Not All Digital Innovation Is Equal: Instructional Alignment Differentiates Motivation and Instructional Expectations in Undergraduate Nursing Education

Abstract

Social media environments and meme-based communication are increasingly incorporated into nursing education, yet it remains unclear whether students respond uniformly to digitally embedded instructional strategies. This study examined whether alignment between meme-based instruction and perceived social media learning utility differentiates motivation, perceived academic impact, and demand for educator presence among undergraduate nursing students. A cross-sectional study was conducted with 458 nursing students from Spanish universities who completed a structured questionnaire assessing perceptions of meme-based instruction, social media learning utility, motivation, perceived academic impact, and expectations of educator presence. Hierarchical regression models examined interaction effects, quadrant comparisons were analysed using Kruskal–Wallis tests, and a sequential mediation model evaluated indirect pathways. Students reported high endorsement of meme-based instruction (M = 4.44, SD = 0.80) and social media learning utility (M = 4.15, SD = 0.80). However, substantial divergence emerged across alignment profiles. Students showing high alignment between meme endorsement and perceived social media utility tended to report higher motivation and different expectations of educator presence, whereas perceived academic impact was primarily explained by additive effects. These findings suggest that digital instructional innovations may not generate entirely homogeneous responses across students and that alignment between instructional format and perceived learning utility is associated with differences in motivational activation and instructional expectations in undergraduate nursing education.

1. Introduction

The expansion of digital communication environments has transformed higher education, reshaping how knowledge is produced, accessed, and interpreted. Social media platforms are no longer limited to informal interaction. They have become structured environments where information is shared, identities are constructed, and professional discussions take place. In health-related fields, these platforms influence not only how information circulates, but also how learners engage with and evaluate disciplinary content (Breland et al., 2017). In nursing education, this shift raises important pedagogical questions, as students increasingly interact with professional knowledge in digital contexts that extend beyond the traditional classroom (Embrey & Taggart, 2022).

Social media environments are characterised by multimodality, immediacy, and participatory culture. Within these environments, visual and symbolic forms of communication have become especially prominent. Internet memes are a distinctive example of this type of communication. They typically combine images, text, and culturally shared references to convey meaning through humour, irony, or contrast. Their effectiveness depends on the interaction between visual and textual elements, allowing users to quickly recognise and interpret meaning through shared cultural codes (Afridi et al., 2021; Sharma et al., 2022). In this way, memes can present complex ideas in concise and accessible formats.

The educational use of memes has received increasing attention in recent years. Experimental studies in pharmacy education have shown that structured meme-based assignments can enhance student engagement and perceived understanding when they are aligned with clear learning objectives (Brown, 2020). Similarly, in physiology education, meme-based approaches have been associated with greater participation and reinforcement of key concepts (Subbiramaaniyan et al., 2022). More broadly, research in science education suggests that memes can support the expression of disciplinary knowledge, especially when students are asked to translate theoretical ideas into visual representations (Riser et al., 2020). Together, these findings indicate that memes can act as effective learning tools when they are integrated into purposeful instructional design, rather than used as isolated or purely entertaining elements.

At the same time, the educational value of meme-based strategies cannot be understood without considering the broader social media environments in which they are used. Social media platforms shape norms related to visibility, credibility, and interaction, which influence how digital content is interpreted. In medical and nursing education, learning initiatives based on social media have been associated with increased accessibility and engagement, particularly when they are clearly linked to curricular objectives (Agrawaal & Agrawal, 2023). However, previous research also highlights variability in student responses, suggesting that digital innovation does not lead to uniform motivational or academic outcomes.

A key limitation of existing research is its focus on aggregate indicators such as satisfaction, engagement, or perceived usefulness. While these measures provide useful descriptive information, they do not fully capture how students differ in their responses to digital instructional strategies. In particular, it remains unclear whether alignment between the format of communication and students’ perceptions of its learning value influences educational outcomes. In educational research, students’ perceptions are important because they shape how learners interpret instructional experiences, assign value to learning resources, and decide how to engage with them. In digitally mediated environments, these subjective evaluations are especially relevant, as the same instructional format may be perceived as legitimate, useful, or motivating in different ways across students. This question is especially relevant in professional programmes such as nursing, where academic rigour and professional identity are central to the learning process.

In this context, the concept of instructional alignment is central to the present study. Instructional alignment refers to the degree of coherence between an instructional format and the learner’s perception of that format as a meaningful and credible learning resource. This perspective is consistent with research on technology-enhanced learning, which emphasises that educational impact depends on how digital tools are integrated into pedagogical design, rather than on the tools themselves (Kirkwood & Price, 2014). In digital environments, alignment reflects whether students perceive specific formats—such as memes or social media-based activities—not only as engaging, but also as educationally valuable. Importantly, this alignment does not depend solely on the characteristics of the tool. Instead, it emerges from the interaction between the instructional design and the learner’s evaluation of its academic relevance.

This distinction is important because social media platforms are not educationally neutral. They differ in their communication styles, interaction patterns, and perceived credibility, all of which may influence how learning content is interpreted (Greenhow & Lewin, 2016). For example, highly visual and fast-paced platforms may promote rapid engagement, but may not always be perceived as suitable for deeper learning. In contrast, other platforms may support more structured or discussion-based learning. Therefore, digital tools should not be assumed to have uniform effects on motivation or learning outcomes. Their impact is likely to depend on how students position them within their overall learning experience (Bond et al., 2020).

In the present study, instructional alignment is operationalised as the interaction between students’ endorsement of meme-based instructional formats and their perception of social media as a useful learning environment. This approach allows us to examine whether alignment between instructional format and perceived learning value is associated with differences in motivation and instructional expectations among nursing students.

