Evaluating the influence of courseware on online learning pedagogy at Pangasinan state university

Abstract

Background: The integration of digital tools in education has transformed pedagogical approaches, particularly through interactive courseware. This study evaluated the impact of courseware usage via Microsoft Teams on the online learning pedagogy at Pangasinan State University(PSU). Objective: To assess the influence of courseware on self-directed learning, learning environment, and learning growth among Bachelor of Secondary Education (BSEd) major in English students at PSU Lingayen campus. Methods: A numerical strategy combined with a design that is descriptive was employed. A stratified random sample of hundred students from a population of 300 participated in a structured survey. Statistical analyses, including weighted means and descriptive interpretation, were conducted. Results: Self-directed learning and learning environment variables showed a high impact (mean scores of 3.53 and 3.43, respectively), while learning growth had a moderate impact (mean score of 3.37). Students valued flexibility and accessibility but identified moderate engagement with courseware. Conclusion: Courseware enhances self-directed learning and optimizes the learning environment, though its impact on learning growth is moderate. Institutions should refine courseware strategies to boost engagement and ensure holistic educational outcomes.

Keywords

Courseware Learning Environment Learning Growth Online Learning Pedagogy Self-Directed Learning

Introduction

The integration of digital learning tools in higher education has transformed traditional pedagogical approaches, enabling more flexible, interactive, and self-directed learning experiences (Aflalo et al., 2024). Technological advancements, such as learning management systems, virtual classrooms, and interactive courseware, have redefined instructional methodologies by fostering engagement and enhancing accessibility (Dritsas and Trigka, 2025). The COVID-19 pandemic accelerated the adoption of online learning strategies, compelling educational institutions worldwide to implement digital learning environments that support remote education (Kayi, 2024). As a result, universities have increasingly relied on courseware and digital platforms to maintain the continuity of learning and improve student outcomes.

Courseware plays an important role in online learning pedagogy by offering structured, interactive, and multimedia enriched content designed to support various learning styles (Adeyele, 2024). Unlike conventional teaching methods, digital courseware enables self-paced learning, providing students with opportunities to review instructional materials at their convenience and reinforcing independent study habits. Additionally, LMS platforms such as Moodle and Microsoft Teams facilitate seamless communication between instructors and students, promoting collaboration and engagement (Vetrivel et al., 2024). However, while these platforms enhance accessibility, research suggests that the effectiveness of digital courseware largely depends on user experience, system usability, and institutional support.

Pangasinan State University has actively embraced digital learning tools to enhance its instructional framework, particularly through Microsoft Teams (Sicuan et al., 2025). This platform enables faculty members to integrate courseware that supports interactive learning, assignment submissions, and real time feedback, fostering a structured and engaging learning environment. Furthermore, research have indicated that the effectiveness of digital learning at PSU is influenced by various factors, including self-directed learning capabilities, the digital learning surroundings, and students overall learning growth (Şahin et al., 2025). Despite the benefits of digital learning platforms, challenges such as digital literacy gaps, internet connectivity issues, and student adaptability to online education remain significant concerns.

This research aimed to evaluate how courseware affects the method of online instruction at PSU, focusing on three critical dimensions: self-directed learning, learning environment, and learning growth. Self-directed learning clarifies students' ability to take initiative in their educational journey, set learning goals, and effectively utilize digital tools. The learning environment encompasses the usability, accessibility, and efficiency of the digital platform in delivering educational content and facilitating communication (Makda, 2025). Learning growth pertains to students academic development, knowledge acquisition, and skill enhancement through the use of courseware.

This research contributes to existing research by examining how digital tools enhance or hinder learning experiences in a higher education setting. By identifying key factors that impact students' online learning experiences, the findings will provide valuable insights into optimizing courseware design, improving learning management systems, and refining instructional strategies to enhance digital pedagogy. The results will aid policymakers and educators in implementing data driven approaches that support effective online learning environments, ensuring a sustainable and innovative academic landscape for future generations.

