Alternative Delivery Modes on Student Engagement: An Explanatory Sequential Mixed-Methods Study

ISSN 3028-1261 10.5281/zenodo.17755898/NIJSE.2025 Alternative Delivery Modes on Student Engagement: An Explanatory Sequential Mixed-Methods Study Mae C. Embalsado Abstract. This study focused on difficulties that gradually affect the student’s ability to read and write in Grade 2, as seen by experienced mentors. However, there are gaps experienced by many young learners that hinder or inhibit their progress towards basic literacy skills and development. In this research, semi-structured interviews with qualified teachers revealed that factors such as restricted word knowledge, poor phonemic processing, and differences in the levels of parents’ engagement hamper learners’ literacy development in the early years. This paper further explored how these teachers managed these challenges and how strategies such as opting for inclusion differentiation and focused instructional interventions are decisive in promoting literacy for learners with English Learners 2. The present study confirmed that factors such as teacher experience can be crucial in managing existing literacy issues. It provided practical implications for improving future approaches to early literacy and supporting them at the primary education level. This work, therefore, sought to join the conversation in the existing literature about literacy development with solutions that teachers may use when teaching young children. KEY WORDS 1. Barriers to reading and writing literacy 2. Student engagement 3. Alternative Delivery Date Received: August 15, 2025 — Date Reviewed: September 20, 2025 — Date Published: October 10, 2025 1. Introduction Alternative Delivery Modes (ADM), including online, blended, and modular learning, provide substantial benefits by offering flexibility and accessibility for learners with special needs, health concerns, or other challenges. However, these modes also present distinct challenges in promoting student engagement. Learners with special needs may encounter difficulties sustaining motivation and participation without the structure and support typically provided by traditional classroom environments. Dependence on technology may pose barriers for students with limited access to digital tools or those requiring specialized resources. The lack of face-to-face interaction may also negatively affect emotional and social engagement, impeding students’ ability to connect with their peers and instructors. Therefore, it is imperative to investigate how ADM can be modified to meet the diverse needs of these learners, ensuring it fosters their academic success and overall engagement in the learning process. Koh and Daniel (2022) conducted a systematic review to explore the teaching and learn- NIJSE (2025) - ing strategies employed during the transition to online education. They examined 36 empirical articles and highlighted both opportunities and challenges associated with online learning. While students’ access to online resources and positive coping mechanisms contributed to a smoother transition, the study also highlighted significant barriers, including limited technological infrastructure and challenges related to the home learning environment. Additionally, the authors noted that while asynchronous learning resources offered flexibility, their effectiveness varied significantly across different educational contexts (Koh and Daniel, 2022). In a similar vein, Lee and colleagues (2023) investigated how the shift to Alternative Delivery Modes during the pandemic resulted in lasting changes in pedagogical practices in higher education. They compared courses before and after the pandemic to assess whether emergency remote teaching had a lasting impact on teaching strategies. While some institutions reverted to traditional in-person classes, others continued to integrate ADM into their teaching models, suggesting that the transition had a lasting impact on educational delivery. This research emphasizes the mixed outcomes of implementing ADM, with some institutions recognizing the benefits of online learning even after the pandemic (Lee et al., 2023). Lastly, a study by Tatiana et al. (2023) investigated how emerging digital practices are supporting student-centered learning in higher education. Through a systematic literature review and a case study, the authors explored how digital tools can be aligned with pedagogical goals to enhance student engagement and learning outcomes. They found that the integration of digital practices plays a crucial role in fostering an interactive and personalized learning experience, which is essential for enhancing student engagement and success in ADM environments. This study highlights the importance of strategic alignment between digital tools and educational objectives in supporting learners effectively in an ADM setting (Tatiana et al., 2023). The Philippine Department of Education (DepEd) has extensively adopted Alternative Delivery Modes (ADM) to address the unique challenges faced by students, particularly during the COVID-19 pandemic. According to a study by Abdullah et al. (2021), the shift to online learning, modular distance learning, and blended learning has allowed students from remote and marginalized areas to continue their education. However, issues such as internet connectivity, limited access to devices, and the challenge of delivering content in rural areas remain significant barriers (Abdullah et al., 2021). These challenges underscore the need for further research to enhance access to and the quality of ADM, particularly for disadvantaged learners. In line with this, Ferrer (2023) discusses how DepEd’s institutionalization of blended learning aims to create a more flexible and accessible learning environment