Accordingly, the aim of this study is to examine whether digital instructional alignment is associated with motivation, perceived academic impact, and demand for educator presence in undergraduate nursing education.

2. Materials and Methods

2.1. Design

A cross-sectional observational study was conducted using a self-administered online questionnaire. The aim was to examine nursing students’ perceptions of meme-based and social media-based instructional formats and to test the Digital Instructional Differentiation framework.

2.2. Setting and Participants

Participants were undergraduate nursing students aged 18 years or older enrolled in Spanish universities. Students from both public and private institutions were eligible to participate.

A total of 458 students completed the questionnaire and met the inclusion criteria. A non-probabilistic snowball sampling strategy was used. The survey link was distributed via institutional email lists and social media platforms (Instagram, X, Facebook, and TikTok). Participants were also encouraged to share the survey with other eligible students. This approach was used to increase geographical diversity and sample heterogeneity.

2.3. Instrument

As no validated instrument was available to assess nursing students’ perceptions of meme-based instruction and social media as educational tools, a study-specific questionnaire was developed.

In this study, perceptions are defined as students’ subjective evaluations of digitally mediated instructional formats, including perceived usefulness, motivational value, and relevance for academic learning. These perceptions reflect how students interpret and use digital tools in their learning processes, rather than objective measures of instructional effectiveness.

The questionnaire consisted of three sections:

Sociodemographic and digital use variables (age band, gender identity, academic year, daily time spent on social media, platforms used, and preferred platforms for general and educational purposes).

Meme-based instructional format (9 items).

Social media-based instructional format (9 items).

All perceptual items were rated on a five-point Likert scale ranging from 1 (strongly disagree) to 5 (strongly agree). Composite indices derived from these items therefore also ranged from 1 to 5, with higher scores indicating stronger endorsement of the corresponding construct.

The social media section included items assessing perceived learning utility, motivation, perceived academic impact, and demand for educator presence.

Before data collection, the questionnaire was piloted with 15 nursing students who met the inclusion criteria to assess clarity and feasibility. Minor wording adjustments were made based on their feedback.

The final questionnaire was administered using Google Forms (Google LLC, Mountain View, CA, USA).

2.4. Variables

Composite indices were calculated as the mean of the corresponding items:

Meme_Index (9 items): Reflects students’ endorsement of meme-based instructional formats as meaningful and educationally relevant learning resources.

SM_Utility (excluding motivation, impact, and educator presence items): Reflects perceived usefulness of social media as a learning environment, including its role in supporting understanding, access to information, and academic engagement.

Motivation (2 items): Reflects self-reported motivational activation associated with using social media for learning.

Impact (2 items): Reflects perceived academic impact, specifically the extent to which students believe that social media contributes to their academic performance or understanding.

Demand for educator presence was analysed as a single-item outcome. In this study, this variable was interpreted as an indicator of instructional expectations, reflecting students’ expectations regarding the role of educators in digitally mediated learning environments. It captures perceived pedagogical support and guidance, rather than digital competence. This distinction allows differentiation between the use of digital tools and the perceived need for academic structure and educator involvement.

All composite variables were treated as continuous measures ranging from 1 to 5, with higher values indicating stronger endorsement.

Pedagogical mismatch was operationalised as the discrepancy between Meme_Index and SM_Utility using median splits, resulting in four instructional alignment quadrants.

2.5. Statistical Analysis

Data were analysed using SPSS version 27.0 (IBM Corp., Armonk, NY, USA).

All composite variables were treated as continuous measures derived from Likert-scale responses (range 1–5). Predictors were mean-centred for regression analyses to facilitate interpretation of interaction effects. Standardised regression coefficients (β) are reported to allow comparison of effect sizes.

Composite indices were calculated as the mean of Likert-type items. The Meme_Index included nine items, and the SM_Utility index included eight items (excluding the educator presence item). Motivation and Impact were calculated as two-item means. Demand for educator presence was measured using a single Likert item and analysed as a continuous variable, consistent with common practice in educational research with large samples.

Descriptive statistics included means and standard deviations for continuous variables. Categorical variables were summarised using frequencies and percentages.

Before inferential analyses, the factorial adequacy of the multi-item scales was assessed. Sampling adequacy was evaluated using the Kaiser–Meyer–Olkin (KMO) statistic and Bartlett’s test of sphericity. Exploratory factor analyses were conducted to examine dimensionality. Internal consistency was assessed using Cronbach’s alpha (α) and McDonald’s omega (ω).

To examine instructional alignment effects without loss of information, hierarchical linear regression models were estimated using mean-centred predictors. In Step 1, Meme_Index and SM_Utility were entered simultaneously. In Step 2, the interaction term (Meme_Index × SM_Utility) was added. Age band, academic year, gender, and daily social media use were included as covariates. Robust HC3 standard errors were applied to account for heteroscedasticity. Model fit was evaluated using R² and change in explained variance (ΔR²).

For descriptive purposes, instructional alignment was also analysed using median splits to generate four groups: High Meme–High SM, Low Meme–Low SM, High Meme–Low SM, and Low Meme–High SM. Group differences were examined using Kruskal–Wallis tests due to non-normality. Effect sizes were estimated using eta-squared (η²). Pairwise comparisons were conducted using Dunn–Bonferroni adjustments, with rank-biserial correlations reported as effect sizes.

To explore heterogeneity in response patterns, the quadrant approach was used to identify discordant profiles (e.g., high meme endorsement with low perceived social media utility, and vice versa). These profiles were analysed as meaningful deviations from general trends, allowing a more nuanced interpretation of instructional alignment. This approach is conceptually aligned with negative case analysis, as it considers patterns that do not fully conform to dominant associations.