Contributions

The novel contributions of this study are:

1. The researcher provides a data driven analysis of how courseware influences self- directed learning, learning environments, and learning growth in an online education setting.

2. The researcher examines the success, utility, and access of Microsoft Teams in facilitating digital pedagogy and academic collaboration.

3. The researcher highlights barriers to effective courseware adoption, including engagement levels, digital literacy, and platform usability.

4. The researcher proposes strategic improvements for courseware integration, focusing on pedagogical refinements and technological advancements to optimize learning outcomes.

Literature review

Orlanda-Ventayen (2024) explored the transformative part of artificial intelligence in studies, emphasizing its including in teaching and learning through a mixed methods approach. The study incorporated methods for gathering subjective information, such as analyzing records and informal conversations with educators from open university systems. It highlighted AI’s benefits in personalized learning, improved engagement, and enhanced academic performance. However, ethical concerns regarding AI implementation are prevalent among educators, leading to the recommendation of incorporating AI governance policies in institutional frameworks. Additionally, the study underscored the increasing scholarly interest in AI in education through bibliometric analysis from the Scopus database, reinforcing the need for ethical and policy driven AI adoption in educational institutions.

Camara and Adom (2024) investigated the competency levels of science graduate teachers in Pangasinan State University across 17 future skills, using a cross-sectional descriptive survey and quantitative analysis via SPSS. Findings indicated very high competence in four critical areas: speaking, reflective proficiency, efficiency and risks proficiency, and collaboration. The study revealed no significant relationship between competency levels and gender or academic background, except for doctoral level teachers who exhibit higher self-competence than their master’s counterparts. The outcomes suggested integrating future skill development into higher education curricula to prepare graduates for industry demands.

Kayi (2024) examined the transition to blended learning during the COVID-19 pandemic in three Ghanaian universities using a qualitative case study approach. Through semi-structured interviews with forty adult learners and twenty instructors, the study identified both the positive and negative effects of digital learning adoption. Key findings highlighted improved pedagogy, competency development, and enhanced course delivery. However, technological challenges, inadequate instructor preparation, and poor-quality pedagogy hinder effective learning experiences. The study emphasized the need for agile policy reforms in higher education institutions to sustain quality distance education beyond the pandemic.

Pavlou and Castro-Varela (2024) explored the role of digital technologies in online arts education and sustainable pedagogies within teacher education. Through interviews with twenty five academics from five European countries, the study identified challenges in online arts instruction, including content conversion, resource accessibility, and maintaining student engagement. Educators adapted by leveraging digital tools to create interactive and inclusive learning environments. The study provided insights into innovative teaching methods and pedagogical redesigns necessary to sustain arts education in digital learning spaces.

Abblitt (2024) examined the redistribution of academic quality in online higher education through learning design. The study highlighted the creation of “third-space” experts in designing learning who collaborate with university academics to maintain academic quality. Using actor network theory and socio material critique, the study conceptualized academic quality as an evolving relational construct shaped by institutional policies, technological affordances, and pedagogical expertise. Findings revealed systemic barriers in universities that hinder collaborative efforts, emphasizing the need for a reevaluation of academic roles in digital education.

Tseng and Lin (2024) investigated the integration of OpenAI’s GPT-3.5 into a university-level English as a Foreign Language (EFL) writing course, employing the ADDIE instructional design model. The research explored how AI enhances writing efficiency, content organization, and feedback mechanisms. It suggested that GPT 3.5 effectively supports students by providing instant reviews, growing structural coherence, and serving as an alternative to traditional peer reviewers. The research underscored artificial intelligence part in fostering critical thinking and personalized learning, emphasizing its potential in academic writing instruction.

Lasekan et al. (2024) utilized the factors influencing people engagement in sustainable digital education using a mixed methods approach. Data collected from 452 university students reveal that high quality course content usage enhances cognitive engagement, with 61.7% of students demonstrating a strong interaction with faculty materials. Finally, the role of teaching presence is emphasized, with interactive classes and timely reviews improving people participation. These findings highlighted the importance of structured and immersive online learning surroundings.

