Mobile application-based teaching tools in animal science education: Educator willingness and perceived usefulness

Introduction

A 2021 survey across 42 universities in the Philippines found that only 29.4% of animal science faculty members had incorporated mobile applications into their regular teaching activities, despite 87.1% of those same institutions reporting institutional-level subscriptions to at least one mobile learning platform [1] . This gap between institutional provision and individual adoption raises questions about the factors that encourage or hinder educators from using mobile-based tools in a discipline that relies heavily on practical demonstrations, field observations, and laboratory work [2] . Animal science education covers a broad range of topics from feed formulation and breeding genetics to livestock health management and poultry production each carrying its own mix of theoretical content and hands-on skill requirements [3] . Mobile applications can support this mix by delivering video demonstrations of surgical procedures, interactive anatomy modules, virtual farm walkthroughs, and quiz-based formative assessments that students can access outside scheduled class hours [4] . Yet the literature on mobile learning in agriculture-related disciplines has focused predominantly on crop science and extension services, leaving anima science programmes comparatively under-explored [5] . The Technology Acceptance Model continues to ofer a practical framework for investigating why educators choose to adopt or resist new instructional technologies [6] . Its two central constructs perceived usefulness and perceived ease of use have been tested across educational setings ranging from primary schools to postgraduate programmes, with perceived usefulness consistently emerging as the stronger predictor of behavioural intention [7] . In animal science contexts, however, perceived usefulness may carry additional weight because the discipline's practical orientation means that educators are particularly sensitive to whether a digital tool can replicate or supplement the experiential learning that characterises their courses [3] . Willingness to adopt, as distinct from actual adoption, captures the atitudinal readiness of an educator to incorporate a technology into their practice should conditions permit [8] . This distinction maters because many animal science departments in developing countries have introduced mobile platforms during emergency remote instruction periods without first assessing whether faculty members were psychologically prepared to use them beyond the crisis window [9] . Willingness serves as a precursor to sustained adoption and ofers a more sensitive measure than binary usage data when the goal is to identify which subgroups of educators need the most support [10] . Several demographic and professional variables have been examined as potential moderators of technology acceptance among educators. Teaching experience is among the most frequently studied, with longer-serving educators generally reporting lower willingness and weaker perceived usefulness compared to their younger counterparts [11] . Gender efects are less consistent some research reports that male educators rate usefulness higher, while others find no significant diference once experience and training exposure are controlled [12] . Departmental afiliation, though rarely examined, may shape acceptance through disciplinespecific norms around what constitutes appropriate pedagogy [13] . For example, educators in animal nutrition may view formula-driven mobile calculators as directly relevant, whereas those in animal behaviour may see fewer obvious applications [3] . Institutional factors also play a part. Access to stable internet connectivity, availability of technical support staf, and the presence of formal training programmes on mobile tool integration have all been linked to higher acceptance scores in comparable educational technology research [14] . In the Philippine higher education context, where connectivity varies sharply between metro and provincial campuses, these infrastructure-related variables can either amplify or dampen the influence of individual-level beliefs on adoption behaviour [1] . Against this background, the present research aimed to assess the willingness and perceived usefulness of mobile applicationbased teaching tools among animal science educators in Quezon City, Philippines. It further sought to identify the demographic and professional predictors of willingness and to map the feature-level usefulness perceptions across diferent experience cohorts. By concentrating on animal science a discipline that balances lecturebased instruction with laboratory and field work the research addressed a gap in the mobile learning literature and ofered evidence-based recommendations for institutional strategies that support educator adoption of mobile teaching platforms.

Theoretical Framework

The Technology Acceptance Model, originally proposed by Davis [6] , provided the theoretical backbone for this investigation. TAM holds that an individual's decision to adopt a technology is primarily shaped by two perceptual constructs: perceived usefulness the belief that the system will improve task performance and perceived ease of use the belief that operating the system will be free of excessive efort. Both constructs influence atitude, which in turn drives behavioural intention and, ultimately, actual usage. For this research, TAM was extended to include willingness as a construct positioned between atitude and behavioural intention. Willingness captures an educator's atitudinal readiness to adopt mobile tools under supportive conditions, even if current infrastructure or institutional mandates have not yet prompted actual use [8] . The model also incorporated three moderating variables teaching experience, gender, and departmental afiliation informed by prior work on technology adoption in agricultural higher education [5,11] . This adapted framework guided the questionnaire design and the hierarchical regression analysis employed in the research.