A sequential mediation model was estimated using ordinary least squares regression with bias-corrected bootstrapping (5000 resamples). The model examined whether the relationship between SM_Utility and demand for educator presence was mediated by Motivation and Impact. Covariates included Meme_Index, age band, academic year, gender, and daily social media use. Standardised coefficients and 95% confidence intervals were reported. Indirect effects were considered significant when confidence intervals did not include zero.

Statistical significance was set at p < 0.05 (two-tailed).

2.6. Ethical Considerations

The study followed the principles of the Declaration of Helsinki.

Participation was voluntary, anonymous, and uncompensated. No identifiable or sensitive personal data were collected. Participants received an information sheet at the beginning of the survey explaining the study purpose, procedures, and data handling. Informed consent was obtained electronically through a mandatory confirmation item.

Data were processed in accordance with applicable data protection regulations, including Organic Law 3/2018 on the Protection of Personal Data and Guarantee of Digital Rights.

Given the anonymous, minimal-risk design and the absence of identifiable data or clinical intervention, formal ethical approval was not required under institutional regulations.

Potential sources of researcher bias were also considered. The research team consists of university educators with an interest in the pedagogical use of digital tools. This was acknowledged during study design and interpretation to minimise bias. The use of an anonymous online questionnaire prevented any linkage between participants and researchers.

The snowball sampling strategy across multiple universities reduced direct researcher–participant interaction and minimised potential hierarchical pressures. Although some participants may have been taught by members of the research team, no identifying data were collected and recruitment did not take place in specific classroom settings. Data collection was independent of any teaching or assessment activities, reducing the risk of coercion or social desirability bias.

3. Results

3.1. Psychometric Evaluation of Instructional Measures

Sampling adequacy indices confirmed that the data were suitable for factor analysis. For the meme-based instructional scale (9 items), the Kaiser–Meyer–Olkin (KMO) measure was 0.89, and Bartlett’s test of sphericity was significant (χ², p < 0.001), supporting factorability. Exploratory factor analysis indicated a dominant factor consistent with a unidimensional structure. Internal consistency was very high (Cronbach’s α = 0.96; McDonald’s ω = 0.96), with all corrected item–total correlations exceeding standard adequacy thresholds.

For the social media learning scale (8 items, excluding the educator presence item), sampling adequacy was also strong (KMO = 0.88; Bartlett’s p < 0.001). A dominant latent factor was identified. Reliability was high (α = 0.90; ω = 0.91), supporting the internal consistency of the scale.

Composite scores were calculated as item means and treated as continuous variables in all subsequent analyses.

3.2. Sample Characteristics and Digital Ecology

The final sample included 458 undergraduate nursing students. The most common age group was 20–24 years (68.3%), and 77.3% of participants identified as female. Students were distributed across academic years as follows: first year (17.0%), second year (35.8%), third year (31.4%), and fourth year (15.7%).

Daily use of social media was high, with 47.6% of participants reporting three or more hours per day. The sample showed widespread use of multiple platforms. WhatsApp (100%), Instagram (97.6%), and TikTok (86.5%) were used by almost all participants. Instagram (37.3%) and TikTok (31.4%) were the most frequently preferred platforms for general use. For nursing-related educational content, Instagram (47.6%) and TikTok (43.4%) were the most commonly reported.

3.3. Descriptive Statistics of Instructional and Outcome Variables

All instructional and outcome variables displayed high mean levels (Table 1), indicating broadly favourable overall perceptions:

• Meme Index: M = 4.44, SD = 0.80;
• SM_Utility: M = 4.15, SD = 0.80;
• Motivation: M = 4.32, SD = 0.77;
• Impact: M = 4.39, SD = 0.75;
• Demand for educator presence: M = 4.50, SD = 0.79.

Despite these high mean values, variability across responses was sufficient to support subsequent analyses of instructional alignment and mediation effects. This indicates that, despite generally favourable evaluations, students differed in how strongly they endorsed these instructional formats.

Table 1. Descriptive statistics for meme-based and social media instructional items.

Item	Mean	SD
Meme-based instructional format
I consider memes to be an appropriate teaching tool	4.31	0.95
Memes help me better understand nursing concepts	4.37	0.98
Memes help simplify complex nursing concepts	4.61	0.74
Memes are an effective way to review course material	4.36	1.04
I consider memes to be an innovative teaching tool in nursing education	4.53	0.84
Memes promote a more relaxed and enjoyable learning environment	4.64	0.72
Memes about nursing concepts support my learning	4.38	0.99
Viewing memes about nursing concepts increases my motivation to study	4.28	0.98
The use of memes by professors has a positive impact on my academic performance	4.48	0.94
Social media as a learning tool
I use social media to resolve doubts related to my studies	3.77	1.15
Social media provides access to a learning community for sharing knowledge and experiences	4.42	0.76
Social media increases my motivation to learn new nursing topics	4.46	0.71
I use social media to seek additional information about course content	3.89	1.28
Social media helps me stay engaged with my studies	4.17	1.00
I consider social media an innovative and effective educational tool	4.53	0.71
Social media has a positive impact on my studies	4.27	0.92
When professors share materials on social media, it helps me study	4.51	0.78
I would like professors to have a greater presence on social media	4.50	0.79

Table 1. Descriptive statistics for meme-based and social media instructional items.