for students nationwide. Blended learning, which combines online classes with in-person sessions, was introduced as a response to the pandemic and as a long-term educational strategy. While it gives students more control over their learning schedules, Ferrer (2023) emphasizes the ongoing concerns regarding the quality of education in blended settings, particularly in schools with limited technological infrastructure and a lack of trained teachers capable of effectively facilitating these modes (Ferrer, 2023). Additionally, the Alternative Learning System (ALS), a nonformal education program in the Philippines, plays a significant role in addressing the educational needs of out-of-school youth, adults, and other marginalized populations. Liu et al. (2022) explore the impact of ALS in providing flexible educational opportunities through various delivery modes, including modular learning and community-based instruction. Despite its success in reaching underserved learners, ALS continues to face challenges related to limited resources, the need for better-trained instructors, 2ISSN 3028-1261 10.5281/zenodo.17755898/NIJSE.2025 NIJSE (2025) - and inadequate learning materials, which hinder its full potential (Liu et al., 2022). In New Bataan, Davao de Oro, the use of Alternative Delivery Modes (ADM), such as online, blended, and modular learning, has been key in maintaining education, particularly for students facing geographic or socio-economic challenges. These methods offer flexibility and accessibility, particularly in rural areas where traditional classrooms are difficult to access. Nonetheless, issues like limited technology, inadequate infrastructure, and insufficient teacher training continue to hinder the effectiveness of ADM. Tackling these obstacles is essential to enhance the quality of education and ensure all learners, especially those in underserved regions, benefit from ADM. Despite these challenges, ADM has made notable progress in educating remote communities. 1.1. Theoretical/Conceptual Framework of the Study —This study is anchored on the theory of Alternative Delivery Mode. The integration of Alternative Delivery Modes (ADM) in education facilitates the concurrent development of language literacy, quantitative skills, and values across various subject areas. ADMs, such as online, blended, and modular learning, offer flexible learning opportunities that can be tailored to individual student needs. This adaptability enables the alignment of teaching strategies with specific learning outcomes, ensuring that instructional methods are both practical and relevant to the needs of students. Moreover, ADMs provide access to diverse instructional materials and resources, enhancing the learning experience and accommodating different learning styles. By creating learning environments that encourage active participation, critical thinking, and ethical reasoning, ADMs foster the development of values essential for holistic growth. Recent studies underscore the importance of aligning instructional materials with learners’ needs to enhance engagement and academic performance (Bacolod, 2022; Gonz ´ alezOcampo, 2020). Additionally, the use of digital tools in ADMs has been shown to improve student engagement and learning outcomes (Wang, Wen, and Quek, 2022). These findings highlight the potential of ADMs to integrate essential skills and values, thereby enriching the educational experience. The theory underlying Alternative Delivery Modes (ADM) is highly applicable to the study ”Investigating the Impact of Alternative Delivery Modes on Student Engagement: An Explanatory Sequential MixedMethods Study,” as it aligns with the core concepts of flexibility, accessibility, and the integration of diverse instructional strategies. ADM encompasses various teaching approaches such as online, blended, and modular learning, which provide students with greater control over their learning experiences. This flexibility in how content is delivered enables educators to tailor their teaching methods and resources more effectively to meet the needs of diverse learners, potentially enhancing student engagement. In the context of the study, ADM is expected to improve student engagement by offering more personalized learning opportunities that cater to diverse learning styles, preferences, and paces, thereby promoting a more active involvement in the learning process. 2. Methodology This study uses an explanatory sequential mixed-methods approach to examine the impact of Alternative Delivery Modes (ADM) on student engagement. It consists of two phases: a quantitative phase that surveys student engagement across various ADM settings, such as online, blended, and modular learning, to identify patterns and relationships; and a qualitative phase that uses semi-structured interviews to explore factors influencing engagement. Combining both 3ISSN 3028-1261 10.5281/zenodo.17755898/NIJSE.2025 NIJSE (2025) - Fig. 1. Theoretical/Conceptual Framework 4ISSN 3028-1261 10.5281/zenodo.17755898/NIJSE.2025 NIJSE (2025) - methods enables a comprehensive analysis of how ADM affects student participation, motivation, and emotional connection to learning, as well as the underlying reasons for these effects. 