Materials and Methods

Materials

This research was conducted across four colleges ofering animal science programmes under Quezon Metropolitan University in Quezon City, Philippines. The four colleges were chosen because each had distributed at least one mobile teaching application (Google Classroom, Edmodo, or a custom departmental app) to faculty members within the preceding three academic semesters. Through proportionate stratified random sampling stratifying by college and by years of teaching experience a sample of 230 educators was drawn. After removing incomplete submissions, 214 valid responses were retained (response rate: 93.0%). Ethical approval was secured from the Quezon Metropolitan University Institutional Review Board. Writen informed consent was collected from each participant prior to questionnaire administration.

Methods

A structured self-administered questionnaire with four sections was used for data collection. Section A gathered demographic and professional information: gender, age range, years of teaching experience, departmental afiliation, and prior mobile technology training. Sections B through D measured perceived usefulness (9 items), perceived ease of use (7 items), and willingness to adopt mobile teaching tools (6 items) on a fivepoint Likert scale (1 = strongly disagree to 5 = strongly agree). A fifth section captured current usage paterns through five binary and frequency-based items. Items were adapted from instruments validated in educational technology research [6,7,14] .

Instrument Development and Validation

The questionnaire was reviewed by four faculty experts in educational measurement and instructional technology. Adjustments were applied to three items flagged for ambiguity. A pilot test followed, involving 25 animal science educators from a fifth college excluded from the main sample. Internal consistency analysis yielded Cronbach's alpha values of 0.87 (perceived usefulness), 0.83 (perceived ease of use), and 0.91 (willingness). No items required deletion, though two were reworded for clarity based on participant feedback during debriefing. Data were processed using SPSS version 27. Descriptive statistics summarised respondent profiles and construct scores. Pearson correlation examined bivariate associations among the constructs and demographic variables. Independent-samples t-tests compared gender groups, while one-way ANOVA with Tukey's post-hoc test explored diferences across experience cohorts and departments. A threestep hierarchical multiple regression model predicted willingness, entering demographics in Step 1, perceived ease of use in Step 2, and perceived usefulness in Step 3. Significance was fixed at α = 0.05 throughout. One-way ANOVA confirmed a significant main efect of teaching experience on willingness (F(4, 209)=14.83, p < 0.001, ηn²=0.22). Tukey's post-hoc comparisons showed that educators with 1-5 years of experience scored significantly higher than those with 16-20 years (mean diference = 0.71, p < 0.001) and 21+ years (mean diference = 0.83, p < 0.001).

Results

Gender produced no significant diferences across any construct (all p > 0.05). Department-level ANOVA revealed a significant efect on willingness (F (4, 209)=3.92, p=0.004), with poultry science scoring higher than animal genetics (mean diference = 0.51, p = 0.009). The pathway model and feature-level heatmap are presented below.

Comprehensive Interpretation

Hierarchical regression showed that demographics alone (Step 1) accounted for 18.4% of the willingness variance. Adding perceived ease of use (Step 2) raised it to 34.1% (ΔR²=15.7%, p < 0.001). Entering perceived usefulness (Step 3) brought the total to 52.6% (ΔR²=18.5%, p < 0.001). In the final model, perceived usefulness was the strongest predictor (β=0.44, p < 0.001), followed by perceived ease of use (β=0.31, p < 0.001) and prior mobile experience (β= 0.13, p=0.018). Teaching experience retained a negative relationship (β=-0.16, p=0.008) Multicollinearity was within acceptable limits (VIF < 2.5 for all predictors). The heatmap confirmed that perceived usefulness scores declined uniformly from the youngest to the oldest experience cohort across all six mobile app features, with video demonstrations maintaining the highest ratings even among the 21+ years group (3.42).