Item	Mean	SD
Meme-based instructional format
I consider memes to be an appropriate teaching tool	4.31	0.95
Memes help me better understand nursing concepts	4.37	0.98
Memes help simplify complex nursing concepts	4.61	0.74
Memes are an effective way to review course material	4.36	1.04
I consider memes to be an innovative teaching tool in nursing education	4.53	0.84
Memes promote a more relaxed and enjoyable learning environment	4.64	0.72
Memes about nursing concepts support my learning	4.38	0.99
Viewing memes about nursing concepts increases my motivation to study	4.28	0.98
The use of memes by professors has a positive impact on my academic performance	4.48	0.94
Social media as a learning tool
I use social media to resolve doubts related to my studies	3.77	1.15
Social media provides access to a learning community for sharing knowledge and experiences	4.42	0.76
Social media increases my motivation to learn new nursing topics	4.46	0.71
I use social media to seek additional information about course content	3.89	1.28
Social media helps me stay engaged with my studies	4.17	1.00
I consider social media an innovative and effective educational tool	4.53	0.71
Social media has a positive impact on my studies	4.27	0.92
When professors share materials on social media, it helps me study	4.51	0.78
I would like professors to have a greater presence on social media	4.50	0.79

3.4. Continuous Interaction Models: Instructional Alignment Effects

Hierarchical regression models with mean-centred predictors and robust HC3 standard errors were estimated for each outcome, controlling for age band, academic year, gender, and daily social media use (

Table 2. Hierarchical regression models examining instructional alignment effects on motivation, impact, and demand for educator presence. (Predictors are mean-centred; robust HC3 standard errors; models adjusted for age band, academic year, gender, and daily social media use).

Predictor	Motivation β (SE)	Impact β (SE)	Demand β (SE)
Meme_Index	0.64 *** (0.04)	0.58 *** (0.04)	0.57 *** (0.08)
SM_Utility	0.40 *** (0.04)	0.55 *** (0.03)	0.35 *** (0.05)
Meme_Index × SM_Utility	0.10 ** (0.04)	−0.02 (0.03)	−0.28 *** (0.04)
R2	0.73	0.84	0.64
ΔR2 (interaction term)	0.004 **	0.000	0.032 ***

Note: β = standardised regression coefficient. Meme_Index and SM_Utility were mean-centred prior to computing the interaction term. Robust HC3 standard errors are reported in parentheses. All models were adjusted for age band, academic year, gender, and daily social media use. ΔR² represents the incremental variance explained by the addition of the interaction term. All composite variables are based on Likert-scale responses ranging from 1 (strongly disagree) to 5 (strongly agree), with higher values indicating greater endorsement of the corresponding construct. Meme_Index = endorsement of meme-based instructional format; SM_Utility = perceived usefulness of social media for learning; Motivation = self-reported motivational activation; Impact = perceived academic impact; Demand = demand for educator presence (instructional expectations). ** p < 0.01, *** p < 0.001.

).

3.4.1. Motivation

In the main-effects model, both Meme_Index and SM_Utility were positively associated with Motivation. In the full model, which included the interaction term, both predictors remained statistically significant (Meme_Index: β = 0.64, p < 0.001; SM_Utility: β = 0.40, p < 0.001).

The interaction term was also positive and significant (β = 0.10, p = 0.008), indicating that the association between meme endorsement and motivation increased slightly at higher levels of perceived social media utility.

Although the interaction effect was small, it explained a significant additional proportion of variance (ΔR² = 0.004). The full model accounted for 73% of the variance in Motivation (R² = 0.73). This suggests that students may report higher motivation when both meme-based instruction and social media are perceived as useful learning resources, although the additional effect of their alignment appears to be relatively small.

3.4.2. Impact

For perceived academic Impact, both Meme_Index (β = 0.58, p < 0.001) and SM_Utility (β = 0.55, p < 0.001) were strong positive predictors. However, the interaction term was not statistically significant (β = −0.02, p = 0.612), and its inclusion did not meaningfully increase the explained variance (ΔR² ≈ 0).

The full model explained 84% of the variance in Impact (R² = 0.84), indicating that perceived academic impact was primarily driven by the independent contributions of both instructional variables, rather than by their interaction. In practical terms, this indicates that students perceive academic impact as depending on each instructional format independently, rather than on their combined alignment.

3.4.3. Demand for Educator Presence

For Demand, both Meme_Index (β = 0.57, p < 0.001) and SM_Utility (β = 0.35, p < 0.001) were positively associated with expectations of greater educator presence. The interaction term was negative and statistically significant (β = −0.28, p < 0.001), indicating that the positive association between meme endorsement and demand for educator presence decreased at higher levels of perceived social media utility.

The interaction contributed a meaningful increase in explained variance (ΔR² = 0.032), and the final model accounted for 64% of the variance in Demand (R² = 0.64).

Across models, covariates did not substantially alter the results. This suggests that the combined influence of meme endorsement and perceived social media utility may be associated with expectations of educator presence. From an educational perspective, alignment between these variables may help explain how students interpret the need for instructional guidance in digital learning environments.

3.5. Quadrant-Based Alignment Analysis

For descriptive and comparative purposes, instructional alignment was also operationalised using median splits, resulting in four groups: High Meme–High SM (n = 144), Low Meme–Low SM (n = 124), High Meme–Low SM (n = 93), and Low Meme–High SM (n = 97).

Kruskal–Wallis tests showed statistically significant differences across groups for Motivation (H(3) = 216.70, p < 0.001, η² = 0.47), Impact (H(3) = 239.10, p < 0.001, η² = 0.52), and Demand for educator presence (H(3) = 201.17, p < 0.001, η² = 0.44), with large effect sizes.

The High Meme–High SM group consistently reported the most favourable outcomes. Pairwise comparisons between the two discordant groups (High Meme–Low SM vs. Low Meme–High SM) showed significant differences for Motivation and Impact (rank-biserial r ≈ 0.26), but not for Demand.

These findings are consistent with the continuous interaction models, although they should be interpreted with caution due to the information loss associated with median splits (

Table 3. Quadrant-based instructional alignment analysis: group differences in motivation, impact, and demand for educator presence.