2.1. Research Design—Explanatory Sequential Mixed Methods Research Design is a two-phase research approach that combines both quantitative and qualitative methods, typically with the quantitative phase occurring first, followed by a qualitative phase. This design is employed when researchers seek to use qualitative data to help explain or provide deeper insights into findings derived from quantitative data. According to Creswell and Plano Clark (2020), the explanatory sequential design is particularly effective when the researcher wishes to understand the contextual or experiential factors behind the patterns observed in the quantitative phase. In the first phase, quantitative data is collected and analyzed, often through surveys or questionnaires, which provide a broad understanding of the research problem. The second phase then builds upon these findings by gathering qualitative data, typically through interviews or focus groups, to explore the reasons behind the quantitative results. The core principle of explanatory sequential mixed methods is to use the qualitative phase to elaborate, expand, or explain the quantitative results. This design assumes that the quantitative results provide the generalizable evidence necessary to understand the scope of the research issue. At the same time, the qualitative data helps to provide depth, context, and nuanced interpretation of the statistical outcomes. Ivankova, Creswell, and Stick (2020) highlight that the sequential nature of this design allows for a deeper exploration of the research problem, as the qualitative phase can address unexpected findings or help clarify ambiguous results from the quantitative phase. This approach is particularly valuable in fields such as the social sciences, education, and health research, where combining numerical data and personal experiences yields a more comprehensive understanding of complex phenomena. Explanatory sequential mixed methods research combines the strengths of both quantitative and qualitative approaches, providing a robust framework for addressing research questions that require both statistical analysis and in-depth contextual exploration. The quantitative data sets the stage by outlining the scope of the problem, and the qualitative data follows to offer a richer, more detailed understanding of the underlying factors and motivations. This design enables researchers to leverage the strengths of both data types, providing a more comprehensive and nuanced explanation of the research findings. The explanatory sequential mixed-methods approach is a research design that combines both quantitative and qualitative methods in a two-phase process, where the quantitative phase precedes the qualitative phase. This approach is particularly suitable for the study “Investigating the Impact of Alternative Delivery Modes on Student Engagement, “ as it allows for a comprehensive understanding of how Alternative Delivery Modes (ADM) impact student engagement, both in terms of measurable outcomes and underlying factors. The first phase of the methodology is quantitative, where surveys are administered to gather numerical data on student engagement levels across various ADM settings, including online, modular, and blended learning. This phase aims to identify patterns, correlations, and statistical relationships between ADM and multiple aspects of student engagement, including behavioral, cognitive, and emotional engagement. The principles of this phase emphasize objectivity and the collection of large-scale data to establish generalizable findings. The quantitative data provide a broad, structured overview of how ADM influences student engagement, allowing the study to identify which delivery modes lead to higher engagement levels. The 5ISSN 3028-1261 10.5281/zenodo.17755898/NIJSE.2025 NIJSE (2025) - second phase of the methodology is qualitative, where semi-structured interviews or focus group discussions are conducted with participants to explore the reasons behind the quantitative findings. This phase seeks to gain deeper insights into students’ personal experiences, perceptions, and challenges in different ADM environments. The qualitative approach allows for flexibility, enabling participants to share their views in greater detail and providing context to the statistical results. This phase also aims to capture the nuanced factors, such as emotional and motivational elements, that quantitative data may not fully address. The principles underlying the explanatory sequential mixed-methods approach focus on integrating both types of data to provide a more complete understanding of the research problem. The quantitative phase offers a broad overview and establishes relationships, while the qualitative phase deepens the knowledge by uncovering the complexities behind those relationships. The findings from the qualitative phase can explain and enrich the quantitative results, leading to a more comprehensive understanding of how ADM affects student engagement. This methodological approach ensures that the study captures both the breadth and depth of the phenomenon being investigated, allowing for more informed conclusions and recommendations for educational practice. 2.2. Ethical Consideration—In conducting this study, several ethical considerations are paramount, especially since teachers are the primary respondents and participants. Informed consent will be obtained from all participants, ensuring they are fully aware of the study’s purpose, procedures, and their right to withdraw at any time without consequence. Confidentiality and anonymity will be maintained throughout the research process by assigning unique identifiers to the participants, and no personal identifying information will be collected or shared. The study will ensure that teachers’ perspectives are respected, and their responses are used solely for academic purposes. Additionally, the research will prioritize minimizing any potential risks or discomforts for the participants, offering support, and clarifying any concerns they may have before, during, and after their involvement in the study. Social Value As an educator myself, I understand the challenges that both teachers and students face in adapting to different learning environments. By examining how ADM affects student engagement, this study offers valuable insights that can inform more effective teaching strategies. The findings could inform educational policies and practices, leading to more inclusive and accessible learning experiences for students, especially those in remote or underserved areas. Moreover, understanding the factors that enhance student engagement through ADM can help teachers better support their students’ academic success and personal growth. Ultimately, the study aims to promote more effective and equitable education, which benefits the teachers and students directly involved and the broader educational community. 