Discussion

The main findings of this research can be summarised in three points: animal science educators in Quezon City expressed moderate-to-high willingness to adopt mobile teaching tools; perceived usefulness was the dominant predictor of that willingness; and teaching experience exerted a persistent negative influence that spanned all app features and constructs. These outcomes carry both theoretical and practical weight.

The grand willingness mean of 3.81 aligns with comparable figures reported by Alenezi [7] in a multi-institution survey of health science educators, where willingness averaged 3.76 on a similar scale. Agreement between the two research contexts is notable given the diferent disciplinary demands animal science leans toward field and laboratory work, while health science foregrounds clinical placements. The convergence may reflect a shared recognition among educators that mobile tools ofer scheduling flexibility and asynchronous content delivery regardless of discipline-specific pedagogical norms.

Where disagreement with the existing literature surfaces is on the mater of gender efects. Several earlier investigations reported significant gender diferences in technology acceptance, with male educators scoring higher on perceived usefulness [12] . In the present sample, gender diferences were negligible and non-significant across all constructs. One plausible explanation is that mobile device ownership and daily usage have become nearly universal in the Philippine urban context, narrowing the gender digital divide that older research captured in setings with lower overall connectivity [1] . Possible explanations for the strong role of perceived usefulness (β = 0.44) centre on the visual and procedural character of animal science instruction. Educators who recognise that a mobile app can display a recorded surgical technique, animate a digestive pathway, or generate a realtime feed ration calculator are more likely to view the tool as directly beneficial to their teaching output [3] . This task-alignment mechanism echoes the task-technology fit argument that Goodhue and Thompson proposed and that has since been integrated into extended TAM frameworks [14] . The broader implication is that institutions seeking to raise adoption rates should invest not only in app provision and bandwidth but also in contextualised training that maps specific app features to specific curricular tasks. The heatmap data make this actionable: video demonstrations and interactive quizzes scored highest even among reluctant experience cohorts, suggesting these features as logical entry points for training programmes targeting mid-career and senior educators. Conversely, features like virtual field trips and discussion boards may require more sustained support before they gain traction among older cohorts.

Limitations

This research was limited to four colleges within a single metropolitan area, which constrains generalisability to provincial or rural institutions where connectivity infrastructure difers markedly. The cross-sectional design captured a snapshot of willingness and perceived usefulness without tracking changes over time, and self-report measures carry the risk of socially desirable responses. Objective usage analytics from the mobile platforms were not accessed. Future research should adopt longitudinal designs and incorporate platformgenerated behavioural data to complement atitudinal measures.

Conclusion

The main contribution of this research lies in providing the first systematic assessment of mobile application-based teaching tool acceptance among animal science educators in the Philippine higher education context. By applying an extended Technology Acceptance Model that incorporated willingness as a distinct construct and tested three moderating variables, the investigation moved beyond binary adoption counts to uncover the atitudinal landscape that underpins actual tool usage. Supporting evidence from the data confirmed several paterns. Perceived usefulness emerged as the most powerful driver of willingness, explaining nearly a fifth of the variance on its own after demographic and ease-of-use variables had been accounted for. This result reinforces the theoretical primacy of usefulness within the TAM framework and aligns with findings from agricultural and health science education contexts internationally. Perceived ease of use, while secondary in efect size, still contributed meaningfully, pointing to the need for intuitive interface design in mobile teaching platforms. Among demographic moderators, teaching experience exerted the strongest and most consistent negative influence a gradient visible not only in the regression coeficients but also in the heatmap of feature-level usefulness scores, where every single mobile app feature showed progressively lower ratings from the youngest to the oldest experience cohort. The significance of these findings extends to institutional planning. Training programmes designed to boost mobile tool adoption in animal science departments should be diferentiated by experience cohort rather than ofered as one-size-fits-all workshops. For junior educators with fewer than six years of service, whose willingness and perceived usefulness scores were already high, the priority is sustained access to highquality apps and reliable connectivity rather than motivational training. For mid-career educators in the 11-15 year bracket, targeted demonstrations linking specific app features to specific curricular needs for example, using a virtual farm walkthrough module in a livestock production course are likely to shift usefulness perceptions upward. For senior educators with more than 20 years of experience, peer-coaching arrangements that pair them with digitally fluent colleagues may be more efective than formal workshops, as this group's lower scores appear rooted less in awareness gaps than in well-established pedagogical habits that resist displacement. Department-level diferences also warrant action. The higher willingness scores in poultry science and livestock production, relative to animal genetics, suggest that disciplines with a stronger visual and procedural component find mobile apps more immediately relevant. Institutional administrators could leverage this by developing discipline-specific app customisation embedding breeding genetics simulations, for instance, to make the tools equally compelling for animal genetics educators. Several open questions remain. Does the experiencewillingness gradient narrow over time as senior educators accumulate exposure, or does it remain stable? Would the introduction of discipline-customised apps shift the departmental diferences observed here? Are the paterns identified in a metropolitan Philippine context reproducible in provincial or international setings with diferent connectivity profiles? And to what extent do institutional mandates such as policies requiring a minimum percentage of content delivery through mobile platforms moderate the relationship between perceived usefulness and actual adoption? Longitudina and comparative research designs will be needed to address these questions and to track whether the atitudinal readiness captured in this research translates into sustained mobile tool use over successive academic cycles.