Quadrant	n	Motivation (Median)	Impact (Median)	Demand (Median)
High Meme–High SM	144	4.8	4.8	4.9
Low Meme–Low SM	124	3.9	3.8	4.0
High Meme–Low SM	93	4.1	4.0	4.5
Low Meme–High SM	97	4.6	4.6	4.6
Overall group differences (Kruskal–Wallis tests)
Outcome	H(3)		p	η2
Motivation	216.70		<0.001	0.47
Impact	239.10		<0.001	0.52
Demand	201.17		<0.001	0.44
Key discordant contrast (High Meme–Low SM vs. Low Meme–High SM)
Outcome	Dunn–Bonferroni p		Rank-biserial r
Motivation	<0.001		0.26
Impact	<0.001		0.26
Demand	0.897		—

Note: Quadrants were derived using median splits of Meme_Index (endorsement of meme-based instructional format) and SM_Utility (perceived usefulness of social media for learning), generating four instructional alignment profiles. All outcome variables (Motivation, Impact, Demand) are based on Likert-scale responses ranging from 1 (strongly disagree) to 5 (strongly agree), with higher values indicating greater endorsement. Motivation = self-reported motivational activation; Impact = perceived academic impact; Demand = demand for educator presence (instructional expectations). Kruskal–Wallis tests were applied due to non-normal distributions. η² represents effect size derived from the H statistic. Pairwise comparisons were conducted using Dunn–Bonferroni correction. Rank-biserial correlation (r) reported for the primary discordant contrast. The discordant contrast compares profiles with opposing alignment patterns (High Meme–Low SM vs. Low Meme–High SM), allowing examination of divergent responses to instructional formats.

).

Taken together, these results suggest that students with similar levels of overall endorsement may interpret the educational value of digital formats in different ways. This pattern reflects meaningful differences in how students engage with these instructional approaches, rather than uniform responses across the cohort.

3.6. Sequential Mediation Model

A sequential mediation model was estimated using ordinary least squares regression with bias-corrected bootstrapping (5000 resamples). The model examined whether the association between SM_Utility and Demand for educator presence operated indirectly through Motivation and Impact, controlling for Meme_Index and demographic covariates.

SM_Utility was positively associated with Motivation (p < 0.001). Motivation was positively associated with Impact (p < 0.001), and Impact was strongly associated with Demand for educator presence (p < 0.001).

The indirect effect through Impact (SM_Utility → Impact → Demand) was statistically significant (95% CI excluding zero). The sequential indirect effect (SM_Utility → Motivation → Impact → Demand) was also significant. The direct association between SM_Utility and Demand was substantially reduced after including the mediators.

The final model explained 58% of the variance in Demand for educator presence (R² = 0.58, p < 0.001), indicating substantial explanatory power (

Table 4. Sequential mediation model predicting demand for educator presence (bootstrapped indirect effects; 5000 resamples).

Pathway	Indirect Effect (β)	95% CI
SM_Utility → Impact → Demand	0.25	[0.18, 0.32]
SM_Utility → Motivation → Impact → Demand	0.24	[0.17, 0.30]
Total indirect effect	0.33	[0.21, 0.44]
Direct effect (SM_Utility → Demand): 95% CI includes zero Final model R2 (Demand) = 0.58

Note: Indirect effects were estimated using bias-corrected bootstrapping (5000 resamples). Confidence intervals that do not include zero indicate statistical significance. The model was adjusted for Meme_Index, age band, academic year, gender, and daily social media use. Estimates were derived from ordinary least squares regression. All variables are based on Likert-scale responses ranging from 1 (strongly disagree) to 5 (strongly agree), with higher values indicating greater endorsement. SM_Utility = perceived usefulness of social media for learning; Motivation = self-reported motivational activation; Impact = perceived academic impact; Demand = demand for educator presence (instructional expectations). The model examines whether the association between perceived social media utility and demand for educator presence operates through motivational and impact-related pathways.

).

From an educational perspective, this pattern suggests that students may be more likely to expect educator involvement when they perceive that engagement with social media contributes meaningfully to their learning.

These findings suggest that students’ expectations of educator presence may be indirectly shaped by how they engage with and evaluate digital learning environments, rather than being determined solely by perceived utility.

4. Discussion

The integration of digital communication formats into nursing education has expanded the range of available teaching strategies, particularly through the use of social media and visual digital content. Recent studies have shown growing interest in meme-based activities and social media in health professions education, highlighting their potential to increase student engagement (Sarginson & Wendler, 2024). However, the educational value of these approaches needs to be examined in relation to instructional alignment and professional learning.

In this context, the present study examined how undergraduate nursing students respond to meme-based and social media-based instructional formats. Specifically, it explored patterns of alignment and divergence and their implications for motivation, perceived academic impact, and expectations of educator presence.

4.1. Structured Differentiation Within Digital Learning Environments

Digital innovation in health profession education is often evaluated using overall indicators such as satisfaction or perceived usefulness. In this study, both meme-based instruction and perceived social media utility showed high average scores. However, when the relationship between these variables was examined in more detail, clear differences between student profiles emerged.

Four alignment groups were identified, with substantial differences in motivation, perceived academic impact, and demand for educator presence. These differences were large and consistent. While group comparisons showed strong variation, regression models indicated that interaction effects were not equally important across outcomes. They were strongest for expectations of educator presence and more limited for motivation.

These findings suggest that digital instructional strategies may not produce fully uniform responses across students. Instead, students may respond differently depending on how they perceive and combine these formats.

This interpretation is consistent with previous research showing that social media blurs the boundaries between formal and informal learning (Greenhow & Lewin, 2016). In nursing education, students engage with content in environments that also include entertainment, peer interaction, and identity development. Previous studies have noted variability in how students engage with these environments (Sarginson & Wendler, 2024), although this variability has often been described at a descriptive level.

The present study extends this work by suggesting that alignment between instructional format and perceived learning value may be associated with differences in motivation and instructional expectations. However, the interaction effect was modest for motivation, and perceived academic impact was largely explained by the independent contribution of each variable.