The effects of melded digital learning on anxiety among pupils and scientific performance in Ethiopian universities were explained by Shishigu et al. (2024). An analysis of variance ANOVA at wolkite university showed an important boost in pupil achievement following a didactic involvement using a time conjunction design. Finally, by focusing on memory hurdles, technology-integrated studying reduces the fear of math, according to the analysis. According to these results, methods of mixed learning can raise student performance and ought to be taken into account for more extensive educational integration.

By means of an examination of the possibilities of EDX platforms, Zienkowski and Lambotte (2024) investigated how agency manifests in the layout of enormously open online courses. Using a linguistic evidence approach, the study looked at how theories of education, technology-mediated instructional habits, and financial constraints affect the planning of courses. The outcomes showed how students, gadgets, and organizations interact dynamically to shape how students learn online through the identification of six types of power triggers: surveillance-based, expertise-oriented, getting along, direction, and rendering.

Situational passion and wanderlust were investigated by Wong et al. (2024) as facilitators of digital learning in a proportional logic math direction. The study, which employed a model for structural equations, discovered that circumstances and accessibility have a major impact on the involvement of learners. The findings highlighted the value of integrating customer service values which is based on proof didactic creation by showing that effective instruction can increase reactions and decrease mind straying. These results offered practical suggestions for enhancing student involvement and recall in instantaneous learning environments.

With its thorough analysis of recent studies on mixed education, the use of artificial intelligence in studies, and digital learning tools, this overview of the literature offers important insights into how online teaching is developing. The studies' gaps are summarized in Table 1.

Table 1.

Summary of research gaps.

Author (Year)	Method	Findings	Research gaps
Orlanda-Ventayen (2024)	Mixed-methods (Qualitative + Bibliometric Analysis)	AI enhances personalized learning but raises ethical concerns	Lack of empirical studies on AI policy implementation in education
Camara and Adom (2024)	Cross-sectional Survey (Quantitative)	Graduate science teachers show high competence in future skills	Limited research on industry-driven curriculum adjustments
Kayi (2024)	Qualitative Case Study	Blended learning improves pedagogy but has technological challenges	Need for strategies to address poor-quality pedagogy in blended learning
Pavlou and Castro-Varela (2024)	Qualitative Interviews	Digital arts education faces engagement and accessibility issues	Gaps in inclusive digital arts pedagogy and student-centered learning
Abblitt (2024)	Actor-Network Theory and Socio-Material Critique	Academic quality is shifting to learning designers, creating systemic barriers	Limited understanding of how systemic barriers impact online education quality
Tseng and Lin (2024)	Experimental Study (ADDIE Model)	AI (GPT-3.5) enhances writing efficiency and feedback	Unexplored ethical considerations in AI-assisted academic writing
Lasekan et al. (2024)	Mixed-methods (Survey + CHAID Decision Tree)	High-quality content and social presence improve online engagement	Lack of longitudinal studies on student engagement in online learning
Shishigu et al. (2024)	Time-Series Pedagogical Intervention	Blended learning enhances math achievement and reduces anxiety	Insufficient data on cognitive mechanisms reducing math anxiety
Zienkowski and Lambotte (2024)	Discursive-Material Approach	Agency in MOOCs is shaped by technology and institutional pressures	Limited research on the scalability of MOOCs for diverse learners
Wong et al. (2024)	Structural Equation Modeling	Engagement in online learning is mediated by user experience and situational interest	Unexamined role of user experience design in mitigating mind-wandering

Research gaps

Numerous gaps persist unfilled despite a great deal of research on blended learning, AI integration, and digital learning technologies. Existing research mostly concentrates on the benefits of digital platforms and courseware, but it offers little empirical support for their long-term effects on academic performance and self-directed learning across a range of institutional contexts. Although AI-powered tools have been investigated for improving feedback and engagement, the practical implementation challenges, policy frameworks, and ethical issues are still lacking. Additionally, the majority of research focuses on the perspectives of either the instructor or the students separately, lacking a comprehensive analysis of how digital courseware influences learning outcomes and teaching effectiveness at the same time.