References

1. Tinio VL. ICT in education in the Philippines. Digital Review of Asia Pacific. 2013;14:226-234.
2. Strong R, Irby TL, Wynn JT, McClure MM. Investigating students' satisfaction with eLearning courses in undergraduate agriculture. J Agric Educ. 2012;53(4):98110.
3. Ruten N, van Joolingen WR, van der Veen JT. The learning efects of computer simulations in science education. Comput Educ. 2012;58(1):136-153.
4. Crompton H, Burke D. The use of mobile learning in higher education: a systematic review. Comput Educ. 2018;123:53-64.
5. Lazar S. The importance of educational technology in teaching. Int J Cogn Res Sci Eng Educ. 2015;3(1):111-114.
6. Davis FD. Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Q. 1989;13(3):319-340.
7. Alenezi A. Barriers to a wider implementation of mobile learning in higher education. Int J Educ Technol. 2020;7(2):100-107.
8. Kakar N, Manjula N, Nadeerpoor MA, Yousafzai I. Teachers' perceptions of factors encouraging the use of information and communication technology (ICT) in agricultural education. South Asian J Agric Sci. 2022;2(2):90-93.
9. Adnan M, Anwar K. Online learning amid the COVID-19 pandemic: students' perspectives. J Pedagog Sociol Psychol. 2020;2(1):45-51.
10. Ajzen I. The theory of planned behavior. Organ Behav Hum Decis Process. 1991;50(2):179-211.
11. Inan FA, Lowther DL. Factors afecting technology integration in K-12 classrooms: a path model. Educ Technol Res Dev. 2010;58(2):137-154.
12. Tarhini A, Hone K, Liu X. The efects of individual diferences on e-learning users' behaviour in developing countries. Comput Hum Behav. 2014;41:153-163.
13. Ertmer PA, Otenbreit-Leftwich AT. Teacher technology change: how knowledge, confidence, beliefs, and culture intersect. J Res Technol Educ. 2010;42(3):255-284.
14. Goodhue DL, Thompson RL. Task-technology fit and individual performance. MIS Q. 1995;19(2):213-236.
15. Sánchez-Prieto JC, Olmos-Migueláñez S, García-Peñalvo FJ. Informal tools in formal contexts: development of a model to assess the acceptance of mobile technologies among teachers. Comput Hum Behav. 2017;55:519-528.
16. Kukulska-Hulme A, Traxler J. Mobile learning: a handbook for educators and trainers. Routledge; 2005.
17. Venkatesh V, Davis FD. A theoretical extension of the technology acceptance model: four longitudinal field studies. Manag Sci. 2000;46(2):186-204.
18. Wang YS, Wu MC, Wang HY. Investigating the determinants and age and gender diferences in the acceptance of mobile learning. Br J Educ Technol. 2009;40(1):92-118.
19. Nassuora AB. Students' acceptance of mobile learning for higher education in Saudi Arabia. Am Acad Scholarly Res J. 2012;4(2):24-30.