4.2. Heterogeneity and Learner Positioning

The heterogeneity observed in this study is consistent with broader analyses of Generation Z healthcare learners, who are often characterised as digitally fluent yet diverse in their learning preferences, cognitive strategies, and expectations of instructional support (Shorey et al., 2021). Our findings suggest that digital fluency does not necessarily translate into uniform pedagogical alignment. Instead, students appear to position instructional formats within personal frameworks of credibility, relevance, and effort investment. When meme endorsement and perceived social media learning utility are aligned, motivational outcomes and expectations of educator presence follow different patterns than when they are misaligned, while perceived academic impact appears to be more strongly driven by additive rather than interaction effects. The magnitude of the Kruskal–Wallis statistics across alignment groups further indicates that these differences are substantial rather than marginal.

Previous research integrating social media into structured educational activities, such as facilitated journal clubs, has highlighted the importance of moderation and academic framing in shaping learning outcomes (Ferguson et al., 2017). The present findings extend this perspective. Demand for educator presence varied significantly across alignment profiles, suggesting that the perceived need for academic anchoring depends on how students situate digital formats within their learning context. This supports the view that educator presence in digital environments functions as an epistemic regulator, guiding interpretation and meaning-making, rather than serving only a technical or supportive role.

Taken together, these results indicate that digital learning environments in nursing education are sensitive to instructional alignment. High overall endorsement may conceal structured differences in how students respond to digital strategies. Recognising this differentiation provides a useful framework for understanding the role of memes and social media utility in shaping motivational processes and perceived academic impact within the cohort.

Importantly, these findings should not be interpreted as evidence that certain digital tools inherently possess greater educational value than others. Rather, the results suggest that the effectiveness of digitally mediated strategies depends on the degree of alignment between instructional design and students’ perceptions of the learning environment. In this sense, digital tools do not operate as inherently high- or low-impact resources. Their educational value emerges from how they are embedded within pedagogically meaningful frameworks that provide structure, relevance, and academic legitimacy.

This distinction reinforces the importance of a pedagogy-driven approach to technology use in nursing education. The use of memes or social media platforms is unlikely to produce consistent educational benefits when implemented as isolated or novelty-driven strategies. In contrast, when these tools are integrated into clearly defined learning objectives and aligned with students’ expectations of academic support, they may contribute to increased motivation and perceived academic impact. These findings therefore support an instructional design perspective in which pedagogical intent precedes and shapes the use of digital technologies, rather than being determined by them.

4.3. Memes in Higher Education Beyond Average Effects

The incorporation of memes into higher education has evolved from anecdotal experimentation to an empirically examined pedagogical practice. Recent scholarship across disciplines has shown that meme-based activities can support engagement, conceptual consolidation, and peer interaction when they are embedded within structured instructional designs. In psychology classrooms, meme-based tasks have been associated with increased participation and perceived conceptual clarity, particularly when students are required to align humour with theoretical precision (Kath et al., 2022). In professional science education contexts, including forensic and applied disciplines, meme production has been linked to enhanced student reflection on session content and improved perceived learning experiences when guided by explicit academic criteria (Tidy et al., 2024). Broader analyses of memes in education conceptualise them as multimodal artefacts capable of condensing disciplinary meaning into culturally resonant forms, thereby creating cognitively efficient entry points into complex material (Dongqiang et al., 2020).

Within digital learning environments, memes also function as participatory communicative tools. Research examining student-generated memes in online settings demonstrates that they can facilitate asynchronous discussion and collaborative meaning-making, particularly when they are integrated into structured discussion prompts rather than used as isolated humour (Lin & Sun, 2023). Similarly, studies exploring the usability of humorous and meme-based resources in virtual learning environments indicate that their perceived educational value depends on clarity of purpose, contextual relevance, and alignment with course objectives (Anton-Sancho et al., 2022). Qualitative research on students’ perceptions of memes, emojis, and GIFs in higher education further suggests that these formats can increase approachability and communicative immediacy when students recognise them as legitimate elements of instructional discourse (Hayes & Fatima, 2024). Across this body of work, a consistent pattern emerges: memes can enhance engagement and cognitive processing when they are academically grounded and perceived as purposeful.

The present findings align with this literature at the level of overall endorsement. Students reported high mean scores for meme-based instruction, with the Meme_Index reaching 4.44 and showing a distribution skewed towards higher levels of agreement. This is consistent with previous studies in which students describe meme-based activities as stimulating and useful for recall and conceptual reinforcement (Kath et al., 2022; Tidy et al., 2024). However, the main contribution of the present study lies in moving beyond mean-level evaluation to examine how meme endorsement interacts with broader perceptions of digital learning utility.

When meme endorsement was analysed together with perceived social media learning utility, the sample separated into four alignment profiles, each with substantial representation. Large between-group differences were observed for motivation and perceived academic impact. Notably, discordant groups showed significant differences, with the Low Meme–High SM profile reporting stronger motivational and impact outcomes than the High Meme–Low SM profile. These findings suggest that favourable attitudes towards memes alone are not sufficient to explain educational impact. Instead, the instructional role of memes appears to depend on how students perceive digital platforms as credible environments for learning.

This interpretation is consistent with research on digital communicative legitimacy. Studies examining identity and digital expression in teacher education contexts show that memes operate within shared cultural codes, and their pedagogical effectiveness depends on whether these codes are recognised as compatible with institutional knowledge practices (Vázquez-Calvo et al., 2025). Similarly, research on social media in nursing education emphasises that digital tools become educationally effective when they are integrated into coherent pedagogical frameworks, rather than introduced as isolated or novelty-driven elements (Sarginson & Wendler, 2024). From this perspective, meme-based pedagogy operates within a broader framework of perceived academic legitimacy.

