenly bolded

Response 8: Thank you for your review. I have made the necessary revisions to the content.

Reviewer 3 Report

Comments and Suggestions for Authors

Thank you for the opportunity to read this article.

My concerns are:

• The paper's conceptual contribution is seen as incremental, affirming existing theories (UTAUT and Media Richness Theory) without proposing new constructs or theoretical advancements.
• Digital literacy is overly simplified, measured as a single factor, which risks overlooking its multidimensional nature and creating artificial categories that inflate group differences.
• Causal implications exceed the study's cross-sectional design, with claims of causality lacking temporal ordering and failing to account for reverse causality.
• The sample's limitations, consisting solely of Korean Generation Z university sports club members, hinder generalizability to broader populations.
• A heavy reliance on self-report measures raises concerns about common method bias, affecting the data's validity and not capturing actual behavior.
• While statistical rigor is strong, some analytic choices, such as tertile grouping and lack of control variables, obscure meaningful interpretations and nuances.
• Practical implications are criticized for being overly optimistic about resources and overlooking structural issues around digital literacy.
• Overall, the paper is methodologically sound but suffers from limited innovation, overly simplified concepts, and overreached claims.

Author Response

Dear Reviewer,

Thank you very much for your thorough and insightful review. Although our initial manuscript had shortcomings, we have diligently incorporated and revised the points you raised, as detailed below. These revisions have substantially enhanced the quality of our research, and we are deeply grateful for your valuable feedback and contributions.

 

Comment 1: The paper's conceptual contribution is seen as incremental, affirming existing theories (UTAUT and Media Richness Theory) without proposing new constructs or theoretical advancements.

Response 1: We appreciate Reviewer’s point regarding conceptual novelty. In the revised manuscript, we strengthened the conceptual contribution by clarifying that our goal is not only to reaffirm UTAUT and MRT, but to advance a boundary-condition explanation for digital sports learning. Specifically, we (a) added a dedicated “Conceptual contribution” paragraph in the Introduction to articulate digital literacy as a boundary condition that shapes both UTAUT beliefs and MRT perceptions; (b) introduced a theoretical linking paragraph before the hypotheses to develop a competence-contingent media richness argument, emphasizing that perceived richness depends on learners’ interpretive competence rather than the medium alone; and (c) expanded the Discussion to explicitly state how these results refine prior “digital native” assumptions and extend the application logic of UTAUT and MRT in skills-based, technology-mediated sports learning. These revisions clarify that the paper offers a conceptual refinement—competence-contingent richness and within-cohort heterogeneity—rather than a purely incremental replication.

Comment 2: Digital literacy is overly simplified, measured as a single factor, which risks overlooking its multidimensional nature and creating artificial categories that inflate group differences.

Response 2: Thank you for this important comment. We agree that digital literacy may be conceptualized as multidimensional. In the revised manuscript, we clarified that our digital literacy measure represents a parsimonious indicator of functional digital competence tailored to sports learning media use, rather than a comprehensive multidimensional framework (Section 4.3). We also explicitly acknowledged this measurement scope as a limitation and recommended that future research employ broader multidimensional digital literacy instruments to capture additional facets of the construct.

Comment 3: Causal implications exceed the study's cross-sectional design, with claims of causality lacking temporal ordering and failing to account for reverse causality.

Response 3: Thank you for raising this methodological concern. We revised the manuscript to ensure that interpretations do not exceed the cross-sectional design. Specifically, we replaced causal wording (e.g., “effects,” “shape,” “decisive,” “essential”) with associational language (e.g., “group differences,” “associated with,” “correlate,” “may help”), and we added a limitation statement explicitly noting the lack of temporal ordering and the possibility of reverse causality.

Comment 4: The sample's limitations, consisting solely of Korean Generation Z university sports club members, hinder generalizability to broader populations.

Response 4: Thank you for raising this important point. We have addressed this issue in the Limitations section by clearly acknowledging that the sample was restricted to Korean Generation Z university sports club members, which may constrain broader generalizability. In addition, we have clarified in the Participants/Sampling description that the primary aim of this study was to examine intra-generational (within-cohort) differences in digital literacy among Generation Z, rather than to make population-level inferences across age cohorts or cultural contexts. We hope these revisions adequately reflect the study’s scope and rationale, and we appreciate the reviewer’s understanding.

Comment 5: A heavy reliance on self-report measures raises concerns about common method bias, affecting the data's validity and not capturing actual behavior.

Response 5: Thank you for this important comment. Because the study relied on self-report measures, we additionally examined the potential influence of common method bias using a one-factor CFA diagnostic. The results showed that the single-factor model demonstrated substantially poorer fit than the hypothesized multi-factor measurement model, indicating that the observed relationships were unlikely to be explained by a single common method factor. This explanation has been added to 5.2 Scale Validity and Reliability section.

Comment 6: While statistical rigor is strong, some analytic choices, such as tertile grouping and lack of control variables, obscure meaningful interpretations and nuances.

Response 6: Thank you for this valuable observation. The tertile grouping was intentionally adopted to facilitate interpretable comparisons of intra-generational differences rather than to maximize statistical significance or estimate predictive relationships. In line with this objective, control variables were not included because the focus of the study was to compare structural tendencies within a relatively homogeneous cohort (Generation Z), rather than to construct a predictive model. To clarify this point, we added explicit justifications in the Data Analysis section and tempered the interpretation in the Discussion by emphasizing that the findings represent relative group tendencies rather than precise predictive effects. We also noted in the Limitations that future research may incorporate control variables and continuous modeling for finer-grained analysis.

Comment 7: Practical implications are criticized for being overly optimistic about resources and overlooking structural issues around digital literacy.

Response 7: We appreciate the reviewer’s insightful comment regarding the realism of the practical implications. We agree that digital literacy in sports education is shaped not only by individual capability but also by structural conditions such as device access, instructor competence, and institutional resources. Accordingly, we revised Section 6.2 to clarify that our implications are not prescriptive implementation directives but staged and scalable design principles contingent upon contextual constraints. These revisions temper the practical claims and align them with realistic educational settings.

Comment 8: Overall, the paper is methodologically sound but suffers from limited innovation, overly simplified concepts, and overreached claims.

Response 8: Thank you for the comprehensive evaluation. We clarified the contribution of the study as a contextual extension and boundary specification of UTAUT and Media Richness Theory rather than a proposal of a new theoretical framework. We also specified that digital literacy was operationalized as a functional construct appropriate for the sports learning context, thereby limiting conceptual overgeneralization. Finally, we revised the Discussion and Limitations sections to avoid causal interpretations and to frame the findings as comparative tendencies, strengthening the theoretical positioning and interpretive precision of the manuscript.

Round 2

Reviewer 3 Report

Comments and Suggestions for Authors

Thank you for the improvement. Minor issues that remain are:
1) there are still language-level issues (articles, verb tense, occasional awkward phrasing).
2) a professional English edit would further strengthen the paper—but this is now a polishing issue, not a conceptual one.