Finally, the adaptability of courseware across disciplines, its scalability in under resourced institutions, and its part in fostering sustainable pedagogical practices require further clarification. The effectiveness of blended learning environments in growing higher order thinking skills, reducing cognitive overload, and enhancing digital literacy among students also warrants deeper exploration. Addressing these gaps is important for optimizing courseware integration and refining digital learning strategies.

Problem statement

More specifically with regard to the use of instruction in learning settings, the quick adoption of technology for learning in universities has drastically changed pedagogical approaches. Teams from Microsoft has become the primary tool for teaching at Pangasinan State University, but little is known about how it affects student participation, autonomy in learning, and academic development. Even though courseware aims to increase accessibility, adaptability, and collaborative education, problems like gaps in loyalty, technological proficiency, and the capacity to promote neural networks still exist. Furthermore, there is a dearth of empirical data regarding the ways in which programs affects various elements of the classroom, such as enrollment, educational performance, and skill loyalty. To maximize the use of courseware, improve student learning, and improve classroom techniques, those holes must be filled.

Objectives

1. To evaluate the influence of courseware on self-directed learning by analyzing how students utilize courseware for independent study, goal setting, and learning management.

2. To examine the effectiveness of the learning environment by assessing the usability, accessibility, and efficiency of Microsoft Teams in delivering course materials and facilitating communication.

3. To determine the impact of courseware on learning growth by investigating how courseware contributes to students’ academic development, knowledge acquisition, and skill enhancement.

4. To identify challenges and opportunities in courseware implementation by exploring barriers to effective adoption and potential improvements for optimizing online learning experiences.

5. To provide recommendations for enhancing courseware-based learning by suggesting pedagogical strategies and technological improvements to maximize the benefits of digital learning platforms at PSU.

Proposed methodology

This research employed a descriptive research model with a innovative approach to assess the impact of courseware usage via Microsoft Teams on online learning method at Pangasinan State University. A stratified random sampling technique was used to select hundred students from a population of three hundred Bachelor of Secondary Education (BSEd) major in English students at PSU Lingayen campus. Data collection was conducted through a structured survey questionnaire, and statistical analyses, including weighted means and descriptive interpretation, were applied to evaluate the influence of courseware on self-directed learning, the learning environment, and learning growth. The results provided insights into the effectiveness of courseware and areas for improvement in digital learning strategies.

Figure 1 illustrates the methodological framework used in this research to assess the impact of courseware usage via Microsoft Teams on online learning method at Pangasinan State University. The sample size was determined using a stratified random sampling approach, targeting BSEd English students. Surveys were then distributed, and responses were collected for data analysis. The collected data underwent cleaning and preparation before statistical analyses, including weighted means and descriptive interpretation. The results were then interpreted and discussed in relation to online learning pedagogy. Finally, conclusions were drawn, and recommendations were formulated to enhance the effectiveness of courseware in digital education.

Research design

The descriptive approach was used in this study. The goal of quantitative study is to accurately and methodically depict a group, setting, or thing. In order to methodically examine and offer data regarding the elements specified in the research aims this investigation employed a statistical journey. Data was collected using the style of quantitative research, which required that information obtained from participants be arranged, described, and tabulated.

Respondents

Naturally, the 300 BSEd English students enrolled at the PSU Lingayen campus for the 2023–2024 year of study, 100 were chosen for this research using random stratification. The purpose of the form for the survey used in this research was to evaluate the effects of courseware use on online learning methodology with respect to certain factors.

Treatment of data

The information was processed statistically. Summary application and purely comparable were used to explain the mean weighted average used in this study. To determine the aforementioned impact, every question asked pertaining to self-directed learning, the learning environment, and other educational growth elements was reviewed and defined using the Likert scale with five points here.