The alignment-sensitive pattern observed in our data was most pronounced for expectations of educator presence and more modest, although still statistically significant, for motivational outcomes. In contrast, perceived academic impact was largely explained by the independent contributions of meme endorsement and perceived social media utility. Existing empirical research supports the role of memes as tools for engagement and conceptual articulation across disciplines (Dongqiang et al., 2020; Kath et al., 2022; Tidy et al., 2024). The present findings extend this literature by demonstrating that the impact of meme-based instruction depends on students’ simultaneous evaluation of social media as a meaningful learning environment. In nursing education, where epistemic standards and professional responsibility are central, this alignment appears particularly important. Meme-based strategies may be most effective in enhancing motivation and perceived impact when they are embedded within digital environments that students already perceive as academically legitimate.

4.4. Social Media Utility and Motivational Pathways

The sequential mediation analysis provides a structured explanation of how perceived social media learning utility translates into educational demand within the cohort. In the adjusted model, perceived social media utility showed a strong positive association with motivation (β = 0.71). Motivation, in turn, was significantly associated with perceived academic impact, and perceived academic impact was strongly associated with demand for educator presence (β = 0.76). The magnitude of these associations is consistent with the high proportion of explained variance observed for perceived academic impact in the regression models. Once perceived academic impact was included, the direct path from social media utility to educator presence was reduced and no longer statistically significant. Bootstrapped indirect effects were robust, and confidence intervals did not include zero for the mediated pathways. Taken together, these results support an indirect association between perceived social media utility and instructional expectations, operating through motivational activation and perceived academic value.

This pathway is consistent with literature that conceptualises social media as a learning environment whose educational contribution depends on perceived relevance and structured engagement. Reviews of social media use in nursing education describe improved interaction and perceived accessibility when platforms are integrated with explicit academic objectives and supported by instructional moderation (Sarginson & Wendler, 2024). Similarly, applied studies in medical and nursing education have shown that platform-based instruction can enhance perceived understanding and engagement when it is directly linked to disciplinary content and guided learning tasks (Vicdan, 2020; Agrawaal & Agrawal, 2023). Although these studies report increases in satisfaction and engagement, they rarely examine the mechanisms through which perceived platform utility translates into sustained academic expectations. The present mediation findings provide empirical clarification of this process.

Research on online interaction tools further supports the importance of structured participation for motivational activation. Studies of video-anchored commenting systems in asynchronous learning environments show that when students perceive digital interaction as clearly connected to learning tasks, both interaction frequency and perceived engagement increase (Lin et al., 2023). This aligns with the strong association observed in our data between perceived social media utility and motivation. When students interpret digital platforms as academically meaningful, motivational activation appears to increase. This activation is then associated with higher perceived academic impact, which in turn shapes demand for educator presence.

Importantly, the reduction in the direct effect after accounting for perceived academic impact suggests that students’ expectations of educator involvement are not driven by platform exposure alone. Rather, educator presence becomes more relevant when students perceive that digital engagement leads to tangible academic benefits. This is consistent with findings from social media-facilitated learning initiatives in nursing education, where structured moderation and alignment with evidence-based practice enhance perceived value (Ferguson et al., 2017). It also aligns with broader research on social media and health information use, which shows that engagement is shaped more by perceived credibility and usefulness than by platform characteristics alone (Carton Erlandsson et al., 2024).

Within nursing education, where clinical reasoning and patient safety are central, perceived academic impact is particularly important. Motivation without a sense of learning gain is unlikely to sustain long-term engagement. The mediation structure observed in this study suggests that digital strategies are most likely to generate meaningful instructional demand when students experience them as academically productive. In this sense, perceived social media utility acts as an upstream variable that activates motivation, which then contributes to perceived academic impact and shapes expectations of instructional support.

These findings extend descriptive accounts of digital engagement by providing a pathway-based explanation. Rather than treating motivation and perceived impact as parallel outcomes of digital exposure, the model indicates a structured relationship in which perceived utility precedes motivational activation, and perceived academic impact mediates the link between engagement and instructional expectations. This alignment-sensitive pathway complements the quadrant-based findings and reinforces the interpretation that digital instructional formats operate within structured motivational systems, rather than functioning as universally effective tools.

4.5. Digital Language and Communicative Legitimacy

Digital pedagogical formats do not enter nursing education as neutral vehicles. They carry communicative codes, cultural associations, and implicit hierarchies of seriousness and informality. Memes, in particular, operate through compression, intertextuality, and visual shorthand, requiring shared cultural literacy for effective interpretation. Their didactic value therefore depends on whether this semiotic form is perceived as compatible with disciplinary rigour.

Recent work examining the didactic use of humorous and graphic meme-based resources in higher education indicates that students’ evaluations are shaped less by the presence of humour itself and more by perceived conceptual coherence and instructional intentionality (Nieto-Sobrino et al., 2022). When humour is integrated into structured pedagogical objectives, students are more likely to perceive it as cognitively supportive rather than distracting. Similarly, pedagogical approaches that explicitly frame memes as analytical tools, rather than as entertainment artefacts, show stronger academic uptake (Byosiere et al., 2021). In these contexts, the meme functions as a cognitive scaffold that supports abstraction and synthesis.

The present findings are consistent with this legitimacy-based interpretation. Although overall endorsement of meme-based instruction was high, the alignment analysis revealed substantial differentiation when meme endorsement was considered alongside perceived social media learning utility. This suggests that cultural familiarity with memes does not guarantee epistemic integration. Students appear to distinguish between communicative fluency and academic authority. When digital environments are perceived as credible learning spaces, meme-based strategies are more likely to be interpreted as pedagogically meaningful. When this broader sense of legitimacy is weaker, meme endorsement does not translate into comparable levels of motivation or perceived academic impact.