2.3. Research Respondents—The respondents in this study are teachers from a population of 280 who will participate in the quantitative phase. Using Slovin’s formula to determine the appropriate sample size, approximately 164 teachers will be selected for the study. This sample size ensures statistical validity and representation, enabling reliable data collection and providing meaningful insights from the survey. The inclusion criteria for this study are based on teachers’ involvement in implementing Alternative Delivery Modes (ADM) in their classrooms. To qualify for participation in the quantitative phase, teachers must have direct experience in using ADM methods such as online, modular, or blended learning. They should also be currently employed in the school district and actively engaged in teaching at the time of the study. Teachers from various 6ISSN 3028-1261 10.5281/zenodo.17755898/NIJSE.2025 NIJSE (2025) - grade levels and subject areas will be included to provide a comprehensive view of how ADM affects student engagement across different educational contexts. These criteria ensure that the selected participants are knowledgeable and experienced in the relevant teaching methods, providing valuable data for the study. For the qualitative phase of this study, a sample of 6 participants was selected for the IDI and 4 for the focus group discussions using the principle of purposeful or criterion-based sampling. This approach ensures that participants are chosen for their ability to provide rich, relevant, and detailed insights into the research topic. The selection criteria are designed to identify teachers who have direct and substantial experience with Alternative Delivery Modes (ADM) such as online, blended, or modular learning. These teachers will be selected based on their ability to offer in-depth perspectives on how ADM influences classroom engagement. The qualifications for inclusion in the qualitative phase are as follows: First, teachers must have experience actively implementing ADM in their teaching practices, ensuring they can provide firsthand insights into the challenges and benefits of these methods. Second, the sample will include teachers from diverse subject areas and grade levels to capture a broad range of perspectives on how ADM impacts student engagement across different contexts. Third, participants must be willing to engage in detailed interviews or focus group discussions, ensuring they can commit the necessary time and effort to the qualitative phase. Finally, teachers must possess an understanding of how ADM affects student engagement, enabling them to provide thoughtful and relevant responses to the study’s research questions. 2.4. Research Instrument—The development and crafting of the survey instruments for this study’s quantitative and qualitative phases were guided by established frameworks and validated tools to ensure reliability and relevance. For the quantitative phase, the survey instrument was adapted from the Student Engagement in Schools Questionnaire (SESQ) by Fredricks, Blumenfeld, and Paris (2004), which is widely recognized for its comprehensive approach to measuring student engagement. The SESQ includes key dimensions such as behavioral, cognitive, and emotional engagement, all of which are relevant to understanding how Alternative Delivery Modes (ADM) impact student engagement. The adoption of this instrument ensures that the survey comprehensively captures these three aspects of engagement, providing a wellrounded measure of student involvement in various learning environments. The instrument was adapted to include questions that specifically address the context of ADM, ensuring its applicability to this study’s research focus. The questionnaire is designed to determine the perceived impact of alternative delivery modes on student engagement, utilizing a 5-point Likert-type scale to capture respondents’ levels of agreement with key indicators. The instrument underwent reliability testing, yielding a Cronbach’s alpha coefficient of 0.722, indicating acceptable internal consistency and reliability of the survey items. This suggests that the instrument is suitable for measuring constructs related to student engagement in the context of alternative delivery modes. The scale, along with its corresponding descriptive rating and interpretation, is presented below: The Semi-Structured Interview Guide developed by the Veterans Health Administration was utilized for the qualitative phase. This guide is designed to allow flexibility in gathering indepth, qualitative data while maintaining consistency in the questions asked across participants. It supports a conversational interview style, enabling participants to share detailed experiences 7ISSN 3028-1261 10.5281/zenodo.17755898/NIJSE.2025 NIJSE (2025) - Range of Mean and Descriptive Rating of Alternative Delivery Modes on Student Engagement Score Range of Mean Descriptive Rating Interpretation 5 4.20 – 5.00 Very Extensive The alternative delivery modes implementation is always observed 4 3.40 – 4.19 Extensive The alternative delivery modes implementation is oftentimes observed 3 2.60 – 3.39 Moderately Extensive The alternative delivery modes implementation is sometimes observed 2 1.80 – 2.59 Less Extensive The alternative delivery modes implementation is seldom observed 1 1.00 – 1.79 Not Extensive The alternative delivery modes implementation is never observed Range of Mean and Descriptive Rating of Student Engagement Score Scale Descriptive Rating Interpretation 5 4.20–5.00 Very Extensive The extent of student engagement is always observed 4 3.40–4.19 Extensive The extent of student engagement is oftentimes observed 3 2.60–3.39 Moderately Extensive The extent of student engagement is sometimes observed 2 1.80–2.59 Less Extensive The extent of student engagement is seldom observed 1 1.00–1.79 Not Extensive The extent of student engagement is never observed 8ISSN 3028-1261 10.5281/zenodo.17755898/NIJSE.2025 NIJSE (2025) - and perspectives on ADM and its impact on student engagement. The open-ended nature of the guide encourages participants to express themselves freely, while the semi-structured format ensures that key topics are consistently covered. Additionally, the Distance Education Learning Environments Survey (DELES) by Arbaugh and Benbunan-Fich (2007), as cited by Abdullah, N., Cruz, R., and Villanueva, R. (2021), was integrated to complement the qualitative insights. This tool is designed to evaluate the quality of online learning environments and their impact on student satisfaction. The DELES instrument provides a framework for evaluating the aspects of ADM that relate to online and blended learning modes, including student interaction, instructor support, and learning materials. By incorporating elements of the DELES survey, the study ensures that students’ experiences in online or hybrid learning settings are addressed. Together, these instruments provide a robust and balanced approach to data collection, allowing the study to capture adequate quantitative measurements of student engagement and qualitative insights into teachers’ and students’ experiences with ADM. The combination of these validated tools ensures that the study’s instruments are grounded in established research, providing a strong foundation for the study’s findings. 2.5. Data Gathering Procedure—The guidelines governing the procedure for quantitative data collection are in strict accordance with the policies established by The Rizal Memorial Colleges, Inc. As a component of the formal request, researchers clearly articulate their intentions regarding the collection, analysis, and dissemination of data, ensuring alignment with the overarching objectives of the research. Anticipated concerns or inquiries from recipients are proactively addressed within this communication, thereby providing reassurance concerning ethical safeguards, confidentiality measures, and the potential advantages of the study. The formal request for permission explicitly seeks authorization to proceed, underscoring the crucial importance of their support in facilitating the success of the research. 2.6. Data Analysis—The following statistical tools will be used to analyze the relationship between time management advocacy on student discipline. The Mean Score and Descriptive Interpretations Will be used to answer statement problem one regarding the extent of alternative delivery modes Implementation and 2, the extent of student engagement. Pearson r or Pearson Product Moment Correlation Coefficient Will be used to answer problem number 3 about the significant relationship between alternative delivery modes Implementation and student engagement. A simple linear regression analysi. Will answer statement 4 on the significant influence of alternative delivery modes implementation on student engagement. To answer statement problems 5 and 6, the application of systematic data analysis in the qualitative phase of this study ensures a thorough and organized exploration of the participants’ insights. Data gathered through semi-structured interviews are first transcribed verbatim and reviewed for completeness and accuracy. A thematic analysis approach is then applied, beginning with familiarizing data to identify initial patterns and recurring ideas. Key phrases are coded systematically, and similar codes are grouped into broader categories or themes that reflect the core research objectives. Themes are further refined and reviewed to ensure the data support 9ISSN 3028-1261 10.5281/zenodo.17755898/NIJSE.2025 NIJSE (2025) - Fig. 2. Standpoints of The Participants Regarding the Extent of Alternative Delivery Modes Implementation and Student Engagement to the internet, gadgets, or online platforms. One participant observed, “Students in our area share one cellphone for two or more learners, making it difficult for them to attend discussions.” This supports the explanation that ADM implementation, regardless of its comprehensiveness, does not necessarily translate to equitable engagement if technological barriers persist. Despite these challenges, teachers acknowledged that emotional and motivational engagement can flourish under ADMs when learners feel supported, encouraged, and consistently guided. This aligns with the quantitative finding from the regression analysis, where emotional engagement was the only dimension with a statistically significant influence on overall engagement ( = 0.157, p = .048). Teachers highlighted that regular interaction, timely feedback, and relational support from instructors keep students emotionally connected and invested. Participants also emphasized that poor implementation negatively impacts engagement, especially when ADM formats lack clarity, interactivity, and personal connection. One teacher recounted that “long, text-heavy modules and limited teacher feedback make it hard for students to stay motivated.” This reveals that ineffective ADM execution can not only fail to improve engagement but may also hinder it, explaining the weak