Results

This section presents the data collected through the administration and/or floating of questionnaires, addressing the research problem through a tabular format. Table 2 illustrates the impact of courseware on online learning method, specifically in relation to self-directed learning, which yielded an total weighted mean of 3.53, classified as high. The highest mean score of 3.65 was observed in indicator 4, suggesting that students frequently seek clarification from their instructors or professors when courseware lessons require further explanation. Indicator 3 followed closely with a mean of 3.62, indicating that students actively develop strategies to meet their learning needs. Indicator 2, with a mean of 3.51, reflects that students find courseware beneficial in learning concepts and principles at their own pace. Indicator 1 received a mean of 3.48, signifying that students take initiative in determining the sequence and content of their learning through courseware when applicable. The lowest mean, 3.41, was recorded in indicator 5, which still falls under the high category and demonstrates students’ adaptability in applying acquired knowledge. These findings suggest that PSU students exhibit independence, strategic learning, and adaptability when using courseware via Microsoft Teams.

Table 2.

Effect of courseware on self-guided learning in an online setting.

Statement	Mean score	Level	Impact
I independently decide on the sequence and content of my learning using courseware when applicable	3.48	High	Significant
Courseware enables me to grasp key concepts and principles at a pace suited to my learning style	3.51	High	Significant
I create a structured learning plan that includes activities, assignments, quizzes, and exams to effectively meet my educational objectives	3.62	High	Significant
I reach out to my instructor/professor whenever I need further clarification on lessons delivered through courseware	3.65	High	Significant
I can easily adapt and apply the knowledge gained through courseware in different learning contexts	3.41	High	Significant
Overall Weighted Mean	3.53	High	Significant

Table 3 presents the impact of courseware on online learning method in terms of the learning environment, with an total weighted mean of 3.43, rated high. The highest score (3.51) in indicator 3 suggests that courseware is well structured and permittable on MS Teams across devices. Indicator 1 follows with 3.48, indicating that students find MS Teams commands easy to use. Indicators 4 and 5, both at 3.42, show that students can communicate effectively with instructors and submit projects smoothly. Indicator 2 had the lowest score (3.32), rated moderate, implying that while MS Teams promotes engagement, it is not fully immersive. Overall, the results indicate that MS Teams provides an organized, user-friendly, and efficient learning environment, supporting seamless access to materials and communication.

Table 3.

Influence of courseware on learning pedagogy in an online setting.

Statement	Mean score	Category	Effect
Navigating and using MS Teams commands is straightforward	3.48	High	Significant
Engaging with MS Teams enhances cognitive stimulation	3.32	Moderate	Significant
Courseware is systematically arranged and easily accessible on multiple devices (PC, tablet, smartphone)	3.51	High	Significant
I can effectively communicate with my instructors and professors	3.42	High	Significant
Submitting assignments and activities is efficient and hassle-free	3.42	High	Significant
Overall Weighted Mean	3.43	High	Significant

Table 4 examines the impact of courseware on learning growth, with an total weighted mean of 3.37 (moderate). The highest mean (3.50) in indicator 4 suggests that students are motivated to plan and assess their cognitive skills. Indicator 2 (3.43) highlights MS Teams as a tool for diverse learning strategies, while indicator 3 (3.42) indicates improvements in skills, knowledge, and abilities. Indicator 1 (3.26) reflects learning progress through modern educational approaches. The lowest mean (3.23, indicator 5) suggests students find online learning provides sufficient study time compared to face-to-face instruction.

Table 4.

Influence of courseware on learning pedagogy in an online environment.

Statement	Mean score	Category	Effect
Learning progress is evident through modern instructional approaches	3.26	Moderate	Significant
MS Teams facilitates diverse strategies that support learning advancement	3.43	High	Significant
Courseware contributes to the enhancement of my skills, knowledge, and competencies	3.42	High	Significant
I am motivated to plan, assess, and refine my cognitive abilities	3.50	High	Significant
Online learning provides more time for studying compared to traditional face-to-face instruction	3.23	Moderate	Significant
Overall Weighted Mean	3.37	Moderate	Significant