Evidence from educational implementations that incorporate meme-based activities to stimulate disciplinary reasoning further supports this interpretation. Studies exploring the “joy of learning” through internet memes report higher levels of engagement when students actively construct memes that demonstrate conceptual understanding, rather than passively consume them (Reddy et al., 2020). This shift from consumption to production reframes the meme from a cultural artefact into a representational task that requires synthesis. This transition appears to be central to its academic legitimacy.

In professional programmes such as nursing, where epistemic standards are closely linked to patient safety and ethical accountability, communicative legitimacy may act as a filtering mechanism. Students may engage with meme-based formats at a surface level while reserving deeper cognitive investment for formats perceived as more closely aligned with professional competence. Research on students’ experiences of teaching and learning during recent disruptions in higher education shows that credibility, clarity of expectations, and perceived academic seriousness strongly influence engagement decisions in digital contexts (Kim et al., 2024). These findings highlight the importance of instructional framing and integration.

The differentiation observed in the present study suggests that meme-based pedagogy achieves its strongest educational value when it is embedded within digitally legitimate instructional environments. Cultural resonance alone is not sufficient. Academic anchoring, alignment with assessment, and clear connections to learning outcomes influence whether digital language is interpreted as pedagogically valid. Understanding this dynamic helps explain why high overall approval of memes can coexist with substantial variability in motivation and perceived impact across students.

4.6. Implications for Nursing Education Practice

The findings suggest that digitally mediated strategies in nursing education should be designed with explicit attention to alignment heterogeneity, rather than relying solely on aggregate satisfaction measures. High levels of endorsement of meme-based instruction do not necessarily translate into uniform motivational or academic outcomes. Early identification of students’ perceived digital learning utility may therefore help educators anticipate differentiated responses and adapt instructional scaffolding accordingly.

The mediation model indicates that perceived social media utility influences instructional expectations primarily through motivation and perceived academic impact. This suggests that digital tools require explicit integration with disciplinary objectives. Meme-based activities are likely to be more educationally effective when they are anchored in conceptual precision, clinical reasoning, and assessment criteria. Cultural familiarity alone appears insufficient to sustain meaningful academic impact.

Educator presence also emerges as a structurally important factor. Demand for instructional guidance was closely associated with perceived academic impact, suggesting that digital strategies should be clearly framed, actively moderated, and academically legitimised. In nursing curricula, where epistemic rigour underpins professional formation, digital formats benefit from transparent alignment with evidence-based standards.

Finally, the quadrant differentiation observed in the cohort indicates that reliance on a single communicative modality may privilege certain learner profiles. More diversified instructional ecosystems, combining concise visual representation, structured discussion, and academically grounded reflection, may help distribute motivational engagement more equitably across students.

5. Limitations and Future Research

This study has limitations that should be acknowledged. The cross-sectional design limits causal inference, particularly regarding the sequential mediation model. Although the pathway structure demonstrated statistical consistency across bootstrapped estimates, longitudinal or experimental designs are needed to confirm temporal directionality and stability of alignment profiles over time.

The use of non-probabilistic sampling may constrain generalisability beyond the participating institutions. Replication in other nursing programmes and in different cultural contexts would strengthen external validity and clarify whether alignment-sensitive patterns are context-dependent.

All variables were self-reported. While internal consistency was high and analytical procedures were rigorous, future research should incorporate objective academic or performance-based indicators to triangulate perceptual findings. The high proportion of explained variance observed for perceived academic impact may partly reflect conceptual proximity between impact-related items and instructional perception indices. Although predictors were modelled as distinct constructs, future research should examine alignment effects using fully independent outcome indicators to further reduce potential construct overlap.

In addition, the study did not explicitly assess digital access conditions or potential equity-related factors, such as variability in internet connectivity, device availability, or learning environments. Although the high levels of social media use observed in the sample suggest relatively widespread digital access, differences in access conditions cannot be fully excluded and may have influenced students’ perceptions of digitally mediated instructional strategies. Future research should incorporate more detailed measures of digital access and equity to further examine how structural factors shape engagement with digital learning tools.

Pedagogical mismatch was operationalised using median splits. Alternative person-centred approaches, such as latent profile analysis, may offer more refined classification of digital alignment structures.

Future studies should test instructional interventions explicitly designed according to Digital Instructional Differentiation principles. Experimental comparison between alignment-responsive and uniform digital strategies would determine whether recognising structured heterogeneity improves motivational activation and perceived academic impact in nursing education.

6. Conclusions

This study examined whether digital instructional alignment is associated with motivation, perceived academic impact, and demand for educator presence in undergraduate nursing education. The findings suggest that alignment between meme-based instructional formats and perceived social media learning utility is differentially related to these outcomes.

Interaction effects were outcome-specific. Alignment showed a modest but statistically significant association with motivational activation and a more pronounced association with expectations of educator presence, while perceived academic impact was largely explained by the additive contributions of both instructional perceptions rather than by their interaction.

Despite high overall endorsement of digital instructional formats, learner responses were not fully homogeneous. The observed alignment profiles indicate that students may interpret and engage with digitally mediated instruction in different ways, particularly in relation to motivation and expectations of instructional guidance.

Sequential modelling was statistically consistent with a pathway in which perceived social media utility is associated with motivation and perceived academic impact, which in turn are related to demand for educator presence. However, given the cross-sectional and perceptual nature of the data, these relationships should be interpreted as associative rather than causal.

Overall, the findings suggest that the educational relevance of digital instructional formats may depend not only on the tools themselves but also on how students perceive their pedagogical value and legitimacy within the learning environment. These results support the importance of aligning digital strategies with students’ expectations and perceptions when integrating social media and culturally embedded formats into nursing education.