correlation in the statistical test. Lastly, the data revealed that student responses to ADM vary significantly based on learner profiles. Some students adapt well to online and blended formats due to their self-motivation, while others require structured face-to-face interaction to stay engaged. As one teacher explained, “Student engagement depends on how well the ADM is designed and on the type of learner involved.” This observation helps interpret the overall finding: ADM implementation is not a universal predictor of engagement but is mediated by instructional quality and learner diversity. In conclusion, the participants’ perspectives affirm that the relationship between ADM implementation and student engagement is not linear or absolute. It is shaped by contex16 ISSN 3028-1261 10.5281/zenodo.17755898/NIJSE.2025 NIJSE (2025) - Fig. 3. Standpoints of The Participants Regarding the Significant Relationship Between Alternative Delivery Modes Implementation and Student Engagement tual factors such as teacher support, access to resources, and responsiveness to students’ emotional and cognitive needs. These insights substantiate the quantitative result and emphasize the importance of intentional, learner-centered ADM practices rather than mere structural compliance. Participants’ standpoints revealed nuanced insights into the significant relationship between the implementation of Alternative Delivery Modes (ADMs) and student engagement. Central to these perspectives is the recognition of a conditional relationship between ADM effectiveness and learner engagement. Rather than yielding uniform outcomes, the influence of ADM on student engagement is shaped by specific factors such as delivery design, teacher facilitation, and learner context. This aligns with the findings of Zhou and Xu (2021), who argue that instructional quality, feedback mechanisms, and digital interactivity significantly mediate learner engagement in remote or blended environments. 3.7. Integration of Quantitative and Qualitative Results: Alternative Delivery Modes and Student Engagement—The study employed a mixed-methods approach to explore how the implementation of Alternative Delivery Modes (ADMs) influences student engagement. Quantitative results, as reflected in Table 5 and Table 10, indicate that ADM implementation was rated as “Extensive” across all indicators (M = 3.73), with emotional engagement (M = 4.57) and behavioral engagement (M = 4.26) receiving the highest ratings. This suggests that students found ADM experiences to be meaningful and participatory, particularly in emotionally resonant and action-driven learning tasks. Emotional engagement emerged as a significant predictor in the regression model (p = 0.048), highlighting its pivotal role in sustaining student 17 ISSN 3028-1261 10.5281/zenodo.17755898/NIJSE.2025 NIJSE (2025) - attention, interest, and motivation in alternative learning settings. However, regression results in Table 12 show that participation (p = .451), behavioral (p = .399), and cognitive (p = .728) dimensions did not significantly predict overall student engagement. Only emotional engagement ( = 0.157, p = .048) was found to influence engagement levels significantly. This aligns with findings by Zhou and Xu (2021), who argue that emotional factors—such as enjoyment, belongingness, and affective connection to content—are critical in digital and blended learning environments, often more than behavioral compliance or cognitive strategies. Qualitative data supported this quantitative trend. As illustrated in the conceptual diagrams, emotional engagement was repeatedly emphasized by participants as central to sustaining student motivation. Themes such as ”Blended Learning as an Effective Mode” and ”Emotional and Motivational Triggers” affirm that students are more engaged when instruction is not only accessible but also emotionally and socially supportive. Guerra Ayala et al. (2024) similarly note that emotional engagement in online learning contexts significantly predicts improved communication skills and academic performance among language learners. Another significant qualitative insight pertains to the differentiated impact across ADM modes. While blended learning was praised for balancing structure and flexibility, participants noted that infrastructure limitations hindered participation, particularly among learners with poor internet connectivity or limited access to digital devices. This theme is consistent with the quantitative findings showing moderate ratings for flexibility (M = 3.62) and technology utilization (M = 3.74). Studies by Nyoni and Bhebhe (2023) and UNESCO (2022) corroborate these findings, highlighting that infrastructure remains a key barrier to equitable engagement in remote and blended learning formats. Furthermore, the theme “Importance of Teacher Support and Course Design” from the qualitative data is crucial in contextualizing the regression findings. Despite ADM being extensively implemented, the insignificant predictive power of behavioral and cognitive dimensions in the regression may reflect inadequacies in instructional scaffolding, interaction, and feedback mechanisms. Sarabi and Ututalum (2023) assert that unless ADM is supported by responsive teaching practices, course clarity, and consistent mentoring, students may engage passively, with minimal impact on deeper cognitive processing or collaborative participation. Another noteworthy integration comes from the qualitative theme “Conditional Relationship”, which aligns with the regression model’s nuanced results. While ADM implementation is generally rated as extensive, its actual influence on student engagement is conditional, depending on learner type, technological readiness, and emotional climate. This insight is reflected in the regression