Table 5 provides a summary of the impact assessment of courseware on online learning method, focusing on self-directed learning, the learning environment, and learning growth. Among these variables, self-directed learning recorded the highest mean score of 3.53, indicating that students actively take initiative in their learning process, manage their study strategies, and seek clarification when needed. This suggests that courseware, particularly through MS Teams, supports independent learning by allowing students to set their own pace and organize their study plans effectively. The learning environment variable had a mean of 3.43, highlighting that students find MS Teams user-friendly, accessible, and efficient for course material delivery and communication. The structured organization of content and seamless interaction with instructors contributes to its high rating. The learning growth variable received the lowest mean score of 3.37, classified as moderate, implying that while courseware contributes to skill enhancement and cognitive development, its impact on long-term academic progress may not be as pronounced. Students may be required additional instructional support, engagement strategies, or interactive components to maximize their learning growth in an online setting. Overall, the findings indicate that courseware significantly enhances self-directed learning and fosters a conducive learning environment, though further improvements could be made to optimize learning growth outcomes.

Table 5.

Overview of Courseware’s influence on online learning pedagogy.

Aspect	Mean score	Category	Effect
Independent Learning	3.53	High	Significant
Learning Environment	3.43	High	Significant
Academic Growth	3.37	Moderate	Significant
Overall Mean	3.44	High	Significant

Discussion

The study explores the impact of courseware on self-directed learning, the learning environment, or learning growth among PSU students. Table 2 shows that self-directed learning had the highest influence (mean = 3.53), with students effectively managing their studies and seeking instructor guidance (indicator 4 = 3.65). This finding aligns with Ray and Nelson (2025), who emphasized that self-directed learning enhances retention and understanding. Table 3 highlights the learning environment (mean = 3.43), where students find MS Teams well-organized and accessible (indicator 3 = 3.51), supporting findings from Wong et al. (2024) on the importance of user-friendly platforms. However, indicator 2 (3.32) suggests that interactive features could improve engagement, consistent with Singh et al. (2024), who stressed the need for interactivity in online classrooms. Table 4 evaluates learning growth (mean = 3.37), where indicator 4 (3.50) shows that students actively monitor their cognitive skills, supporting Mentz (2025), who highlighted the role of self-assessment in meaningful learning. Indicator 2 (3.43) suggests that MS Teams accommodates diverse learning strategies, aligning with Hidayat et al. (2025), who emphasized technology’s role in personalized learning. Indicator 5 (3.23) confirms online learning’s flexibility, resonating with Makda (2025) on the advantages of digital education. Table 5 summarizes that self-directed learning (3.53) has the most significant impact, while learning growth (3.37) still supports skill development. The findings highlight the importance of a structured and engaging digital learning environment. Future research should explore AI-driven tools, interactive features, and long-term effectiveness to enhance online education (Chen and Wu, 2024).

Conclusion

The findings indicate that Microsoft Teams courseware effectively enhances self-directed learning (mean = 3.53) and provides a structured learning environment (mean = 3.43), though its influence on learning growth (mean = 3.37) is moderate. While the platform supports independent learning and accessibility, further refinements are needed to strengthen its role in academic development. Future research should explore the long term effectiveness of courseware in varied educational settings and identify strategies to increase student engagement and digital literacy. Incorporating AI-driven tools for adaptive learning and interactive features may further optimize its impact. Additionally, future studies could investigate the effect of gamification and real-time feedback on improving knowledge retention and online learning experiences.

Footnotes

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

ORCID iD

Angelou O Ramos

Author Biography

Angelou O. Ramos has been in the teaching profession for 12 years. He is currently an Assistant Professor under the Department of Languages Education, College of Teacher Education at the Pangasinan State University, Lingayen Campus, Pangasinan, Philippines. As to date, he is a Doctor of Philosophy in English Language Studies (PhD ELS) candidate at the University of the Cordilleras, Baguio City, Philippines. Mr. Ramos has taught major courses in the BSEd English program. Likewise, he has also published researches in peer-reviewed international journals. His research interests include linguistics, language and culture and language and literature assessment among others.

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