model’s weak standardized coefficients for participation, behavioral, and cognitive domains, suggesting that ADM’s impact is not uniformly experienced across learner groups. Finally, the qualitative insights on ”Negative Impact of Poor Implementation” and ”Variability Across Learner Types” help explain the nonsignificance of several regression predictors. Poorly executed ADM—marked by static modules, delayed feedback, and rigid delivery—fails to activate deeper engagement. As Santos and Dizon (2023) report, learning engagement dramatically varies when ADMs are poorly contextualized or lack interaction, particularly in modular and offline settings. The integration of quantitative and qualitative data reveals a complex yet coherent picture: while ADM implementation is broadly effective, its impact on student engagement is most strongly mediated by emotional factors and conditioned by contextual variables such as infrastructure, course design, and learner readiness. Emotional engagement emerged as the most significant predictor, 18 ISSN 3028-1261 10.5281/zenodo.17755898/NIJSE.2025 NIJSE (2025) - both statistically and narratively. These findings underscore the importance of designing emotionally responsive, technologically supported, and pedagogically adaptive ADM strategies to ensure sustained student engagement in diverse educational settings. 4. Conclusions and Recommendations This chapter presents the conclusions and recommendations derived from the study’s findings on the impact of alternative delivery modes on student engagement. Guided by the statement of the problem, the conclusions highlight key insights derived from both the quantitative and qualitative phases of the explanatory sequential mixed-methods design. These are followed by evidence-based recommendations designed to inform educational policy, instructional practices, and program implementation strategies aimed at enhancing learner engagement across various delivery modalities. 4.1. Findings—On the extent of alternative delivery modes (ADM) implementation. The study found that the overall implementation of alternative delivery modes across public schools was perceived to be extensive. Among the various components assessed, the mode of delivery was identified as the most effectively executed, with blended learning being especially valued for its balance between structure and flexibility. Technology utilization and the frequency of teacher-learner interaction were also implemented to a significant degree. Flexibility in learning, while slightly less emphasized, was still generally practiced across schools. These findings were corroborated by qualitative responses, wherein participants expressed appreciation for the adaptability offered by blended learning. However, challenges were also reported, particularly with modular and online learning formats. These included limited internet connectivity, lack of real-time feedback, and the demands of self-paced learning, which at times impeded consistent learner engagement. On the extent of student engagement. Student engagement was also perceived to be extensive overall. Emotional engagement emerged as the most pronounced dimension, with learners reportedly demonstrating strong emotional investment when appropriate support systems were in place. Behavioral and cognitive engagement followed closely, indicating that students were generally focused and able to process and apply academic content effectively. However, participation was considered only moderately extensive, suggesting some limitations in active involvement, especially in asynchronous or modular settings. These quantitative trends were reinforced by qualitative narratives, where teachers emphasized that emotional engagement was nurtured through timely feedback, encouragement, and teacher-student rapport. Conversely, technological limitations and restricted peer interaction were noted as key factors diminishing learner participation in some ADM contexts. On the relationship between ADM implementation and student engagement. The statistical analysis revealed that there was no significant relationship between the implementation of alternative delivery modes and student engagement. This finding indicates that merely establishing ADM structures does not automatically result in heightened learner involvement. The qualitative data helped contextualize this outcome by highlighting that the effectiveness of ADM implementation relies heavily on factors such as instructional quality, ongoing teacher support, learner motivation, and access to appropriate learning resources. Thus, while systems may be in place, their educational impact depends largely on the depth and quality of delivery. On 19 ISSN 3028-1261 10.5281/zenodo.17755898/NIJSE.2025 NIJSE (2025) - the ADM component that significantly influences student engagement. Among the components examined in the regression analysis, only emotional engagement was found to have a significant influence on overall student engagement. Other dimensions such as participation, behavioral involvement, and cognitive processing did not demonstrate predictive power in the model. This outcome was strongly supported by the qualitative data, wherein participants consistently identified emotional connection, encouragement, and timely teacher feedback as essential drivers of sustained learner interest and commitment. These elements were often cited as more influential than procedural or structural features of ADM. Participants confirmed that the implementation of ADM across schools was broad and actively contributed to fostering student engagement, particularly when paired with responsive and innovative instructional strategies. Blended learning, in particular, stood out as the most effective mode due to its interactive nature and adaptability. On the other hand, modular learning formats were perceived as limiting, primarily because of the absence of teacher presence and fewer opportunities for peer interaction. Teachers highlighted the importance of integrating emotional and motivational support within ADM delivery, further reinforcing the value placed on affective dimensions of engagement observed in the quantitative phase. On the participants’ standpoints regarding the relationship between ADM implementation and student engagement. Participants viewed the relationship between ADM implementation and student engagement not as inherently direct, but rather as conditional and context-dependent. They emphasized that while ADM has the potential to enhance engagement, it can also hinder it when implementation lacks quality, relevance, or adequate support. Key determinants identified include instructional design, accessibility of digital tools, teacher responsiveness, and student readiness. This nuanced understanding aligns with the quantitative finding of a non-significant correlation between ADM implementation and engagement and suggests that the success of ADM lies more in how it is carried out than in its mere existence or reach. 4.2. Conclusions—The implementation of alternative delivery modes (ADMs) is perceived as extensive across public secondary schools, with the highest ratings in the mode of delivery and technology utilization. Teachers acknowledged the widespread use of blended, modular, and online learning platforms, particularly blended learning, which they viewed as the most effective for promoting engagement and self-paced study. Student engagement is generally extensive, especially in emotional and behavioral domains. Emotional engagement received the highest mean score, underscoring the critical role of motivation, encouragement, and learner-teacher relationships. Participation, however, was only moderately extensive, indicating that not all learners are equally involved across ADM formats. The relationship between ADM implementation and overall student engagement was not statistically significant. This implies that having ADM structures in place does not automatically translate into higher student engagement. Qualitative findings affirmed this, highlighting that effective engagement requires instructional quality, contextual responsiveness, and consistent teacher support. Among the ADM components, only emotional engagement had a significant influence on overall student engagement. This supports the idea that affective dimensions, such as feeling connected and supported, are foundational to student motivation and involvement, particularly in flexible and technology-mediated learning environments. Teachers view the success of ADM as contingent upon instructional design, access to technology, and learner readiness. While the delivery formats offer potential, their success varies greatly depending on how well they are planned, facilitated, and supported. 20 ISSN 3028-1261 10.5281/zenodo.17755898/NIJSE.2025 NIJSE (2025) - Poorly implemented ADM, especially modular learning without feedback or interactivity, was frequently associated with disengagement. The standpoints of participants confirm that the effectiveness of ADM implementation is highly variable and context-dependent. ADM modes, such as blended learning, enhance participation when teacher presence is strong, whereas modular learning often isolates students. Engagement is highest when students feel emotionally connected and academically supported. 4.3. Recommendations—In light of the findings and conclusions, the following recommendations are offered to improve ADM implementation and its capacity to foster student engagement: 1.Prioritize Emotional Engagement through Teacher Presence and Support. Educational leaders and teachers should integrate affective support mechanisms into ADM practices by maintaining regular feedback, encouragement, and personal interaction. Building a sense of community and belonging is crucial for sustaining learner motivation. 2.Enhance Instructional Design Across ADM Formats. Curriculum planners and teachers should ensure that learning modules—especially in modular and online formats—are interactive, logically sequenced, and include tasks that promote critical thinking and reflection. Well-structured blended learning formats should be expanded. 3.Improve Access to Technology and Digital Literacy. School administrators and policymakers must address infrastructure gaps by providing students with access to digital tools and stable internet connections. Additionally, both students and teachers should receive training on the effective use of online platforms to ensure equitable engagement. 4.Contextualize ADM Implementation Based on Learner Needs. Recognize that different learners respond differently to each ADM mode. Schools should assess learner profiles and tailor their ADM strategies accordingly, maximizing the effectiveness of blended learning where feasible. 5.Monitor and Evaluate ADM Effectiveness Beyond Structural Delivery. Schools should not limit ADM evaluation to deployment rates but must include monitoring tools that assess student interaction, participation, and learning outcomes. Feedback mechanisms from students and teachers should be institutionalized to refine ADM implementation continually. 6.Strengthen Professional Development for ADM Facilitation. Provide targeted capacity-building for teachers on designing engaging learning activities, giving constructive feedback, and supporting learners emotionally in flexible learning environments. 5. References Abdullah, N., Cruz, R., & Villanueva, R. (2021). Exploring the challenges and opportunities of alternative learning delivery modalities in the philippines. 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